{"pageNumber":"630","pageRowStart":"15725","pageSize":"25","recordCount":184883,"records":[{"id":70211035,"text":"70211035 - 2020 - Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise","interactions":[],"lastModifiedDate":"2020-07-13T12:49:43.365018","indexId":"70211035","displayToPublicDate":"2020-05-12T07:46:26","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise","docAbstract":"Coastal wetlands are rich and diverse ecosystems with a wide variety of birdlife and other natural resources. Decision making for coastal wetland management is difficult given the complex nature of these ecological systems and the frequent need to meet multiple objectives for varied resources. Management challenges in the coastal zone are exacerbated by uncertainty about sea level rise and impacts on infrastructure, particularly the levees and structures which provide managers the ability to manipulate water levels in managed wetlands and create high quality habitat for birds and other wildlife. The most challenging decisions in coastal wetland management involve resource allocation for habitat manipulations and longer-term investments to maintain management control in wetlands that are increasingly compromised by sea level rise and increasing storm frequency and intensity associated with a changing climate.\nWe used multi-criteria decision analysis to create a resource allocation framework for managed wetlands that identifies the most effective and efficient management strategies that are robust to uncertainty about sea level rise. The prototype framework includes a small number of managed wetlands, for which subject matter experts articulated potential management and restoration actions. The consequences of these actions were predicted using expert elicitation with the subject matter experts; furthermore, expert judgment was used to articulate expected outcomes with two hypotheses about the rate of sea level rise. We used a constrained optimization (integer linear programming) to find optimal resource allocation strategies given a range of budget constraints; we also used a Pareto efficiency analysis for a graphical solution to the problem if the exact budget constraint is not known. Finally, given the importance of preference weights in a multi-criteria decision analysis, we also evaluated sensitivity to objective weights. With this resource allocation framework, we showed how to identify optimal combinations of management and restoration actions to maximize benefits in terms of stated objectives. We show how multiple working hypotheses about sea level rise can be incorporated into decisions for coastal wetland management. Our resource allocation approach can be modified for a wide variety of natural resource management settings.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Structured decision making: Case studies in natural resource management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins Press","usgsCitation":"Lyons, J., Kalasz, K., Breese, G., and Boal, C.W., 2020, Resource allocation for coastal wetland management: Confronting uncertainty about sea level rise, chap. 10 of Structured decision making: Case studies in natural resource management, p. 108-123.","productDescription":"16 p.","startPage":"108","endPage":"123","ipdsId":"IP-102721","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":376271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":376270,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/structured-decision-making/table-of-contents"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":228916,"corporation":false,"usgs":true,"family":"Lyons","given":"James E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":792525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalasz, Kevin S.","contributorId":228917,"corporation":false,"usgs":false,"family":"Kalasz","given":"Kevin S.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":792526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breese, Gregory","contributorId":228918,"corporation":false,"usgs":false,"family":"Breese","given":"Gregory","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":792527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":792528,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226671,"text":"70226671 - 2020 - Feeding ecology of age-0 gar at Lake Texoma inferred from analysis of stable isotopes","interactions":[],"lastModifiedDate":"2021-12-03T13:14:39.832751","indexId":"70226671","displayToPublicDate":"2020-05-12T07:13:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Feeding ecology of age-0 gar at Lake Texoma inferred from analysis of stable isotopes","docAbstract":"

Conservation and restoration of gar (Lepisosteidae) populations in North America are increasingly of interest to fisheries managers. Alligator Gar Atractosteus spatula are being stocked as age-0 fish in efforts to re-establish extirpated populations. However, gars are known to be highly cannibalistic in hatcheries, suggesting that age-0 Alligator Gar introduced into natural habitats may face predation pressures from other gar species, limiting the likelihood of released fish recruiting to the population. Furthermore, introduced age-0 gar may not have the proper prey resources for rapid growth that would facilitate recruitment to adulthood. Texoma Reservoir, located on the Oklahoma–Texas border, hosts four native gar species, including the Alligator Gar, whose population is supported by supplemental stocking of age-0 fingerlings. We investigated feeding by age-0 gar to obtain a baseline level of trophic ecology for this group of fishes, including the potential for poststocking cannibalism. Food webs were reconstructed via analysis of carbon (δ13C) and nitrogen (δ15N) isotopes using Bayesian mixing model approaches. Isotopic values for age-0 fish of all four gar species were similar. Invertebrates represented a large fraction of the diet for all gars, followed by Common Carp Cyprinus carpio and Grass Carp Ctenopharyngodon idella. Competitive interactions among Bluegill Lepomis macrochirus, White Bass Morone chrysops, White Crappie Pomoxis annularis, and young gar may occur for invertebrates, shads Dorosoma spp., and Western Mosquitofish Gambusia affinis but are likely short-lived due to the rapid growth of age-0 gar after their transition to piscivory. Trophic position of age-0 Alligator Gar, Longnose Gar Lepisosteus osseus, and Spotted Gar Lepisosteus oculatus was positively related to TL, but this relationship was not observed for Shortnose Gar Lepisosteus platostomus. In Texoma Reservoir, the four native gar species, including stocked Alligator Gar, appear to have adequate food resources for recruitment, with little indication of within-family or interspecific predation. This suggests that stocked Alligator Gar quickly acclimated to their new environment.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10436","usgsCitation":"Snow, R.A., Stewart, D., Porta, M., and Long, J.M., 2020, Feeding ecology of age-0 gar at Lake Texoma inferred from analysis of stable isotopes: North American Journal of Fisheries Management, v. 40, no. 3, p. 638-650, https://doi.org/10.1002/nafm.10436.","productDescription":"12 p.","startPage":"638","endPage":"650","ipdsId":"IP-106049","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":392433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Snow, Richard A.","contributorId":264712,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":827623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, D.R.","contributorId":269640,"corporation":false,"usgs":false,"family":"Stewart","given":"D.R.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":827624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porta, M. J.","contributorId":264714,"corporation":false,"usgs":false,"family":"Porta","given":"M. J.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":827625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":827626,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210018,"text":"fs20203030 - 2020 - Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","interactions":[],"lastModifiedDate":"2020-05-12T11:33:15.420536","indexId":"fs20203030","displayToPublicDate":"2020-05-11T15:05:45","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3030","displayTitle":"Trends in Streamflow, Nutrients, and Total Suspended Solids in the Upper White River Basin, Indiana","title":"Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana","docAbstract":"

The U.S. Geological Survey, in partnership with The Nature Conservancy, analyzed existing water-quality and streamflow data from three locations in the Upper White River Basin, Indiana, to estimate annual mean concentrations and fluxes and to identify and quantify changes in water quality and streamflow over time. Water-quality data used in the analyses were collected between water years 1992 and 2017. Annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus as phosphorus, nitrate plus nitrite as nitrogen, and total Kjeldahl nitrogen as nitrogen were estimated for U.S. Geological Survey streamgage locations in Indiana on the Upper White River at Muncie, near Nora, and near Centerton. In addition, flow-normalized annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated and used to assess changes in these constituents between water years 1997 and 2017. Flow normalization is a process that attempts to remove the effects of year-to-year variation in streamflow on concentrations and fluxes without removing the effects associated with seasonal and long-term (multiyear) trends in streamflow.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203030","collaboration":"Prepared in cooperation with The Nature Conservancy with generous support from the Nina Mason Pulliam Charitable Trust","usgsCitation":"Koltun, G.F., and Hauswald, C., 2020, Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana: U.S. Geological Survey Fact Sheet 2020–3030, 6 p., https://doi.org/10.3133/fs20203030.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-114324","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":374596,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3030/coverthb.jpg"},{"id":374597,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3030/fs20203030.pdf","text":"Report","size":"9.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3030"}],"country":"United States","state":"Indiana","otherGeospatial":"Upper White River Basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-86.6546,39.6001],[-86.6522,39.6087],[-86.6463,39.6128],[-86.6403,39.6201],[-86.6404,39.6305],[-86.6654,39.6305],[-86.6858,39.63],[-86.6853,39.6884],[-86.6849,39.7773],[-86.6845,39.8648],[-86.6929,39.8643],[-86.6937,39.9228],[-86.6938,39.9528],[-86.6946,40.0402],[-86.6961,40.1282],[-86.6962,40.1785],[-86.2424,40.1807],[-86.2435,40.2152],[-86.242,40.3013],[-86.2423,40.3734],[-86.2429,40.3884],[-86.2422,40.4029],[-85.8624,40.407],[-85.8621,40.3784],[-85.5784,40.3794],[-85.4451,40.3792],[-85.2205,40.379],[-85.2182,40.3073],[-85.1302,40.3082],[-85.0186,40.3092],[-84.901,40.3096],[-84.8064,40.3102],[-84.8079,40.1741],[-84.8106,40.1351],[-84.8112,40.1265],[-84.8131,40.006],[-84.8603,40.0066],[-84.8952,40.0061],[-85.2014,40.0042],[-85.2013,39.875],[-85.2133,39.8751],[-85.2205,39.8748],[-85.2214,39.7895],[-85.243,39.7902],[-85.3017,39.789],[-85.3519,39.7894],[-85.4651,39.7886],[-85.5765,39.7858],[-85.5968,39.786],[-85.6333,39.7862],[-85.6338,39.6987],[-85.6876,39.6987],[-85.7993,39.6993],[-85.913,39.6976],[-85.9518,39.6969],[-85.9523,39.638],[-85.9521,39.347],[-85.9812,39.3466],[-85.9902,39.3467],[-86.0247,39.3464],[-86.0854,39.3452],[-86.0919,39.3452],[-86.1008,39.3453],[-86.1377,39.3445],[-86.249,39.342],[-86.3566,39.3404],[-86.3816,39.3399],[-86.4631,39.3391],[-86.5732,39.3395],[-86.6309,39.3413],[-86.6309,39.3481],[-86.6323,39.4696],[-86.6859,39.47],[-86.686,39.5144],[-86.6861,39.5262],[-86.6706,39.5339],[-86.6533,39.5475],[-86.6491,39.5552],[-86.6528,39.5666],[-86.6546,39.5865],[-86.6552,39.5965],[-86.6546,39.6001]]]},\"properties\":{\"name\":\"Boone\",\"state\":\"IN\"}}]}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229

","tableOfContents":"","publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":140048,"corporation":false,"usgs":true,"family":"Koltun","given":"G.","email":"gfkoltun@usgs.gov","middleInitial":"F.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hauswald, Cassie 0000-0002-9265-0603","orcid":"https://orcid.org/0000-0002-9265-0603","contributorId":224621,"corporation":false,"usgs":false,"family":"Hauswald","given":"Cassie","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":true,"id":788823,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211205,"text":"70211205 - 2020 - Generalizing indirect defense and resistance of plants","interactions":[],"lastModifiedDate":"2020-07-17T18:01:09.69254","indexId":"70211205","displayToPublicDate":"2020-05-11T12:59:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Generalizing indirect defense and resistance of plants","docAbstract":"

Indirect defence, the adaptive top‐down control of herbivores by plant traits that enhance predation, is a central component of plant–herbivore interactions. However, the scope of interactions that comprise indirect defence and associated ecological and evolutionary processes has not been clearly defined. We argue that the range of plant traits that mediate indirect defence is much greater than previously thought, and we further organise major concepts surrounding their ecological functioning. Despite the wide range of plant traits and interacting organisms involved, indirect defences show commonalities when grouped. These categories are based on whether indirect defences boost natural enemy abundance via food or shelter resources, or, alternatively, increase natural enemy foraging efficiency via information or alteration of habitat complexity. The benefits of indirect defences to natural enemies should be further explored to establish the conditions in which indirect defence generates a plant–natural enemy mutualism. By considering the broader scope of plant–herbivore–natural enemy interactions that comprise indirect defence, we can better understand plant‐based food webs, as well as the evolutionary processes that have shaped them.

","language":"English","publisher":"Wiley","doi":"10.1111/ele.13512","usgsCitation":"Pearse, I.S., LoPresti, E., Schaeffer, R.N., Wetzel, W.C., Mooney, K.A., Ali, J.G., Ode, P.J., Eubanks, M., Bronstein, J., and Weber, M.G., 2020, Generalizing indirect defense and resistance of plants: Ecology Letters, v. 23, no. 7, p. 1137-1152, https://doi.org/10.1111/ele.13512.","productDescription":"16 p.","startPage":"1137","endPage":"1152","ipdsId":"IP-109178","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.13512","text":"Publisher Index Page"},{"id":376472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":793180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LoPresti, Eric","contributorId":208296,"corporation":false,"usgs":false,"family":"LoPresti","given":"Eric","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":793181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaeffer, Robert N.","contributorId":229436,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":41641,"text":"Utah State U.","active":true,"usgs":false}],"preferred":false,"id":793182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wetzel, William C.","contributorId":229437,"corporation":false,"usgs":false,"family":"Wetzel","given":"William","email":"","middleInitial":"C.","affiliations":[{"id":41642,"text":"Michigan State U","active":true,"usgs":false}],"preferred":false,"id":793183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mooney, Kailen A.","contributorId":229438,"corporation":false,"usgs":false,"family":"Mooney","given":"Kailen","email":"","middleInitial":"A.","affiliations":[{"id":34134,"text":"UC Irvine","active":true,"usgs":false}],"preferred":false,"id":793184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ali, Jared G.","contributorId":229439,"corporation":false,"usgs":false,"family":"Ali","given":"Jared","email":"","middleInitial":"G.","affiliations":[{"id":41643,"text":"Penn State U.","active":true,"usgs":false}],"preferred":false,"id":793185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ode, Paul J.","contributorId":197314,"corporation":false,"usgs":false,"family":"Ode","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":793186,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eubanks, Micky D.","contributorId":229440,"corporation":false,"usgs":false,"family":"Eubanks","given":"Micky D.","affiliations":[{"id":36313,"text":"Texas A&M","active":true,"usgs":false}],"preferred":false,"id":793187,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bronstein, Judith L.","contributorId":229441,"corporation":false,"usgs":false,"family":"Bronstein","given":"Judith L.","affiliations":[{"id":35523,"text":"U Arizona","active":true,"usgs":false}],"preferred":false,"id":793188,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weber, Marjorie G.","contributorId":229442,"corporation":false,"usgs":false,"family":"Weber","given":"Marjorie","email":"","middleInitial":"G.","affiliations":[{"id":41642,"text":"Michigan State U","active":true,"usgs":false}],"preferred":false,"id":793189,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70209985,"text":"sir20205035 - 2020 - Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","interactions":[],"lastModifiedDate":"2020-05-12T11:44:31.472549","indexId":"sir20205035","displayToPublicDate":"2020-05-11T11:54:36","publicationYear":"2020","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":"2020-5035","displayTitle":"Ecological Status of Aquatic Communities in Selected Streams in the Milwaukee Metropolitan Sewerage District Planning Area of Wisconsin, 2004–13","title":"Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13","docAbstract":"

A total of 14 wadable streams in urban or urbanizing watersheds near Milwaukee, Wisconsin, were sampled in 2004, 2007, 2010, and 2013 to assess the ecological status of aquatic communities (biota), including benthic algae and invertebrates, and fish. To assess temporal variation, additional community sampling was also done at a subset of three sites in 2011 and 2012. Relative abundances of each type of organism were used to calculate biological metrics, such as richness and diversity, percentages of intolerant and tolerant organisms, and indexes of biotic integrity for invertebrates and fish. Selected environmental (physical and chemical) data in the streams were collected to evaluate potential relations to the biota and the ecological health of the stream. Physical and chemical data included land use/land cover, stream discharge from U.S. Geological Survey (USGS) streamgages (except at 2 creeks that were not gaged), stream habitat, microhabitat at invertebrate collection locations, water quality (except at 2 creeks that were not gaged), field measurements of several water-quality constituents, measures of benthic algal biomass, and toxicity and chemical tests on extracts from passive samplers deployed at a subset of 6 sites. Relative abundances of organisms and biological metrics were compared among sampling years and with environmental metrics to evaluate the ecological status of these streams and determine primary stressors on the aquatic communities, with the aim of helping resource managers understand and work toward improving the ecological health of these and other urban and urbanizing rivers in the study area.

Biological metrics for most sites indicated some level of diminished ecological status when compared across all sampled sites and when compared with rating scales for selected metrics. The least degraded sites among all those sampled—indicated by aggregate bioassessments for algae, invertebrates, and fish metrics and in order starting with the best overall condition—were the Milwaukee River near Cedarburg, Menomonee River at Menomonee Falls, Jewel Creek, and Milwaukee River at Milwaukee. The most degraded sites were Menomonee River at Wauwatosa, Root River at Greenfield, Lincoln Creek, and the Kinnickinnic River. Differences in aggregate bioassessments indicate that aquatic communities at the Menomonee River at Wauwatosa site and the Root River at Greenfield site were worse in 2013 than in 2004; however, Oak Creek and Honey Creek sites were better. In 2013, several sites had less than 30-percent pollution-sensitive diatoms indicating degraded algal assemblages. Invertebrate metrics for most of the 14 sites in 2013 were lower than in 2004 and indicate that invertebrate assemblages at most sampled sites were more degraded in 2013. Tolerant fish taxa made up more than 40 percent of assemblages at most sites and nearly 100 percent of assemblages at four sites. At times, in some smaller streams, too few fish were captured to compute an Index of Biotic Integrity with confidence, and invertebrates provided a better means for assessing the ecological status and water quality. With these few exceptions, the use of all three groups of biota provided the most robust assessments at the 14 sites in 2004–13.

Physical and chemical stressors were correlated to adverse effects on aquatic biota at the sampled streams. Passive samplers were deployed at a subset of six sites in 2013. Microtox results indicated there was little or no toxicity at the Milwaukee River near Cedarburg site and at the Oak Creek site, slight toxicity at the Lincoln Creek and Honey Creek sites, and moderate toxicity at the Milwaukee River at Milwaukee site and the Little Menomonee River site; however, based on cytochrome-P450 reporter gene system toxicity tests, potential toxicity from hydrophobic organic contaminants was measured at all six sites. For all 14 sites, physical and chemical stressors related to urbanization correlated with biological metrics for algae, invertebrates, and fish. Most stressors for aquatic biota reflected an urban signature. Stressors related to ecological condition in our study were chemical and physical, such as developed land, impervious surface in the watershed, urban land in a buffer area around the stream (a 100-foot [30-meter]-wide area on each side of the stream, and maximum instantaneous discharge normalized by drainage area (a measure of flood and scour effects). Chemical stressors included low waterborne concentrations of dissolved oxygen and high concentrations of chloride, zinc and other metals, nutrients (nitrite and phosphorus), and fecal coliform bacteria.

Although algae, invertebrates, and fish did not always demonstrate a significant response to the same stressors, higher abundances of high total phosphorus-indicator diatoms, lower ratings for invertebrate biotic integrity indexes and percentages of mayflies-stoneflies-caddisflies, and lower values for fish biotic integrity indexes underscored possible adverse effects of even low levels of developed land. Developed land is typically associated with more rapid runoff, which washes chemicals from impervious surfaces into area waterways and degrades stream habitat for aquatic communities. However, with respect to at least chloride from road salt, diatoms tolerant to dissolved salts were significantly lower with as little as 1-percent mixed forest in the watershed. Lower percentages of urban land in the stream buffer correlated with healthier aquatic assemblages of algae, invertebrates, and fish. The assessment of algal, invertebrate, and fish assemblages coupled with physical and chemical data were highly useful in evaluating the ecological status of aquatic communities at the 14 sites and for determining environmental stressors that may be contributing to reduced stream condition. Some of the stressors could potentially be removed or lessened with stream rehabilitation or changes in watershed management.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205035","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Scudder Eikenberry, B.C., Nott, M.A., Stewart, J.S., Sullivan, D.J., Alvarez, D.A., Bell, A.H., and Fitzpatrick, F.A., 2020, Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13: U.S. Geological Survey Scientific Investigations Report 2020–5035, 84 p., https://doi.org/10.3133/sir20205035.","productDescription":"Report: viii, 84 p.; Data Release; Dataset","numberOfPages":"96","onlineOnly":"Y","ipdsId":"IP-106552","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5035/coverthb.jpg"},{"id":374558,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5035/sir20205035.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5035"},{"id":374559,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FWMODL","text":"USGS data release","linkHelpText":"Aquatic community and environmental data for 14 rivers and streams in the Milwaukee Metropolitan Sewerage District Planning Area, 2004-13"},{"id":374560,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"National Water Information System—","linkHelpText":"USGS water data for the Nation"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee Metropolitan Sewerage District Planning Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.187255859375,\n 42.512601715736665\n ],\n [\n -87.81372070312499,\n 42.512601715736665\n ],\n [\n -87.81372070312499,\n 43.15710884095329\n ],\n [\n -88.187255859375,\n 43.15710884095329\n ],\n [\n -88.187255859375,\n 42.512601715736665\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Eikenberry, Barbara C. Scudder 0000-0001-8058-1201 beikenberry@usgs.gov","orcid":"https://orcid.org/0000-0001-8058-1201","contributorId":172148,"corporation":false,"usgs":true,"family":"Eikenberry","given":"Barbara C. Scudder","email":"beikenberry@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nott, Michelle A. 0000-0003-3968-7586","orcid":"https://orcid.org/0000-0003-3968-7586","contributorId":221766,"corporation":false,"usgs":true,"family":"Nott","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Jana S. 0000-0002-8121-1373 jsstewar@usgs.gov","orcid":"https://orcid.org/0000-0002-8121-1373","contributorId":539,"corporation":false,"usgs":true,"family":"Stewart","given":"Jana","email":"jsstewar@usgs.gov","middleInitial":"S.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Daniel J. 0000-0003-2705-3738","orcid":"https://orcid.org/0000-0003-2705-3738","contributorId":204322,"corporation":false,"usgs":true,"family":"Sullivan","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":1369,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":788708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788709,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788710,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209987,"text":"ds1124 - 2020 - Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","interactions":[],"lastModifiedDate":"2020-05-11T20:21:59.676539","indexId":"ds1124","displayToPublicDate":"2020-05-11T11:20:43","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1124","displayTitle":"Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project, January through December 2016, and Previously Unpublished Data from 2013 to 2015","title":"Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015","docAbstract":"

Environmental groundwater-quality data were collected from 648 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program and are included in this report. Most of the wells (514) were sampled from January through December 2016, and 60 of them were sampled in 2013 and 74 in 2014. The data were collected from seven types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public-water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes; vertical flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths; flow-path study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths over a horizontal distance; and modeling support studies, which are used to provide data to support groundwater modeling. Groundwater samples were analyzed for many water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release. Some data from environmental samples collected in 2013–14 and quality-control samples collected in 2012–15 also are included in the associated data release. Data from samples collected in 2016 are associated with networks described in this report and have not been published previously; data from samples collected between 2012 and 2015 are associated with networks described in previous reports in this data series.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1124","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Arnold, T.L., Bexfield, L.M., Musgrove, M., Erickson, M.L., Kingsbury, J.A., Degnan, J.R., Tesoriero, A.J., Kulongoski, J.T., and Belitz, K., 2020, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, January through December 2016, and previously unpublished data from 2013 to 2015: U.S. Geological Survey Data Series 1124, 135 p., https://doi.org/10.3133/ds1124. 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Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-05-11","noUsgsAuthors":false,"publicationDate":"2020-05-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Arnold, Terri 0000-0003-1406-6054 tlarnold@usgs.gov","orcid":"https://orcid.org/0000-0003-1406-6054","contributorId":1598,"corporation":false,"usgs":false,"family":"Arnold","given":"Terri","email":"tlarnold@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":788711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bexfield, Laura M. 0000-0002-1789-654X bexfield@usgs.gov","orcid":"https://orcid.org/0000-0002-1789-654X","contributorId":1273,"corporation":false,"usgs":true,"family":"Bexfield","given":"Laura","email":"bexfield@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":788713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - 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2020 - The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view","interactions":[],"lastModifiedDate":"2020-09-28T14:20:50.183031","indexId":"70214484","displayToPublicDate":"2020-05-11T09:18:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view","docAbstract":"

Observation, theory, and intuition all suggest that larger earthquakes should trigger larger landslides. Many factors could contribute to this, including depth-dependent shear strength or non-linearity of ground motion in soils and rock, but we hypothesize that the key characteristics of large earthquakes causing this phenomenon are (in addition to magnitude) the frequency and duration of the strong ground motion. Because of the paucity of site-specific data for detailed analysis, we take a regional approach to this question by analyzing strong-motion records and earthquake-induced landslide (EQIL) inventories from six well-documented earthquakes. Ground motion is characterized using earthquake magnitude and the median durations and frequencies (mean periods) of subsets of strong-motion records relevant to landslide triggering. EQIL inventories are characterized using the median landslide area of the entire inventory as well as the median areas of the largest 1% of the landslides and the largest 10 landslides. We then compare ground-motion characteristics with landslide size statistics to determine possible correlations. Comparisons of all earthquake- and landslide-size statistics show strong positive correlations between landslide size and (1) magnitude, (2) ground-motion duration, and (3) mean period. Although all the ground-motion measures yield highly correlated regressions, mean period appears to be the best overall predictor of landslide size. Landslide modeling using Newmark's sliding-block method also shows that longer mean periods and durations and larger magnitudes correlate strongly with increases in modeled displacements. These results support our hypothesis that increasing period and duration of seismic ground motion are the physical factors driving increased landslide sizes for larger earthquakes. Additional studies including data from a much larger set of earthquakes is needed to confirm the results of this initial study.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2020.105671","usgsCitation":"Jibson, R.W., and Tanyas, H., 2020, The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view: Engineering Geology, v. 273, 105671, 10 p., https://doi.org/10.1016/j.enggeo.2020.105671.","productDescription":"105671, 10 p.","ipdsId":"IP-119229","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":378806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"273","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanyas, Hakan","contributorId":215531,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","email":"","affiliations":[{"id":39272,"text":"University of Twente","active":true,"usgs":false}],"preferred":false,"id":799702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210175,"text":"70210175 - 2020 - Fluoride occurrence in United States groundwater","interactions":[],"lastModifiedDate":"2020-05-19T13:38:58.950932","indexId":"70210175","displayToPublicDate":"2020-05-11T08:30:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluoride occurrence in United States groundwater","docAbstract":"Data from 38,105 wells were used to characterize fluoride (F) occurrence in untreated United States (U.S.) groundwater. For domestic wells (n = 11,032), water from which is generally not purposely fluoridated or monitored for quality, 10.9% of the samples have F concentrations >0.7 mg/L (U.S. Public Health Service recommended optimal F concentration in drinking water for preventing tooth decay) (87% are <0.7 mg/L); 2.6% have F > 2 mg/L (EPA Secondary Maximum Contaminant Level, SMCL); and 0.6% have F > 4 mg/L (EPA MCL). The data indicate the biggest concern with F in domestic wells at the national scale could be one of under consumption of F with respect to the oral-health benchmark (0.7 mg/L). Elevated F concentrations relative to the SMCL and MCL are regionally important, particularly in the western U.S. Statistical comparisons of potentially important controlling factors in four F-concentration categories (<0.1–0.7 mg/L; >0.7–2 mg/L; >2–4 mg/L; >4 mg/L) at the national scale indicate the highest F-concentration category is associated with groundwater that has significantly greater pH values, TDS and alkalinity concentrations, and well depths, and lower Ca/Na ratios and mean annual precipitation, than the lowest F-concentration category. The relative importance of the controlling factors appears to be regionally variable. Three case studies illustrate the spatial variability in controlling factors using groundwater-age (groundwater residence time), water-isotope (evaporative concentration), and water-temperature (geothermal processes) data. Populations potentially served by domestic wells with F concentrations <0.7, >0.7, >2, and >4 mg/L are estimated to be ~28,200,000, ~3,110,000; ~522,000; and ~172,000 people, respectively, in 40 principal aquifers with at least 25 F analyses per aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.139217","collaboration":"","usgsCitation":"McMahon, P.B., Brown, C., Johnson, T., Belitz, K., and Lindsey, B.D., 2020, Fluoride occurrence in United States groundwater: Science of the Total Environment, v. 732, https://doi.org/10.1016/j.scitotenv.2020.139217.","productDescription":"139217, 15 p.","startPage":"","ipdsId":"IP-114693","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science 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Center","active":true,"usgs":true}],"preferred":true,"id":789428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Tyler D. 0000-0002-7334-9188","orcid":"https://orcid.org/0000-0002-7334-9188","contributorId":201888,"corporation":false,"usgs":true,"family":"Johnson","given":"Tyler D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":213728,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":789430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789431,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210389,"text":"70210389 - 2020 - Trends in thermal maturity indicators for the organic sulfur-rich Eagle Ford Shale","interactions":[],"lastModifiedDate":"2020-06-02T13:13:46.645331","indexId":"70210389","displayToPublicDate":"2020-05-11T08:10:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in thermal maturity indicators for the organic sulfur-rich Eagle Ford Shale","docAbstract":"Thermal maturity is critical to evaluate petroleum systems and to interpret biomarker results for paleoenvironmental and geobiology studies. Many thermal maturity indices were developed for marine source rocks containing type II kerogen, but their behavior in organic sulfur-rich source rocks requires more investigation. Here, we present geochemical analyses of whole and extracted rock, isolated kerogens, and extractable organic matter across a natural thermal maturity transect of the Upper Cretaceous Eagle Ford Shale to evaluate the behavior of maturity parameters in organic sulfur-rich source rocks. The samples contain similar mineralogy and trace element composition, minimizing potential facies effects on thermal maturity parameters. Atomic H/C ratios of isolated kerogens, extractable organic matter yield, and programmed pyrolysis results show that the samples range from the pre-oil through dry gas generation windows. Programmed pyrolysis data and kerogen elemental ratios show that the immature samples host both type IIS (atomic Sorg/C > 0.04) and sulfur-rich type II kerogen (kerogen Sorg/C: 0.032 to 0.045) while the samples with lower kerogen Sorg/C ratios (kerogen Sorg/C < 0.03) are more mature. The vitrinite reflectance values corresponding to the onset of oil generation in the Eagle Ford are comparable to other type II petroleum systems. Likewise, the organic sulfur-rich Eagle Ford follows a similar hydrogen index and kerogen H/C trend as other marine type II source rocks. Hopane and sterane stereoisomer maturity ratios are anomalously elevated at low thermal maturities, so they should not be applied in organic sulfur-rich petroleum systems to infer thermal maturity. However, some biomarker ratios, including those that are more commonly used as source parameters, strongly track thermal maturity in this case study with limited facies variability.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2020.104459","usgsCitation":"French, K.L., Birdwell, J.E., and Lewan, M., 2020, Trends in thermal maturity indicators for the organic sulfur-rich Eagle Ford Shale: Marine and Petroleum Geology, v. 118, 104459, 21 p., https://doi.org/10.1016/j.marpetgeo.2020.104459.","productDescription":"104459, 21 p.","ipdsId":"IP-116987","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":456812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpetgeo.2020.104459","text":"Publisher Index Page"},{"id":375242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":790138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":790137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewan, Michael 0000-0001-6347-1553 mlewan@usgs.gov","orcid":"https://orcid.org/0000-0001-6347-1553","contributorId":173938,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael","email":"mlewan@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":790139,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210015,"text":"ofr20201049 - 2020 - 2018 U.S. Geological Survey–California Geological Survey fault-imaging surveys across the Hollywood and Santa Monica Faults, Los Angeles County, California","interactions":[],"lastModifiedDate":"2020-05-11T11:55:34.993752","indexId":"ofr20201049","displayToPublicDate":"2020-05-08T15:09:35","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1049","displayTitle":"2018 U.S. Geological Survey–California Geological Survey Fault-Imaging Surveys Across the Hollywood and Santa Monica Faults, Los Angeles County, California","title":"2018 U.S. Geological Survey–California Geological Survey fault-imaging surveys across the Hollywood and Santa Monica Faults, Los Angeles County, California","docAbstract":"

We acquired multiple types of seismic data across the Hollywood Fault in Hollywood, Calif., and the Santa Monica Fault in Beverly Hills, Calif., in May and June 2018. On the basis of our data, we infer near-surface locations of various traces of these faults.
From two separate profiles across the Hollywood Fault, we evaluated multiple seismic datasets and models, including guided-wave data, tomographic VP data, tomographic VS data, VP/VS and Poisson’s ratio models derived from tomographic VP and VS data, Rayleigh-wave–based VS models, Love-wave–based VS models, VP/VS and Poisson’s ratio models (derived from combinations of tomographic-based VP and surface-wave–based VS models), P-wave reflection images, and S-wave reflection images. All of these data and models can be used to delineate near-surface faulting, and the data consistently infer near-surface fault traces of the Hollywood Fault in the same locations. Importantly, the combined data indicate more than one near-surface fault trace of the Hollywood Fault. Between North Bronson and North Gower Avenues, evidence exists for a near-surface trace of the Hollywood Fault slightly south of Carlos Avenue. Farther west, along Argyle Avenue, our data contain high levels of cultural noise, but we interpret near-surface faulting slightly south of the intersection of Carlos and Argyle Avenues and between Carlos Avenue and Yucca Street.
For the Santa Monica Fault in Beverly Hills, we acquired guided-wave data only along Lasky Drive between Moreno Drive and South Santa Monica Boulevard, owing to limited access permissions. However, we used two separate source locations to generate the guided-wave data (SP1 and SP2). The data from more distant source location (relative to the recording array, SP1) were noisy, but on the basis of those data, we infer near-surface faulting at several locations along Lasky Drive, with concentrated near-surface faulting slightly south of the intersection of Lasky Drive and Charleville Boulevard. Guided-wave data generated at the closer source location (relative to recording array, SP2) more clearly show evidence for distributed near-surface faulting at several locations along Lasky Drive, with concentrated faulting near the intersection of Lasky Drive and Charleville Boulevard.
Although the seismic surveys across both faults provide strong evidence for the locations of near-surface fault traces, the seismic data provide little or no information about the rupture history of the fault traces.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201049","collaboration":"Prepared in cooperation with California Geological Survey","usgsCitation":"Catchings, R.D., Hernandez, J., Goldman, M.R., Chan, J.H., Sickler, R.R., Olson, B., and Criley, C.J., 2020, 2018 U.S. Geological Survey–California Geological Survey fault-imaging surveys across the Hollywood and Santa Monica Faults, Los Angeles County, California: U.S. Geological Survey Open-File Report 2020–1049, 42 p., https://doi.org/10.3133/ofr20201049.","productDescription":"Report: vi, 42 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-113953","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":374593,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ENA8D4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Release for the 2018 U.S. Geological Survey–California Geological Survey Fault-Imaging Surveys Across the Hollywood and Santa Monica Faults, Los Angeles County, California"},{"id":374591,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1049/coverthb.jpg"},{"id":374592,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1049/ofr20201049.pdf","text":"Report","size":"15.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1049"}],"country":"United States","state":"California ","county":"Los Angeles County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.49304199218749,\n 33.80653802509606\n ],\n [\n -117.81875610351562,\n 33.529947711130646\n ],\n [\n -117.476806640625,\n 33.742612777346864\n ],\n [\n -117.52624511718749,\n 34.47712785074854\n ],\n [\n -118.60290527343749,\n 34.45674800347809\n ],\n [\n -118.83911132812499,\n 34.098159345215535\n ],\n [\n -118.49304199218749,\n 33.80653802509606\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025

","tableOfContents":"","publishedDate":"2020-05-08","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":788805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hernandez, Janis","contributorId":216335,"corporation":false,"usgs":false,"family":"Hernandez","given":"Janis","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":788806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldman, Mark R. 0000-0002-0802-829X goldman@usgs.gov","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":1521,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","email":"goldman@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":788807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chan, Joanne H. 0000-0002-2065-2423 jchan@usgs.gov","orcid":"https://orcid.org/0000-0002-2065-2423","contributorId":178625,"corporation":false,"usgs":true,"family":"Chan","given":"Joanne","email":"jchan@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":788808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sickler, Robert R. 0000-0002-9141-625X rsickler@usgs.gov","orcid":"https://orcid.org/0000-0002-9141-625X","contributorId":3235,"corporation":false,"usgs":true,"family":"Sickler","given":"Robert","email":"rsickler@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":788809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olson, Brian","contributorId":217365,"corporation":false,"usgs":false,"family":"Olson","given":"Brian","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":788810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Criley, Coyn J. 0000-0002-0227-0165 ccriley@usgs.gov","orcid":"https://orcid.org/0000-0002-0227-0165","contributorId":3312,"corporation":false,"usgs":true,"family":"Criley","given":"Coyn","email":"ccriley@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":788811,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70209808,"text":"sir20205037 - 2020 - Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States","interactions":[],"lastModifiedDate":"2020-05-11T11:42:40.648542","indexId":"sir20205037","displayToPublicDate":"2020-05-08T14:55:00","publicationYear":"2020","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":"2020-5037","displayTitle":"Compositional Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells in the Southwestern United States","title":"Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States","docAbstract":"

Studies of naturally occurring subsurface carbon dioxide (CO2) accumulations can provide useful information for potential CO2 injection projects; however, the microbial communities and formation water geochemistry of most reservoirs are understudied. Formation water and microbial biomass were sampled at four CO2-rich reservoir sites: two within Bravo Dome, a commercial CO2 field in New Mexico; one northwest of Bravo Dome in Colorado (Oakdale Field); and one southwest of Bravo Dome in New Mexico (Rafter “K” Ranch). Aside from the Rafter “K” Ranch site, minor differences were observed in the geochemistry of formation water collected from these sites compared to historical data. No organisms were significantly associated with Oakdale Field compared to the other three sites, nor were any hydrogeochemical or gas geochemical parameters (for example, CO2 concentration) found to have significant associations with the microbial ecology of these four sites. Microorganisms from these sites were metabolically diverse and had the potential to (1) generate methane, (2) produce corrosive hydrogen sulfide (H2S), and (3) rapidly biofoul and (or) clog pore spaces by shifting microbial communities with changes in salinity or nutrient supply. This study demonstrates that high concentrations of CO2 in subsurface reservoirs apparently have not imparted a distinct geochemical or microbiological signature on the associated formation waters and that the microorganisms in these reservoirs are metabolically diverse and could adapt to geochemical changes in the subsurface.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205037","usgsCitation":"Shelton, J.L., Andrews, R.S., Akob, D.M., DeVera, C.A., Mumford, A.C., Engle, M., Plampin, M.R., and Brennan, S.T., 2020, Compositional analysis of formation water geochemistry and microbiology of commercial and carbon dioxide-rich wells in the southwestern United States: U.S. Geological Survey Scientific Investigations Report 2020–5037, 26 p., https://doi.org/10.3133/sir20205037.","productDescription":"viii, 26 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-098514","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":374365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5037/sir20205037.pdf","text":"Report","size":"1.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5037"},{"id":374364,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5037/coverthb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Texas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.16064453125,\n 34.07086232376631\n ],\n [\n -102.919921875,\n 34.07086232376631\n ],\n [\n -102.919921875,\n 37.43997405227057\n ],\n [\n -107.16064453125,\n 37.43997405227057\n ],\n [\n -107.16064453125,\n 34.07086232376631\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-05-08","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Robert S. 0000-0002-6166-720X","orcid":"https://orcid.org/0000-0002-6166-720X","contributorId":204981,"corporation":false,"usgs":true,"family":"Andrews","given":"Robert","email":"","middleInitial":"S.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":788115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akob, Denise M. 0000-0003-1534-3025 dakob@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":4980,"corporation":false,"usgs":true,"family":"Akob","given":"Denise","email":"dakob@usgs.gov","middleInitial":"M.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":788116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVera, Christina A. 0000-0002-4691-6108 cdevera@usgs.gov","orcid":"https://orcid.org/0000-0002-4691-6108","contributorId":3845,"corporation":false,"usgs":true,"family":"DeVera","given":"Christina","email":"cdevera@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mumford, Adam C. 0000-0002-8082-8910 amumford@usgs.gov","orcid":"https://orcid.org/0000-0002-8082-8910","contributorId":197795,"corporation":false,"usgs":true,"family":"Mumford","given":"Adam","email":"amumford@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":788118,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engle, Mark 0000-0001-5258-7374","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":222085,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788119,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":788120,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brennan, Sean T. 0000-0002-7102-9359 sbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-7102-9359","contributorId":559,"corporation":false,"usgs":true,"family":"Brennan","given":"Sean","email":"sbrennan@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":788121,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228452,"text":"70228452 - 2020 - A review of pathogens, diseases, and contaminants of muskrats (Ondatra zibethicus) in North America","interactions":[],"lastModifiedDate":"2022-02-11T18:41:06.207591","indexId":"70228452","displayToPublicDate":"2020-05-08T12:02:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5720,"text":"Frontiers in Veterinary Science","onlineIssn":"2297-1769","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A review of pathogens, diseases, and contaminants of muskrats (Ondatra zibethicus )in North America","title":"A review of pathogens, diseases, and contaminants of muskrats (Ondatra zibethicus) in North America","docAbstract":"Over the last 50 years, significant muskrat (Ondatra zibethicus) harvest declines have been observed throughout North America. Several theories for the decline have been proposed, including increased parasite infections and disease within muskrat populations. No existing wholistic review of muskrat exposure to pathogens, contaminants, and diseases exists. To address this knowledge gap, we conducted a thorough review of existing literature on muskrat pathogens, contaminants, and diseases across their natural range. This review is comprised of 129 articles from 1915-2019and from 27 U.S. states and 9 Canadian provinces. A wide diversity of contaminants, toxins, and pathogens were reported in muskrats, with the most common diseases being cysticercosis, tularemia, Tyzzer’s disease, and biotoxin poisoning from cyanobacteria. This review provides a summary of muskrat pathogens, contaminants, and disease over a century that has observed significant population declines throughout the species’ range in North America. Such data provides baseline data for understanding the potential role of disease in these declines. In addition, these data highlight critical knowledge gaps that warrant future research efforts.","language":"English","publisher":"Elsevier","doi":"10.3389/fvets.2020.00233","usgsCitation":"Ganoe, L.S., Walter, W., Brown, J., Yabsley, M.J., and Lovallo, M.J., 2020, A review of pathogens, diseases, and contaminants of muskrats (Ondatra zibethicus) in North America: Frontiers in Veterinary Science, v. 7, 233, 13 p, https://doi.org/10.3389/fvets.2020.00233.","productDescription":"233, 13 p","ipdsId":"IP-115816","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":456815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fvets.2020.00233","text":"Publisher Index Page"},{"id":395855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Alberta, British Columbia, Colorado, Idaho, Illinois, Indiana, Iowa, Kansas, Louisiana, Maine, Manitoba, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nebraska, New Brunswick, New Hampshire, New York, North Dakota, Northwest Territories, Ohio, Ontario, Oregon, Pennsylvania, Saskatchewan, South Carolina, Tennessee, Texas, Utah, Virginia, Washington, 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\"}}]}","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganoe, Laken S","contributorId":275813,"corporation":false,"usgs":false,"family":"Ganoe","given":"Laken","email":"","middleInitial":"S","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Justin D.","contributorId":275814,"corporation":false,"usgs":false,"family":"Brown","given":"Justin D.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":834335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yabsley, Michael J.","contributorId":275815,"corporation":false,"usgs":false,"family":"Yabsley","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":56897,"text":"University of Geogia","active":true,"usgs":false}],"preferred":false,"id":834336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovallo, Matthew J","contributorId":275816,"corporation":false,"usgs":false,"family":"Lovallo","given":"Matthew","email":"","middleInitial":"J","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":834337,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223419,"text":"70223419 - 2020 - Seasonal movements and tributary-specific fidelity of blue sucker Cycleptus elongatus in a Southern Plains riverscape","interactions":[],"lastModifiedDate":"2021-08-26T16:26:28.171603","indexId":"70223419","displayToPublicDate":"2020-05-08T11:21:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2285,"text":"Journal of Fish Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Seasonal movements and tributary-specific fidelity of blue sucker Cycleptus elongatus in a Southern Plains riverscape","title":"Seasonal movements and tributary-specific fidelity of blue sucker Cycleptus elongatus in a Southern Plains riverscape","docAbstract":"

This study used acoustic telemetry and a multistate Cormack–Jolly–Seber model to determine the seasonal movement patterns of blue sucker Cycleptus elongatus from 2015 to 2017. Several hypotheses were ranked using AICc, and it was determined that the movement patterns of blue suckers in a mainstem reach below a hydropower dam (i.e., tailwater) differed from those of blue suckers tagged in the major tributaries (perennial with stream order >3). This study estimated a low probability (≤0.13) blue suckers would leave the tailwater reach at any time during the study. Conversely, blue suckers tagged in the major tributaries had a high probability (≥0.88) of leaving after the spawning season (February–May). Blue suckers tagged in the major tributaries displayed a high probability (0.83) of returning to the tributaries in the spawning season of 2016 when discharges were high. Blue suckers also had a higher probability of fidelity to the tributary where they were tagged (0.65) rather than straying to different tributaries (0.18). The majority of tagged blue suckers that strayed selected the only undammed tributary in the study area. In 2017, spring discharges were low, and the probability of blue suckers returning to any major tributary was low (0.19), with little difference in the probability of displaying site fidelity (0.10) vs. straying (0.09).

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.14374","usgsCitation":"Dyer, J.J., and Brewer, S.K., 2020, Seasonal movements and tributary-specific fidelity of blue sucker Cycleptus elongatus in a Southern Plains riverscape: Journal of Fish Biology, v. 97, no. 1, p. 279-292, https://doi.org/10.1111/jfb.14374.","productDescription":"14 p.","startPage":"279","endPage":"292","ipdsId":"IP-102994","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":388551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"lower Red River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -456.6522216796875,\n 33.687781758439364\n ],\n [\n -455.1470947265625,\n 33.687781758439364\n ],\n [\n -455.1470947265625,\n 34.334364487026306\n ],\n [\n -456.6522216796875,\n 34.334364487026306\n ],\n [\n -456.6522216796875,\n 33.687781758439364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Dyer, J. J.","contributorId":264808,"corporation":false,"usgs":false,"family":"Dyer","given":"J.","email":"","middleInitial":"J.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":822007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":822008,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70214538,"text":"70214538 - 2020 - Applications and utility of the surface elevation table–marker horizon method for measuring wetland elevation and shallow soil subsidence-expansion: Discussion/reply to: Byrnes M., Britsch L., Berlinghoff J., Johnson R., and Khalil S. 2019. Recent subsidence rates for Barataria Basin, Louisiana. Geo-Marine Letters 39:265–278","interactions":[],"lastModifiedDate":"2020-09-30T14:49:02.792091","indexId":"70214538","displayToPublicDate":"2020-05-08T09:47:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1742,"text":"Geo-Marine Letters","active":true,"publicationSubtype":{"id":10}},"title":"Applications and utility of the surface elevation table–marker horizon method for measuring wetland elevation and shallow soil subsidence-expansion: Discussion/reply to: Byrnes M., Britsch L., Berlinghoff J., Johnson R., and Khalil S. 2019. Recent subsidence rates for Barataria Basin, Louisiana. Geo-Marine Letters 39:265–278","docAbstract":"

Byrnes et al. (Geo-Marine Letters 39:265–278, Byrnes et al. 2019) present subsidence data for Barataria Basin located south and west of New Orleans in coastal Louisiana to better inform wetland protection and restoration planning by the Louisiana Coastal Protection and Restoration Authority. They measured subsidence using geodetic GPS elevation surveys of rod benchmarks, similar to the rod benchmarks of the surface elevation table–marker horizon (SET-MH) method used to measure surface biophysical processes influencing elevation dynamics and shallow subsidence (i.e., subsidence occurring above the base of the rod) in coastal wetlands. Byrnes et al. (Geo-Marine Letters 39:265–278, Byrnes et al. 2019) argue that (1) SET-MH measures should not be included in subsidence measures because subsidence is a purely geologic process, separate from biophysical processes occurring in the active marsh zone, (2) shallow subsidence measured by the SET-MH method in deep Holocene sediments are not valid because of downdrag on the rod, and (3) high spatial variability of wetland surface processes precludes the ability to make meaningful estimates of subsidence using the SET-MH method. This reply paper presents an extensive summary of the peer-reviewed literature that refutes all three of these claims and demonstrates that it is not only reasonable but also essential to apply the SET-MH method to obtain a complete as possible assessment of surface elevation dynamics to inform coastal wetland restoration and management planning in Barataria Basin and other coastal wetlands worldwide.

","language":"English","publisher":"Springer","doi":"10.1007/s00367-020-00656-6","usgsCitation":"Cahoon, D., Reed, D., Day, J.W., Lynch, J.C., Swales, A., and Lane, R.R., 2020, Applications and utility of the surface elevation table–marker horizon method for measuring wetland elevation and shallow soil subsidence-expansion: Discussion/reply to: Byrnes M., Britsch L., Berlinghoff J., Johnson R., and Khalil S. 2019. Recent subsidence rates for Barataria Basin, Louisiana. Geo-Marine Letters 39:265–278: Geo-Marine Letters, v. 40, p. 809-815, https://doi.org/10.1007/s00367-020-00656-6.","productDescription":"7 p.","startPage":"809","endPage":"815","ipdsId":"IP-115288","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":378911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Cahoon, Donald R. 0000-0002-2591-5667","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":219657,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":799844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Denise","contributorId":215697,"corporation":false,"usgs":false,"family":"Reed","given":"Denise","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":799845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day, John W.","contributorId":200323,"corporation":false,"usgs":false,"family":"Day","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, James C.","contributorId":179352,"corporation":false,"usgs":false,"family":"Lynch","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":799847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swales, Andrew","contributorId":149632,"corporation":false,"usgs":false,"family":"Swales","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":799848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, Robert R.","contributorId":195573,"corporation":false,"usgs":false,"family":"Lane","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":16756,"text":"Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":799849,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70210138,"text":"70210138 - 2020 - Species richness responses to water withdrawal scenarios and minimum flow levels: Evaluating presumptive standards in the Tennessee and Cumberland River basins","interactions":[],"lastModifiedDate":"2020-05-15T14:06:18.349418","indexId":"70210138","displayToPublicDate":"2020-05-08T08:59:49","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Species richness responses to water withdrawal scenarios and minimum flow levels: Evaluating presumptive standards in the Tennessee and Cumberland River basins","docAbstract":"Water resource managers are challenged to balance growing water demand with protecting aquatic ecosystems and biodiversity. Management decisions can benefit from improved understanding of water withdrawal impacts on hydrologic regimes and ecological assemblages. This study used Ecological Limit Functions for fish groups within the Tennessee and Cumberland river basins to predict species richness responses under simulated constant-rate (CR) and percent-of-flow (POF) withdrawals and for different minimum flow level protections. Streamflow characteristics (SFC) and richness were generally less sensitive to POF withdrawals than CR withdrawals among sites, fish groups, and ecoregions. Species richness generally declined with increasing withdrawals, but responses were variable depending on site-specific departures of SFCs from reference conditions, drainage area, fish group, ecoregion, and minimum flow level. Under POF withdrawals, 10% and 20% daily flow reductions often resulted in loss of <1 species and/or ≤5% richness among fish groups. Median ecological withdrawal thresholds ranged from 3.5-31% for POF withdrawals and from 0.01-0.92 m3/s for CR withdrawals across fish groups and ecoregions. Application of minimum flow level cutoffs often resulted in damping effects on SFC and richness responses, indicating that protection of low streamflows may mitigate hydrologic alteration and fish species richness loss related to water withdrawals. Site-specific and regionally summarized responses of flow regimes and fish assemblages under alternative withdrawal strategies in this study may be useful in informing water management decisions regarding streamflow allocation and maintaining ecological flows.","language":"English","publisher":"MDPI","doi":"10.3390/w12051334","collaboration":"","usgsCitation":"Driver, L., Cartwright, J.M., Knight, R., and Wolfe, W., 2020, Species richness responses to water withdrawal scenarios and minimum flow levels: Evaluating presumptive standards in the Tennessee and Cumberland River basins: Water, v. 12, no. 5, https://doi.org/10.3390/w12051334.","productDescription":"1334, 24 p.","startPage":"","ipdsId":"IP-113154","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":456820,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12051334","text":"Publisher Index Page"},{"id":436994,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q23Z4B","text":"USGS data release","linkHelpText":"Ecological flow analyses of surface water withdrawal scenarios in the Cumberland and Tennessee River basins"},{"id":374871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"","otherGeospatial":"Cumberland River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.857421875,\n 35.06597313798418\n ],\n [\n -82.705078125,\n 34.77771580360469\n ],\n [\n -80.771484375,\n 37.43997405227057\n ],\n [\n -86.66015624999999,\n 37.64903402157866\n ],\n [\n -88.857421875,\n 35.06597313798418\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Driver, Lucas 0000-0003-2549-1849","orcid":"https://orcid.org/0000-0003-2549-1849","contributorId":219176,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Rodney 0000-0001-9588-0167 rrknight@usgs.gov","orcid":"https://orcid.org/0000-0001-9588-0167","contributorId":152422,"corporation":false,"usgs":true,"family":"Knight","given":"Rodney","email":"rrknight@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolfe, William J. 0000-0002-3292-051X","orcid":"https://orcid.org/0000-0002-3292-051X","contributorId":224729,"corporation":false,"usgs":false,"family":"Wolfe","given":"William J.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":789272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210098,"text":"70210098 - 2020 - Growth and behavior of North American microbes on Phragmites australis leaves","interactions":[],"lastModifiedDate":"2020-05-14T13:44:19.292527","indexId":"70210098","displayToPublicDate":"2020-05-08T08:42:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5020,"text":"Microorganisms","active":true,"publicationSubtype":{"id":10}},"title":"Growth and behavior of North American microbes on Phragmites australis leaves","docAbstract":"Phragmites australis subsp. australis is a cosmopolitan wetland grass that is invasive in many regions of the world, including North America, where it co-occurs with the closely related Phragmites australis subsp. americanus. Because the difference in invasive behavior is unlikely to be related to physiological differences, we hypothesize that interactions with unique members of their microbiomes may significantly affect the behavior of each subspecies. Therefore, we systematically inoculated both plant lineages with a diverse array of 162 fungal and bacterial isolates to determine which could (1) differentiate between Phragmites hosts, (2) infect leaves at various stages of development, or (3) obtain plant-based carbon saprophytically. We found that many of the microbes isolated from Phragmites leaves behave as saprophytes. Only 1% (two taxa) were determined to be strong pathogens, 12% (20 taxa) were weakly pathogenic, and the remaining 87% were nonpathogenic. None of the isolates clearly discriminated between host plant lineages, and the Phragmites cuticle was shown to be a strong nonspecific barrier to infection. These results largely agree with the broad body of literature on leaf-associated phyllosphere microbes in Phragmites.","language":"English","publisher":"MDPI","doi":"10.3390/microorganisms8050690","collaboration":"","usgsCitation":"Devries, A.E., Kowalski, K., and Bickford, W.A., 2020, Growth and behavior of North American microbes on Phragmites australis leaves: Microorganisms, v. 8, no. 5, https://doi.org/10.3390/microorganisms8050690.","productDescription":"690, 19 p.","startPage":"","ipdsId":"IP-116886","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":456824,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/microorganisms8050690","text":"Publisher Index Page"},{"id":436995,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QYEMGJ","text":"USGS data release","linkHelpText":"The effects of North American fungi and bacteria on Phragmites australis leaves 2017-2019, with comparisons to the global Phragmites microbiome"},{"id":374815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Devries, Aaron E. 0000-0001-8034-2104","orcid":"https://orcid.org/0000-0001-8034-2104","contributorId":224684,"corporation":false,"usgs":true,"family":"Devries","given":"Aaron","email":"","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":789097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":789098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bickford, Wesley A. 0000-0001-7612-1325 wbickford@usgs.gov","orcid":"https://orcid.org/0000-0001-7612-1325","contributorId":5687,"corporation":false,"usgs":true,"family":"Bickford","given":"Wesley","email":"wbickford@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":789099,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210688,"text":"70210688 - 2020 - Projected impacts of climate change on the range and phenology of three culturally-important shrub species","interactions":[],"lastModifiedDate":"2020-06-17T13:34:51.108521","indexId":"70210688","displayToPublicDate":"2020-05-08T08:26:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Projected impacts of climate change on the range and phenology of three culturally-important shrub species","docAbstract":"

Climate change is shifting both the habitat suitability and the timing of critical biological events, such as flowering and fruiting, for plant species across the globe. Here, we ask how both the distribution and phenology of three food-producing shrubs native to northwestern North America might shift as the climate changes. To address this question, we compared gridded climate data with species location data to identify climate variables that best predicted the current bioclimatic niches of beaked hazelnut (Corylus cornuta), Oregon grape (Mahonia aquifolium), and salal (Gaultheria shallon). We also developed thermal-sum models for the timing of flowering and fruit ripening for these species. We then used multi-model ensemble future climate projections to estimate how species range and phenology may change under future conditions. Modelling efforts showed extreme minimum temperature, climate moisture deficit, and mean summer precipitation were predictive of climatic suitability across all three species. Future bioclimatic niche models project substantial reductions in habitat suitability across the lower elevation and southern portions of the species’ current ranges by the end of the 21st century. Thermal-sum phenology models for these species indicate that flowering and the ripening of fruits and nuts will advance an average of 25 days by the mid-21st century, and 36 days by the late-21st century under a high emissions scenario (RCP 8.5). Future changes in the climatic niche and phenology of these important food-producing species may alter trophic relationships, with cascading impacts on regional ecosystems.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0232537","usgsCitation":"Prevey, J.S., Parker, L.E., and Harrington, C., 2020, Projected impacts of climate change on the range and phenology of three culturally-important shrub species: PLoS ONE, v. 15, no. 5, e0232537, 19 p., https://doi.org/10.1371/journal.pone.0232537.","productDescription":"e0232537, 19 p.","ipdsId":"IP-114286","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":456827,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0232537","text":"Publisher Index Page"},{"id":436996,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G0UTKF","text":"USGS data release","linkHelpText":"Location and phenology observations for beaked hazelnut (Corylus cornuta), Oregon grape (Mahonia aquifolium), and salal (Gaultheria shallon) in western North America"},{"id":375664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British, Columbia, California, Idaho, Montana, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.4560546875,\n 47.57652571374621\n ],\n [\n -117.333984375,\n 50.56928286558243\n ],\n [\n -121.5087890625,\n 52.32191088594773\n ],\n [\n -133.2421875,\n 54.34214886448341\n ],\n [\n -132.7587890625,\n 52.9883372533954\n ],\n [\n -126.60644531250001,\n 48.922499263758255\n ],\n [\n -124.541015625,\n 46.07323062540835\n ],\n [\n -125.0244140625,\n 42.22851735620852\n ],\n [\n -125.068359375,\n 39.80853604144591\n ],\n [\n -120.4541015625,\n 33.797408767572485\n ],\n [\n -117.333984375,\n 35.92464453144099\n ],\n [\n -120.32226562500001,\n 40.01078714046552\n ],\n [\n -119.00390625,\n 40.91351257612758\n ],\n [\n -112.32421875,\n 42.52069952914966\n ],\n [\n -111.357421875,\n 45.61403741135093\n ],\n [\n -111.8408203125,\n 47.100044694025215\n ],\n [\n -112.4560546875,\n 47.57652571374621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Prevéy, Janet S. 0000-0003-2879-6453","orcid":"https://orcid.org/0000-0003-2879-6453","contributorId":222702,"corporation":false,"usgs":true,"family":"Prevéy","given":"Janet","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Lauren E.","contributorId":225389,"corporation":false,"usgs":false,"family":"Parker","given":"Lauren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":790979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, Constance A","contributorId":167297,"corporation":false,"usgs":false,"family":"Harrington","given":"Constance A","affiliations":[{"id":24677,"text":"USDA Pacific Northwest Research Station, Olympia WA","active":true,"usgs":false}],"preferred":false,"id":790980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210177,"text":"70210177 - 2020 - Does habitat partitioning by sympatric plovers affect nest survival?","interactions":[],"lastModifiedDate":"2020-05-19T13:23:09.960563","indexId":"70210177","displayToPublicDate":"2020-05-08T08:17:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Does habitat partitioning by sympatric plovers affect nest survival?","docAbstract":"The vertical structure and composition of vegetation can influence the quantity and quality of potential nesting sites for birds. Interspecific competition for high-quality nesting habitat may force some individuals into suboptimal habitat and lead to reduced reproductive success, eventually leading to changes in distribution or abundance. Large climate-mediated shifts in vegetation, including the rapid expansion of shrubs onto tundra, are occurring in the Arctic across important breeding grounds of many shorebird species of conservation concern. We investigated effects of vegetation structure and composition on nest-site selection and nest success of sympatrically breeding American Golden-Plovers (Pluvialis dominica) and Pacific Golden-Plovers (P. fulva), which nest along an elevational gradient ranging from coastal tundra meadows to alpine tundra. Both species strongly selected nest sites with less cover of tall shrubs and other tall vegetation than available at random sites within their territories. American Golden-Plovers selected territories and nest sites that were higher in elevation and had more rocky substrates and less graminoid vegetation than those selected by Pacific Golden-Plovers. The daily nest survival rate was equivalent in the two species (0.966, 95% CI: 0.954, 0.974) and similar to that found in other Arctic-breeding shorebirds; however, contrary to predictions, nest survival was not associated with habitat features selected for nest sites for either species. Strong selection of open habitat for nest sites suggests that continued climate-related shrub expansion may reduce the amount of suitable breeding habitat for both species, but partitioning along the elevational gradient and differences in body size suggest that impacts may be more severe for Pacific Golden-Plovers. Additional research is needed to determine if differential selection of nesting habitat is related to survival of the adults or their young.","language":"English","publisher":"Oxford Academic","doi":"10.1093/auk/ukaa018","collaboration":"","usgsCitation":"Overduijn, K.S., Handel, C.M., and Powell, A., 2020, Does habitat partitioning by sympatric plovers affect nest survival?: The Auk, v. 137, ukaa018, 16 p., https://doi.org/10.1093/auk/ukaa018.","productDescription":"ukaa018, 16 p.","ipdsId":"IP-112622","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":456829,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/auk/ukaa018","text":"Publisher Index Page"},{"id":436997,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93EGFPO","text":"USGS data release","linkHelpText":"Nesting Habitat and Nest Survival Data for American (Pluvialis dominica) and Pacific (P. fulva) Golden-Plovers on the Seward Peninsula, Alaska, 2012-2013"},{"id":374916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"137","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Overduijn, Kelly S","contributorId":224774,"corporation":false,"usgs":false,"family":"Overduijn","given":"Kelly","email":"","middleInitial":"S","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":789433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":789434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":789435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215238,"text":"70215238 - 2020 - GeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning","interactions":[],"lastModifiedDate":"2020-10-14T12:34:15.624122","indexId":"70215238","displayToPublicDate":"2020-05-08T07:33:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3618,"text":"Transactions in GIS","active":true,"publicationSubtype":{"id":10}},"title":"GeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning","docAbstract":"

Machine learning allows “the machine” to deduce the complex and sometimes unrecognized rules governing spatial systems, particularly topographic mapping, by exposing it to the end product. Often, the obstacle to this approach is the acquisition of many good and labeled training examples of the desired result. Such is the case with most types of natural features. To address such limitations, this research introduces GeoNat v1.0, a natural feature dataset, used to support artificial intelligence‐based mapping and automated detection of natural features under a supervised learning paradigm. The dataset was created by randomly selecting points from the U.S. Geological Survey’s Geographic Names Information System and includes approximately 200 examples each of 10 classes of natural features. Resulting data were tested in an object‐detection problem using a region‐based convolutional neural network. The object‐detection tests resulted in a 62% mean average precision as baseline results. Major challenges in developing training data in the geospatial domain, such as scale and geographical representativeness, are addressed in this article. We hope that the resulting dataset will be useful for a variety of applications and shed light on training data collection and labeling in the geospatial artificial intelligence domain.

","language":"English","publisher":"Wiley","doi":"10.1111/tgis.12633","usgsCitation":"Arundel, S., Li, W., and Wang, S., 2020, GeoNat v1.0: A dataset for natural feature mapping with artificial intelligence and supervised learning: Transactions in GIS, v. 24, no. 3, p. 556-572, https://doi.org/10.1111/tgis.12633.","productDescription":"17 p.","startPage":"556","endPage":"572","ipdsId":"IP-115822","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":436998,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X5BN1L","text":"USGS data release","linkHelpText":"GeoNatShapes: a natural feature reference dataset for mapping and AI training"},{"id":379346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":801249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":801250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Sizhe","contributorId":242975,"corporation":false,"usgs":false,"family":"Wang","given":"Sizhe","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":801251,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210040,"text":"70210040 - 2020 - Harnessing multiple models for outbreak management","interactions":[],"lastModifiedDate":"2020-05-12T12:22:55.482558","indexId":"70210040","displayToPublicDate":"2020-05-08T07:18:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing multiple models for outbreak management","docAbstract":"The coronavirus disease 2019 (COVID-19) pandemic has triggered efforts by multiple modeling groups to forecast disease trajectory, assess interventions, and improve understanding of the pathogen. Such models can often differ substantially in their projections and recommendations, reflecting different policy assumptions and objectives, as well as scientific, logistical, and other uncertainty about biological and management processes (1). Disparate predictions during any outbreak can hinder intervention planning and response by policy-makers (2, 3), who may instead choose to rely on single trusted sources of advice, or on consensus where it appears. Thus, valuable insights and information from other models may be overlooked, limiting the opportunity for decision-makers to account for risk and uncertainty and resulting in more lives lost or resources used than necessary. We advocate a more systematic approach, by merging two well-established research fields. The first element involves formal expert elicitation methods applied to multiple models to deliberately generate, retain, and synthesize valuable individual model ideas and share important insights during group discussions, while minimizing various cognitive biases. The second element uses a decision-theoretic framework to capture and account for within- and between-model uncertainty as we evaluate actions in a timely manner to achieve management objectives.","language":"English","publisher":"AAAS","doi":"10.1126/science.abb9934","collaboration":"","usgsCitation":"Shea, K., Runge, M.C., Pannell, D., Probert, W.J., Li, S., Tildesley, M.J., and Ferrari, M.J., 2020, Harnessing multiple models for outbreak management: Science, v. 368, no. 6491, p. 577-579, https://doi.org/10.1126/science.abb9934.","productDescription":"3 p.","startPage":"577","endPage":"579","ipdsId":"IP-118099","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":456831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/12b8d798-e5d2-4d7d-ac12-1493a2ed76d8","text":"Publisher Index Page"},{"id":374646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"368","issue":"6491","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shea, Katriona 0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":788901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":788902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pannell, David","contributorId":217709,"corporation":false,"usgs":false,"family":"Pannell","given":"David","email":"","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":788903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Probert, William J. M. 0000-0002-3437-759X","orcid":"https://orcid.org/0000-0002-3437-759X","contributorId":216183,"corporation":false,"usgs":false,"family":"Probert","given":"William","email":"","middleInitial":"J. M.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":788904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Shou-Li","contributorId":193644,"corporation":false,"usgs":false,"family":"Li","given":"Shou-Li","email":"","affiliations":[],"preferred":false,"id":788905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tildesley, Michael J.","contributorId":126971,"corporation":false,"usgs":false,"family":"Tildesley","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6620,"text":"University of Nottingham, School of Biology","active":true,"usgs":false}],"preferred":false,"id":788906,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ferrari, Matthew J. 0000-0001-5251-8168","orcid":"https://orcid.org/0000-0001-5251-8168","contributorId":216186,"corporation":false,"usgs":false,"family":"Ferrari","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":788907,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216928,"text":"70216928 - 2020 - Successful restoration of Metrosideros polymorpha (ʻōhiʻa) is possible in forest sites with active Rapid ‘Ōhiʻa Death infections","interactions":[],"lastModifiedDate":"2020-12-17T13:01:02.211174","indexId":"70216928","displayToPublicDate":"2020-05-08T07:01:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Successful restoration of Metrosideros polymorpha (ʻōhiʻa) is possible in forest sites with active Rapid ‘Ōhiʻa Death infections","title":"Successful restoration of Metrosideros polymorpha (ʻōhiʻa) is possible in forest sites with active Rapid ‘Ōhiʻa Death infections","docAbstract":"

Rapid ʻŌhiʻa Death (ROD), caused by the fungal pathogen Ceratocystis, is killing large numbers of ʻōhiʻa trees (Metrosideros polymorpha) in Hawaiʻi. ʻŌhiʻa are a dominant tree in Hawaiian forests, have a range that goes from arid to wet forest climates, and are important for endangered species habitat and ecosystem function. To test whether actively planting ʻōhiʻa seedlings is a viable restoration strategy in areas with high ROD mortality, we planted ʻōhiʻa in a ROD‐affected forest and crossed this with weeding and fencing treatments to compare ROD mortality to other stressors. We also tested for viable Ceratocystis spores in soils around planting areas. We found that seedlings were more likely to die in unweeded and unfenced treatments than controls. Although viable Ceratocystis spores were found in soil, none of the 41 dead seedlings tested positive for Ceratocystis. This indicates that competition from exotic plants and exotic feral ungulate damage are more likely to kill seedlings than ROD within the first year after planting.

","language":"English","publisher":"Wiley","doi":"10.1111/rec.13197","usgsCitation":"Yelenik, S.G., Roy, K., and Stallman, J., 2020, Successful restoration of Metrosideros polymorpha (ʻōhiʻa) is possible in forest sites with active Rapid ‘Ōhiʻa Death infections: Restoration Ecology, v. 28, no. 5, p. 1257-1261, https://doi.org/10.1111/rec.13197.","productDescription":"5 p.","startPage":"1257","endPage":"1261","ipdsId":"IP-118403","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":436999,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q65YGR","text":"USGS data release","linkHelpText":"Keaukaha Military Reservation Ohia Restoration under ROD-infected Trees 2019-2020"},{"id":381411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"28","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":806973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Kylle 0000-0002-7993-9031","orcid":"https://orcid.org/0000-0002-7993-9031","contributorId":213271,"corporation":false,"usgs":true,"family":"Roy","given":"Kylle","email":"","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":806974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stallman, Jeff 0000-0003-4713-2193","orcid":"https://orcid.org/0000-0003-4713-2193","contributorId":245750,"corporation":false,"usgs":false,"family":"Stallman","given":"Jeff","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":806975,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208798,"text":"sir20205015 - 2020 - Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17","interactions":[],"lastModifiedDate":"2020-05-08T11:50:49.347355","indexId":"sir20205015","displayToPublicDate":"2020-05-07T15:47:32","publicationYear":"2020","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":"2020-5015","displayTitle":"Pilot-Scale Testing of Dairy Manure Treatments to Reduce Nutrient Transport from Land Application, Northwest Ohio, 2015–17","title":"Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17","docAbstract":"

Manure and wastewater from large livestock operations have the potential to negatively affect surface water and groundwater, including the eutrophication of surface waters and harmful algal blooms. In the Western Lake Erie Basin, where there is a high density of animal agriculture, harmful algal blooms have been attributed, in part, to phosphorus loading from dairy manure and fertilizer applications. Liquid lagoon manure produced by dairy operations typically has low nutrient concentrations and high-water content, so transportation costs are high relative to the value of the nutrients when applied to fields. Treatment systems are needed to transform manure into a dewatered product that is more economical to transport greater distances and that slows and (or) reduces the release of nutrients in soil, allowing nutrients to remain available for crop growth.

This study was designed to pilot test a treatment solution in the Western Lake Erie Basin. The U.S. Geological Survey and Bowling Green State University field tested a dewatering treatment process (coagulant/polymer mixture) for dairy manure at pilot-scale test plots at The Ohio State University Agricultural Research and Development Center Northwest Agricultural Research Station. Automatic samplers were used to collect samples during 13 baseline and 9 post-manure application rainfall events that resulted in substantial surface runoff and (or) tile flow from October 2015 through early November 2017. Results are reported for three test plots that received liquid lagoon manure (raw manure) and three test plots that received polymer-treated manure (treated manure).

Nutrient concentrations and flow volumes in surface runoff and tile flow were determined in baseline and post-manure application rainfall events. Nutrient concentration ranges are reported for 9 baseline and 9 post-manure application events as follows: dissolved reactive phosphorus, less than (<) 0.013−2.16 milligrams per liter (mg/L); nitrate plus nitrite, filtered, 0.32−77 mg/L; ammonia, filtered, <0.05−2.6 mg/L; total phosphorus, <0.01−12.8 mg/L; and total nitrogen, 1.49−77.2 mg/L. Volumes are reported for 6 baseline and 9 post-manure application rainfall events. None of the post-manure application runoff volumes were significantly different by plot or by treatment type (raw manure versus treated manure).

Because concentrations alone do not reflect the true effects of different manure treatments, loads and flow-weighted mean concentrations of nutrients during post-manure application rainfall events were compared between plots with treated manure and those with raw manure. Loads of dissolved reactive phosphorus, total phosphorus, nitrate plus nitrite, and total nitrogen were calculated using the U.S. Geological Survey Graphical Constituent Loading and Analysis System. Loads of ammonia were not calculated because many of the ammonia concentrations were below the reporting limit.

During the post-manure application period, higher nitrogen loads resulted from tile flow than surface runoff. For phosphorus, the opposite was true in that higher loads resulted from surface runoff than tile flow. Combined loads (surface runoff and tile flow) of dissolved reactive phosphorus were significantly different between raw manure and treated manure plots, but there was no significant difference in combined loads of total phosphorus, nitrate plus nitrite, or total nitrogen between raw manure and treated manure plots. Flow-weighted mean concentrations were calculated for the combined loads for the post-manure application rainfall events. Flow-weighted mean concentrations of dissolved reactive phosphorus and, to a lesser extent, total phosphorus were significantly different between raw manure and treated manure plots. Flow-weighted mean concentrations of nitrate plus nitrite and total nitrogen were not significantly different between raw manure and treated manure plots. The differences in loads and flow-weighted mean concentrations between raw manure and treated manure plots indicate that dissolved reactive phosphorus was likely retained in the soil and hydrological transport was reduced for the plots amended with the treated manure as compared to raw manure. Although confirmation field testing needs to be done, these results indicate that the use of this coagulant/polymer mixture shows potential in helping to reduce flow of dissolved phosphorus from agricultural fields with applied manure.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205015","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Francy, D.S., Brady, A.M.G., Ash, B.L., and Midden, W.R., 2020, Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17: U.S. Geological Survey Scientific Investigations Report 2020–5015, 31 p., https://doi.org/10.3133/sir20205015.","productDescription":"Report: viii, 31 p.; Appendix Tables","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-095889","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":374487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5015/sir20205015.pdf","text":"Report","size":"1.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5015"},{"id":374488,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5015/sir20205015_appendix2.xlsx","text":"Appendix 2 Tables 2.1–2.4","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5015 Appendix 2 Tables"},{"id":374486,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5015/coverthb.jpg"}],"country":"United States","state":"Ohio","county":"Ottawa County, Wood County, Putnam County, Allen County, Hardin County, Hancock County, Wyandot County, Seneca County, Sandusky 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Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Boulevard Suite 100
Columbus, OH 43229–1737

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-07","noUsgsAuthors":false,"publicationDate":"2020-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M.G. 0000-0002-7414-0992 amgbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-7414-0992","contributorId":2544,"corporation":false,"usgs":true,"family":"Brady","given":"Amie","email":"amgbrady@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ash, Bethany L. 0000-0003-0590-882X","orcid":"https://orcid.org/0000-0003-0590-882X","contributorId":222890,"corporation":false,"usgs":false,"family":"Ash","given":"Bethany","email":"","middleInitial":"L.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":783433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Midden, W. Robert 0000-0002-1838-1046","orcid":"https://orcid.org/0000-0002-1838-1046","contributorId":222889,"corporation":false,"usgs":false,"family":"Midden","given":"W.","email":"","middleInitial":"Robert","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":783432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209328,"text":"ofr20201032 - 2020 - Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","interactions":[],"lastModifiedDate":"2020-05-08T11:44:10.706967","indexId":"ofr20201032","displayToPublicDate":"2020-05-07T14:53:18","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1032","displayTitle":"Simulation of the Probabilistic Plume Extent for a Potential Replacement Wastewater-Infiltration Lagoon, and Probabilistic Contributing Areas for Supply Wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","title":"Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin","docAbstract":"

An existing two-dimensional, steady-state groundwater-flow model of the shallow groundwater-flow system of the Lac du Flambeau Reservation in Vilas County, Wisconsin, originally developed by the U.S. Geological Survey, was used to simulate the potential for wastewater from a proposed relocation of a wastewater lagoon to contaminate the Lac du Flambeau Band of Lake Superior Chippewa’s drinking-water-supply wells. This simulation was completed by the U.S. Geological Survey in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service. The simulated scenarios consisted of removing wastewater infiltration from existing lagoons and re-applying that infiltration at the proposed location. Two analyses were performed for the scenarios. First, the probable extent of the plume discharging from the proposed infiltration lagoons was mapped with a Monte Carlo algorithm that used uncertainty identified during the calibration process to simulate thousands of possible outcomes. Second, the Monte Carlo method was again used to simulate a probabilistic contributing area for the Tribe’s nearby “Main Pumphouse” supply wells. The purpose of the simulations was to evaluate the potential for infiltrated wastewater to be captured by the public-supply wells.

Most features of the previously developed model remained unchanged, including calibrated parameters such as hydraulic conductivity and recharge. Thus, the same covariance distributions that were generated during calibration of the regional model (Juckem and others, 2014) remained unchanged and were used to inform the Monte Carlo simulations for the scenario simulations described in this report. The reader is encouraged to read the full report by Juckem and others (available at https://doi.org/10.3133/sir20145020) for a detailed description of the model design and calibration, as well as a description of the Monte Carlo method, its limitations, and the original results.

Results for these new scenarios indicate that the probabilistic plume extent for the proposed infiltration lagoons does not reach the Main Pumphouse wells using pumping rates and wastewater volumes estimated for 2010. Similarly, the contributing area for the Main Pumphouse wells does not capture water from within the proposed infiltration lagoon footprint. However, at higher pumping rates and wastewater volumes, as projected by the Tribe for about 2035, the contributing area for the Main Pumphouse wells do include particles that originated within the proposed lagoon footprint, albeit at low probabilities. That is, for a few of the thousands of simulations that represented a range of calibration-informed parameter covariances, some amount of infiltrated wastewater was captured by the Main Pumphouse wells under projected 2035 conditions.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201032","collaboration":"Prepared in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service","usgsCitation":"Juckem, P.F., and Fienen, M.N., 2020, Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin: U.S. Geological Survey Open-File Report 2020–1032, 10 p., https://doi.org/10.3133/ofr20201032.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-109305","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":374398,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1032/coverthb.jpg"},{"id":374399,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1032/ofr20201032.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1032"},{"id":374400,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z2YUW5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"GFLOW model files used to generate probabilistic waste-water plume extents and contributing areas to supply wells for a proposed waste-water infil-tration lagoon scenario, Lac du Flambeau, Wisconsin"}],"country":"United States","state":"Wisconsin ","county":"Vilas County","city":"Lac du Flambeau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.92378234863281,\n 45.94386878224691\n ],\n [\n -89.85013961791992,\n 45.94386878224691\n ],\n [\n -89.85013961791992,\n 45.98408084285212\n ],\n [\n -89.92378234863281,\n 45.98408084285212\n ],\n [\n -89.92378234863281,\n 45.94386878224691\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 55562

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-07","noUsgsAuthors":false,"publicationDate":"2020-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786107,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208323,"text":"sir20205009 - 2020 - Biological and habitat assessment of the Lower Rouge River, Michigan 2018","interactions":[],"lastModifiedDate":"2020-05-19T11:34:31.742175","indexId":"sir20205009","displayToPublicDate":"2020-05-07T14:26:45","publicationYear":"2020","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":"2020-5009","displayTitle":"Biological and Habitat Assessment of the Lower Rouge River, Michigan, 2018","title":"Biological and habitat assessment of the Lower Rouge River, Michigan 2018","docAbstract":"

A key component of evaluating the success of habitat remediation projects is determining preremediation conditions, biotic and abiotic, to establish a baseline and compare with postproject conditions. The Rouge River, Michigan, is a Great Lakes Area of Concern with a listed Beneficial Use Impairment related to loss of fish and wildlife habitat. A biological and habitat assessment was completed in the lower Rouge River, focused along a nearly 7-kilometer stretch of river that includes a concrete channel anticipated to be removed by 2022, to determine prerestoration conditions. Surveys documented the presence and quality of physical habitat, presence of herpetofauna, and quantified macroinvertebrate and fish assemblages at 12 sites (3 upstream from the concrete channel, 6 within the concrete channel, and 3 downstream from the concrete channel). Macroinvertebrate assemblages were dominated by Chironomidae and Oligochaeta for June and September. The electrofishing catch per unit effort was driven by Notropis atherinoides (emerald shiner) catches in June and emerald shiner and Dorosoma cepedianum (gizzard shad) catches in September. Graptemys geographica (northern map turtle) was the most common reptile observed throughout the lower Rouge River. No submergent macrophytes were discovered, and riparian vegetation was sparse in the concrete channel section. No sites scored “excellent” (total score greater than 154), upstream control sites scored “good” for overall qualitative habitat assessments (total score 105–154), and all concrete channel and downstream control sites were ranked as “marginal” (total score 56–104) or “poor” habitat (total score 0–55). Results from this assessment can be used to compare with postremediation projects in the lower Rouge River.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205009","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Roseman E.F., Fischer J., DeBruyne R.L., and Jackson, S.A., 2020, Biological and habitat assessment of the lower Rouge River, Michigan, 2018: U.S. Geological Survey Scientific Investigations Report 2020–5009, 54 p., https://doi.org/10.3133/sir20205009.","productDescription":"Report: viii, 54 p.; Data Release","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-105540","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":374499,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GUZ668","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Pre-restoration biological and physical assessment of the lower Rouge River, MI, 2018"},{"id":374498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5009/sir20205009.pdf","text":"Report","size":"5.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5009"},{"id":374497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5009/coverthb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Lower Rouge River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.49472045898436,\n 42.189355296506314\n ],\n [\n -83.09097290039062,\n 42.189355296506314\n ],\n [\n -83.09097290039062,\n 42.4417010906216\n ],\n [\n -83.49472045898436,\n 42.4417010906216\n ],\n [\n -83.49472045898436,\n 42.189355296506314\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Great Lakes Science Center
U.S. Geological Survey
1451 Green Road
Ann Arbor, MI 48105

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-05-07","noUsgsAuthors":false,"publicationDate":"2020-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Jason 0000-0001-7226-6500","orcid":"https://orcid.org/0000-0001-7226-6500","contributorId":222153,"corporation":false,"usgs":true,"family":"Fischer","given":"Jason","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin L. 0000-0002-9232-7937 rdebruyne@usgs.gov","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":4936,"corporation":false,"usgs":true,"family":"DeBruyne","given":"Robin","email":"rdebruyne@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Scott A. 0000-0003-1272-9918","orcid":"https://orcid.org/0000-0003-1272-9918","contributorId":222154,"corporation":false,"usgs":true,"family":"Jackson","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781414,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227941,"text":"70227941 - 2020 - “Good” and “bad”: Human perceptions of and interactions with urban wildlife","interactions":[],"lastModifiedDate":"2022-02-04T17:34:43.634365","indexId":"70227941","displayToPublicDate":"2020-05-07T11:29:20","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"5","title":"“Good” and “bad”: Human perceptions of and interactions with urban wildlife","docAbstract":"

Urban environments offer habitat for many species of animals. Although some of those are ubiquitous and/or undesirable, others are native and in some cases, of conservation value. In many cases, urban wildlife populations are a source of enjoyment for human residents, who sometimes invest considerable amounts in attracting them to yards and public spaces. Their presence there can serve an important educational role that helps protect non-urban habitats and species. Nonetheless, urban wildlife must survive what has been termed a “landscape of fear.” Although some of the urban wildlife that do well in this environment are benign, other populations – sometimes of a species that, in other locations, is iconic and desirable – can become problematic. Some species can serve as vectors that carry important zoonosis, such as the plague or diseases that affect other wildlife. Others can create noise or olfactory nuisances and degrade structures or usability of public spaces. Some pose hazards at busy airports, whereas still others may present an envenomation or predation risk on unwary humans. Here, we review the role that reptiles, birds, and mammals play in urban environments and discuss how urban wildlife rehabilitation centers help address some related issues. We close by looking ahead and trying to predict how global patterns such as increased urbanization and population growth may affect urban wildlife and its value for conservation.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Problematic wildlife II: New conservation and management challenges in the human-wildlife interactions","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","doi":"10.1007/978-3-030-42335-3_5","usgsCitation":"Perry, G., Boal, C.W., Verble, R., and Wallace, M., 2020, “Good” and “bad”: Human perceptions of and interactions with urban wildlife, chap. 5 of Problematic wildlife II: New conservation and management challenges in the human-wildlife interactions, p. 141-170, https://doi.org/10.1007/978-3-030-42335-3_5.","productDescription":"30 p.","startPage":"141","endPage":"170","ipdsId":"IP-094183","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, G.","contributorId":273160,"corporation":false,"usgs":false,"family":"Perry","given":"G.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verble, R.","contributorId":273161,"corporation":false,"usgs":false,"family":"Verble","given":"R.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wallace, M.","contributorId":273162,"corporation":false,"usgs":false,"family":"Wallace","given":"M.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":832641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}