Long-term fish sampling data from the San Francisco Estuary were combined with detailed three dimensional hydrodynamic modeling to investigate the relationship between historical fish catch and hydrodynamic complexity. Delta Smelt catch data at 45 stations from the Fall Midwater Trawl (FMWT) survey in the vicinity of Suisun Bay were used to develop a quantitative catch-based station index. This index was used to rank stations based on historical Delta Smelt catch. The correlations between historical Delta Smelt catch and 35 quantitative metrics of environmental complexity were evaluated at each station. Eight metrics of environmental conditions were derived from FMWT data and 27 metrics were derived from model predictions at each FMWT station. To relate the station index to conceptual models of Delta Smelt habitat, the metrics were used to predict the station ranking based on the quantified environmental conditions. Salinity, current speed, and turbidity metrics were used to predict the relative ranking of each station for Delta Smelt catch. Including a measure of the current speed at each station improved predictions of the historical ranking for Delta Smelt catch relative to similar predictions made using only salinity and turbidity. Current speed was also found to be a better predictor of historical Delta Smelt catch than water depth. The quantitative approach developed using the FMWT data was validated using the Delta Smelt catch data from the San Francisco Bay Study. Complexity metrics in Suisun Bay were-evaluated during 2010 and 2011. This analysis indicated that a key to historical Delta Smelt catch is the overlap of low salinity, low maximum velocity, and low Secchi depth regions. This overlap occurred in Suisun Bay during 2011, and may have contributed to higher Delta Smelt abundance in 2011 than in 2010 when the favorable ranges of the metrics did not overlap in Suisun Bay.
","language":"English","publisher":"University of California at Davis John Muir Institute of the Environment and the Delta Stewardship Council","doi":"10.15447/sfews.2016v14iss1art3","usgsCitation":"Bever, A.J., MacWilliams, M.L., Herbold, B., Brown, L.R., and Feyrer, F.V., 2016, Linking hydrodynamic complexity to delta smelt (Hypomesus transpacificus) distribution in the San Francisco Estuary, USA: San Francisco Estuary and Watershed Science, v. 14, no. 1, p. 1-27, https://doi.org/10.15447/sfews.2016v14iss1art3.","productDescription":"27 p.","startPage":"1","endPage":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063936","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":471146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss1art3","text":"Publisher Index Page"},{"id":325464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.6845703125,\n 38.1734326790354\n ],\n [\n -121.6680908203125,\n 38.14103736644331\n ],\n [\n -121.64611816406249,\n 38.089174937729794\n ],\n [\n -121.66259765625001,\n 38.035112420612975\n ],\n [\n -121.67495727539061,\n 37.99724489645483\n ],\n [\n -121.75048828124999,\n 38.00049145082287\n ],\n [\n -121.86447143554686,\n 38.01888587738773\n ],\n [\n -121.96197509765625,\n 38.034030762875844\n ],\n [\n -122.05535888671875,\n 38.037275688165614\n ],\n [\n -122.09793090820311,\n 38.031867399480674\n ],\n [\n -122.14187622070311,\n 38.024295124443995\n ],\n [\n -122.19680786132812,\n 38.034030762875844\n ],\n [\n -122.21054077148438,\n 38.04700960141592\n ],\n [\n -122.22702026367188,\n 38.06647354576796\n ],\n [\n -122.2119140625,\n 38.0729603768343\n ],\n [\n -122.14462280273436,\n 38.052416771864834\n ],\n [\n -122.12265014648438,\n 38.064311140919\n ],\n [\n -122.08694458007812,\n 38.09782123329514\n ],\n [\n -122.07046508789062,\n 38.129155479572624\n ],\n [\n -122.05261230468751,\n 38.23386541556983\n ],\n [\n -122.02926635742188,\n 38.25004423627535\n ],\n [\n -122.00042724609374,\n 38.23170796744926\n ],\n [\n -121.99630737304688,\n 38.182068998322094\n ],\n [\n -121.97708129882812,\n 38.155077102180655\n ],\n [\n -121.87408447265625,\n 38.134556577054134\n ],\n [\n -121.761474609375,\n 38.1334763895322\n ],\n [\n -121.6845703125,\n 38.1734326790354\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-23","publicationStatus":"PW","scienceBaseUri":"5790a183e4b030378fb4743b","contributors":{"authors":[{"text":"Bever, Aaron J.","contributorId":173009,"corporation":false,"usgs":false,"family":"Bever","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":642984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacWilliams, Michael L.","contributorId":173010,"corporation":false,"usgs":false,"family":"MacWilliams","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":27140,"text":"Delta Modeling Associates, Inc.","active":true,"usgs":false}],"preferred":false,"id":642985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herbold, Bruce","contributorId":51223,"corporation":false,"usgs":false,"family":"Herbold","given":"Bruce","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":642986,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":5901,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642987,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169061,"text":"70169061 - 2016 - Threshold responses of Blackside Dace (Chrosomus cumberlandensis) and Kentucky Arrow Darter (Etheostoma spilotum) to stream conductivity","interactions":[],"lastModifiedDate":"2016-03-16T10:08:20","indexId":"70169061","displayToPublicDate":"2016-03-16T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Threshold responses of Blackside Dace (Chrosomus cumberlandensis) and Kentucky Arrow Darter (Etheostoma spilotum) to stream conductivity","docAbstract":"Chrosomus cumberlandensis (Blackside Dace [BSD]) and Etheostoma spilotum (Kentucky Arrow Darter [KAD]) are fish species of conservation concern due to their fragmented distributions, their low population sizes, and threats from anthropogenic stressors in the southeastern United States. We evaluated the relationship between fish abundance and stream conductivity, an index of environmental quality and potential physiological stressor. We modeled occurrence and abundance of KAD in the upper Kentucky River basin (208 samples) and BSD in the upper Cumberland River basin (294 samples) for sites sampled between 2003 and 2013. Segmented regression indicated a conductivity change-point for BSD abundance at 343 μS/cm (95% CI: 123–563 μS/cm) and for KAD abundance at 261 μS/cm (95% CI: 151–370 μS/cm). In both cases, abundances were negligible above estimated conductivity change-points. Post-hoc randomizations accounted for variance in estimated change points due to unequal sample sizes across the conductivity gradients. Boosted regression-tree analysis indicated stronger effects of conductivity than other natural and anthropogenic factors known to influence stream fishes. Boosted regression trees further indicated threshold responses of BSD and KAD occurrence to conductivity gradients in support of segmented regression results. We suggest that the observed conductivity relationship may indicate energetic limitations for insectivorous fishes due to changes in benthic macroinvertebrate community composition.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.015.0104","usgsCitation":"Hitt, N.P., Floyd, M., Compton, M., and McDonald, K., 2016, Threshold responses of Blackside Dace (Chrosomus cumberlandensis) and Kentucky Arrow Darter (Etheostoma spilotum) to stream conductivity: Southeastern Naturalist, v. 15, no. 1, p. 41-60, https://doi.org/10.1656/058.015.0104.","productDescription":"20 p.","startPage":"41","endPage":"60","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067031","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":318899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ea759de4b0f59b85d897a4","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":622729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Floyd, Michael","contributorId":167568,"corporation":false,"usgs":false,"family":"Floyd","given":"Michael","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":622730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Compton, Michael","contributorId":167569,"corporation":false,"usgs":false,"family":"Compton","given":"Michael","email":"","affiliations":[{"id":24755,"text":"Kentucky State Nature Preserves Commission","active":true,"usgs":false}],"preferred":false,"id":622731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDonald, Kenneth","contributorId":167570,"corporation":false,"usgs":false,"family":"McDonald","given":"Kenneth","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":622732,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169068,"text":"70169068 - 2016 - Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications","interactions":[],"lastModifiedDate":"2016-06-24T11:08:13","indexId":"70169068","displayToPublicDate":"2016-03-16T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications","docAbstract":"The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.
","language":"English","publisher":"American Meterorological Society","doi":"10.1175/EI-D-15-0033.1","usgsCitation":"Rastogi, B., Williams, A.P., Fischer, D.T., Iacobellis, S.F., McEachern, K., Carvalho, L., Jones, C.L., Baguskas, S.A., and Still, C.J., 2016, Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications: Earth Interactions, v. 20, Paper 15; 19 p., https://doi.org/10.1175/EI-D-15-0033.1.","productDescription":"Paper 15; 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073097","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/ei-d-15-0033.1","text":"Publisher Index Page"},{"id":318897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.45959472656249,\n 33.880677127838844\n ],\n [\n -120.45959472656249,\n 34.08564930273551\n ],\n [\n -119.32662963867188,\n 34.08564930273551\n ],\n [\n -119.32662963867188,\n 33.880677127838844\n ],\n [\n -120.45959472656249,\n 33.880677127838844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"56ea759ce4b0f59b85d8979f","contributors":{"authors":[{"text":"Rastogi, Bharat","contributorId":167577,"corporation":false,"usgs":false,"family":"Rastogi","given":"Bharat","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, A. 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Seasonal adaptations are well studied in Arctic, Sub-Arctic, and hibernating mammals; however, limited studies have been conducted in sub-tropical species. The Florida manatee (Trichechus manatus latirostris), a sub-tropical marine mammal, forages less during colder temperatures and may rely on adipose stores for maintenance energy requirements. Metabolic hormones, growth hormone (GH), insulin-like growth factor (IGF)-I, and ghrelin influence growth rate, accretion of lean and adipose tissue. They have been shown to regulate seasonal changes in body composition. The objective of this research was to investigate manatee metabolic hormones in two seasons to determine if manatees exhibit seasonality and if these hormones are associated with seasonal changes in body composition. In addition, age related differences in these metabolic hormones were assessed in multiple age classes. Concentrations of GH, IGF-I, and ghrelin were quantified in adult manatee serum using heterologous radioimmunoassays. Samples were compared between short (winter) and long (summer) photoperiods (n = 22 male, 20 female) and by age class (adult, juvenile, and calf) in long photoperiods (n = 37). Short photoperiods tended to have reduced GH (p = 0.08), greater IGF-I (p = 0.01), and greater blubber depth (p = 0.03) compared with long photoperiods. No differences were observed in ghrelin (p = 0.66). Surprisingly, no age related differences were observed in IGF-I or ghrelin concentrations (p > 0.05). However, serum concentrations of GH tended (p = 0.07) to be greater in calves and juveniles compared with adults. Increased IGF-I, greater blubber thickness, and reduced GH during short photoperiod suggest a prioritization for adipose deposition. Whereas, increased GH, reduced blubber thickness, and decreased IGF-I in long photoperiod suggest prioritization of lean tissue accretion. Hormone profiles in conjunction with difference in body composition between photoperiods indicate seasonal adjustments in manatee nutrient partitioning priorities.
\nToxoplasma gondii is a protozoan parasite transmitted by domestic cats (Felis catus) that has historically caused mortality in native Hawaiian birds. To estimate how widespread exposure to the parasite is in nene (Hawaiian Geese, Branta sandvicensis), we did a serologic survey for T. gondii antibody and genetically characterized parasite DNA from the tissues of dead birds that had confirmed infections by immunohistochemistry. Of 94 geese sampled, prevalence on the island of Kauai, Maui, and Molokai was 21% (n=42), 23% (n=31), and 48% (n=21), respectively. Two new T. gondii genotypes were identified by PCR-restriction fragment length polymorphism from four geese, and these appeared segregated geographically. Exposure to T. gondii in wild nene is widespread and, while the parasite is not a major cause of death, it could have sublethal or behavioral effects. How to translate such information to implement effective ways to manage feral cats in Hawaii poses challenges.
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]\n}","volume":"52","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ea7598e4b0f59b85d89795","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":622796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verma, Shiv K.","contributorId":167589,"corporation":false,"usgs":false,"family":"Verma","given":"Shiv","email":"","middleInitial":"K.","affiliations":[{"id":24764,"text":"US Department of Agriculture, Agricultural Research Service, Animal Parasitic Diseases Laboratory, Beltsville, MD, 20705-2350","active":true,"usgs":false}],"preferred":false,"id":622797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Su, Chunlei","contributorId":167590,"corporation":false,"usgs":false,"family":"Su","given":"Chunlei","email":"","affiliations":[{"id":24765,"text":"University of Tennessee, Department of Microbiology, Knoxville, TN 37996-0845","active":true,"usgs":false}],"preferred":false,"id":622798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Medeiros, John","contributorId":167591,"corporation":false,"usgs":false,"family":"Medeiros","given":"John","email":"","affiliations":[{"id":24766,"text":"4. State of Hawaii, Division of Forestry and Wildlife-Maui, 54 South High Street # 101, Wailuku, HI 96793.","active":true,"usgs":false}],"preferred":false,"id":622799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaiakapu, Thomas","contributorId":167592,"corporation":false,"usgs":false,"family":"Kaiakapu","given":"Thomas","email":"","affiliations":[{"id":24767,"text":"State of Hawaii, Division of Forestry and Wildlife-Kauai, 3060 Eiwa Street # 306, Lihue, HI 96766","active":true,"usgs":false}],"preferred":false,"id":622800,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwok, Oliver C.","contributorId":167593,"corporation":false,"usgs":false,"family":"Kwok","given":"Oliver","email":"","middleInitial":"C.","affiliations":[{"id":24764,"text":"US Department of Agriculture, Agricultural Research Service, Animal Parasitic Diseases Laboratory, Beltsville, MD, 20705-2350","active":true,"usgs":false}],"preferred":false,"id":622801,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dubey, Jitender P.","contributorId":41707,"corporation":false,"usgs":true,"family":"Dubey","given":"Jitender","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":622802,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169101,"text":"70169101 - 2016 - Susceptibility and antibody response of Vesper Sparrows (Pooecetes gramineus) to West Nile virus: A potential amplification host in sagebrush-grassland habitat","interactions":[],"lastModifiedDate":"2016-03-18T10:05:20","indexId":"70169101","displayToPublicDate":"2016-03-16T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Susceptibility and antibody response of Vesper Sparrows (Pooecetes gramineus) to West Nile virus: A potential amplification host in sagebrush-grassland habitat","docAbstract":"West Nile virus (WNV) spread to the US western plains states in 2003, when a significant mortality event attributed to WNV occurred in Greater Sage-grouse ( Centrocercus urophasianus ). The role of avian species inhabiting sagebrush in the amplification of WNV in arid and semiarid regions of the North America is unknown. We conducted an experimental WNV challenge study in Vesper Sparrows ( Pooecetes gramineus ), a species common to sagebrush and grassland habitats found throughout much of North America. We found Vesper Sparrows to be moderately susceptible to WNV, developing viremia considered sufficient to transmit WNV to feeding mosquitoes, but the majority of birds were capable of surviving infection and developing a humoral immune response to the WNV nonstructural 1 and envelope proteins. Despite clearance of viremia, after 6 mo, WNV was detected molecularly in three birds and cultured from one bird. Surviving Vesper Sparrows were resistant to reinfection 6 mo after the initial challenge. Vesper sparrows could play a role in the amplification of WNV in sagebrush habitat and other areas of their range, but rapid clearance of WNV may limit their importance as competent amplification hosts of WNV.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Diseases","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wildlife Disease Association","publisherLocation":"Lawrence, KS","doi":"10.7589/2015-06-148","usgsCitation":"Hofmeister, E.K., Dusek, R.J., Fassbinder-Orth, C., Owen, B., and Franson, J., 2016, Susceptibility and antibody response of Vesper Sparrows (Pooecetes gramineus) to West Nile virus: A potential amplification host in sagebrush-grassland habitat: Journal of Wildlife Diseases, v. 52, no. 2, 9 p., https://doi.org/10.7589/2015-06-148.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068995","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":318951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.075,\n 41.475\n ],\n [\n -118.075,\n 41.465\n ],\n [\n -118.065,\n 41.465\n ],\n [\n -118.065,\n 41.475\n ],\n [\n -118.075,\n 41.475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ed26b6e4b0f59b85db0a33","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":622930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":152316,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":622931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fassbinder-Orth, Carol","contributorId":167623,"corporation":false,"usgs":false,"family":"Fassbinder-Orth","given":"Carol","email":"","affiliations":[{"id":24786,"text":"Creighton University, Omaha, NE, 68178, USA","active":true,"usgs":false}],"preferred":false,"id":622932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Owen, Benjamin","contributorId":167624,"corporation":false,"usgs":false,"family":"Owen","given":"Benjamin","email":"","affiliations":[{"id":24786,"text":"Creighton University, Omaha, NE, 68178, USA","active":true,"usgs":false}],"preferred":false,"id":622933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Franson, J. Christian jfranson@usgs.gov","contributorId":149318,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","email":"jfranson@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":622934,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171335,"text":"70171335 - 2016 - Abundance, distribution, and removals of feral pigs at Big Island National Wildlife Refuge Complex 2010–2015","interactions":[],"lastModifiedDate":"2018-01-04T12:39:30","indexId":"70171335","displayToPublicDate":"2016-03-16T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-075","title":"Abundance, distribution, and removals of feral pigs at Big Island National Wildlife Refuge Complex 2010–2015","docAbstract":"The Hakalau Forest Unit (HFU) of Big Island National Wildlife Refuge Complex (BINWRC) has intensively monitored non-native ungulate presence and distribution during surveys of all managed areas since 1988. In this report we: 1) provide results from recent ungulate surveys and the number of removals at HFU to determine the distribution, abundance, and efficacy of removals of feral pigs, the dominant ungulate, from 2010 to 2015; 2) present results of surveys of the presence and distribution of several ungulate species at the Kona Forest Unit (KFU) of BINWRC from November of 2012 to April of 2015; 3) present results of surveys of weed presence and cover at both refuge units; and 4) present comparative analyses of forest canopy cover at KFU from visual estimates and geospatial imagery. Removals of feral pigs at HFU appear to have significantly decreased pig abundance over the study period from 2010–2015. A grand total of 1,660 feral pigs were removed from managed areas of HFU from 2010 until September of 2015. Management units 2 and 4 contained the majority of pigs at HFU. Recent surveys recorded high densities of pigs in the unenclosed, unmanaged area of Lower Maulua, reaching 14.9 ± (3.2) pigs/km2 in March of 2015. The total amount of ungulate sign ranged from 22.2 to 54.3 percent of plots surveyed at KFU from November of 2012 to April of 2015. The ability to differentiate sign of ungulate species remains problematic at KFU; although there appears to have been a significant decline in feral cattle sign at KFU, this result is likely to be unreliable because cattle and pig sign were not differentiated consistently during later surveys. Spatial distributions in weed cover are distinctive; however, some weed species may not be reliably represented due to observers’ inconsistencies in recording data and abilities to recognize less common weeds.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","collaboration":"This product was prepared under Cooperative Agreement G13AC00097 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey.","usgsCitation":"Leopold, C.R., Hess, S.C., Kendall, S.J., and Judge, S.W., 2016, Abundance, distribution, and removals of feral pigs at Big Island National Wildlife Refuge Complex 2010–2015: Technical Report HCSU-075, iii, 44 p.","productDescription":"iii, 44 p.","startPage":"1","endPage":"44","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073412","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328012,"type":{"id":15,"text":"Index Page"},"url":"https://dspace.lib.hawaii.edu/handle/10790/2684"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hakalau Forest Unit (HFU) of Big Island National Wildlife Refuge Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.36041259765625,\n 19.751194318940865\n ],\n [\n -155.36041259765625,\n 19.89911667339186\n ],\n [\n -155.21141052246094,\n 19.89911667339186\n ],\n [\n -155.21141052246094,\n 19.751194318940865\n ],\n [\n -155.36041259765625,\n 19.751194318940865\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad2de4b05e859bdfb7c3","contributors":{"authors":[{"text":"Leopold, Christina R.","contributorId":46817,"corporation":false,"usgs":true,"family":"Leopold","given":"Christina","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":630613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":630612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Steve J. 0000-0002-9290-5629","orcid":"https://orcid.org/0000-0002-9290-5629","contributorId":169663,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":630614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Judge, Seth W.","contributorId":8718,"corporation":false,"usgs":true,"family":"Judge","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":630615,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170130,"text":"70170130 - 2016 - Estimating abundance in the presence of species uncertainty","interactions":[],"lastModifiedDate":"2016-09-19T15:52:34","indexId":"70170130","displayToPublicDate":"2016-03-16T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating abundance in the presence of species uncertainty","docAbstract":"1.N-mixture models have become a popular method for estimating abundance of free-ranging animals that are not marked or identified individually. These models have been used on count data for single species that can be identified with certainty. However, co-occurring species often look similar during one or more life stages, making it difficult to assign species for all recorded captures. This uncertainty creates problems for estimating species-specific abundance and it can often limit life stages to which we can make inference.
\n2.We present a new extension of N-mixture models that accounts for species uncertainty. In addition to estimating site-specific abundances and detection probabilities, this model allows estimating probability of correct assignment of species identity. We implement this hierarchical model in a Bayesian framework and provide all code for running the model in BUGS-language programs.
\n3.We present an application of the model on count data from two sympatric freshwater fishes, the brook stickleback (Culaea inconstans) and the ninespine stickleback (Pungitius pungitius), ad illustrate implementation of covariate effects (habitat characteristics). In addition, we used a simulation study to validate the model and illustrate potential sample size issues. We also compared, for both real and simulated data, estimates provided by our model to those obtained by a simple N-mixture model when captures of unknown species identification were discarded. In the latter case, abundance estimates appeared highly biased and very imprecise, while our new model provided unbiased estimates with higher precision.
\n4.This extension of the N-mixture model should be useful for a wide variety of studies and taxa, as species uncertainty is a common issue. It should notably help improve investigation of abundance and vital rate characteristics of organisms’ early life stages, which are sometimes more difficult to identify than adults.
\nThe Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2.
\nFollowing on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data–model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land–ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models.
\nFinally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/cp-12-663-2016","usgsCitation":"Haywood, A.M., Dowsett, H.J., Dolan, A.M., Rowley, D., Abe-Ouchi, A., Otto-Bliesner, B., Chandler, M.A., Hunter, S.J., Lunt, D.J., Pound, M., and Salzmann, U., 2016, The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific objectives and experimental design: Climate of the Past, v. 12, no. 3, p. 663-675, https://doi.org/10.5194/cp-12-663-2016.","productDescription":"13 p.","startPage":"663","endPage":"675","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060058","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":471149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-12-663-2016","text":"Publisher Index Page"},{"id":325565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-16","publicationStatus":"PW","scienceBaseUri":"5793444de4b0eb1ce79e8c1d","contributors":{"authors":[{"text":"Haywood, Alan M.","contributorId":86663,"corporation":false,"usgs":true,"family":"Haywood","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":643339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dolan, Aisling M.","contributorId":30117,"corporation":false,"usgs":true,"family":"Dolan","given":"Aisling","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":643341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowley, David","contributorId":173099,"corporation":false,"usgs":false,"family":"Rowley","given":"David","email":"","affiliations":[{"id":12621,"text":"University of Chicago and University of South Florida","active":true,"usgs":false}],"preferred":false,"id":643342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abe-Ouchi, Ayako","contributorId":94942,"corporation":false,"usgs":true,"family":"Abe-Ouchi","given":"Ayako","email":"","affiliations":[],"preferred":false,"id":643343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Otto-Bliesner, Bette","contributorId":58171,"corporation":false,"usgs":true,"family":"Otto-Bliesner","given":"Bette","affiliations":[],"preferred":false,"id":643344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chandler, Mark A.","contributorId":101768,"corporation":false,"usgs":true,"family":"Chandler","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643345,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hunter, Stephen J.","contributorId":55711,"corporation":false,"usgs":true,"family":"Hunter","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":643346,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lunt, Daniel J.","contributorId":101168,"corporation":false,"usgs":true,"family":"Lunt","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":643347,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pound, Matthew","contributorId":173100,"corporation":false,"usgs":false,"family":"Pound","given":"Matthew","email":"","affiliations":[{"id":18103,"text":"Northumbria University, Newcastle Upon Tyne, UK","active":true,"usgs":false}],"preferred":false,"id":643357,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Salzmann, Ulrich","contributorId":173101,"corporation":false,"usgs":false,"family":"Salzmann","given":"Ulrich","email":"","affiliations":[{"id":18103,"text":"Northumbria University, Newcastle Upon Tyne, UK","active":true,"usgs":false}],"preferred":false,"id":643358,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70162692,"text":"ofr20161013 - 2016 - Ecological requirements for pallid sturgeon reproduction and recruitment in the Missouri River—Annual report 2014","interactions":[],"lastModifiedDate":"2016-03-17T09:14:13","indexId":"ofr20161013","displayToPublicDate":"2016-03-16T00:00:00","publicationYear":"2016","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":"2016-1013","title":"Ecological requirements for pallid sturgeon reproduction and recruitment in the Missouri River—Annual report 2014","docAbstract":"The Comprehensive Sturgeon Research Project is a multiyear, multiagency collaborative research framework developed to provide information to support pallid sturgeon recovery and Missouri River management decisions. The project strategy integrates field and laboratory studies of sturgeon reproductive ecology, early life history, habitat requirements, and physiology. The project scope of work is developed annually with collaborating research partners and in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery Program–Integrated Science Program. The project research consists of several interdependent and complementary tasks that involve multiple disciplines.
The project research tasks in the 2014 scope of work emphasized understanding of reproductive migrations and spawning of adult pallid sturgeon and hatch and drift of larvae. These tasks were addressed in three hydrologically and geomorphologically distinct parts of the Missouri River Basin: the Lower Missouri River downstream from Gavins Point Dam, the Upper Missouri River downstream from Fort Peck Dam and downstream reaches of the Milk River, and the Lower Yellowstone River. The project research is designed to inform management decisions related to channel re-engineering, flow modification, and pallid sturgeon population augmentation on the Missouri River and throughout the range of the species. Research and progress made through this project are reported to the U.S. Army Corps of Engineers annually. This annual report details the research effort and progress made by the Comprehensive Sturgeon Research Project during 2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161013","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Missouri River Recovery—Integrated Science Program","usgsCitation":"DeLonay, A.J., Chojnacki, K.A., Jacobson, R.B., Braaten, P.J., Buhl, K.J., Elliott, C.M., Erwin, S.O., Faulkner, J.D.A., Candrl, J.S., Fuller, D.B., Backes, K.M., Haddix, T.M., Rugg, M.L., Wesolek, C.J., Eder, B.L., and Mestl, G.E., 2016,\nEcological requirements for pallid sturgeon reproduction and recruitment in the Missouri River—Annual report 2014: U.S. Geological Survey Open-File Report 2016–1013, 131 p., https://dx.doi.org/10.3133/ofr20161013.","productDescription":"xv, 131 p.","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065464","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":318883,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1013/coverthb.jpg"},{"id":318884,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1013/ofr20161013.pdf","text":"Report","size":"24.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1013"}],"country":"United States","state":"Missouri, Montana, Nebraska","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.57812499999999,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 48.629278127969414\n ],\n [\n -104.029541015625,\n 47.956823800497475\n ],\n [\n -107.57812499999999,\n 47.956823800497475\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.84423828125,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 42.956422511073335\n ],\n [\n -95.78979492187499,\n 41.054501963290505\n ],\n [\n -97.84423828125,\n 41.054501963290505\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.08441162109374,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 39.3024245604149\n ],\n [\n -91.67816162109375,\n 38.52668162061619\n ],\n [\n -93.08441162109374,\n 38.52668162061619\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
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To address concerns about the effects of water-resource management practices and rising sea level on saltwater intrusion, the U.S. Geological Survey in cooperation with the Broward County Environmental Planning and Community Resilience Division, initiated a study to examine causes of saltwater intrusion and predict the effects of future alterations to the hydrologic system on salinity distribution in eastern Broward County, Florida. A three-dimensional, variable-density solute-transport model was calibrated to conditions from 1970 to 2012, the period for which data are most complete and reliable, and was used to simulate historical conditions from 1950 to 2012. These types of models are typically difficult to calibrate by matching to observed groundwater salinities because of spatial variability in aquifer properties that are unknown, and natural and anthropogenic processes that are complex and unknown; therefore, the primary goal was to reproduce major trends and locally generalized distributions of salinity in the Biscayne aquifer. The methods used in this study are relatively new, and results will provide transferable techniques for protecting groundwater resources and maximizing groundwater availability in coastal areas. The model was used to (1) evaluate the sensitivity of the salinity distribution in groundwater to sea-level rise and groundwater pumping, and (2) simulate the potential effects of increases in pumping, variable rates of sea-level rise, movement of a salinity control structure, and use of drainage recharge wells on the future distribution of salinity in the aquifer.
\nResults from the simulation of historical conditions indicate that the model generally represents the observed greater westward extent of elevated salinity in the central part of the intruded area relative to the northern and southernmost parts of the intruded area. Results of sensitivity testing indicate that the extent of elevated salinity is most sensitive to pumping in areas where the source of saltwater is largely offshore, from the Atlantic Ocean, and is most sensitive to sea-level rise in areas where the source of salinity is downward leakage of brackish water from canals.
\nSimulations of future scenarios indicate that increases in pumping near the existing interface may cause the interface to advance and decreases in pumping may cause it to retreat. Climatic effects, such as periods of prolonged drought or high precipitation, may augment or counteract long-term effects of changes in pumping on aquifer salinity at well fields. With increasing rates of sea-level rise, the freshwater-saltwater interface advances progressively inland, and flow-averaged salinities at well fields near the existing interface increase commensurately. Hypothetical southeastward (downstream) re-positioning of the existing G–54 salinity-control structure may prevent the interface from moving northwestward along and near the North New River canal, but beneficial effects are localized. Implementation of freshwater recharge wells in the city of Hallandale Beach may also have only a localized freshening effect in the aquifer and little appreciable effect on the freshwater-saltwater interface or on concentrations of salinity at well fields.
\nModel accuracy and use are limited by uncertainty in the physical properties and boundary conditions of the system, uncertainty in historical and future conditions, and generalizations made in the mathematical relationships used to describe the physical processes of groundwater flow and transport. Because of these limitations, model results should be considered in relative rather than absolute terms. Nonetheless, model results do provide useful information on the relative scale of response of the system to changes in pumping distribution, sea-level rise, and mitigation activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165022","collaboration":"Prepared in cooperation with the Broward County Environmental Planning and Community Resilience Division","usgsCitation":"Hughes, J.D., Sifuentes, D.F., and White, J.T., 2016, Potential effects of alterations to the hydrologic system on the distribution of salinity in the Biscayne aquifer in Broward County, Florida: U.S. Geological Survey Scientific Investigations Report 2016–5022, 114 p., https://dx.doi.org/10.3133/sir20165022.","productDescription":"Report: x, 114 p.; Data Release","numberOfPages":"128","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056536","costCenters":[{"id":269,"text":"FLWSC-Ft. 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Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
http://fl.water.usgs.gov/
Many species are distributed as metapopulations in dynamic landscapes, where habitats change through space and time. Individuals locate habitat through dispersal, and the relationship between a species and landscape characteristics can have profound effects on population persistence. Despite the importance of connectivity in dynamic environments, few empirical studies have examined temporal variability in dispersal or its effect on metapopulation dynamics. In response to this knowledge gap, we studied the dispersal, demography, and viability of a metapopulation of an endangered, disturbance-dependent shorebird. We examined three subpopulations of piping plovers (Charadrius melodus) on the lower Platte and Missouri rivers from 2008–2013. High flow events from an upstream dam on the Missouri River in 2010 and 2011 allowed us to assess the effect of total habitat loss and the subsequent creation of new habitat associated with a large disturbance at one ‘natural’ study location. The other two sites within the metapopulation, which were maintained by anthropogenic activities (e.g., mining, development, habitat restoration), were largely unaffected by this disturbance, resulting in a controlled natural experiment.
\nHigh flow events were associated with increased emigration, decreased immigration, and decreased survival in the subpopulation that experienced high flows. Following the high flow event, immigration into that subpopulation increased. Dispersal rates among subpopulations were negatively correlated with distance. The metapopulation had a low probability of extinction over 100 years (0%) under the current disturbance interval and associated dispersal and survival rates. However, persistence depended on relatively stable, human-created habitats, not the dynamic, natural habitat (47.7 % extinction probability for this subpopulation).
\nWe found that functional connectivity, as measured by the rate of dispersal among subpopulations, increased as a result of the high flow event in our study metapopulation. Plovers also increased reproductive output following this event. Although the study metapopulation had a low overall probability of extinction, metapopulation persistence depended on anthropogenically created habitats that provided a small but stable source of nesting habitat and dispersers through time. However, all subpopulations remained small, even if persistent, making them individually vulnerable to extinction through stochastic events. Given the highly dynamic nature of habitat availability in this system, maintaining several subpopulations within the metapopulation and stable sources of habitat will be critical, and this species will likely remain conservation-reliant.
\nExfoliation of rock deteriorates cliffs through the formation and subsequent opening of fractures, which in turn can lead to potentially hazardous rockfalls. Although a number of mechanisms are known to trigger rockfalls, many rockfalls occur during periods when likely triggers such as precipitation, seismic activity and freezing conditions are absent. It has been suggested that these enigmatic rockfalls may occur due to solar heating of rock surfaces, which can cause outward expansion. Here we use data from 3.5 years of field monitoring of an exfoliating granite cliff in Yosemite National Park in California, USA, to assess the magnitude and temporal pattern of thermally induced rock deformation. From a thermodynamic analysis, we find that daily, seasonal and annual temperature variations are sufficient to drive cyclic and cumulative opening of fractures. Application of fracture theory suggests that these changes can lead to further fracture propagation and the consequent detachment of rock. Our data indicate that the warmest times of the day and year are particularly conducive to triggering rockfalls, and that cyclic thermal forcing may enhance the efficacy of other, more typical rockfall triggers.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/ngeo2686","collaboration":"National Park Service","usgsCitation":"Collins, B.D., and Stock, G.M., 2016, Rockfall triggering by cyclic thermal stressing of exfoliation fractures: Nature Geoscience, v. 9, p. 395-400, https://doi.org/10.1038/ngeo2686.","productDescription":"7 p.","startPage":"395","endPage":"400","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064900","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":323258,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.66308593749999,\n 37.496652341233364\n ],\n [\n -119.57244873046874,\n 37.49556277942662\n ],\n [\n -119.57382202148439,\n 37.53368798315969\n ],\n [\n -119.43923950195312,\n 37.536954951447285\n ],\n [\n -119.388427734375,\n 37.554376365024865\n ],\n [\n -119.36920166015624,\n 37.63054716639914\n ],\n [\n -119.32388305664064,\n 37.63380988687157\n ],\n [\n -119.25659179687499,\n 37.72836644908416\n ],\n [\n -119.26895141601562,\n 37.74248523826606\n ],\n [\n -119.20166015625,\n 37.80001858607365\n ],\n [\n -119.20028686523438,\n 37.89002800137122\n ],\n [\n -119.23599243164062,\n 37.91061711049342\n ],\n [\n -119.31289672851562,\n 37.9593578107923\n ],\n [\n -119.32113647460936,\n 37.97451499202459\n ],\n [\n -119.31015014648438,\n 38.04484662140698\n ],\n [\n -119.34722900390625,\n 38.08593231319764\n ],\n [\n -119.42825317382811,\n 38.11943249695316\n ],\n [\n -119.44198608398438,\n 38.098901948321256\n ],\n [\n -119.46533203125,\n 38.098901948321256\n ],\n [\n -119.47219848632812,\n 38.13023573104302\n ],\n [\n -119.50241088867188,\n 38.158316657442\n ],\n [\n -119.50790405273436,\n 38.135636748588574\n ],\n [\n -119.57382202148439,\n 38.161556068786886\n ],\n [\n -119.58755493164061,\n 38.187466178077905\n ],\n [\n -119.62326049804688,\n 38.1680344597114\n ],\n [\n -119.62600708007812,\n 38.15291731872143\n ],\n [\n -119.7015380859375,\n 38.13239618602294\n ],\n [\n -119.73724365234375,\n 38.09998264736481\n ],\n [\n -119.81414794921875,\n 38.09674050228651\n ],\n [\n -119.83886718750001,\n 38.089174937729794\n ],\n [\n -119.87457275390625,\n 38.05566088242076\n ],\n [\n -119.88693237304688,\n 37.98642201062662\n ],\n [\n -119.88555908203126,\n 37.89327929625019\n ],\n [\n -119.82650756835938,\n 37.89219554724437\n ],\n [\n -119.827880859375,\n 37.83798775896512\n ],\n [\n -119.871826171875,\n 37.81195385919268\n ],\n [\n -119.87594604492188,\n 37.791337175930686\n ],\n [\n -119.85260009765624,\n 37.738141282210385\n ],\n [\n -119.7784423828125,\n 37.73922729512254\n ],\n [\n -119.77981567382812,\n 37.7109857819458\n ],\n [\n -119.7674560546875,\n 37.68708070686609\n ],\n [\n -119.81277465820312,\n 37.67947293019486\n ],\n [\n -119.81277465820312,\n 37.665342132088284\n ],\n [\n -119.761962890625,\n 37.669690356567855\n ],\n [\n -119.71389770507814,\n 37.65338320128765\n ],\n [\n -119.72625732421874,\n 37.642509774448754\n ],\n [\n -119.72351074218749,\n 37.62945956107554\n ],\n [\n -119.69604492187499,\n 37.62837193983584\n ],\n [\n -119.69467163085936,\n 37.58267747761301\n ],\n [\n -119.70428466796875,\n 37.579412513438385\n ],\n [\n -119.70016479492188,\n 37.54893261064111\n ],\n [\n -119.66308593749999,\n 37.496652341233364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-28","publicationStatus":"PW","scienceBaseUri":"57594231e4b04f417c256989","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":637686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stock, Greg M.","contributorId":88593,"corporation":false,"usgs":true,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637687,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70158609,"text":"sir20155141 - 2016 - Hydrologic data and groundwater-flow simulations in the Brown Ditch Watershed, Indiana Dunes National Lakeshore, near Beverly Shores and Town of Pines, Indiana","interactions":[],"lastModifiedDate":"2016-03-18T09:27:57","indexId":"sir20155141","displayToPublicDate":"2016-03-15T09:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5141","title":"Hydrologic data and groundwater-flow simulations in the Brown Ditch Watershed, Indiana Dunes National Lakeshore, near Beverly Shores and Town of Pines, Indiana","docAbstract":"The U.S. Geological Survey (USGS) collected data and simulated groundwater flow to increase understanding of the hydrology and the effects of drainage alterations on the water table in the vicinity of Great Marsh, near Beverly Shores and Town of Pines, Indiana. Prior land-management practices have modified drainage and caused changes in the distribution of open water, streams and ditches, and groundwater abundance and flow paths.
\nCollected hydrologic data indicate that the majority of water entering Great Marsh flows from the southern dune ridge beneath Town of Pines, Indiana. Groundwater flow is intercepted by Brown Ditch in the eastern portion of the study area and Derby Ditch in the western portion of the study area. A smaller amount of groundwater from the northern dune ridge beneath Beverly Shores also contributed water to Great Marsh. Continuous groundwater-level data collected indicate that the predominant north-south groundwater-flow gradients vary during the course of the year due to increased levels of precipitation or during periods of drainage obstructions. Continuous surface-water discharge and surface-water elevation were measured at three USGS streamgages, one each on Brown, Kintzele and Derby Ditches. The monthly mean discharge statistics indicate that during the period of record— June 2012 to September 2013—streamflow in Kintzele Ditch was lowest during July 2012 and highest during April 2013. In Derby Ditch, streamflow also was lowest during July 2012 and highest during April 2013.
\nPeriods of relatively high and low groundwater levels during August 1982, March 2013, and April 2014 were examined and simulated by using MODFLOW and companion software. Results from the simulation of conditions during March 2013 include that nearly 100 percent of all water entering the area simulating Town of Pines is from recharge. Of all the water simulated to enter the eastern and western portions of Great Marsh, nearly 20 and 18 percent, respectively, flows from Town of Pines to the western and eastern portions of Great Marsh. The dune ridges beneath Town of Pines and to a lesser extent beneath Beverly Shores are a major source of recharge to the surficial aquifer and Great Marsh.
\nResults from the simulation of the conditions of April 2014 include that, despite increases in the amount of water entering Great Marsh due to a beaver-dam-modified hydrologic condition, there is still virtually zero simulated groundwater flow from Great Marsh to Town of Pines. The volume of water simulated to be entering the zone representing Beverly Shores decreased by 0.43 cubic foot per second from the results of the March 2013 simulation. This simulated difference in water budgets can be attributed to increased simulated recharge in Great Marsh and Town of Pines. Effects of the inclusion of the beaver dam included the increase of the simulated water table and simulated inundated area upstream of the beaver dam due to the effects of ponding surface water.
\nResults from the simulation scenario that includes six proposed pool-riffle control structures in Brown Ditch under the hydrologic conditions of March 2013 indicate areas inundated by water are larger, including areas just to the north of the entrance of Brown Ditch into Great Marsh, and areas north of the confluence of Brown and Kintzele Ditches.
\nResults from the scenario simulating the increase of the Lake Michigan water level to the historical high of May 31, 1998, showed inundated areas of Great Marsh south of Beverly Shores enlarged on both sides of Lakeshore County Road with the greatest enlargement simulated to be southeast of the intersection of Lakeshore County Road and Beverly Drive. For the scenario simulating the decrease of the Lake Michigan water level to the historical low of December 23, 2007, results show little change from the original March 2013 inundated area.
\nThe results of this study can be used by water-resource managers to understand how surrounding ditches affect water levels in Great Marsh and other inland wetlands and residential areas. The groundwater model developed can be applied to answer questions about how alterations to the drainage system in the area affects water levels in the public and residential areas surrounding Great Marsh. The modeling methods developed in this study provide a template for other studies of groundwater flow and groundwater/surface-water interactions within the shallow surficial aquifer in northern Indiana, and in similar hydrologic settings that include surficial sand aquifers in coastal areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155141","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lampe, D.C., 2015, Hydrologic data and groundwater-flow simulations in the Brown Ditch Watershed, Indiana Dunes National Lakeshore, near Beverly Shores and Town of Pines, Indiana: U.S. Geological Survey Scientific Investigations Report 2015– 5141, 97 p., https://dx.doi.org/10.3133/sir20155141.","productDescription":"xi, 97 p.","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055857","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":318807,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5141/coverthb.jpg"},{"id":318808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5141/sir20155141.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5141"}],"country":"United States","state":"Indiana","otherGeospatial":"Brown Ditch Watershed, Indiana Dunes National Lakeshore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1,\n 41.65\n ],\n [\n -87.1,\n 41.73\n ],\n [\n -86.9,\n 41.73\n ],\n [\n -86.9,\n 41.65\n ],\n [\n -87.1,\n 41.65\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
Phone: (317) 290-3333
http://in.water.usgs.gov/
Drought conditions during the study period of January 1, 2009, to September 30, 2013, caused a reduction in surface-water releases from water-supply storage infrastructure of the Rio Grande Project, which led to changes in surface-water and groundwater (conjunctive) use in downstream agricultural alluvial valleys. Surface water and groundwater in the agriculturally dominated alluvial Rincon and Mesilla Valleys were investigated in this study to measure the influence of drought and subsequent change in conjunctive water use on quantity and quality of these water resources. In 2013, the U.S. Geological Survey, in cooperation with the New Mexico Environment Department and the New Mexico Interstate Stream Commission, began a study to (1) calculate dissolved-solids loads over the study period at streamgages in the study area where data are available, (2) assess the temporal variability of dissolved-solids loads at and between each streamgage where data are available, and (3) relate the spatiotemporal variability of shallow groundwater data (groundwater levels and quality) within the alluvial valleys of the study area to spatiotemporal variability of surface-water data over the study period. This assessment included the calculation of surface-water dissolved-solids loads at streamgages as well as a mass-balance approach to measure the change in salt load between these streamgages. Bimodal surface-water discharge data led to a temporally-dynamic volumetric definition of release and nonrelease seasons. Continuous surface-water discharge and water-quality data from three streamgages on the Rio Grande were used to calculate daily dissolved-solids loads over the study period, and the results were aggregated annually and seasonally. Results show the majority of dissolved-solids loading occurs during release season; however, decreased duration of the release season over the 5-year study period has resulted in a decrease of the total annual loads at each streamgage. Calculation of the change of salt loads using a mass-balance approach was applied between streamgages. Results from these calculations suggest differing responses to releases in the Rincon and Mesilla Valleys over the period of study; there is a decreasing sink of salt in the Rincon Valley whereas there is an increasing sink of salt in the Mesilla Valley. Daily groundwater-level and water-quality data from shallow wells within the two alluvial valleys show spatial heterogeneity of water quality over the study period. Mass-balance salt-loading trends during the study period are similar to previous trends during the 1950s drought as well as a wet period in the 1980s. The similarity of salt-loading trends from the 1950s, 1980s, and 2000s independent of the climate indicates salt loading in this hydrologic setting may be driven by water-use practices rather than a single climatic variable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165006","collaboration":"Prepared in cooperation with the New Mexico Environment Department and the New Mexico Interstate Stream Commission","usgsCitation":"Driscoll, J.M., and Sherson, L.R., 2016, Variability of surface-water quantity and quality and shallow groundwater levels and quality within the Rio Grande Project area, New Mexico and Texas, 2009–13: U.S. Geological Survey Scientific Investigations Report 2016–5006, 33 p., https://dx.doi.org/10.3133/sir20165006.","productDescription":"vi, 33 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065706","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":318886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5006/coverthb.jpg"},{"id":318887,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5006/sir20165006.pdf","text":"Report","size":"1.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5006"}],"country":"United States","state":"New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.46826171874999,\n 31.076460800121122\n ],\n [\n -107.46826171874999,\n 33.367237465838315\n ],\n [\n -105.6060791015625,\n 33.367237465838315\n ],\n [\n -105.6060791015625,\n 31.076460800121122\n ],\n [\n -107.46826171874999,\n 31.076460800121122\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery, NE
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This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS).
Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 wk depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2–4 wk), whereas corn conditions were more closely related to longer-range (8–12 wk) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2015.12.065","usgsCitation":"Otkin, J.A., Anderson, M.C., Hain, C., Svoboda, M., Johnson, D., Mueller, R., Tadesse, T., Wardlow, B.D., and Brown, J.F., 2016, Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought: Agricultural and Forest Meteorology, v. 218-219, p. 230-242, https://doi.org/10.1016/j.agrformet.2015.12.065.","productDescription":"13 p.","startPage":"230","endPage":"242","ipdsId":"IP-071141","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2015.12.065","text":"Publisher Index Page"},{"id":342143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"218-219","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2ee4b0f6c2d0d9c762","contributors":{"authors":[{"text":"Otkin, Jason A.","contributorId":192635,"corporation":false,"usgs":false,"family":"Otkin","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":697203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Martha C.","contributorId":96579,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","email":"","middleInitial":"C.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":697204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hain, Christopher","contributorId":191966,"corporation":false,"usgs":false,"family":"Hain","given":"Christopher","email":"","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight 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Center","active":true,"usgs":true}],"preferred":true,"id":697191,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70156192,"text":"70156192 - 2016 - Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4","interactions":[],"lastModifiedDate":"2017-05-12T11:35:31","indexId":"70156192","displayToPublicDate":"2016-03-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4","docAbstract":"Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Climate change in wildlands: Pioneering approaches to science and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Island Press","publisherLocation":"Washington, D.C.","doi":"10.5822/978-1-61091-713-1_4","usgsCitation":"Gross, J.E., Tercek, M., Guay, K., Chang, T., Talbert, M., Thoma, D., Rodman, A., Jantz, P., and Morisette, J.T., 2016, Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4, chap. of Climate change in wildlands: Pioneering approaches to science and management, p. 55-77, https://doi.org/10.5822/978-1-61091-713-1_4.","productDescription":"23 p.","startPage":"55","endPage":"77","ipdsId":"IP-067022","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":341203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountains","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b5e4b044b359e4869c","contributors":{"authors":[{"text":"Gross, John E.","contributorId":106777,"corporation":false,"usgs":false,"family":"Gross","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":567988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tercek, Michael","contributorId":146469,"corporation":false,"usgs":false,"family":"Tercek","given":"Michael","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":694979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guay, Kevin","contributorId":146470,"corporation":false,"usgs":false,"family":"Guay","given":"Kevin","email":"","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":694980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chang, Tony","contributorId":191992,"corporation":false,"usgs":false,"family":"Chang","given":"Tony","email":"","affiliations":[],"preferred":false,"id":694981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":191730,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":694982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rodman, Ann","contributorId":150932,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":694983,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thoma, David","contributorId":190258,"corporation":false,"usgs":false,"family":"Thoma","given":"David","affiliations":[],"preferred":false,"id":694984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jantz, Patrick","contributorId":191993,"corporation":false,"usgs":false,"family":"Jantz","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":694985,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":567987,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70169030,"text":"ofr20161041 - 2016 - Effects of experimental removal of barred owls on population demography of northern spotted owls in Washington and Oregon—2015 progress report","interactions":[],"lastModifiedDate":"2017-11-22T15:49:13","indexId":"ofr20161041","displayToPublicDate":"2016-03-14T19:00:00","publicationYear":"2016","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":"2016-1041","title":"Effects of experimental removal of barred owls on population demography of northern spotted owls in Washington and Oregon—2015 progress report","docAbstract":"Evidence indicates that competition with newly established barred owls (Strix varia) is causing rapid declines in populations of northern spotted owls (Strix occidentalis caurina), and that the longterm persistence of spotted owls may be in question without additional management intervention. A pilot study in California showed that lethal removal of barred owls in combination with habitat conservation may be able to slow or even reverse population declines of spotted owls at local scales, but it remains unknown whether similar results can be obtained in larger areas with different forest conditions and where barred owls are more abundant. In 2015, we implemented a before-after-controlimpact (BACI) experimental design on two study areas in Oregon and Washington with at least 20 years of pre-treatment demographic data on spotted owls to determine if removal of barred owls can improve population trends of spatially associated spotted owls. Here we provide an overview of our research accomplishments and preliminary results in Oregon and Washington in 2015.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161041","usgsCitation":"Wiens, J.D., Dugger, K.M., Lewicki, K.E., and Simon, D.C., 2016, Effects of experimental removal of barred owls on population demography of northern spotted owls in Washington and Oregon—2015 progress report: U.S. Geological Survey Open-File Report 2016-1041, 16 p., https://dx.doi.org/10.3133/ofr20161041.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072911","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":318862,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1041/ofr20161041.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1041"},{"id":318861,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1041/coverthb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.31054687499999,\n 49.023461463214126\n ],\n [\n -117.04833984375001,\n 49.023461463214126\n ],\n [\n -117.02636718749999,\n 46.31658418182218\n ],\n [\n -116.91650390625,\n 46.164614496897094\n ],\n [\n -116.89453125,\n 46.07323062540838\n ],\n [\n -117.02636718749999,\n 45.9511496866914\n ],\n [\n -116.71874999999999,\n 45.82879925192134\n ],\n [\n -116.49902343749999,\n 45.72152152227954\n ],\n [\n -116.52099609375,\n 45.537136680398596\n ],\n [\n -116.65283203124999,\n 45.30580259943578\n ],\n [\n -116.69677734375,\n 45.1510532655634\n ],\n [\n -116.8505859375,\n 44.98034238084973\n ],\n [\n -116.8505859375,\n 44.91813929958515\n ],\n [\n -117.04833984375001,\n 44.68427737181225\n ],\n [\n -117.158203125,\n 44.55916341529184\n ],\n [\n -117.20214843749999,\n 44.38669150215206\n ],\n [\n -117.158203125,\n 44.26093725039923\n ],\n [\n -116.91650390625,\n 44.213709909702054\n ],\n [\n -116.806640625,\n 44.071800467511565\n ],\n [\n -116.93847656250001,\n 43.929549935614595\n ],\n [\n -117.04833984375001,\n 43.73935207915473\n ],\n [\n -117.04833984375001,\n 41.96765920367816\n ],\n [\n -124.25537109375,\n 41.96765920367816\n ],\n [\n -124.45312499999999,\n 42.19596877629178\n ],\n [\n -124.49707031249999,\n 42.42345651793833\n ],\n [\n -124.43115234375,\n 42.569264372193864\n ],\n [\n -124.51904296875,\n 42.68243539838623\n ],\n [\n -124.60693359374999,\n 42.81152174509788\n ],\n [\n -124.43115234375,\n 43.229195113965005\n ],\n [\n -124.51904296875,\n 43.34116005412307\n ],\n [\n -124.29931640625,\n 43.40504748787035\n ],\n [\n -124.21142578125,\n 43.73935207915473\n ],\n [\n -124.21142578125,\n 44.402391829093915\n ],\n [\n -124.12353515624999,\n 44.762336674810996\n ],\n [\n -124.01367187499999,\n 45.19752230305685\n ],\n [\n -123.99169921875,\n 45.61403741135093\n ],\n [\n -124.01367187499999,\n 45.9511496866914\n ],\n [\n -123.99169921875,\n 46.13417004624326\n ],\n [\n -124.1455078125,\n 46.240651955001695\n ],\n [\n -124.16748046874999,\n 46.66451741754235\n ],\n [\n -124.21142578125,\n 46.93526088057719\n ],\n [\n -124.25537109375,\n 47.234489635299184\n ],\n [\n -124.43115234375,\n 47.39834920035926\n ],\n [\n -124.47509765625,\n 47.635783590864854\n ],\n [\n -124.73876953125,\n 47.945786463687185\n ],\n [\n -124.73876953125,\n 48.268569112964336\n ],\n [\n -124.73876953125,\n 48.516604348867475\n ],\n [\n -124.34326171874999,\n 48.45835188280866\n ],\n [\n -123.94775390625,\n 48.268569112964336\n ],\n [\n -123.59619140625001,\n 48.25394114463431\n ],\n [\n -123.33251953125,\n 48.25394114463431\n ],\n [\n -123.1787109375,\n 48.4146186174932\n ],\n [\n -123.31054687499999,\n 48.69096039092549\n ],\n [\n -123.06884765625,\n 48.76343113791796\n ],\n [\n -123.11279296875001,\n 48.850258199721495\n ],\n [\n -123.31054687499999,\n 49.023461463214126\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov
Linking marine epizootics to a specific aetiology is notoriously difficult. Recent diagnostic successes show that marine disease diagnosis requires both modern, cutting-edge technology (e.g. metagenomics, quantitative real-time PCR) and more classic methods (e.g. transect surveys, histopathology and cell culture). Here, we discuss how this combination of traditional and modern approaches is necessary for rapid and accurate identification of marine diseases, and emphasize how sole reliance on any one technology or technique may lead disease investigations astray. We present diagnostic approaches at different scales, from the macro (environment, community, population and organismal scales) to the micro (tissue, organ, cell and genomic scales). We use disease case studies from a broad range of taxa to illustrate diagnostic successes from combining traditional and modern diagnostic methods. Finally, we recognize the need for increased capacity of centralized databases, networks, data repositories and contingency plans for diagnosis and management of marine disease.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2015.0207","usgsCitation":"Burge, C.A., Friedman, C., Getchell, R.G., House, M., Lafferty, K.D., Mydlarz, L.D., Prager, K.C., Sutherland, K.P., Renault, T., Kiryu, I., and Vega-Thurber, R., 2016, Complementary approaches to diagnosing marine diseases: a union of the modern and the classic: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 371, p. 1-11, https://doi.org/10.1098/rstb.2015.0207.","productDescription":"Article 20150207; 11 p.","startPage":"1","endPage":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071582","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471153,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2015.0207","text":"Publisher Index Page"},{"id":318858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"371","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56e7d299e4b0f59b85d64006","contributors":{"authors":[{"text":"Burge, Colleen A.","contributorId":34814,"corporation":false,"usgs":true,"family":"Burge","given":"Colleen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":622715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedman, Carolyn S.","contributorId":13890,"corporation":false,"usgs":true,"family":"Friedman","given":"Carolyn S.","affiliations":[],"preferred":false,"id":622716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Getchell, Rodman G.","contributorId":32416,"corporation":false,"usgs":true,"family":"Getchell","given":"Rodman","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":622717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"House, Marcia","contributorId":167561,"corporation":false,"usgs":false,"family":"House","given":"Marcia","email":"","affiliations":[{"id":7059,"text":"Northwest Indian Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":622718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":622714,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mydlarz, Laura D.","contributorId":167562,"corporation":false,"usgs":false,"family":"Mydlarz","given":"Laura","email":"","middleInitial":"D.","affiliations":[{"id":24751,"text":"University of Texas Arlington","active":true,"usgs":false}],"preferred":false,"id":622719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prager, Katherine C.","contributorId":8366,"corporation":false,"usgs":true,"family":"Prager","given":"Katherine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":622720,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sutherland, Kathryn P.","contributorId":167563,"corporation":false,"usgs":false,"family":"Sutherland","given":"Kathryn","email":"","middleInitial":"P.","affiliations":[{"id":24752,"text":"Rollins College","active":true,"usgs":false}],"preferred":false,"id":622721,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Renault, Tristan","contributorId":167564,"corporation":false,"usgs":false,"family":"Renault","given":"Tristan","email":"","affiliations":[{"id":24753,"text":"Ifremer, De´partement Ressources Biologiques et Environnement, rue de l’Ile d’Yeu","active":true,"usgs":false}],"preferred":false,"id":622722,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kiryu, Ikunari","contributorId":167565,"corporation":false,"usgs":false,"family":"Kiryu","given":"Ikunari","email":"","affiliations":[{"id":24754,"text":"National Research Institute of Aquaculture, Fisheries Research Agency","active":true,"usgs":false}],"preferred":false,"id":622723,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vega-Thurber, Rebecca","contributorId":167566,"corporation":false,"usgs":false,"family":"Vega-Thurber","given":"Rebecca","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":622724,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70169058,"text":"70169058 - 2016 - What a drag: Quantifying the global impact of chronic bottom trawling on continental shelf sediment","interactions":[],"lastModifiedDate":"2021-01-07T18:48:40.164069","indexId":"70169058","displayToPublicDate":"2016-03-14T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2381,"text":"Journal of Marine Systems","active":true,"publicationSubtype":{"id":10}},"title":"What a drag: Quantifying the global impact of chronic bottom trawling on continental shelf sediment","docAbstract":"Continental shelves worldwide are subject to intense bottom trawling that causes sediment to be resuspended. The widely used traditional concepts of modern sedimentary transport systems on the shelf rely only on estimates for naturally driven sediment resuspension such as through storm waves, bottom currents, and gravity-driven flows but they overlook a critical anthropogenic factor. The strong influence of bottom trawling on a source-to-sink sediment budget is explored on the NW Iberian shelf. Use of Automated Information System vessel tracking data provides for a high-resolution vessel track reconstruction and the accurate calculation of the spatial distribution of bottom trawling intensity and associated resuspended sediment load. The mean bottom trawling-induced resuspended sediment mass for the NW Iberian shelf is 13.50 Mt yr− 1, which leads to a six-fold increase in off-shelf sediment transport when compared to natural resuspension mechanisms. The source-to-sink budget analysis provides evidence that bottom trawling causes a rapid erosion of the fine sediment on human time scales. Combining global soft sediment distribution data of the shelves with worldwide bottom trawling intensity estimates we show that the bottom trawling-induced resuspended sediment mass amounts to approximately the same mass of all sediment entering the shelves through rivers. Spatial delineations between natural and anthropogenic sediment resuspension areas are presented to aid in marine management questions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jmarsys.2015.12.007","usgsCitation":"Oberle, F.K., Storlazzi, C.D., and Hanebuth, T.J., 2016, What a drag: Quantifying the global impact of chronic bottom trawling on continental shelf sediment: Journal of Marine Systems, v. 159, p. 109-119, https://doi.org/10.1016/j.jmarsys.2015.12.007.","productDescription":"11 p.","startPage":"109","endPage":"119","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063932","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":318859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"159","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e7d29be4b0f59b85d6401a","contributors":{"authors":[{"text":"Oberle, Ferdinand K. J. 0000-0001-8871-3619","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":167559,"corporation":false,"usgs":false,"family":"Oberle","given":"Ferdinand","email":"","middleInitial":"K. J.","affiliations":[{"id":24749,"text":"University of Bremen","active":true,"usgs":false}],"preferred":false,"id":622712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":622711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanebuth, Till J.J.","contributorId":167560,"corporation":false,"usgs":false,"family":"Hanebuth","given":"Till","email":"","middleInitial":"J.J.","affiliations":[{"id":24750,"text":"Coastal Carolina University","active":true,"usgs":false}],"preferred":false,"id":622713,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70162298,"text":"sir20155181 - 2016 - Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota","interactions":[],"lastModifiedDate":"2016-03-14T11:52:52","indexId":"sir20155181","displayToPublicDate":"2016-03-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5181","title":"Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota","docAbstract":"Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water; however, streamgages cannot be installed at every location where streamflow information is needed. Therefore, methods for estimating streamflow at ungaged stream locations need to be developed. This report presents a statewide study to develop methods to estimate the structure of historical daily streamflow at ungaged stream locations in Minnesota. Historical daily mean streamflow at ungaged locations in Minnesota can be estimated by transferring streamflow data at streamgages to the ungaged location using the QPPQ method. The QPPQ method uses flow-duration curves at an index streamgage, relying on the assumption that exceedance probabilities are equivalent between the index streamgage and the ungaged location, and estimates the flow at the ungaged location using the estimated flow-duration curve. Flow-duration curves at ungaged locations can be estimated using recently developed regression equations that have been incorporated into StreamStats (http://streamstats.usgs.gov/), which is a U.S. Geological Survey Web-based interactive mapping tool that can be used to obtain streamflow statistics, drainage-basin characteristics, and other information for user-selected locations on streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155181","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Lorenz, D.L., and Ziegeweid, J.R., 2016, Methods to estimate historical daily streamflow for ungaged stream locations in Minnesota: U.S. Geological Survey Scientific Investigations Report 2015–5181, 18 p., https://dx.doi.org/10.3133/sir20155181.","productDescription":"iv, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068751","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":318797,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5181/coverthb.jpg"},{"id":318798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5181/sir20155181.pdf","text":"Report","size":"2.91 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\"}}]}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
The loss of historic ecosystem conditions has led forest managers to implement woodland and savanna ecosystem restoration on a landscape scale (≥10,000 ha) in the Ozark Plateau of Arkansas. Managers are attempting to restore and conserve these ecosystems through the reintroduction of disturbance, mainly short-rotation early-growing-season prescribed fire. Short-rotation early-growing season prescribed fire in the Ozarks typically occurs immediately before bud-break, through bud-break, and before leaf-out, and fire events occur on a three-to five-year interval. We examined short-rotation early-growing season prescribed fire as a restoration tool on vegetation characteristics. We collected vegetation measurements at 70 locations annually from 2011 to 2012 in and around the White Rock Ecosystem Restoration Area (WRERA), Ozark-St. Francis National Forest, Arkansas, and used generalized linear models to investigate the impact and efficacy of prescribed fire on vegetation structure. We found the number of large shrubs (>5 cm base diameter) decreased and small shrubs (<5 cm ground diameter) increased with prescribed fire severity. We found that horizontal understory cover from ground level to 1 m in height increased with time-since-prescribed-fire and woody ground cover decreased with the number of prescribed fire treatments. Using LANDFIRE datasets at the landscape scale, we found that since the initiation of a short-rotation early-growing season prescribed fire management regime, forest canopy cover has not reverted to levels characteristic of woodlands and savannas or reached restoration objectives over large areas. Without greater reductions in forest canopy cover and increases in forest-canopy cover heterogeneity, advanced regeneration will be limited in success, and woodland and savanna conditions will not return soon or to the extent desired.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Pittman, H.T., and Krementz, D.G., 2016, Efficacy of landscape scale woodland and savanna restoration at multiple spatial and temporal scales: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 3, p. 233-242.","productDescription":"10 p.","startPage":"233","endPage":"242","ipdsId":"IP-059541","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349021,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.seafwa.org/publications/journal/?id=402058"},{"id":349022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Ozark Highlands","volume":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd6be4b06e28e9c24d6e","contributors":{"authors":[{"text":"Pittman, H. Tyler","contributorId":200530,"corporation":false,"usgs":false,"family":"Pittman","given":"H.","email":"","middleInitial":"Tyler","affiliations":[],"preferred":false,"id":722562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718106,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169057,"text":"70169057 - 2016 - Coherent late-Holocene climate-driven shifts in the structure of three Rocky Mountain lakes","interactions":[],"lastModifiedDate":"2016-12-16T11:07:43","indexId":"70169057","displayToPublicDate":"2016-03-11T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3562,"text":"The Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Coherent late-Holocene climate-driven shifts in the structure of three Rocky Mountain lakes","docAbstract":"Large-scale atmospheric pressure centers, such as the Aleutian and Icelandic Low, have a demonstrated relationship with physical lake characteristics in contemporary monitoring studies, but the responses to these phenomena are rarely observed in lake records. We observe coherent changes in the stratification patterns of three deep (>30 m) lakes inferred from fossil diatom assemblages as a response to shifts in the location and intensity of the Aleutian Low and compare these changes with similar long-term changes observed in the δ18O record from the Yukon. Specifically, these records indicate that between 3.2 and 1.4 ka, the Aleutian Low shifted westward, resulting in an increased frequency of storm tracks across the Pacific Northwest during winter and spring. This change in atmospheric circulation ultimately produced deeper mixing in the upper waters of these three lake systems. Enhanced stratification between 4.5 and 3.3 ka and from 1.3 ka to present suggests a strengthened Aleutian Low and more meridional circulation.
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demographic consequences vary across species","docAbstract":"Behavioural responses to reduce predation risk might cause demographic ‘costs of fear’. Costs differ among species, but a conceptual framework to understand this variation is lacking. We use a life-history framework to tie together diverse traits and life stages to better understand interspecific variation in responses and costs. We used natural and experimental variation in predation risk to test phenotypic responses and associated demographic costs for 10 songbird species. Responses such as increased parental attentiveness yielded reduced development time and created benefits such as reduced predation probability. Yet, responses to increased risk also created demographic costs by reducing offspring production in the absence of direct predation. This cost of fear varied widely across species, but predictably with the probability of repeat breeding. Use of a life-history framework can aid our understanding of potential demographic costs from predation, both from responses to perceived risk and from direct predation mortality.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12573","usgsCitation":"LaManna, J.A., and Martin, T.E., 2016, Costs of fear: Behavioral and life-history responses to risk and their demographic consequences vary across species: Ecology Letters, v. 19, no. 4, p. 403-413, https://doi.org/10.1111/ele.12573.","productDescription":"10 p.","startPage":"403","endPage":"413","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069480","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-22","publicationStatus":"PW","scienceBaseUri":"575be4abe4b04f417c27f515","contributors":{"authors":[{"text":"LaManna, Joseph A.","contributorId":171738,"corporation":false,"usgs":false,"family":"LaManna","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":638459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638367,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169195,"text":"70169195 - 2016 - Hydrologic controls on nitrogen cycling processes and functional gene abundance in sediments of a groundwater flow-through lake","interactions":[],"lastModifiedDate":"2018-08-07T12:10:20","indexId":"70169195","displayToPublicDate":"2016-03-11T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic controls on nitrogen cycling processes and functional gene abundance in sediments of a groundwater flow-through lake","docAbstract":"The fate and transport of inorganic nitrogen (N) is a critically important issue for human and aquatic ecosystem health because discharging N-contaminated groundwater can foul drinking water and cause algal blooms. Factors controlling N-processing were examined in sediments at three sites with contrasting hydrologic regimes at a lake on Cape Cod, MA. These factors included water chemistry, seepage rates and direction of groundwater flow, and the abundance and potential rates of activity of N-cycling microbial communities. Genes coding for denitrification, anaerobic ammonium oxidation (anammox), and nitrification were identified at all sites regardless of flow direction or groundwater dissolved oxygen concentrations. Flow direction was, however, a controlling factor in the potential for N-attenuation via denitrification in the sediments. Potential rates of denitrification varied from 6 to 4500 pmol N/g/h from the inflow to the outflow side of the lake, owing to fundamental differences in the supply of labile organic matter. The results of laboratory incubations suggested that when anoxia and limiting labile organic matter prevailed, the potential existed for concomitant anammox and denitrification. Where oxic lake water was downwelling, potential rates of nitrification at shallow depths were substantial (1640 pmol N/g/h). Rates of anammox, denitrification, and nitrification may be linked to rates of organic N-mineralization, serving to increase N-mobility and transport downgradient.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5b06155","usgsCitation":"Stoliker, D., Repert, D.A., Smith, R.L., Song, B., LeBlanc, D.R., McCobb, T.D., Conaway, C.H., Hyun, S.P., Koh, D., Moon, H.S., and Kent, D.B., 2016, Hydrologic controls on nitrogen cycling processes and functional gene abundance in sediments of a groundwater flow-through lake: Environmental Science & Technology, v. 50, no. 7, p. 3649-3657, https://doi.org/10.1021/acs.est.5b06155.","productDescription":"9 p.","startPage":"3649","endPage":"3657","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071251","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology 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