The U.S. Geological Survey (USGS) Wetland and Aquatic Research Center (WARC) has two primary locations (Gainesville, Florida, and Lafayette, Louisiana) and field stations throughout the southeastern United States and Caribbean. WARC’s roots are in U.S. Fish and Wildlife Service (USFWS) and National Park Service research units that were brought into the USGS as the Biological Research Division in 1996. Founded in 2015, WARC was created from the merger of two long-standing USGS biology science Centers—the Southeast Ecological Science Center and the National Wetlands Research Center—to bring together expertise in biology, ecology, landscape science, geospatial applications, and decision support in order to address issues nationally and internationally. WARC scientists apply their expertise to a variety of wetland and aquatic research and monitoring issues that require coordinated, integrated efforts to better understand natural environments. By increasing basic understanding of the biology of important species and broader ecological and physiological processes, this research provides information to policymakers and aids managers in their stewardship of natural resources and in regulatory functions.
This strategic science plan (SSP) was developed to guide WARC research during the next 5–10 years in support of Department of the Interior (DOI) partnering bureaus such as the USFWS, the National Park Service, and the Bureau of Ocean Energy Management, as well as other Federal, State, and local natural resource management agencies. The SSP demonstrates the alignment of the WARC goals with the USGS mission areas, associated programs, and other DOI initiatives. The SSP is necessary for workforce planning and, as such, will be used as a guide for future needs for personnel. The SSP also will be instrumental in developing internal funding priorities and in promoting WARC’s capabilities to both external cooperators and other groups within the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161193","usgsCitation":"U.S. Geological Survey, 2017, The Wetland and Aquatic Research Center strategic science plan: U.S. Geological Survey Open-File Report 2016–1193, 17 p., https://doi.org/10.3133/ofr20161193.","productDescription":"iii, 17 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-072367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":334602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1193/ofr20161193.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1193"},{"id":331220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1193/coverthb.jpg"}],"contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"Renibacterium salmoninarum, the causative agent of salmonid bacterial kidney disease (BKD), is endemic in many wild trout species in northerly regions. The aim of the present study was to determine the optimal R. salmoninarum sampling/testing strategy for wild brown trout (Salmo trutta L.) populations in Iceland. Fish were netted in a lake and multiple organs—kidney, spleen, gills, oesophagus and mid-gut—were sampled and subjected to five detection tests i.e. culture, polyclonal enzyme-linked immunosorbent assay (pELISA) and three different PCR tests. The results showed that each fish had encountered R. salmoninarum but there were marked differences between results obtained depending on organ and test. The bacterium was not cultured from any kidney sample while all kidney samples were positive by pELISA. At least one organ from 92.9% of the fish tested positive by PCR. The results demonstrated that the choice of tissue and diagnostic method can dramatically influence the outcome of R. salmoninarum surveys.
","language":"English","publisher":"European Association of Fish Pathologists","usgsCitation":"Guomundsdottir, S., Applegate, L.M., Arnason, I., Kristmundsson, A., Purcell, M., and Elliott, D.G., 2017, Detecting Renibacterium salmoninarum in wild brown trout by use of multiple organ samples and diagnostic methods: Bulletin of the European Association of Fish Pathologists, v. 37, no. 1, p. 31-40.","productDescription":"12 p.","startPage":"31","endPage":"40","numberOfPages":"12","ipdsId":"IP-080542","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":347174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347206,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://eafp.org/bulletin-contents-37-1/"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffa9e4b0220bbd988fb5","contributors":{"authors":[{"text":"Guomundsdottir, S.","contributorId":198069,"corporation":false,"usgs":false,"family":"Guomundsdottir","given":"S.","email":"","affiliations":[],"preferred":false,"id":714997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Applegate, Lynn M. capplegate@usgs.gov","contributorId":5647,"corporation":false,"usgs":true,"family":"Applegate","given":"Lynn","email":"capplegate@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":714998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnason, I.O.","contributorId":198070,"corporation":false,"usgs":false,"family":"Arnason","given":"I.O.","email":"","affiliations":[],"preferred":false,"id":714999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kristmundsson, A.","contributorId":198071,"corporation":false,"usgs":false,"family":"Kristmundsson","given":"A.","email":"","affiliations":[],"preferred":false,"id":715000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":3061,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":715001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":715002,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199536,"text":"70199536 - 2017 - Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms","interactions":[],"lastModifiedDate":"2018-09-20T15:32:04","indexId":"70199536","displayToPublicDate":"2017-02-01T15:31:58","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms","docAbstract":"Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practical sense, its direct use leads to distorted sample moments and percentiles. Spatial clusters are a problem that has been identified in the past and solved with approaches ranging from ad hoc solutions to highly elaborate mathematical formulations, covering mostly the effect of clustering on the cumulative frequency distribution. The method proposed here is a form of resample, free of special assumptions, does not use weights to ponder the measurements, does not find solutions by successive approximation and provides variability in the results. The new method is illustrated with a synthetic dataset with an exponential semivariogram and purposely generated to follow a lognormal distribution. The lognormal distribution is both difficult to work with and typical of many attributes of practical interest. Testing of the new solution shows that sample subsets derived from resampled datasets can closely approximate the true probability distribution and the semivariogram, clearly outperforming the original preferentially sampled data.
","language":"English","publisher":"Springer","doi":"10.1007/s00477-016-1289-4","usgsCitation":"Olea, R., 2017, Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms: Stochastic Environmental Research and Risk Assessment, v. 31, no. 2, p. 481-491, https://doi.org/10.1007/s00477-016-1289-4.","productDescription":"11 p.","startPage":"481","endPage":"491","ipdsId":"IP-075731","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-09","publicationStatus":"PW","scienceBaseUri":"5bc031e1e4b0fc368eb53a4e","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745812,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200023,"text":"70200023 - 2017 - In situ assessment of lampricide toxicity to age-0 lake sturgeon","interactions":[],"lastModifiedDate":"2018-10-11T11:01:41","indexId":"70200023","displayToPublicDate":"2017-02-01T11:01:35","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"In situ assessment of lampricide toxicity to age-0 lake sturgeon","title":"In situ assessment of lampricide toxicity to age-0 lake sturgeon","docAbstract":"The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and 2′, 5-dichloro-4′-nitrosalicylanilide (niclosamide) are used to control sea lamprey (Petromyzon marinus), an invasive species in the Great Lakes. Age-0 lake sturgeon (Acipenser fulvescens), a species of conservationconcern, share similar stream habitats with larval sea lampreys and these streams can be targeted for lampricide applications on a 3- to 5-year cycle. Previous laboratory researchfound that lake sturgeon smaller than 100 mm could be susceptible to lampricide treatments. We conducted stream-side toxicity (bioassay) and in situ studies in conjunction with 10 lampricide applications in nine Great Lakes tributaries to determine whether sea lamprey treatments could result in in situ age-0 lake sturgeon mortality, and developed a logistic model to help predict lake sturgeon survival during future treatments. In the bioassays the observed concentrations where no lake sturgeon mortality occurred (no observable effect concentration, NOEC) were at or greater than the observed sea lamprey minimum lethal concentration (MLC or LC99) in 7 of 10 tests. We found that the mean in situ survival of age-0 lake sturgeon during 10 lampricide applications was 80%, with a range of 45–100% survival within streams. Modeling indicated that in age-0 lake sturgeon survival was negatively correlated with absolute TFM concentration and stream alkalinity, and positively correlated with stream pH and temperature. Overall survival was higher than expected based on previous research, and we expect that these data will help managers with decisions on the trade-offs between sea lamprey control and the effect on stream-specific populations of age-0 lake sturgeon.
When and whence does wood enter large mountain alluvial rivers? How stable through time are characteristics and quantities of wood deposited in a reach? These simple questions related to the complex practice of wood budgeting are explored on the Isère River in France. We hypothesise that (i) the wood originates from the riparian zone all along the alluvial reach and that (ii) the characters and quantity of wood in the reach can vary through time according to flood occurrence and provenance. In order to validate these hypotheses, two complementary approaches were performed: (i) wood pieces were surveyed along 190 km river length and taxonomy, in-channel wood macromorphology, and dendrochemistry were used to infer wood origin (local vs. upstream, respective subbasin contributions) and transport conditions; (ii) wood movement was monitored using both tracking techniques in specific sampling plots and with an experiment orchestrated using wood placement coupled with a significant artificial flood. Surveys were done over a period of 3 years so as to include two distinct sampling events to explore wood deposition and mobilisation within a channel network under different flood conditions. One of the subbasins, the Arly River, underwent a 1-in-30-year flood in 2004, allowing us to assess its effect on in-channel wood quantity and characteristics.
Results confirm that wood is primarily introduced by erosion from river banks but they are not always as close as expected from the sites of deposition. Temporal variability of wood introduced, deposited, and transferred downstream is also significant in terms of abundance and origin as shown by dendrochemical and macromorphological signatures. The types of wood observed along the channel length changes through time. Large flood signature can be detected from wood characteristics and uplands make a slight contribution. But in average, wood characteristics do not change much (no significant difference between years and tributaries in wood characteristics based on discriminant analysis). Data suggest that the interannual variability is fairly low, so that the diversity of wood characteristics is maintained by the complex and multiple sources of wood in the network. Further research is needed to better understand such patterns and to study physical breakage in space and time to better infer distance between sources and depositional zones.
We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR019141","usgsCitation":"Christensen, N.K., Minsley, B.J., and Christensen, S., 2017, Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error: Water Resources Research, v. 53, no. 2, p. 1019-1038, https://doi.org/10.1002/2016WR019141.","productDescription":"20 p.","startPage":"1019","endPage":"1038","ipdsId":"IP-081403","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488731,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pure.au.dk/portal/en/publications/dcdb9b5e-bf3c-4826-83aa-0fb5cd606845","text":"External Repository"},{"id":348146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea5e4b0531197b27f85","contributors":{"authors":[{"text":"Christensen, Nikolaj K","contributorId":199736,"corporation":false,"usgs":false,"family":"Christensen","given":"Nikolaj","email":"","middleInitial":"K","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":719888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Steen","contributorId":199737,"corporation":false,"usgs":false,"family":"Christensen","given":"Steen","email":"","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":719890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189348,"text":"70189348 - 2017 - Variability of runoff-based drought conditions in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:35:36","indexId":"70189348","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Variability of runoff-based drought conditions in the conterminous United States","docAbstract":"In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.4756","usgsCitation":"McCabe, G., Wolock, D.M., and Austin, S.H., 2017, Variability of runoff-based drought conditions in the conterminous United States: International Journal of Climatology, v. 37, no. 2, p. 1014-1021, https://doi.org/10.1002/joc.4756.","productDescription":"8 p.","startPage":"1014","endPage":"1021","ipdsId":"IP-073812","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}\n","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"5965b227e4b0d1f9f05b37dd","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":704314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":704315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Samuel H. 0000-0001-5626-023X saustin@usgs.gov","orcid":"https://orcid.org/0000-0001-5626-023X","contributorId":153,"corporation":false,"usgs":true,"family":"Austin","given":"Samuel","email":"saustin@usgs.gov","middleInitial":"H.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":704316,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189149,"text":"70189149 - 2017 - Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","interactions":[],"lastModifiedDate":"2023-11-08T15:51:27.424228","indexId":"70189149","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","docAbstract":"Sublacustrine landslide stratigraphy is considered useful for quantitative paleoseismology in low-seismicity settings. However, as the recharging of underwater slopes with sediments is one of the factors that governs the recurrence of slope failures, it is not clear if landslide deposits can provide continuous paleoseismic records in settings of frequent strong shaking. To test this, we selected three lakes in south-central Alaska that experienced a strong historical megathrust earthquake (the 1964 Mw9.2 Great Alaska Earthquake) and exhibit high sedimentation rates in their main basins (0.2 cm yr− 1–1.0 cm yr− 1). We present high-resolution reflection seismic data (3.5 kHz) and radionuclide data from sediment cores in order to investigate factors that control the establishment of a reliable landslide record. Seismic stratigraphy analysis reveals the presence of several landslide deposits in the lacustrine sedimentary infill. Most of these landslide deposits can be attributed to specific landslide events, as multiple landslide deposits sourced from different lacustrine slopes occur on a single stratigraphic horizon. We identify numerous events in the lakes: Eklutna Lake proximal basin (14 events), Eklutna Lake distal basin (8 events), Skilak Lake (7 events) and Kenai Lake (7 events). The most recent event in each basin corresponds to the historic 1964 megathrust earthquake. All events are characterized by multiple landslide deposits, which hints at a regional trigger mechanism, such as an earthquake (the synchronicity criterion). This means that the landslide record in each basin represents a record of past seismic events. Based on extrapolation of sedimentation rates derived from radionuclide dating, we roughly estimate a mean recurrence interval in the Eklutna Lake proximal basin, Eklutna Lake distal basin, Skilak Lake and Kenai Lake, at ~ 250 yrs., ~ 450 yrs., ~ 900 yrs. and ~ 450 yrs., respectively. This distinct difference in recording can be explained by variations in preconditioning factors like slope angle, slope recharging (sedimentation rate) and the sediment source area: faster slope recharging and a predominance of delta and alluvial fan failures, increase the sensitivity and lower the intensity threshold for slope instability. Also, the seismotectonic setting of the lakes has to be taken into account. This study demonstrates that sublacustrine landslides in several Alaskan lakes can be used as reliable recorders of strong earthquake shaking, when a multi-lake approach is used, and can enhance the temporal and spatial resolution of the paleoseismic record of south-central Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.05.004","usgsCitation":"Praet, N., Moernaut, J., Van Daele, M., Boes, E., Haeussler, P.J., Strupler, M., Schmidt, S., Loso, M.G., and De Batist, M., 2017, Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska): Marine Geology, v. 384, p. 103-119, https://doi.org/10.1016/j.margeo.2016.05.004.","productDescription":"17 p.","startPage":"103","endPage":"119","ipdsId":"IP-073802","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":489654,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GK6YZG","text":"USGS data release","linkHelpText":"Gridded Data from Multibeam Bathymetric Surveys of Eklutna, Kenai, and Skilak Lakes, Alaska"},{"id":470106,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2016.05.004","text":"Publisher Index Page"},{"id":343261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.5009765625,\n 59.108308258604964\n ],\n [\n -147.48046875,\n 59.108308258604964\n ],\n [\n -147.48046875,\n 61.37567331572747\n ],\n [\n -153.5009765625,\n 61.37567331572747\n ],\n [\n -153.5009765625,\n 59.108308258604964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"384","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536db1","contributors":{"authors":[{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":703165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moernaut, Jasper","contributorId":194084,"corporation":false,"usgs":false,"family":"Moernaut","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":703166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":703167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boes, Evelien","contributorId":194086,"corporation":false,"usgs":false,"family":"Boes","given":"Evelien","email":"","affiliations":[],"preferred":false,"id":703168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":703164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Strupler, Michael","contributorId":194087,"corporation":false,"usgs":false,"family":"Strupler","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Sabine","contributorId":194088,"corporation":false,"usgs":false,"family":"Schmidt","given":"Sabine","email":"","affiliations":[],"preferred":false,"id":703170,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loso, Michael G.","contributorId":146361,"corporation":false,"usgs":false,"family":"Loso","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":703171,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"De Batist, Marc 0000-0002-1625-2080","orcid":"https://orcid.org/0000-0002-1625-2080","contributorId":194089,"corporation":false,"usgs":false,"family":"De Batist","given":"Marc","email":"","affiliations":[],"preferred":false,"id":703172,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70182204,"text":"70182204 - 2017 - Donor life stage influences juvenile American eel Anguilla rostrata attraction to conspecific chemical cues","interactions":[],"lastModifiedDate":"2018-03-28T11:20:32","indexId":"70182204","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","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":"Donor life stage influences juvenile American eel Anguilla rostrata attraction to conspecific chemical cues","title":"Donor life stage influences juvenile American eel Anguilla rostrata attraction to conspecific chemical cues","docAbstract":"The present study investigated the potential role of conspecific chemical cues in inland juvenile American eel Anguilla rostrata migrations by assessing glass eel and 1 year old elver affinities to elver washings, and elver affinity to adult yellow eel washings. In two-choice maze assays, glass eels were attracted to elver washings, but elvers were neither attracted to nor repulsed by multiple concentrations of elver washings or to yellow eel washings. These results suggest that A. rostrata responses to chemical cues may be life-stage dependent and that glass eels moving inland may use the odour of the previous year class as information to guide migration. The role of chemical cues and olfaction in eel migrations warrants further investigation as a potential restoration tool.
","language":"English","publisher":"Wiley","doi":"10.1111/jfb.13190","usgsCitation":"Galbraith, H.S., Blakeslee, C.J., Schmucker, A.K., Johnson, N., Hansen, M.J., and Li, W., 2017, Donor life stage influences juvenile American eel Anguilla rostrata attraction to conspecific chemical cues: Journal of Fish Biology, v. 90, no. 1, p. 384-395, https://doi.org/10.1111/jfb.13190.","productDescription":"12 p.","startPage":"384","endPage":"395","ipdsId":"IP-074217","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":335870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-28","publicationStatus":"PW","scienceBaseUri":"58ad5fc1e4b01ccd54f8b519","contributors":{"authors":[{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":669972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":669973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmucker, Andrew K.","contributorId":173159,"corporation":false,"usgs":false,"family":"Schmucker","given":"Andrew","email":"","middleInitial":"K.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":669974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":669975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":669976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":669977,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193472,"text":"70193472 - 2017 - Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies","interactions":[],"lastModifiedDate":"2017-11-10T18:32:18","indexId":"70193472","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5153,"text":"The American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies","docAbstract":"Population monitoring is an essential component of endangered species recovery programs. The federally endangered Diamond Darter Crystallaria cincotta is in need of an effective monitoring design to improve our understanding of its distribution and track population trends. Because of their small size, cryptic coloration, and nocturnal behavior, along with limitations associated with current sampling methods, individuals are difficult to detect at known occupied sites. Therefore, research is needed to determine if survey efforts can be improved by increasing probability of individual detection. The primary objective of this study was to determine if there are seasonal and diel patterns in Diamond Darter detectability during population surveys. In addition to temporal factors, we also assessed five habitat variables that might influence individual detection. We used N-mixture models to estimate site abundances and relationships between covariates and individual detectability and ranked models using Akaike's information criteria. During 2015 three known occupied sites were sampled 15 times each between May and Oct. The best supported model included water temperature as a quadratic function influencing individual detectability, with temperatures around 22 C resulting in the highest detection probability. Detection probability when surveying at the optimal temperature was approximately 6% and 7.5% greater than when surveying at 16 C and 29 C, respectively. Time of Night and day of year were not strong predictors of Diamond Darter detectability. The results of this study will allow researchers and agencies to maximize detection probability when surveying populations, resulting in greater monitoring efficiency and likely more precise abundance estimates.
","language":"English","doi":"10.1674/0003-0031-178.1.123","usgsCitation":"Rizzo, A.A., Brown, D., Welsh, S., and Thompson, P., 2017, Factors influencing detection of the federally endangered Diamond Darter Crystallaria cincotta: Implications for long-term monitoring strategies: The American Midland Naturalist, v. 178, no. 1, p. 123-131, https://doi.org/10.1674/0003-0031-178.1.123.","productDescription":"9 p.","startPage":"123","endPage":"131","ipdsId":"IP-079169","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"178","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8d1e4b09af898c86146","contributors":{"authors":[{"text":"Rizzo, Austin A.","contributorId":191439,"corporation":false,"usgs":false,"family":"Rizzo","given":"Austin","email":"","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":721636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Donald J.","contributorId":191568,"corporation":false,"usgs":false,"family":"Brown","given":"Donald J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":721637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":721638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":721639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186026,"text":"70186026 - 2017 - Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","interactions":[],"lastModifiedDate":"2017-03-30T12:02:00","indexId":"70186026","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)","docAbstract":"Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-017-5774-0","usgsCitation":"De Jager, N.R., and Rohweder, J.J., 2017, Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010): Environmental Monitoring and Assessment, v. 189, p. 1-14, https://doi.org/10.1007/s10661-017-5774-0.","productDescription":"Article 77; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-078207","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.31787109374999,\n 36.914764288955936\n ],\n [\n -87.47314453125,\n 36.914764288955936\n ],\n [\n -87.47314453125,\n 44.94924926661153\n ],\n [\n -93.31787109374999,\n 44.94924926661153\n ],\n [\n -93.31787109374999,\n 36.914764288955936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"189","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"58de194ee4b02ff32c699c9d","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. jrohweder@usgs.gov","contributorId":460,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":687383,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182740,"text":"70182740 - 2017 - Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants","interactions":[],"lastModifiedDate":"2017-02-28T11:28:47","indexId":"70182740","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","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":"Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants","docAbstract":"In vitro bioassays have been successfully used to screen for estrogenic activity in wastewater and surface water,\nhowever, few have been applied to treated drinking water. Here, extracts of source and treated water samples\nwere assayed for estrogenic activity using T47D-KBluc cells and analyzed by liquid chromatography-Fourier transform\nmass spectrometry (LC-FTMS) for natural and synthetic estrogens (including estrone, 17β-estradiol, estriol,\nand ethinyl estradiol). None of the estrogenswere detected above the LC-FTMS quantification limits in treated samples\nand only 5 source waters had quantifiable concentrations of estrone, whereas 3 treated samples and 16 source\nsamples displayed in vitro estrogenicity. Estrone accounted for themajority of estrogenic activity in respective samples,\nhowever the remaining samples that displayed estrogenic activity had no quantitative detections of known estrogenic\ncompounds by chemical analyses. Source water estrogenicity (max, 0.47 ng 17β-estradiol equivalents\n(E2Eq) L−1) was below levels that have been linked to adverse effects in fish and other aquatic organisms. Treated\nwater estrogenicity (max, 0.078 ng E2Eq L−1) was considerably below levels that are expected to be biologically\nrelevant to human consumers. Overall, the advantage of using in vitro techniques in addition to analytical chemical\ndeterminations was displayed by the sensitivity of the T47D-KBluc bioassay, coupled with the ability tomeasure cumulative\neffects of mixtures, specifically when unknown chemicals may be present.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.02.093","collaboration":"U.S. Environmental Protection Agency","usgsCitation":"Conley, J.M., Evans, N., Mash, H., Rosenblum, L., Schenck, K., Glassmeyer, S., Furlong, E.T., Kolpin, D.W., and Wilson, V.S., 2017, Comparison of in vitro estrogenic activity and estrogen concentrations insource and treated waters from 25 U.S. drinking water treatment plants: Science of the Total Environment, v. 579, p. 1610-1617, https://doi.org/10.1016/j.scitotenv.2016.02.093.","productDescription":"8 p. ","startPage":"1610","endPage":"1617","ipdsId":"IP-072842","costCenters":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"links":[{"id":336329,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336298,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0048969716303035"}],"volume":"579","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b69a3fe4b01ccd54ff3f80","contributors":{"authors":[{"text":"Conley, Justin M.","contributorId":184086,"corporation":false,"usgs":false,"family":"Conley","given":"Justin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Nicola","contributorId":184087,"corporation":false,"usgs":false,"family":"Evans","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":673523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mash, Heath","contributorId":184088,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","affiliations":[],"preferred":false,"id":673524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosenblum, Laura","contributorId":184089,"corporation":false,"usgs":false,"family":"Rosenblum","given":"Laura","email":"","affiliations":[],"preferred":false,"id":673525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenck, Kathleen","contributorId":184090,"corporation":false,"usgs":false,"family":"Schenck","given":"Kathleen","affiliations":[],"preferred":false,"id":673526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glassmeyer, Susan","contributorId":184091,"corporation":false,"usgs":false,"family":"Glassmeyer","given":"Susan","affiliations":[],"preferred":false,"id":673527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":673521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673528,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673529,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70177786,"text":"70177786 - 2017 - Suppression of invasive lake trout in an isolated backcountry lake in Glacier National Park","interactions":[],"lastModifiedDate":"2018-03-26T14:16:36","indexId":"70177786","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Suppression of invasive lake trout in an isolated backcountry lake in Glacier National Park","docAbstract":"Fisheries managers have implemented suppression programmes to control non-native lake trout, Salvelinus namaycush (Walbaum), in several lakes throughout the western United States. This study determined the feasibility of experimentally suppressing lake trout using gillnets in an isolated backcountry lake in Glacier National Park, Montana, USA, for the conservation of threatened bull trout, Salvelinus confluentus (Suckley). The demographics of the lake trout population during suppression (2009–2013) were described, and those data were used to assess the effects of suppression scenarios on population growth rate (λ) using an age-structured population model. Model simulations indicated that the population was growing exponentially (λ = 1.23, 95% CI: 1.16–1.28) prior to suppression. However, suppression resulted in declining λ(0.61–0.79) for lake trout, which was concomitant with stable bull trout adult abundances. Continued suppression at or above observed exploitation levels is needed to ensure continued population declines.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12200","usgsCitation":"Fredenberg, C.R., Muhlfeld, C.C., Guy, C.S., D'Angelo, V., Downs, C.C., and Syslo, J.M., 2017, Suppression of invasive lake trout in an isolated backcountry lake in Glacier National Park: Fisheries Management and Ecology, v. 24, no. 1, p. 33-48, https://doi.org/10.1111/fme.12200.","productDescription":"16 p.","startPage":"33","endPage":"48","ipdsId":"IP-067234","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":330287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"5810c52ce4b0f497e7972c24","chorus":{"doi":"10.1111/fme.12200","url":"http://dx.doi.org/10.1111/fme.12200","publisher":"Wiley-Blackwell","authors":"Fredenberg C. R., Muhlfeld C. C., Guy C. S., D'Angelo V. S., Downs C. C., Syslo J. M.","journalName":"Fisheries Management and Ecology","publicationDate":"1/20/2017","auditedOn":"1/24/2017","publiclyAccessibleDate":"1/20/2017"},"contributors":{"authors":[{"text":"Fredenberg, C. R.","contributorId":187695,"corporation":false,"usgs":true,"family":"Fredenberg","given":"C.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":651809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":651797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":651796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"D'Angelo, Vincent S. vdangelo@usgs.gov","contributorId":4176,"corporation":false,"usgs":true,"family":"D'Angelo","given":"Vincent S.","email":"vdangelo@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":681371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Downs, Christopher C.","contributorId":105067,"corporation":false,"usgs":true,"family":"Downs","given":"Christopher","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":651808,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Syslo, John M.","contributorId":171452,"corporation":false,"usgs":false,"family":"Syslo","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":681372,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179238,"text":"sir20165179 - 2017 - Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","interactions":[],"lastModifiedDate":"2017-02-02T10:11:06","indexId":"sir20165179","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","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":"2016-5179","title":"Flood-inundation maps for the St. Joseph River at Elkhart, Indiana","docAbstract":"Digital flood-inundation maps for a 6.6-mile reach of the St. Joseph River at Elkhart, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind. Real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS site EKMI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current stage-discharge rating at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind., and the documented high-water marks from the flood of March 1982. The hydraulic model was then used to compute six water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 23.0 ft (the NWS “action stage”) to 28.0 ft, which is the highest stage interval of the current USGS stage-discharge rating curve and 1 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft root mean squared error and 4.9-ft horizontal resolution, resampled to a 10-ft grid) to delineate the area flooded at each stage.
The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165179","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the St. Joseph River at Elkhart, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5179, 10 p., https://doi.org/10.3133/sir20165179.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079008","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":333769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ2836","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"St. Joseph River at Elkhart, Indiana, Flood-Inundation HEC-RAS Model"},{"id":333734,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5179/coverthb.jpg"},{"id":333735,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5179/sir20165179.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5179"}],"country":"United States","state":"Indiana","otherGeospatial":"St. Joseph River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.04475021362305,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.67355293097283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
The interplay of ecology and evolution has been a rich area of research for decades. A surge of interest in this area was catalyzed by the observation that evolution by natural selection can operate at the same contemporary timescales as ecological dynamics. Specifically, recent eco-evolutionary research focuses on how rapid adaptation influences ecology, and vice versa. Evolution by non-adaptive forces also occurs quickly, with ecological consequences, but understanding the full scope of ecology–evolution (eco–evo) interactions requires explicitly addressing population-level processes – genetic and demographic. We show the strong ecological effects of non-adaptive evolutionary forces and, more broadly, the value of population-level research for gaining a mechanistic understanding of eco–evo interactions. The breadth of eco-evolutionary research should expand to incorporate the breadth of evolution itself.
No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Grear, D.A., Ballmann, A., Dusek, R.J., and Bodenstein, B., 2017, Quarterly wildlife mortality report January 2017: Wildlife Disease Association Newsletter, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-082240","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":338351,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338322,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58da2519e4b0543bf7fda7f6","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523 brichards@usgs.gov","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":3533,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"brichards@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":174374,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":686144,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188352,"text":"70188352 - 2017 - Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","interactions":[],"lastModifiedDate":"2018-03-16T11:29:21","indexId":"70188352","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","docAbstract":"Previously reported whole-rock δ18O values (5.6–7.8‰) for primitive quaternary mafic lavas from the southernmost Cascades (SMC) are often elevated (up to 1‰) relative to δ18O values expected for mafic magmas in equilibrium with mantle peridotite. Olivine, clinopyroxene, and plagioclase crystals were separated from 29 geochemically well-characterized mafic lavas for δ18O measurements by laser fluorination to assess modification of the mantle sources by ancient and modern subducted components. Oxygen isotope values of olivine phenocrysts in calc-alkaline lavas and contemporaneous high alumina olivine tholeiitic (HAOT) lavas generally exceed depleted mantle olivine values (~4.9–5.3‰). Modern addition of up to 6 wt% slab-derived fluid from Gorda serpentinized peridotite dehydration (~15‰) or chlorite dehydration (~10‰) within the serpentinized peridotite can provide the 18O enrichment detected in olivine phenocrysts (δ18Oolivine = 5.3–6.3‰) in calc-alkaline mafic lavas, and elevate 18O in overlying mantle lithosphere, as well. Specifically, although HAOT δ18Oolivine values (5.5–5.7‰) may reflect partial melting in heterogeneous 18O enriched mantle source domains that developed during multiple subduction events associated with terrane accretion (e.g., <1 wt% of ~15‰ materials), an additional 18O enrichment of up to 2 wt% of 10–15‰ slab-derived hydrous fluids might be accommodated. The calc-alkaline primitive magmas appear to have experienced a continuous range of open system processes, which operate in the mantle and during rapid magma ascent to eruption, and occasionally post quench. Textural relationships and geochemistry of these lava samples are consistent with blends of mafic phenocrysts and degassed melts in varying states of 18O disequilibrium. In lenses of accumulated melt within peridotite near the base of the crust, coexisting olivine and clinopyroxene δ18O values probably are not at isotopic equilibrium because fluids introduced into the system perturbed the δ18Omelt values. A “sudden” melt extraction event interrupts 18O equilibration in phenocrysts and poorly mixed melt(s). Rapid ascent of volatile oversaturated primitive mafic magma through the crust appears to be accompanied by devolatilization and crystallization of anorthite-rich plagioclase with elevated δ18Oplag values. The (Sr/P)N values for the whole rock geochemistry are consistent with a 87Sr/86Sr ~0.7027 slab-derived fluid addition into the infertile peridotite source of magmas, and melt devolatilization is recorded in the mixture of disequilibrium δ18O values for the constituent phases of lavas. Morbidity of the Gorda Plate as it undergoes intense deformation from the spreading ridge to the trench is likely a key factor to developing the carrying capacity of hydrous fluids and mineral phases in the slab subducting into the SMC mantle.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2017-5588","usgsCitation":"Underwood, S.J., and Clynne, M.A., 2017, Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California: American Mineralogist, v. 102, no. 2, p. 251-261, https://doi.org/10.2138/am-2017-5588.","productDescription":"11 p.","startPage":"251","endPage":"261","ipdsId":"IP-075965","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4920654296875,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4be","contributors":{"authors":[{"text":"Underwood, Sandra J.","contributorId":192684,"corporation":false,"usgs":false,"family":"Underwood","given":"Sandra","email":"","middleInitial":"J.","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":697361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189596,"text":"70189596 - 2017 - A discrete stage-structured model of California newt population dynamics during a period of drought","interactions":[],"lastModifiedDate":"2018-03-26T12:18:31","indexId":"70189596","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2475,"text":"Journal of Theoretical Biology","active":true,"publicationSubtype":{"id":10}},"title":"A discrete stage-structured model of California newt population dynamics during a period of drought","docAbstract":"We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtbi.2016.11.011","usgsCitation":"Jones, M.T., Milligan, W.R., Kats, L.B., Vandergon, T.L., Honeycutt, R.L., Fisher, R.N., Davis, C.L., and Lucas, T.A., 2017, A discrete stage-structured model of California newt population dynamics during a period of drought: Journal of Theoretical Biology, v. 414, p. 245-253, https://doi.org/10.1016/j.jtbi.2016.11.011.","productDescription":"9 p.","startPage":"245","endPage":"253","ipdsId":"IP-081597","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":343986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"414","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e25e4b0d1f9f064075b","contributors":{"authors":[{"text":"Jones, Marjorie T.","contributorId":194782,"corporation":false,"usgs":false,"family":"Jones","given":"Marjorie","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":705333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milligan, William R.","contributorId":194783,"corporation":false,"usgs":false,"family":"Milligan","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":705334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kats, Lee B.","contributorId":106034,"corporation":false,"usgs":true,"family":"Kats","given":"Lee","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":705335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergon, Thomas L.","contributorId":38489,"corporation":false,"usgs":true,"family":"Vandergon","given":"Thomas","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":705336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Honeycutt, Rodney L.","contributorId":106426,"corporation":false,"usgs":true,"family":"Honeycutt","given":"Rodney","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":705337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Courtney L.","contributorId":181922,"corporation":false,"usgs":false,"family":"Davis","given":"Courtney","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":705339,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lucas, Timothy A.","contributorId":194784,"corporation":false,"usgs":false,"family":"Lucas","given":"Timothy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705340,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195760,"text":"70195760 - 2017 - Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results","interactions":[],"lastModifiedDate":"2018-02-28T14:03:02","indexId":"70195760","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results","docAbstract":"Drought is a natural climatic phenomenon that occurs throughout the world and impacts many sectors of society. To help decision-makers reduce the impacts of drought, it is important to improve monitoring tools that provide relevant and timely information in support of drought mitigation decisions. Given that drought is a complex natural hazard that manifests in different forms, monitoring can be improved by integrating various types of information (e.g., remote sensing and climate) that is timely and region specific to identify where and when droughts are occurring. The Vegetation Drought Response Index for Canada (VegDRI-Canada) is a recently developed drought monitoring tool for Canada. VegDRI-Canada extends the initial VegDRI concept developed for the conterminous United States to a broader transnational coverage across North America. VegDRI-Canada models are similar to those developed for the United States, integrating satellite observations of vegetation status, climate data, and biophysical information on land use and land cover, soil characteristics, and other environmental factors. Collectively, these different types of data are integrated into the hybrid VegDRI-Canada to isolate the effects of drought on vegetation. Twenty-three weekly VegDRI-Canada models were built for the growing season (April–September) through the weekly analysis of these data using a regression tree-based data mining approach. A 15-year time series of VegDRI-Canada results (s to 2014) was produced using these models and the output was validated by randomly selecting 20% of the historical data, as well as holdout year (15% unseen data) across the growing season that the Pearson’s correlation ranged from 0.6 to 0.77. A case study was also conducted to evaluate the VegDRI-Canada results over the prairie region of Canada for two drought years and one non-drought year for three weekly periods of the growing season (i.e., early-, mid-, and late season). The comparison of the VegDRI-Canada map with the Canadian Drought Monitor (CDM), an independent drought indicator, showed that the VegDRI-Canada maps depicted key spatial drought severity patterns during the two targeted drought years consistent with the CDM. In addition, VegDRI-Canada was compared with canola yields in the Prairie Provinces at the regional scale for a period from 2000 to 2014 to evaluate the indices’ applicability for monitoring drought impacts on crop production. The result showed that VegDRI-Canada values had a relatively higher correlation (i.e., r > 0.5) with canola yield for nonirrigated croplands in the Canadian Prairies region in areas where drought is typically a limiting factor on crop growth, but showed a negative relationship in the southeastern Prairie region, where water availability is less of a limiting factor and in some cases a hindrance to crop growth when waterlogging occurs. These initial results demonstrate VegDRI-Canada’s utility for monitoring drought-related vegetation conditions, particularly in drought prone areas. In general, the results indicated that the VegDRI-Canada models showed sensitivity to known agricultural drought events in Canada over the 15-year period mainly for nonirrigated areas.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2017.1286728","usgsCitation":"Tadesse, T., Champagne, C., Wardlow, B.D., Hadwen, T.A., Brown, J.F., Demisse, G.B., Bayissa, Y.A., and Davidson, A.M., 2017, Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results: GIScience and Remote Sensing, v. 54, no. 2, p. 230-257, https://doi.org/10.1080/15481603.2017.1286728.","productDescription":"28 p.","startPage":"230","endPage":"257","ipdsId":"IP-082660","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499999,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/99a8bce08c6143daaa4fc548ecdb117b","text":"External Repository"},{"id":352144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -138.779296875,\n 41.83682786072714\n ],\n [\n -51.67968749999999,\n 41.83682786072714\n ],\n [\n -51.67968749999999,\n 60\n ],\n [\n -138.779296875,\n 60\n ],\n [\n -138.779296875,\n 41.83682786072714\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-08","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4bc","contributors":{"authors":[{"text":"Tadesse, Tsegaye 0000-0002-4102-1137","orcid":"https://orcid.org/0000-0002-4102-1137","contributorId":147617,"corporation":false,"usgs":false,"family":"Tadesse","given":"Tsegaye","email":"","affiliations":[],"preferred":false,"id":729876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champagne, Catherine","contributorId":202836,"corporation":false,"usgs":false,"family":"Champagne","given":"Catherine","email":"","affiliations":[{"id":27920,"text":"Agriculture and Agrifood Canada","active":true,"usgs":false}],"preferred":false,"id":729877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wardlow, Brian D. 0000-0002-4767-581X","orcid":"https://orcid.org/0000-0002-4767-581X","contributorId":191403,"corporation":false,"usgs":false,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":729878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hadwen, Trevor A.","contributorId":202837,"corporation":false,"usgs":false,"family":"Hadwen","given":"Trevor","email":"","middleInitial":"A.","affiliations":[{"id":27920,"text":"Agriculture and Agrifood Canada","active":true,"usgs":false}],"preferred":false,"id":729879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":729875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Demisse, Getachew B.","contributorId":202845,"corporation":false,"usgs":false,"family":"Demisse","given":"Getachew","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":729894,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bayissa, Yared A.","contributorId":202846,"corporation":false,"usgs":false,"family":"Bayissa","given":"Yared","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729895,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davidson, Andrew M.","contributorId":202847,"corporation":false,"usgs":false,"family":"Davidson","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":729896,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189597,"text":"70189597 - 2017 - Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","interactions":[],"lastModifiedDate":"2017-07-18T12:03:52","indexId":"70189597","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific","docAbstract":"Between September and November 1991, 54 adult skinks from 15 species were collected by hand or blowpipe from several localities on Rarotonga, Cook Islands, Ovalau Island, Fiji, and Papua New Guinea (PNG), and their feces were examined for coccidians. Species included 5 seaside skinks (Emoia atrocostata), 1 Pacific blue-tailed skink (Emoia caeroleocauda), 2 Fiji slender treeskinks (Emoia concolor), 15 white-bellied copper-striped skinks (Emoia cyanura), 1 Bulolo River forest skink (Emoia guttata), 6 dark-bellied copper-striped skinks (Emoia impar), 5 Papua five-striped skinks (Emoia jakati), 2 Papua slender treeskinks (Emoia kordoana), 3 Papua robust treeskinks (Emoia longicauda), 1 brown-backed forest skink (Emoia loveridgei), 3 Papua black-sided skinks (Emoia pallidiceps), 2 Papua white-spotted skinks (Emoia physicae), 2 Papua yellow-head skinks (Emoia popei), 1 Papua brown forest skink (Emoia submetallica), and 5 Fiji barred treeskinks (Emoia trossula) Species of Eimeria (Ei.) were detected from these Emoia (Em.) spp. and are described here as new. Oocysts of Eimeria iovai n. sp. from Em. pallidiceps from PNG were ellipsoidal with a bilayered wall (L × W) 26.5 × 18.1 μm, with a length/width ratio (L/W) of 1.1. Both micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian also was found in Em. atrocostata from PNG. Oocysts of Eimeria kirkpatricki n. sp. from Em. atrocostata from PNG were ellipsoidal with a bilayered wall, 18.6 × 13.5 μm, L/W 1.4. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. This eimerian was also shared by Em. cyanura from the Cook Islands and Fiji, Em. imparfrom the Cook Islands, Em. loveridgei from PNG, Em. pallidicepsfrom PNG, Em. popei from PNG, and Em. submetallica from PNG. Oocysts of Eimeria stevejayuptoni n. sp. from Em. longicaudawere subspheroidal to ellipsoidal with a bilayered wall, 18.7 × 16.6 μm, L/W 1.1. A micropyle and oocyst residuum were absent, but a fragmented polar granule was present. Oocysts of Eimeria emoia n. sp. from Em. longicauda from PNG were cylindroidal with a bilayered wall, 29.2 × 15.7 μm, L/W 1.9. A micropyle and oocyst residuum were absent, but a polar granule was present. These are the first eimerians reported from Emoia spp. and they add to our growing knowledge of the coccidian fauna of scincid lizards of the South Pacific.
","language":"English","publisher":"American Society of Parasitologists","doi":"10.1645/16-67","usgsCitation":"McAllister, C.T., Duszynski, D.W., Austin, C., and Fisher, R.N., 2017, Four new species of Eimeria (Apicomplexa: Eimeriidae) from Emoia spp. Skinks (Sauria: Scincidae), from Papua New Guinea and the Insular Pacific: Journal of Parasitology, v. 103, no. 1, p. 103-110, https://doi.org/10.1645/16-67.","productDescription":"8 p.","startPage":"103","endPage":"110","ipdsId":"IP-078006","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":343987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Papua New Guinea","otherGeospatial":"Insular Pacific","volume":"103","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e25e4b0d1f9f0640756","contributors":{"authors":[{"text":"McAllister, Chris T.","contributorId":22704,"corporation":false,"usgs":true,"family":"McAllister","given":"Chris","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":705341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duszynski, Donald W.","contributorId":87869,"corporation":false,"usgs":true,"family":"Duszynski","given":"Donald","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":705342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Austin, Christopher C.","contributorId":8772,"corporation":false,"usgs":true,"family":"Austin","given":"Christopher C.","affiliations":[],"preferred":false,"id":705343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":705344,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195840,"text":"70195840 - 2017 - Using diurnal temperature signals to infer vertical groundwater-surface water exchange","interactions":[],"lastModifiedDate":"2018-03-06T11:07:46","indexId":"70195840","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Using diurnal temperature signals to infer vertical groundwater-surface water exchange","docAbstract":"Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12459","usgsCitation":"Irvine, D.J., Briggs, M.A., Lautz, L.K., Gordon, R.P., McKenzie, J.M., and Cartwright, I., 2017, Using diurnal temperature signals to infer vertical groundwater-surface water exchange: Groundwater, v. 55, no. 1, p. 10-26, https://doi.org/10.1111/gwat.12459.","productDescription":"17 p.","startPage":"10","endPage":"26","ipdsId":"IP-077274","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":470089,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.12459","text":"Publisher Index Page"},{"id":352253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-03","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4b8","contributors":{"authors":[{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":730253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Ryan P.","contributorId":202947,"corporation":false,"usgs":false,"family":"Gordon","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":7257,"text":"Maine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":730254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":730255,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cartwright, Ian","contributorId":190405,"corporation":false,"usgs":false,"family":"Cartwright","given":"Ian","affiliations":[],"preferred":false,"id":730256,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189714,"text":"70189714 - 2017 - Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure","interactions":[],"lastModifiedDate":"2017-07-21T11:50:56","indexId":"70189714","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure","docAbstract":"The ShakeCast system is an openly available, near real-time post-earthquake information management system. ShakeCast is widely used by public and private emergency planners and responders, lifeline utility operators and transportation engineers to automatically receive and process ShakeMap products for situational awareness, inspection priority, or damage assessment of their own infrastructure or building portfolios. The success of ShakeCast to date and its broad, critical-user base mandates improved software usability and functionality, including improved engineering-based damage and loss functions. In order to make the software more accessible to novice users—while still utilizing advanced users’ technical and engineering background—we have developed a “ShakeCast Workbook”, a well documented, Excel spreadsheet-based user interface that allows users to input notification and inventory data and export XML files requisite for operating the ShakeCast system. Users will be able to select structure based on a minimum set of user-specified facility (building location, size, height, use, construction age, etc.). “Expert” users will be able to import user-modified structural response properties into facility inventory associated with the HAZUS Advanced Engineering Building Modules (AEBM). The goal of the ShakeCast system is to provide simplified real-time potential impact and inspection metrics (i.e., green, yellow, orange and red priority ratings) to allow users to institute customized earthquake response protocols. Previously, fragilities were approximated using individual ShakeMap intensity measures (IMs, specifically PGA and 0.3 and 1s spectral accelerations) for each facility but we are now performing capacity-spectrum damage state calculations using a more robust characterization of spectral deamnd.We are also developing methods for the direct import of ShakeMap’s multi-period spectra in lieu of the assumed three-domain design spectrum (at 0.3s for constant acceleration; 1s or 3s for constant velocity and constant displacement at very long response periods). As part of ongoing ShakeCast research and development, we will also explore the use of ShakeMap IM uncertainty estimates and evaluate the assumption of employing multiple response spectral damping values rather than the single 5%-damped value currently employed. Developing and incorporating advanced fragility assignments into the ShakeCast Workbook requires related software modifications and database improvements; these enhancements are part of an extensive rewrite of the ShakeCast application.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th World Conference on Earthquake Engineering","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"16th World Conference on Earthquake Engineering","language":"English","publisher":"16th World Conference on Earthquake Engineering","usgsCitation":"Wald, D.J., Lin, K., Kircher, C.A., Jaiswal, K.S., Luco, N., Turner, L., and Slosky, D., 2017, Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure, in Proceedings of the 16th World Conference on Earthquake Engineering.","ipdsId":"IP-080219","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344163,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usgs.github.io/shakecast/2017_16WCEE.html"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597312aae4b0ec1a488718d7","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kircher, C. A.","contributorId":194952,"corporation":false,"usgs":false,"family":"Kircher","given":"C.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, L.","contributorId":194953,"corporation":false,"usgs":false,"family":"Turner","given":"L.","email":"","affiliations":[],"preferred":false,"id":705902,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slosky, Daniel 0000-0001-7407-3606 dslosky@usgs.gov","orcid":"https://orcid.org/0000-0001-7407-3606","contributorId":194954,"corporation":false,"usgs":true,"family":"Slosky","given":"Daniel","email":"dslosky@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705903,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192059,"text":"70192059 - 2017 - Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach","interactions":[],"lastModifiedDate":"2017-10-19T14:44:32","indexId":"70192059","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach","title":"Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach","docAbstract":"Trout species often segregate along elevational gradients, yet the mechanisms driving this pattern are not fully understood. On the Logan River, Utah, USA, exotic brown trout (Salmo trutta) dominate at low elevations but are near-absent from high elevations with native Bonneville cutthroat trout (Onchorhynchus clarkii utah). We used a spatially-explicit Bayesian modeling approach to evaluate how abiotic conditions (describing mechanisms related to temperature and physical habitat) as well as propagule pressure explained the distribution of brown trout in this system. Many covariates strongly explained redd abundance based on model performance and coefficient strength, including average annual temperature, average summer temperature, gravel availability, distance from a concentrated stocking area, and anchor ice-impeded distance from a concentrated stocking area. In contrast, covariates that exhibited low performance in models and/or a weak relationship to redd abundance included reach-average water depth, stocking intensity to the reach, average winter temperature, and number of days with anchor ice. Even if climate change creates more suitable summer temperature conditions for brown trout at high elevations, our findings suggest their success may be limited by other conditions. The potential role of anchor ice in limiting movement upstream is compelling considering evidence suggesting anchor ice prevalence on the Logan River has decreased significantly over the last several decades, likely in response to climatic changes. Further experimental and field research is needed to explore the role of anchor ice, spawning gravel availability, and locations of historical stocking in structuring brown trout distributions on the Logan River and elsewhere.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1322-z","usgsCitation":"Meredith, C.S., Budy, P., Hooten, M., and Oliveira Prates, M., 2017, Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach: Biological Invasions, v. 19, no. 2, p. 503-519, https://doi.org/10.1007/s10530-016-1322-z.","productDescription":"17 p.","startPage":"503","endPage":"519","ipdsId":"IP-069503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Logan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8023681640625,\n 41.734941789858006\n ],\n [\n -111.53594970703125,\n 41.734941789858006\n ],\n [\n -111.53594970703125,\n 41.95336258301847\n ],\n [\n -111.8023681640625,\n 41.95336258301847\n ],\n [\n -111.8023681640625,\n 41.734941789858006\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65cac","contributors":{"authors":[{"text":"Meredith, Christy S.","contributorId":197695,"corporation":false,"usgs":false,"family":"Meredith","given":"Christy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":714105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":714038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliveira Prates, Marcos","contributorId":197696,"corporation":false,"usgs":false,"family":"Oliveira Prates","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":714106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187165,"text":"70187165 - 2017 - Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","interactions":[],"lastModifiedDate":"2017-04-25T15:20:57","indexId":"70187165","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Tracer-based characterization of hyporheic exchange and benthic biolayers in streams","docAbstract":"Shallow benthic biolayers at the top of the streambed are believed to be places of enhanced biogeochemical turnover within the hyporheic zone. They can be investigated by reactive stream tracer tests with tracer recordings in the streambed and in the stream channel. Common in-stream measurements of such reactive tracers cannot localize where the processing primarily takes place, whereas isolated vertical depth profiles of solutes within the hyporheic zone are usually not representative of the entire stream. We present results of a tracer test where we injected the conservative tracer bromide together with the reactive tracer resazurin into a third-order stream and combined the recording of in-stream breakthrough curves with multidepth sampling of the hyporheic zone at several locations. The transformation of resazurin was used as an indicator of metabolism, and high-reactivity zones were identified from depth profiles. The results from our subsurface analysis indicate that the potential for tracer transformation (i.e., the reaction rate constant) varied with depth in the hyporheic zone. This highlights the importance of the benthic biolayer, which we found to be on average 2 cm thick in this study, ranging from one third to one half of the full depth of the hyporheic zone. The reach-scale approach integrated the effects of processes along the reach length, isolating hyporheic processes relevant for whole-stream chemistry and estimating effective reaction rates.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR019393","usgsCitation":"Knapp, J., Gonzalez-Pinzon, R., Drummond, J.D., Larsen, L., Cirpka, O.A., and Harvey, J.W., 2017, Tracer-based characterization of hyporheic exchange and benthic biolayers in streams: Water Resources Research, v. 53, no. 2, p. 1575-1594, https://doi.org/10.1002/2016WR019393.","productDescription":"20 p.","startPage":"1575","endPage":"1594","ipdsId":"IP-080169","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019393","text":"Publisher Index Page"},{"id":340374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"59006062e4b0e85db3a5ddd1","contributors":{"authors":[{"text":"Knapp, Julia L.A.","contributorId":191389,"corporation":false,"usgs":false,"family":"Knapp","given":"Julia L.A.","affiliations":[],"preferred":false,"id":692887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez-Pinzon, Ricardo","contributorId":191362,"corporation":false,"usgs":false,"family":"Gonzalez-Pinzon","given":"Ricardo","email":"","affiliations":[],"preferred":false,"id":692888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drummond, Jennifer D.","contributorId":191390,"corporation":false,"usgs":false,"family":"Drummond","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":692889,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G.","contributorId":191391,"corporation":false,"usgs":false,"family":"Larsen","given":"Laurel G.","affiliations":[],"preferred":false,"id":692890,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cirpka, Olaf A.","contributorId":191392,"corporation":false,"usgs":false,"family":"Cirpka","given":"Olaf","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":692891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692886,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184967,"text":"70184967 - 2017 - Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)","interactions":[],"lastModifiedDate":"2017-03-15T12:07:21","indexId":"70184967","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5071,"text":"NeoBiota","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)","docAbstract":"Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.
","language":"English","publisher":"Pensoft","doi":"10.3897/neobiota.32.8884","usgsCitation":"Jarnevich, C.S., Young, N.E., Sheffels, T.R., Carter, J., Systma, M.D., and Talbert, C., 2017, Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus): NeoBiota, v. 32, p. 107-125, https://doi.org/10.3897/neobiota.32.8884.","productDescription":"19 p.","startPage":"107","endPage":"125","ipdsId":"IP-065118","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/neobiota.32.8884","text":"Publisher Index Page"},{"id":337613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58ca52cce4b0849ce97c869a","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":189060,"corporation":false,"usgs":false,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":683742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheffels, Trevor R.","contributorId":140176,"corporation":false,"usgs":false,"family":"Sheffels","given":"Trevor","email":"","middleInitial":"R.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":683743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Jacoby 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":2399,"corporation":false,"usgs":true,"family":"Carter","given":"Jacoby","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":683744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Systma, Mark D.","contributorId":140177,"corporation":false,"usgs":false,"family":"Systma","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":13401,"text":"Portland State University, Portland Oregon","active":true,"usgs":false}],"preferred":false,"id":683745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":683746,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}