{"pageNumber":"582","pageRowStart":"14525","pageSize":"25","recordCount":40783,"records":[{"id":70174027,"text":"70174027 - 2014 - Supplemental feeding alters migration of a temperate ungulate","interactions":[],"lastModifiedDate":"2018-09-18T16:01:08","indexId":"70174027","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Supplemental feeding alters migration of a temperate ungulate","docAbstract":"

Conservation of migration requires information on behavior and environmental determinants. The spatial distribution of forage resources, which migration exploits, often are altered and may have subtle, unintended consequences. Supplemental feeding is a common management practice, particularly for ungulates in North America and Europe, and carryover effects on behavior of this anthropogenic manipulation of forage are expected in theory, but have received limited empirical evaluation, particularly regarding effects on migration. We used global positioning system (GPS) data to evaluate the influence of winter feeding on migration behavior of 219 adult female elk (Cervus elaphus) from 18 fed ranges and 4 unfed ranges in western Wyoming. Principal component analysis revealed that the migratory behavior of fed and unfed elk differed in distance migrated, and the timing of arrival to, duration on, and departure from summer range. Fed elk migrated 19.2 km less, spent 11 more days on stopover sites, arrived to summer range 5 days later, resided on summer range 26 fewer days, and departed in the autumn 10 days earlier than unfed elk. Time-to-event models indicated that differences in migratory behavior between fed and unfed elk were caused by altered sensitivity to the environmental drivers of migration. In spring, unfed elk migrated following plant green-up closely, whereas fed elk departed the feedground but lingered on transitional range, thereby delaying their arrival to summer range. In autumn, fed elk were more responsive to low temperatures and precipitation events, causing earlier departure from summer range than unfed elk. Overall, supplemental feeding disconnected migration by fed elk from spring green-up and decreased time spent on summer range, thereby reducing access to quality forage. Our findings suggest that ungulate migration can be substantially altered by changes to the spatial distribution of resources, including those of anthropogenic origin, and that management practices applied in one season may have unintended behavioral consequences in subsequent seasons.

","language":"English","publisher":"Ecology Society of America","doi":"10.1890/13-2092.1","usgsCitation":"Jones, J.D., Kauffman, M., Monteith, K.L., Scurlock, B.M., Albeke, S.E., and Cross, P.C., 2014, Supplemental feeding alters migration of a temperate ungulate: Ecological Applications, v. 24, no. 7, p. 1769-1779, https://doi.org/10.1890/13-2092.1.","productDescription":"11 p.","startPage":"1769","endPage":"1779","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051734","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324298,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1890/13-2092.1/abstract"},{"id":324334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.830078125,\n 41.705728515237524\n ],\n [\n -110.830078125,\n 44.276671273775186\n ],\n [\n -107.22656249999999,\n 44.276671273775186\n ],\n [\n -107.22656249999999,\n 41.705728515237524\n ],\n [\n -110.830078125,\n 41.705728515237524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d0836e4b07657d1a37586","contributors":{"authors":[{"text":"Jones, Jennifer D.","contributorId":145754,"corporation":false,"usgs":false,"family":"Jones","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[{"id":16227,"text":"Institute on Ecosystems,Montana State University MT, 59715 USA","active":true,"usgs":false}],"preferred":false,"id":640635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew mkauffman@usgs.gov","contributorId":171443,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":640572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monteith, Kevin L.","contributorId":83400,"corporation":false,"usgs":true,"family":"Monteith","given":"Kevin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":640636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":640637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Albeke, Shannon E.","contributorId":81781,"corporation":false,"usgs":true,"family":"Albeke","given":"Shannon","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":640638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":640639,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70143395,"text":"70143395 - 2014 - Mississippi River nitrate loads from high frequency sensor measurements and regression-based load estimation","interactions":[],"lastModifiedDate":"2015-03-19T09:35:13","indexId":"70143395","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Mississippi River nitrate loads from high frequency sensor measurements and regression-based load estimation","docAbstract":"

Accurately quantifying nitrate (NO3–) loading from the Mississippi River is important for predicting summer hypoxia in the Gulf of Mexico and targeting nutrient reduction within the basin. Loads have historically been modeled with regression-based techniques, but recent advances with high frequency NO3– sensors allowed us to evaluate model performance relative to measured loads in the lower Mississippi River. Patterns in NO3– concentrations and loads were observed at daily to annual time steps, with considerable variability in concentration-discharge relationships over the two year study. Differences were particularly accentuated during the 2012 drought and 2013 flood, which resulted in anomalously high NO3– concentrations consistent with a large flush of stored NO3– from soil. The comparison between measured loads and modeled loads (LOADEST, Composite Method, WRTDS) showed underestimates of only 3.5% across the entire study period, but much larger differences at shorter time steps. Absolute differences in loads were typically greatest in the spring and early summer critical to Gulf hypoxia formation, with the largest differences (underestimates) for all models during the flood period of 2013. In additional to improving the accuracy and precision of monthly loads, high frequency NO3– measurements offer additional benefits not available with regression-based or other load estimation techniques.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/es504029c","usgsCitation":"Pellerin, B.A., Bergamaschi, B., Gilliom, R.J., Crawford, C.G., Saraceno, J.F., Frederick, C.P., Downing, B.D., and Murphy, J., 2014, Mississippi River nitrate loads from high frequency sensor measurements and regression-based load estimation: Environmental Science & Technology, v. 48, no. 21, p. 12612-12619, https://doi.org/10.1021/es504029c.","productDescription":"8 p.","startPage":"12612","endPage":"12619","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055261","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":472726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es504029c","text":"Publisher Index Page"},{"id":298741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","county":"Baton Rouge","otherGeospatial":"Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.23458862304688,\n 30.40485985382934\n ],\n [\n -91.23458862304688,\n 30.526779182105784\n ],\n [\n -91.15631103515625,\n 30.526779182105784\n ],\n [\n -91.15631103515625,\n 30.40485985382934\n ],\n [\n -91.23458862304688,\n 30.40485985382934\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"21","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-24","publicationStatus":"PW","scienceBaseUri":"550bf332e4b02e76d759cdf1","chorus":{"doi":"10.1021/es504029c","url":"http://dx.doi.org/10.1021/es504029c","publisher":"American Chemical Society (ACS)","authors":"Pellerin Brian A., Bergamaschi Brian A., Gilliom Robert J., Crawford Charles G., Saraceno JohnFranco, Frederick C. Paul, Downing Bryan D., Murphy Jennifer C.","journalName":"Environmental Science & Technology","publicationDate":"11/4/2014","auditedOn":"3/4/2016","publiclyAccessibleDate":"11/4/2014"},"contributors":{"authors":[{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":1448,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","email":"bbergama@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":542690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saraceno, John Franco 0000-0003-0064-1820 saraceno@usgs.gov","orcid":"https://orcid.org/0000-0003-0064-1820","contributorId":2328,"corporation":false,"usgs":true,"family":"Saraceno","given":"John","email":"saraceno@usgs.gov","middleInitial":"Franco","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542691,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frederick, C. Paul 0000-0003-1762-519X pfreder@usgs.gov","orcid":"https://orcid.org/0000-0003-1762-519X","contributorId":4755,"corporation":false,"usgs":true,"family":"Frederick","given":"C.","email":"pfreder@usgs.gov","middleInitial":"Paul","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542694,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542693,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":139729,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer C.","email":"jmurphy@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542695,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70142181,"text":"70142181 - 2014 - Depth gradients in food-web processes linking habitats in large lakes: Lake Superior as an exemplar ecosystem","interactions":[],"lastModifiedDate":"2015-03-03T11:00:00","indexId":"70142181","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Depth gradients in food-web processes linking habitats in large lakes: Lake Superior as an exemplar ecosystem","docAbstract":"
    \n
  1. In large lakes around the world, depth-based changes in the abundance and distribution of invertebrate and fish species suggest that there may be concomitant changes in patterns of resource allocation. Using Lake Superior of the Laurentian Great Lakes as an example, we explored this idea through stable isotope analyses of 13 major fish taxa.
    2. \n
  2. Patterns in carbon and nitrogen isotope ratios revealed use of both littoral and profundal benthos among populations of most taxa analysed regardless of the depth of their habitat, providing evidence of nearshore–offshore trophic linkages in the largest freshwater lake by area in the world.
    3. \n
  3. Isotope-mixing model results indicated that the overall importance of benthic food-web pathways to fish was highest in nearshore species, whereas the importance of planktonic pathways increased in offshore species. These characteristics, shared with the Great Lakes of Africa, Russia and Japan, appear to be governed by two key processes: high benthic production in nearshore waters and the prevalence of diel vertical migration (DVM) among offshore invertebrate and fish taxa. DVM facilitates use of pelagic food resources by deep-water biota and represents an important process of trophic linkage among habitats in large lakes.
    4. \n
  4. Support of whole-lake food webs through trophic linkages among pelagic, profundal and littoral habitats appears to be integral to the functioning of large lakes. These linkages can be disrupted though ecosystem disturbance such as eutrophication or the effects of invasive species and should be considered in native species restoration efforts.
    5. \n
","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12415","usgsCitation":"Sierszen, M.E., Hrabik, T.R., Stockwell, J.D., Cotter, A.M., Hoffman, J.C., and Yule, D.L., 2014, Depth gradients in food-web processes linking habitats in large lakes: Lake Superior as an exemplar ecosystem: Freshwater Biology, v. 59, no. 10, p. 2122-2136, https://doi.org/10.1111/fwb.12415.","productDescription":"15 p.","startPage":"2122","endPage":"2136","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050895","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":298243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.363037109375,\n 49.01625665778159\n ],\n [\n -89.439697265625,\n 48.42920055556841\n ],\n [\n -89.703369140625,\n 48.04136507445029\n ],\n [\n -91.461181640625,\n 47.44294999517949\n ],\n [\n -92.120361328125,\n 46.852678248531106\n ],\n [\n -92.0654296875,\n 46.5739667965278\n ],\n [\n -91.01074218749999,\n 46.7549166192819\n ],\n [\n -91.021728515625,\n 46.52863469527167\n ],\n [\n -90.296630859375,\n 46.543749602738565\n ],\n [\n -89.09912109375,\n 46.90524554642923\n ],\n [\n -88.41796875,\n 47.27177506640826\n ],\n [\n -88.65966796875,\n 46.7549166192819\n ],\n [\n -88.428955078125,\n 46.64189395892874\n ],\n [\n -88.06640625,\n 46.81509864599243\n ],\n [\n -87.099609375,\n 46.354510837365254\n ],\n [\n -85.78125,\n 46.55886030311719\n ],\n [\n -85.133056640625,\n 46.63435070293566\n ],\n [\n -85.0341796875,\n 46.37725420510028\n ],\n [\n -84.254150390625,\n 46.37725420510028\n ],\n [\n -84.210205078125,\n 46.63435070293566\n ],\n [\n -84.44091796875,\n 47.04766864046083\n ],\n [\n -84.61669921875,\n 47.53945544742392\n ],\n [\n -84.91333007812499,\n 47.67278567576541\n ],\n [\n -84.67163085937499,\n 48.04136507445029\n ],\n [\n -85.02319335937499,\n 48.158757304569235\n ],\n [\n -85.62744140625,\n 48.019324184801185\n ],\n [\n -86.341552734375,\n 48.80686346108517\n ],\n [\n -88.143310546875,\n 49.0738659012854\n ],\n [\n -88.363037109375,\n 49.01625665778159\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","issue":"10","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-14","publicationStatus":"PW","scienceBaseUri":"54f6e93ce4b02419550d309c","contributors":{"authors":[{"text":"Sierszen, Michael E.","contributorId":63320,"corporation":false,"usgs":false,"family":"Sierszen","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":541695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":541696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":541697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cotter, Anne M","contributorId":139531,"corporation":false,"usgs":false,"family":"Cotter","given":"Anne","email":"","middleInitial":"M","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":541698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":541699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yule, Daniel L. dyule@usgs.gov","contributorId":139525,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":541694,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189179,"text":"70189179 - 2014 - A computer program for uncertainty analysis integrating regression and Bayesian methods","interactions":[],"lastModifiedDate":"2018-09-14T16:01:30","indexId":"70189179","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A computer program for uncertainty analysis integrating regression and Bayesian methods","docAbstract":"

This work develops a new functionality in UCODE_2014 to evaluate Bayesian credible intervals using the Markov Chain Monte Carlo (MCMC) method. The MCMC capability in UCODE_2014 is based on the FORTRAN version of the differential evolution adaptive Metropolis (DREAM) algorithm of Vrugt et al. (2009), which estimates the posterior probability density function of model parameters in high-dimensional and multimodal sampling problems. The UCODE MCMC capability provides eleven prior probability distributions and three ways to initialize the sampling process. It evaluates parametric and predictive uncertainties and it has parallel computing capability based on multiple chains to accelerate the sampling process. This paper tests and demonstrates the MCMC capability using a 10-dimensional multimodal mathematical function, a 100-dimensional Gaussian function, and a groundwater reactive transport model. The use of the MCMC capability is made straightforward and flexible by adopting the JUPITER API protocol. With the new MCMC capability, UCODE_2014 can be used to calculate three types of uncertainty intervals, which all can account for prior information: (1) linear confidence intervals which require linearity and Gaussian error assumptions and typically 10s–100s of highly parallelizable model runs after optimization, (2) nonlinear confidence intervals which require a smooth objective function surface and Gaussian observation error assumptions and typically 100s–1,000s of partially parallelizable model runs after optimization, and (3) MCMC Bayesian credible intervals which require few assumptions and commonly 10,000s–100,000s or more partially parallelizable model runs. Ready access allows users to select methods best suited to their work, and to compare methods in many circumstances.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2014.06.002","usgsCitation":"Lu, D., Ye, M., Hill, M.C., Poeter, E.P., and Curtis, G., 2014, A computer program for uncertainty analysis integrating regression and Bayesian methods: Environmental Modelling and Software, v. 60, p. 45-56, https://doi.org/10.1016/j.envsoft.2014.06.002.","productDescription":"12 p.","startPage":"45","endPage":"56","ipdsId":"IP-057730","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c42e4b0d1f9f057e35e","contributors":{"authors":[{"text":"Lu, Dan","contributorId":194172,"corporation":false,"usgs":false,"family":"Lu","given":"Dan","email":"","affiliations":[],"preferred":false,"id":703376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Ming","contributorId":70276,"corporation":false,"usgs":true,"family":"Ye","given":"Ming","affiliations":[],"preferred":false,"id":703377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poeter, Eileen P.","contributorId":78805,"corporation":false,"usgs":true,"family":"Poeter","given":"Eileen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Gary gpcurtis@usgs.gov","contributorId":194175,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","affiliations":[],"preferred":true,"id":703379,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160094,"text":"70160094 - 2014 - Population-level effects of egg predation on a native planktivore in a large freshwater lake","interactions":[],"lastModifiedDate":"2015-12-11T15:21:46","indexId":"70160094","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Population-level effects of egg predation on a native planktivore in a large freshwater lake","docAbstract":"

Using a 37-year recruitment time series, we uncovered a field pattern revealing a strong, inverse relationship between bloater Coregonus hoyi recruitment success and slimy sculpin Cottus cognatus biomass in Lake Michigan (United States), one of the largest freshwater lakes of the world. Given that slimy sculpins (and deepwater sculpin Myoxocephalus thompsonii) are known egg predators that spatiotemporally overlap with incubating bloater eggs, we used recently published data on sculpin diets and daily ration to model annual bloater egg consumption by sculpins for the 1973–2010 year-classes. Although several strong year-classes were produced in the late 1980s when the proportion of eggs consumed by slimy sculpins was extremely low (i.e., <0.001) and several weak year-classes were produced when the proportion of bloater eggs consumed was at its highest (i.e., >0.10–1.0), egg predation failed to explain why recruitment was weak for the 1995–2005 year-classes when the proportion consumed was also low (i.e., <0.02). We concluded that egg predation by slimy and deepwater sculpins could have limited bloater recruitment in some years, but that some undetermined factor was more important in many other years. Given that slimy sculpin densities are influenced by piscivorous lake trout Salvelinus namaycush, the restoration of which in Lake Michigan has lagged behind those in lakes Superior and Huron, our study highlights the importance of an ecosystem perspective when considering population dynamics of fishes.

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]\n}","volume":"23","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-18","publicationStatus":"PW","scienceBaseUri":"566c01ece4b09cfe53ca5afa","contributors":{"authors":[{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mychek-Londer, Justin G.","contributorId":64138,"corporation":false,"usgs":true,"family":"Mychek-Londer","given":"Justin G.","affiliations":[],"preferred":false,"id":581966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madenjian, Charles P. 0000-0002-0326-164X 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Regime shifts are generally defined as the point of ‘abrupt’ change in the state of a system. However, a seemingly abrupt transition can be the product of a system reorganization that has been ongoing much longer than is evident in statistical analysis of a single component of the system. Using both univariate and multivariate statistical methods, we tested a long-term high-resolution paleoecological dataset with a known change in species assemblage for a regime shift. Analysis of this dataset with Fisher Information and multivariate time series modeling showed that there was a∼2000 year period of instability prior to the regime shift. This period of instability and the subsequent regime shift coincide with regional climate change, indicating that the system is undergoing extrinsic forcing. Paleoecological records offer a unique opportunity to test tools for the detection of thresholds and stable-states, and thus to examine the long-term stability of ecosystems over periods of multiple millennia.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0108936","usgsCitation":"Spanbauer, T., Allen, C.R., Angeler, D., Eason, T., Fritz, S.C., Garmestani, A.S., Nash, K.L., and Stone, J., 2014, Prolonged instability prior to a regime shift: PLoS ONE, v. 9, no. 10, p. 1-7, https://doi.org/10.1371/journal.pone.0108936.","productDescription":" e108936; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-056958","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472728,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0108936","text":"Publisher Index Page"},{"id":346841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-03","publicationStatus":"PW","scienceBaseUri":"59e8683ee4b05fe04cd4d255","contributors":{"authors":[{"text":"Spanbauer, Trisha","contributorId":146435,"corporation":false,"usgs":false,"family":"Spanbauer","given":"Trisha","email":"","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":713313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":712972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":713314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eason, Tarsha","contributorId":82220,"corporation":false,"usgs":true,"family":"Eason","given":"Tarsha","email":"","affiliations":[],"preferred":false,"id":713315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fritz, Sherilyn C.","contributorId":30155,"corporation":false,"usgs":true,"family":"Fritz","given":"Sherilyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":713316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":713317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nash, Kirsty L.","contributorId":40897,"corporation":false,"usgs":true,"family":"Nash","given":"Kirsty","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":713318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stone, Jeffery R.","contributorId":95501,"corporation":false,"usgs":true,"family":"Stone","given":"Jeffery R.","affiliations":[],"preferred":false,"id":713319,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168384,"text":"70168384 - 2014 - Transdisciplinary application of the cross-scale resilience model","interactions":[],"lastModifiedDate":"2016-02-11T12:57:03","indexId":"70168384","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Transdisciplinary application of the cross-scale resilience model","docAbstract":"

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlying discontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/ anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems.

","language":"English","publisher":"MDPI","doi":"10.3390/su6106925","usgsCitation":"Sundstrom, S.M., Angeler, D., Garmestani, A.S., Garcia, J.H., and Allen, C.R., 2014, Transdisciplinary application of the cross-scale resilience model: Sustainability, v. 6, no. 10, p. 6925-6948, https://doi.org/10.3390/su6106925.","productDescription":"24 p.","startPage":"6925","endPage":"6948","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059658","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su6106925","text":"Publisher Index Page"},{"id":317953,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-02","publicationStatus":"PW","scienceBaseUri":"56bdbed1e4b06458514aeeef","contributors":{"authors":[{"text":"Sundstrom, Shana M.","contributorId":7159,"corporation":false,"usgs":true,"family":"Sundstrom","given":"Shana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":619930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":619931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Jorge H.","contributorId":91714,"corporation":false,"usgs":true,"family":"Garcia","given":"Jorge","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":619933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193632,"text":"70193632 - 2014 - Straddling the tholeiitic/calc-alkaline transition: The effects of modest amounts of water on magmatic differentiation at Newberry Volcano, Oregon","interactions":[],"lastModifiedDate":"2019-03-11T13:47:50","indexId":"70193632","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Straddling the tholeiitic/calc-alkaline transition: The effects of modest amounts of water on magmatic differentiation at Newberry Volcano, Oregon","docAbstract":"

Melting experiments have been performed at 1 bar (anhydrous) and 1- and 2-kbar H2O-saturated conditions to study the effect of water on the differentiation of a basaltic andesite. The starting material was a mafic pumice from the compositionally zoned tuff deposited during the ~75 ka caldera-forming eruption of Newberry Volcano, a rear-arc volcanic center in the central Oregon Cascades. Pumices in the tuff of Newberry caldera (TNC) span a continuous silica range from 53 to 74 wt% and feature an unusually high-Na2O content of 6.5 wt% at 67 wt% SiO2. This wide range of magmatic compositions erupted in a single event makes the TNC an excellent natural laboratory in which to study the conditions of magmatic differentiation. Our experimental results and mineral–melt hygrometers/thermometers yield similar estimates of pre-eruptive H2O contents and temperatures of the TNC liquids. The most primitive (mafic) basaltic andesites record a pre-eruptive H2O content of 1.5 wt% and a liquidus temperature of 1,060–1,070 °C at upper crustal pressure. This modest H2O content produces a distinctive fractionation trend that is much more enriched in Na, Fe, and Ti than the calc-alkaline trend typical of wetter arc magmas, but slightly less enriched in Fe and Ti than the tholeiitic trend of dry magmas. Modest H2O contents might be expected at Newberry Volcano given its location in the Cascade rear arc, and the same fractionation trend is also observed in the rim andesites of the rear-arc Medicine Lake volcano in the southern Cascades. However, the Na–Fe–Ti enrichment characteristic of modest H2O (1–2 wt%) is also observed to the west of Newberry in magmas erupted from the arc axis, such as the Shevlin Park Tuff and several lava flows from the Three Sisters. This shows that modest-H2O magmas are being generated directly beneath the arc axis as well as in the rear arc. Because liquid lines of descent are particularly sensitive to water content in the range of 0–3 wt% H2O, they provide a quantitative and reliable tool for precisely determining pre-eruptive H2O content using major-element data from pumices or lava flows. Coupled enrichment in Na, Fe, and Ti relative to the calc-alkaline trend is a general feature of fractional crystallization in the presence of modest amounts of H2O, which may be used to look for “damp” fractionation sequences elsewhere.

","language":"English","publisher":"Springer","doi":"10.1007/s00410-014-1066-7","usgsCitation":"Mandler, B.E., Donnelly-Nolan, J.M., and Grove, T.L., 2014, Straddling the tholeiitic/calc-alkaline transition: The effects of modest amounts of water on magmatic differentiation at Newberry Volcano, Oregon: Contributions to Mineralogy and Petrology, v. 168, Article 1066; 25 p., https://doi.org/10.1007/s00410-014-1066-7.","productDescription":"Article 1066; 25 p.","ipdsId":"IP-060074","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Newberry Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.28047943115236,\n 43.69915480258559\n ],\n [\n -121.19327545166016,\n 43.69989944167303\n ],\n [\n -121.19327545166016,\n 43.739352079154706\n ],\n [\n -121.27841949462889,\n 43.73736766145917\n ],\n [\n -121.28047943115236,\n 43.69915480258559\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"168","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-01","publicationStatus":"PW","scienceBaseUri":"59fc2eaae4b0531197b27fa1","contributors":{"authors":[{"text":"Mandler, Ben E.","contributorId":199667,"corporation":false,"usgs":false,"family":"Mandler","given":"Ben","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":719685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donnelly-Nolan, Julie M. 0000-0001-8714-9606 jdnolan@usgs.gov","orcid":"https://orcid.org/0000-0001-8714-9606","contributorId":3271,"corporation":false,"usgs":true,"family":"Donnelly-Nolan","given":"Julie","email":"jdnolan@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grove, Timothy L.","contributorId":193070,"corporation":false,"usgs":false,"family":"Grove","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":719686,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187369,"text":"70187369 - 2014 - Smolting in coastal cutthroat trout Onchorhynchus clarkii clarkii","interactions":[],"lastModifiedDate":"2017-05-01T10:00:37","indexId":"70187369","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","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}},"title":"Smolting in coastal cutthroat trout Onchorhynchus clarkii clarkii","docAbstract":"

Gill Na+, K+-ATPase activity, condition factor and seawater (SW) challenges were used to assess the development of smolt characteristics in a cohort of hatchery coastal cutthroat trout Oncorhynchus clarkii clarkii from the Cowlitz River in Washington State, U.S.A. Gill Na+, K+-ATPase activity increased slightly in the spring, coinciding with an increase in hypo-osmoregulatory ability. These changes were of lesser magnitude than are observed in other salmonine species. Even at the peak of tolerance, these fish exhibited notable osmotic perturbations in full strength SW. Condition factor in these hatchery fish declined steadily through the spring. Wild captured migrants from four tributaries of the Columbia River had moderately elevated gill Na+, K+-ATPase activity, consistent with smolt development and with greater enzyme activity than autumn captured juveniles from one of the tributaries, Abernathy Creek. Migrant fish also had reduced condition factor. General linear models of 7 years of data from Abernathy Creek suggest that yearly variation, advancing photoperiod (as ordinal date) and fish size (fork length) were significant factors for predicting gill Na+, K+-ATPase activity in these wild fish. Both yearly variation and temperature were significant factors for predicting condition factor. These results suggest that coastal O. c. clarkii exhibit weakly developed characteristics of smolting. These changes are influenced by environmental conditions with great individual variation. The data suggest great physiological plasticity consistent with the variable life-history tactics observed in this species.

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.12480","usgsCitation":"Zydlewski, J.D., Zydlewski, G., Kennedy, B., and Gale, W., 2014, Smolting in coastal cutthroat trout Onchorhynchus clarkii clarkii: Journal of Fish Biology, v. 85, no. 4, p. 1111-1130, https://doi.org/10.1111/jfb.12480.","productDescription":"20 p.","startPage":"1111","endPage":"1130","ipdsId":"IP-052400","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-31","publicationStatus":"PW","scienceBaseUri":"5908492ee4b0fc4e448ffd70","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":693618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zydlewski, G.","contributorId":69452,"corporation":false,"usgs":true,"family":"Zydlewski","given":"G.","email":"","affiliations":[],"preferred":false,"id":693623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, B.","contributorId":191614,"corporation":false,"usgs":false,"family":"Kennedy","given":"B.","affiliations":[],"preferred":false,"id":693624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gale, W.","contributorId":191615,"corporation":false,"usgs":false,"family":"Gale","given":"W.","email":"","affiliations":[],"preferred":false,"id":693625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133616,"text":"70133616 - 2014 - Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling","interactions":[],"lastModifiedDate":"2014-11-18T13:08:15","indexId":"70133616","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling","docAbstract":"

Evacuation of the population from a tsunami hazard zone is vital to reduce life-loss due to inundation. Geospatial least-cost distance modelling provides one approach to assessing tsunami evacuation potential. Previous models have generally used two static exposure scenarios and fixed travel speeds to represent population movement. Some analyses have assumed immediate departure or a common evacuation departure time for all exposed population. Here, a method is proposed to incorporate time-variable exposure, distributed travel speeds, and uncertain evacuation departure time into an existing anisotropic least-cost path distance framework. The method is demonstrated for hypothetical local-source tsunami evacuation in Napier City, Hawke's Bay, New Zealand. There is significant diurnal variation in pedestrian evacuation potential at the suburb level, although the total number of people unable to evacuate is stable across all scenarios. Whilst some fixed travel speeds approximate a distributed speed approach, others may overestimate evacuation potential. The impact of evacuation departure time is a significant contributor to total evacuation time. This method improves least-cost modelling of evacuation dynamics for evacuation planning, casualty modelling, and development of emergency response training scenarios. However, it requires detailed exposure data, which may preclude its use in many situations.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-14-2975-2014","usgsCitation":"Fraser, S.A., Wood, N.J., Johnston, D.A., Leonard, G.S., Greening, P.D., and Rossetto, T., 2014, Variable population exposure and distributed travel speeds in least-cost tsunami evacuation modelling: Natural Hazards and Earth System Sciences, v. 14, p. 2975-2991, https://doi.org/10.5194/nhess-14-2975-2014.","productDescription":"17 p.","startPage":"2975","endPage":"2991","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056507","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472724,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-14-2975-2014","text":"Publisher Index Page"},{"id":296159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2014-11-17","publicationStatus":"PW","scienceBaseUri":"546c763ee4b0f4a3478a61e7","contributors":{"authors":[{"text":"Fraser, Stuart A.","contributorId":127468,"corporation":false,"usgs":false,"family":"Fraser","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":525303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":525302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnston, David A.","contributorId":64637,"corporation":false,"usgs":false,"family":"Johnston","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":525304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leonard, Graham S.","contributorId":127469,"corporation":false,"usgs":false,"family":"Leonard","given":"Graham","email":"","middleInitial":"S.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":525305,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greening, Paul D.","contributorId":127470,"corporation":false,"usgs":false,"family":"Greening","given":"Paul","email":"","middleInitial":"D.","affiliations":[{"id":6957,"text":"University College London","active":true,"usgs":false}],"preferred":false,"id":525306,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rossetto, Tiziana","contributorId":127471,"corporation":false,"usgs":false,"family":"Rossetto","given":"Tiziana","email":"","affiliations":[{"id":6957,"text":"University College London","active":true,"usgs":false}],"preferred":false,"id":525307,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70140711,"text":"70140711 - 2014 - Photoperiod control of downstream movements of Atlantic salmon Salmo salar smolts","interactions":[],"lastModifiedDate":"2015-02-10T13:11:54","indexId":"70140711","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","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}},"title":"Photoperiod control of downstream movements of Atlantic salmon Salmo salar smolts","docAbstract":"

This study provides the first direct observations that photoperiod controls the initiation of downstream movement in Atlantic salmon Salmo salar smolts. Under simulated natural day length (LDN) conditions and seasonal increases in temperature, smolts increased their downstream movements five-fold for a period of 1 month in late spring. Under the same conditions, parr did not show changes in downstream movement behaviour. When given a shortened day length (10L:14D) beginning in late winter, smolts did not increase the number of downstream movements. An early increase in day length (16L:8D) in late winter resulted in earlier initiation and termination of downstream movements compared to the LDN group. Physiological status and behaviour were related but not completely coincident: gill Na+/K+-ATPase activity increased in all treatments and thyroid hormone was elevated prior to movement in 16L:8D treatment. The most parsimonious model describing downstream movement of smolts included synergistic effects of photoperiod treatment and temperature, indicating that peak movements occurred at colder temperatures in the 16L:8D treatment than in LDN, and temperature did not influence movement of smolts in the 10L:14D treatment. The complicated interactions of photoperiod and temperature are not surprising since many organisms have evolved to rely on correlations among environmental cues and windows of opportunity to time behaviours associated with life-history transitions. These complicated interactions, however, have serious implications for phenological adjustments and persistence ofS. salar populations in response to climate change.

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.12509","usgsCitation":"Zydlewski, G., Stich, D.S., and McCormick, S., 2014, Photoperiod control of downstream movements of Atlantic salmon Salmo salar smolts: Journal of Fish Biology, v. 85, p. 1023-1041, https://doi.org/10.1111/jfb.12509.","productDescription":"19 p.","startPage":"1023","endPage":"1041","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055595","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":297899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"85","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-26","publicationStatus":"PW","scienceBaseUri":"54dd2c24e4b08de9379b365e","chorus":{"doi":"10.1111/jfb.12509","url":"http://dx.doi.org/10.1111/jfb.12509","publisher":"Wiley-Blackwell","authors":"Zydlewski G. B., Stich D. S., McCormick S. D.","journalName":"Journal of Fish Biology","publicationDate":"9/26/2014"},"contributors":{"authors":[{"text":"Zydlewski, Gayle B.","contributorId":139211,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle B.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":540364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":540365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139201,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","email":"smccormick@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":540363,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70144529,"text":"70144529 - 2014 - Breeding site selection by coho salmon (Oncorhynchus kisutch) in relation to large wood additions and factors that influence reproductive success","interactions":[],"lastModifiedDate":"2018-10-11T16:40:04","indexId":"70144529","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Breeding site selection by coho salmon (Oncorhynchus kisutch) in relation to large wood additions and factors that influence reproductive success","title":"Breeding site selection by coho salmon (Oncorhynchus kisutch) in relation to large wood additions and factors that influence reproductive success","docAbstract":"

The fitness of female Pacific salmon (Oncorhynchus spp.) with respect to breeding behavior can be partitioned into at least four fitness components: survival to reproduction, competition for breeding sites, success of egg incubation, and suitability of the local environment near breeding sites for early rearing of juveniles. We evaluated the relative influences of habitat features linked to these fitness components with respect to selection of breeding sites by coho salmon (Oncorhynchus kisutch). We also evaluated associations between breeding site selection and additions of large wood, as the latter were introduced into the study system as a means of restoring habitat conditions to benefit coho salmon. We used a model selection approach to organize specific habitat features into groupings reflecting fitness components and influences of large wood. Results of this work suggest that female coho salmon likely select breeding sites based on a wide range of habitat features linked to all four hypothesized fitness components. More specifically, model parameter estimates indicated that breeding site selection was most strongly influenced by proximity to pool-tail crests and deeper water (mean and maximum depths). Linkages between large wood and breeding site selection were less clear. Overall, our findings suggest that breeding site selection by coho salmon is influenced by a suite of fitness components in addition to the egg incubation environment, which has been the emphasis of much work in the past.

","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2014-0020","usgsCitation":"Clark, S.M., Dunham, J., McEnroe, J.R., and Lightcap, S.W., 2014, Breeding site selection by coho salmon (Oncorhynchus kisutch) in relation to large wood additions and factors that influence reproductive success: Canadian Journal of Fisheries and Aquatic Sciences, v. 71, no. 10, p. 1498-1507, https://doi.org/10.1139/cjfas-2014-0020.","productDescription":"10 p.","startPage":"1498","endPage":"1507","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057024","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":299201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Douglas County","otherGeospatial":"Little Wolf Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.904052734375,\n 43.09697190802465\n ],\n [\n -122.904052734375,\n 44.000717834282774\n ],\n [\n -121.431884765625,\n 44.000717834282774\n ],\n [\n -121.431884765625,\n 43.09697190802465\n ],\n [\n -122.904052734375,\n 43.09697190802465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"71","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551bc529e4b0323842783a3c","contributors":{"authors":[{"text":"Clark, Steven M.","contributorId":7989,"corporation":false,"usgs":false,"family":"Clark","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":543678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":1808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","email":"jdunham@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":543679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEnroe, Jeffery R.","contributorId":139990,"corporation":false,"usgs":false,"family":"McEnroe","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":543680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lightcap, Scott W.","contributorId":139991,"corporation":false,"usgs":false,"family":"Lightcap","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":543681,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189750,"text":"70189750 - 2014 - Laboratory generated M -6 earthquakes","interactions":[],"lastModifiedDate":"2017-07-24T15:19:36","indexId":"70189750","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Laboratory generated M -6 earthquakes","docAbstract":"

We consider whether mm-scale earthquake-like seismic events generated in laboratory experiments are consistent with our understanding of the physics of larger earthquakes. This work focuses on a population of 48 very small shocks that are foreshocks and aftershocks of stick–slip events occurring on a 2.0 m by 0.4 m simulated strike-slip fault cut through a large granite sample. Unlike the larger stick–slip events that rupture the entirety of the simulated fault, the small foreshocks and aftershocks are contained events whose properties are controlled by the rigidity of the surrounding granite blocks rather than characteristics of the experimental apparatus. The large size of the experimental apparatus, high fidelity sensors, rigorous treatment of wave propagation effects, and in situ system calibration separates this study from traditional acoustic emission analyses and allows these sources to be studied with as much rigor as larger natural earthquakes. The tiny events have short (3–6 μs) rise times and are well modeled by simple double couple focal mechanisms that are consistent with left-lateral slip occurring on a mm-scale patch of the precut fault surface. The repeatability of the experiments indicates that they are the result of frictional processes on the simulated fault surface rather than grain crushing or fracture of fresh rock. Our waveform analysis shows no significant differences (other than size) between the M -7 to M -5.5 earthquakes reported here and larger natural earthquakes. Their source characteristics such as stress drop (1–10 MPa) appear to be entirely consistent with earthquake scaling laws derived for larger earthquakes.

","language":"English","publisher":"Springer","doi":"10.1007/s00024-013-0772-9","usgsCitation":"McLaskey, G.C., Kilgore, B.D., Lockner, D.A., and Beeler, N.M., 2014, Laboratory generated M -6 earthquakes: Pure and Applied Geophysics, v. 171, no. 10, p. 2601-2615, https://doi.org/10.1007/s00024-013-0772-9.","productDescription":"15 p.","startPage":"2601","endPage":"2615","ipdsId":"IP-046204","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-17","publicationStatus":"PW","scienceBaseUri":"59770751e4b0ec1a48889f90","contributors":{"authors":[{"text":"McLaskey, Gregory C. gmclaskey@usgs.gov","contributorId":4112,"corporation":false,"usgs":true,"family":"McLaskey","given":"Gregory","email":"gmclaskey@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706188,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706190,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70148129,"text":"70148129 - 2014 - Evaluating the effects of land use on headwater wetland amphibian assemblages in coastal Alabama","interactions":[],"lastModifiedDate":"2015-05-29T15:01:26","indexId":"70148129","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the effects of land use on headwater wetland amphibian assemblages in coastal Alabama","docAbstract":"

Anthropogenic land use is known to impact aquatic ecosystems in several ways, including increased frequency and intensity of floods, stream channel incision, sedimentation, and loss of microtopography. Amphibians are susceptible to changes in wetland and surrounding habitats. This study evaluated amphibian assemblages of fifteen headwater slope wetlands in coastal Alabama across a gradient of land uses. Amphibians were surveyed on a seasonal basis and land use was delineated within wetland watersheds and within a 200-m buffer surrounding each wetland. Amphibian presence/absence and land use data were used to develop species occupancy models. Both urban and agricultural land use were shown to influence amphibian occurrence. Species richness ranged from five to ten species across sites; however, five species only occurred in wetlands surrounded by forested lands. Many species were detected more frequently on these wetlands compared to wetlands surrounded by urban or mixed land uses. Occupancy models showed Acris gryllus was negatively associated with the amount of agriculture within a buffer around the wetland. Hyla squirella, Lithobates clamitans, and L. sphenocephalus were positively associated with agricultural land within a watershed. Anaxyrus terrestris and the non-native Eleutherodactylus planirostris were positively associated with the amount of impervious surface area within the wetland buffer.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-014-0553-y","usgsCitation":"Alix, D.M., Anderson, C.J., Grand, J.B., and Guyer, C., 2014, Evaluating the effects of land use on headwater wetland amphibian assemblages in coastal Alabama: Wetlands, v. 34, no. 5, p. 917-926, https://doi.org/10.1007/s13157-014-0553-y.","productDescription":"10 p.","startPage":"917","endPage":"926","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051560","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","county":"Baldwin County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.7423095703125,\n 31.04587480670449\n ],\n [\n -87.66128540039062,\n 31.049404461655996\n ],\n [\n -87.6324462890625,\n 30.86215257839766\n ],\n [\n -87.53356933593749,\n 30.741835717889792\n ],\n [\n -87.4017333984375,\n 30.667447179098694\n ],\n [\n -87.49786376953125,\n 30.37405999207125\n ],\n [\n -87.64755249023438,\n 30.317173211357414\n ],\n [\n -87.83706665039061,\n 30.414334780625396\n ],\n [\n -87.9345703125,\n 30.483000484352313\n ],\n [\n -87.89886474609375,\n 30.55043513509528\n ],\n [\n -87.93731689453125,\n 30.7241293640261\n ],\n [\n -87.91397094726562,\n 30.851542445605972\n ],\n [\n -87.7423095703125,\n 31.04587480670449\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-28","publicationStatus":"PW","scienceBaseUri":"55698dcfe4b0d9246a9f649e","contributors":{"authors":[{"text":"Alix, Diane M.","contributorId":140996,"corporation":false,"usgs":false,"family":"Alix","given":"Diane","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":547894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Christopher J.","contributorId":11516,"corporation":false,"usgs":true,"family":"Anderson","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":547895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guyer, Craig","contributorId":104800,"corporation":false,"usgs":false,"family":"Guyer","given":"Craig","email":"","affiliations":[],"preferred":false,"id":547896,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159345,"text":"70159345 - 2014 - Probabilistic estimation of dune retreat on the Gold Coast, Australia","interactions":[],"lastModifiedDate":"2018-03-15T12:46:10","indexId":"70159345","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3385,"text":"Shore & Beach","printIssn":"0037-4237","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic estimation of dune retreat on the Gold Coast, Australia","docAbstract":"

Sand dunes are an important natural buffer between storm impacts and development backing the beach on the Gold Coast of Queensland, Australia. The ability to forecast dune erosion at a prediction horizon of days to a week would allow efficient and timely response to dune erosion in this highly populated area. Towards this goal, we modified an existing probabilistic dune erosion model for use on the Gold Coast. The original model was trained using observations of dune response from Hurricane Ivan on Santa Rosa Island, Florida, USA (Plant and Stockdon 2012. Probabilistic prediction of barrier-island response to hurricanes, Journal of Geophysical Research, 117(F3), F03015). The model relates dune position change to pre-storm dune elevations, dune widths, and beach widths, along with storm surge and run-up using a Bayesian network. The Bayesian approach captures the uncertainty of inputs and predictions through the conditional probabilities between variables. Three versions of the barrier island response Bayesian network were tested for use on the Gold Coast. One network has the same structure as the original and was trained with the Santa Rosa Island data. The second network has a modified design and was trained using only pre- and post-storm data from 1988-2009 for the Gold Coast. The third version of the network has the same design as the second version of the network and was trained with the combined data from the Gold Coast and Santa Rosa Island. The two networks modified for use on the Gold Coast hindcast dune retreat with equal accuracy. Both networks explained 60% of the observed dune retreat variance, which is comparable to the skill observed by Plant and Stockdon (2012) in the initial Bayesian network application at Santa Rosa Island. The new networks improved predictions relative to application of the original network on the Gold Coast. Dune width was the most important morphologic variable in hindcasting dune retreat, while hydrodynamic variables, surge and run-up elevation, were also important

","language":"English","publisher":"American Shore and Beach Preservation Association (ASBPA)","usgsCitation":"Palmsten, M.L., Splinter, K.D., Plant, N.G., and Stockdon, H.F., 2014, Probabilistic estimation of dune retreat on the Gold Coast, Australia: Shore & Beach, v. 82, no. 4, p. 35-43.","productDescription":"9 p.","startPage":"35","endPage":"43","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059175","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":310746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328830,"type":{"id":15,"text":"Index Page"},"url":"https://asbpa.org/publications/shore-and-beach/"}],"country":"Australia","state":"Queensland","otherGeospatial":"Gold Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 151.98486328125,\n -28.786918085420226\n ],\n [\n 151.98486328125,\n -24.567108352575975\n ],\n [\n 153.885498046875,\n -24.567108352575975\n ],\n [\n 153.885498046875,\n -28.786918085420226\n ],\n [\n 151.98486328125,\n -28.786918085420226\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56334340e4b048076347eeda","contributors":{"authors":[{"text":"Palmsten, Margaret L.","contributorId":149363,"corporation":false,"usgs":false,"family":"Palmsten","given":"Margaret","email":"","middleInitial":"L.","affiliations":[{"id":17718,"text":"Naval Research Laboratory, Stennis Space Center","active":true,"usgs":false}],"preferred":false,"id":578103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Splinter, Kristen D.","contributorId":147358,"corporation":false,"usgs":false,"family":"Splinter","given":"Kristen","email":"","middleInitial":"D.","affiliations":[{"id":16827,"text":"UNSW Australia","active":true,"usgs":false}],"preferred":false,"id":578104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":578102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":578105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187367,"text":"70187367 - 2014 - Survival of Atlantic salmon Salmo salar smolts through a hydropower complex","interactions":[],"lastModifiedDate":"2017-05-01T10:05:26","indexId":"70187367","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","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}},"title":"Survival of Atlantic salmon Salmo salar smolts through a hydropower complex","docAbstract":"

This study evaluated Atlantic salmon Salmo salar smolt survival through the lower Penobscot River, Maine, U.S.A., and characterized relative differences in proportional use and survival through the main-stem of the river and an alternative migration route, the Stillwater Branch. The work was conducted prior to removal of two main-stem dams and operational changes in hydropower facilities in the Stillwater Branch. Survival and proportional use of migration routes in the lower Penobscot were estimated from multistate (MS) models based on 6 years of acoustic telemetry data from 1669 smolts and 2 years of radio-telemetry data from 190 fish. A small proportion (0·12, 95% c.i. = 0·06–0·25) of smolts used the Stillwater Branch, and mean survival through the two operational dams in this part of the river was relatively high (1·00 and 0·97). Survival at Milford Dam, the dam that will remain in the main-stem of the Penobscot River, was relatively low (0·91), whereas survival through two dams that were removed was relatively high (0·99 and 0·98). Smolt survival could decrease in the Stillwater Branch with the addition of two new powerhouses while continuing to meet fish passage standards. The effects of removing two dams in the main-stem are expected to be negligible for smolt survival based on high survival observed from 2005 to 2012 at those locations. Survival through Milford Dam was been well below current regulatory standards, and thus improvement of passage at this location offers the best opportunity for improving overall smolt survival in the lower river.

","language":"English","publisher":"Wiley","doi":"10.1111/jfb.12483","usgsCitation":"Stich, D., Bailey, M., and Zydlewski, J.D., 2014, Survival of Atlantic salmon Salmo salar smolts through a hydropower complex: Journal of Fish Biology, v. 85, no. 4, p. 1074-1096, https://doi.org/10.1111/jfb.12483.","productDescription":"23 p.","startPage":"1074","endPage":"1096","ipdsId":"IP-052398","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.9337158203125,\n 44.56894765233198\n ],\n [\n -68.51898193359375,\n 44.56894765233198\n ],\n [\n -68.51898193359375,\n 45.236217535866025\n ],\n [\n -68.9337158203125,\n 45.236217535866025\n ],\n [\n -68.9337158203125,\n 44.56894765233198\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-06","publicationStatus":"PW","scienceBaseUri":"5908492ee4b0fc4e448ffd72","contributors":{"authors":[{"text":"Stich, D.S.","contributorId":169719,"corporation":false,"usgs":false,"family":"Stich","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":693626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, M.M.","contributorId":7494,"corporation":false,"usgs":true,"family":"Bailey","given":"M.M.","email":"","affiliations":[],"preferred":false,"id":693627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":693616,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155825,"text":"70155825 - 2014 - Assessing the risk persistent drought using climate model simulations and paleoclimate data","interactions":[],"lastModifiedDate":"2018-04-03T13:58:37","indexId":"70155825","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the risk persistent drought using climate model simulations and paleoclimate data","docAbstract":"

Projected changes in global rainfall patterns will likely alter water supplies and ecosystems in semiarid regions during the coming century. Instrumental and paleoclimate data indicate that natural hydroclimate fluctuations tend to be more energetic at low (multidecadal to multicentury) than at high (interannual) frequencies. State-of-the-art global climate models do not capture this characteristic of hydroclimate variability, suggesting that the models underestimate the risk of future persistent droughts. Methods are developed here for assessing the risk of such events in the coming century using climate model projections as well as observational (paleoclimate) information. Where instrumental and paleoclimate data are reliable, these methods may provide a more complete view of prolonged drought risk. In the U.S. Southwest, for instance, state-of-the-art climate model projections suggest the risk of a decade-scale megadrought in the coming century is less than 50%; the analysis herein suggests that the risk is at least 80%, and may be higher than 90% in certain areas. The likelihood of longer-lived events (>35 yr) is between 20% and 50%, and the risk of an unprecedented 50-yr megadrought is nonnegligible under the most severe warming scenario (5%–10%). These findings are important to consider as adaptation and mitigation strategies are developed to cope with regional impacts of climate change, where population growth is high and multidecadal megadrought—worse than anything seen during the last 2000 years—would pose unprecedented challenges to water resources in the region.

","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-12-00282.1","usgsCitation":"Ault, T.R., Cole, J.E., Overpeck, J.T., Pederson, G.T., and Meko, D.M., 2014, Assessing the risk persistent drought using climate model simulations and paleoclimate data: Journal of Climate, v. 27, no. 20, p. 7529-7549, https://doi.org/10.1175/JCLI-D-12-00282.1.","productDescription":"21 p.","startPage":"7529","endPage":"7549","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-024658","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472725,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-12-00282.1","text":"Publisher Index Page"},{"id":306605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0185546875,\n 48.980216985374994\n ],\n [\n -103.6669921875,\n 32.0639555946604\n ],\n [\n -108.06152343749999,\n 31.840232667909365\n ],\n [\n -108.2373046875,\n 31.240985378021307\n ],\n [\n -111.0498046875,\n 31.39115752282472\n ],\n [\n -115.04882812499999,\n 32.62087018318113\n ],\n [\n -117.333984375,\n 32.62087018318113\n ],\n [\n -118.125,\n 33.61461929233378\n ],\n [\n -119.66308593749999,\n 34.19817309627726\n ],\n [\n -120.80566406250001,\n 34.59704151614417\n ],\n [\n -120.76171875,\n 35.137879119634185\n ],\n [\n -122.16796875,\n 36.77409249464195\n ],\n [\n -123.1787109375,\n 37.96152331396616\n ],\n [\n -123.662109375,\n 39.198205348894795\n ],\n [\n -124.5849609375,\n 40.51379915504413\n ],\n [\n -124.23339843749999,\n 41.705728515237524\n ],\n [\n -124.8046875,\n 43.03677585761058\n ],\n [\n -124.1015625,\n 44.62175409623324\n ],\n [\n -124.18945312500001,\n 45.79816953017265\n ],\n [\n -124.27734374999999,\n 46.92025531537451\n ],\n [\n -124.67285156250001,\n 47.96050238891509\n ],\n [\n -124.98046874999999,\n 48.45835188280866\n ],\n [\n -123.3544921875,\n 48.25394114463431\n ],\n [\n -122.607421875,\n 47.96050238891509\n ],\n [\n -122.29980468749999,\n 48.48748647988415\n ],\n [\n -122.87109375,\n 48.951366470947725\n ],\n [\n -122.34374999999999,\n 49.009050809382046\n ],\n [\n -104.0185546875,\n 48.980216985374994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"20","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-07","publicationStatus":"PW","scienceBaseUri":"55cc6e28e4b08400b1fe0fcb","contributors":{"authors":[{"text":"Ault, Toby R.","contributorId":146164,"corporation":false,"usgs":false,"family":"Ault","given":"Toby","email":"","middleInitial":"R.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":566503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Julia E.","contributorId":69871,"corporation":false,"usgs":true,"family":"Cole","given":"Julia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":566502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overpeck, Jonathan T.","contributorId":146162,"corporation":false,"usgs":false,"family":"Overpeck","given":"Jonathan","email":"","middleInitial":"T.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":566501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":566499,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meko, David M.","contributorId":145887,"corporation":false,"usgs":false,"family":"Meko","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":566500,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70137269,"text":"70137269 - 2014 - Subsurface geometry of the San Andreas-Calaveras fault junction: Influence of serpentinite and the Coast Range Ophiolite","interactions":[],"lastModifiedDate":"2022-01-21T16:32:03.713914","indexId":"70137269","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface geometry of the San Andreas-Calaveras fault junction: Influence of serpentinite and the Coast Range Ophiolite","docAbstract":"

While an enormous amount of research has been focused on trying to understand the geologic history and neotectonics of the San Andreas-Calaveras fault (SAF-CF) junction, fundamental questions concerning fault geometry and mechanisms for slip transfer through the junction remain. We use potential-field, geologic, geodetic, and seismicity data to investigate the 3-D geologic framework of the SAF-CF junction and identify potential slip-transferring structures within the junction. Geophysical evidence suggests that the San Andreas and Calaveras fault zones dip away from each other within the northern portion of the junction, bounding a triangular-shaped wedge of crust in cross section. This wedge changes shape to the south as fault geometries change and fault activity shifts between fault strands, particularly along the Calaveras fault zone (CFZ). Potential-field modeling and relocated seismicity suggest that the Paicines and San Benito strands of the CFZ dip 65° to 70° NE and form the southwest boundary of a folded 1 to 3 km thick tabular body of Coast Range Ophiolite (CRO) within the Vallecitos syncline. We identify and characterize two steeply dipping, seismically active cross structures within the junction that are associated with serpentinite in the subsurface. The architecture of the SAF-CF junction presented in this study may help explain fault-normal motions currently observed in geodetic data and help constrain the seismic hazard. The abundance of serpentinite and related CRO in the subsurface is a significant discovery that not only helps constrain the geometry of structures but may also help explain fault behavior and the tectonic evolution of the SAF-CF junction.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014TC003561","usgsCitation":"Watt, J.T., Ponce, D.A., Graymer, R.W., Jachens, R.C., and Simpson, R.W., 2014, Subsurface geometry of the San Andreas-Calaveras fault junction: Influence of serpentinite and the Coast Range Ophiolite: Tectonics, v. 33, no. 10, p. 2025-2044, https://doi.org/10.1002/2014TC003561.","productDescription":"20 p.","startPage":"2025","endPage":"2044","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058037","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014tc003561","text":"Publisher Index Page"},{"id":297025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas-Calaveras fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.03613281249999,\n 36.4433803110554\n ],\n [\n -122.03613281249999,\n 37.46613860234406\n ],\n [\n -120.7781982421875,\n 37.46613860234406\n ],\n [\n -120.7781982421875,\n 36.4433803110554\n ],\n [\n -122.03613281249999,\n 36.4433803110554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-27","publicationStatus":"PW","scienceBaseUri":"54dd2c64e4b08de9379b3789","chorus":{"doi":"10.1002/2014tc003561","url":"http://dx.doi.org/10.1002/2014tc003561","publisher":"Wiley-Blackwell","authors":"Watt Janet T., Ponce David A., Graymer Russell W., Jachens Robert C., Simpson Robert W.","journalName":"Tectonics","publicationDate":"10/2014","auditedOn":"3/17/2016"},"contributors":{"authors":[{"text":"Watt, Janet Tilden 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":1754,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","middleInitial":"Tilden","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":537627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":537628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graymer, Russell W. 0000-0003-4910-5682 rgraymer@usgs.gov","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":1052,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","email":"rgraymer@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":537629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jachens, Robert C. jachens@usgs.gov","contributorId":1180,"corporation":false,"usgs":true,"family":"Jachens","given":"Robert","email":"jachens@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":537630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Simpson, Robert W. simpson@usgs.gov","contributorId":1053,"corporation":false,"usgs":true,"family":"Simpson","given":"Robert","email":"simpson@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":537631,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70154893,"text":"70154893 - 2014 - Spatial structuring within a reservoir fish population: implications for management","interactions":[],"lastModifiedDate":"2015-07-15T11:52:50","indexId":"70154893","displayToPublicDate":"2014-10-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2681,"text":"Marine and Freshwater Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatial structuring within a reservoir fish population: implications for management","docAbstract":"

Spatial structuring in reservoir fish populations can exist because of environmental gradients, species-specific behaviour, or even localised fishing effort. The present study investigated whether white crappie exhibited evidence of improved population structure where the northern more productive half of a lake is closed to fishing to provide waterfowl hunting opportunities. Population response to angling was modelled for each substock of white crappie (north (protected) and south (unprotected) areas), the entire lake (single-stock model) and by combining simulations of the two independent substock models (additive model). White crappie in the protected area were more abundant, consisting of larger, older individuals, and exhibited a lower total annual mortality rate than in the unprotected area. Population modelling found that fishing mortality rates between 0.1 and 0.3 resulted in sustainable populations (spawning potential ratios (SPR) >0.30). The population in the unprotected area appeared to be more resilient (SPR > 0.30) at the higher fishing intensities (0.35–0.55). Considered additively, the whole-lake fishery appeared more resilient than when modelled as a single-panmictic stock. These results provided evidence of spatial structuring in reservoir fish populations, and we recommend model assessments used to guide management decisions should consider those spatial differences in other populations where they exist.

","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/MF14085","usgsCitation":"Stewart, D., Long, J.M., and Shoup, D.E., 2014, Spatial structuring within a reservoir fish population: implications for management: Marine and Freshwater Research, v. 66, no. 3, p. 202-212, https://doi.org/10.1071/MF14085.","productDescription":"11 p.","startPage":"202","endPage":"212","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054699","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a78439e4b0183d66e45e98","contributors":{"authors":[{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":564861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoup, Daniel E.","contributorId":141325,"corporation":false,"usgs":false,"family":"Shoup","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":564862,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70123433,"text":"ofr20141190 - 2014 - Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications","interactions":[],"lastModifiedDate":"2014-09-30T16:52:51","indexId":"ofr20141190","displayToPublicDate":"2014-09-30T16:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1190","title":"Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications","docAbstract":"Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several downscaled climate projections (or downscaled datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these downscaled datasets, known as downscaling, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for downscaling and the number of downscaled datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available downscaled datasets, how do these model outputs compare to each other? Which variables are available, and are certain downscaled datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these downscaled datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141190","usgsCitation":"Wootten, A., Smith, K., Boyles, R., Terando, A., Stefanova, L., Misra, V., Smith, T., Blodgett, D.L., and Semazzi, F., 2014, Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications: U.S. Geological Survey Open-File Report 2014-1190, Report: v, 54 p.; 3 Appendices, https://doi.org/10.3133/ofr20141190.","productDescription":"Report: v, 54 p.; 3 Appendices","numberOfPages":"64","onlineOnly":"Y","ipdsId":"IP-055253","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":294687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141190.jpg"},{"id":294685,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1190/appendix/ofr2014-1190_appendix3.pdf"},{"id":294686,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1190/appendix/ofr2014-1190_appendix4.pdf"},{"id":294682,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1190/"},{"id":294683,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1190/pdf/ofr2014-1190.pdf"},{"id":294684,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1190/appendix/ofr2014-1190_appendix2.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.00,25.00 ], [ -95.00,40.00 ], [ -75.00,40.00 ], [ -75.00,25.00 ], [ -95.00,25.00 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542bb80be4b0abfb4c809678","contributors":{"authors":[{"text":"Wootten, Adrienne","contributorId":23465,"corporation":false,"usgs":true,"family":"Wootten","given":"Adrienne","affiliations":[],"preferred":false,"id":500122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Kara","contributorId":78658,"corporation":false,"usgs":true,"family":"Smith","given":"Kara","email":"","affiliations":[],"preferred":false,"id":500126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyles, Ryan","contributorId":42897,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[],"preferred":false,"id":500123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terando, Adam aterando@usgs.gov","contributorId":4792,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":500120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stefanova, Lydia","contributorId":48300,"corporation":false,"usgs":true,"family":"Stefanova","given":"Lydia","email":"","affiliations":[],"preferred":false,"id":500124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Misra, Vasru","contributorId":48886,"corporation":false,"usgs":true,"family":"Misra","given":"Vasru","email":"","affiliations":[],"preferred":false,"id":500125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Tom","contributorId":7387,"corporation":false,"usgs":true,"family":"Smith","given":"Tom","affiliations":[],"preferred":false,"id":500121,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":500119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Semazzi, Fredrick","contributorId":92978,"corporation":false,"usgs":true,"family":"Semazzi","given":"Fredrick","email":"","affiliations":[],"preferred":false,"id":500127,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70127500,"text":"70127500 - 2014 - Shaking from injection-induced earthquakes in the central and eastern United States","interactions":[],"lastModifiedDate":"2014-10-10T16:43:06","indexId":"70127500","displayToPublicDate":"2014-09-30T10:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Shaking from injection-induced earthquakes in the central and eastern United States","docAbstract":"In this study I consider the ground motions generated by 11 moderate (Mw4.0-5.6) earthquakes in the central and eastern United States that are thought or suspected to be induced by fluid injection. Using spatially rich intensity data from the USGS “Did You Feel It?” system, I show that the distance decay of intensities for all events is consistent with that observed for tectonic earthquakes in the region, but for all of the events, intensities are lower than values predicted from an intensity prediction equation that successfully characterizes intensities for regional tectonic events. I introduce an effective intensity magnitude, MIE, defined as the magnitude that on average would generate a given intensity distribution. For all 11 events, MIE is lower than the event magnitude by 0.4-1.3 magnitude units, with an average difference of 0.82 units. This suggests that stress drops of injection-induced earthquakes are systematically lower than tectonic earthquakes by an estimated factor of 2-10. However, relatively limited data suggest that intensities for epicentral distances less than 10 km are more commensurate with expectations for the event magnitude, which can be reasonably explained by the shallow focal depth of the events. The results suggest that damage from injection-induced earthquakes will be especially concentrated in the immediate epicentral region.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120140099","usgsCitation":"Hough, S.E., 2014, Shaking from injection-induced earthquakes in the central and eastern United States: Bulletin of the Seismological Society of America, v. 104, no. 5, p. 2619-2626, https://doi.org/10.1785/0120140099.","productDescription":"8 p.","startPage":"2619","endPage":"2626","numberOfPages":"8","ipdsId":"IP-056080","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":294617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294591,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120140099"}],"country":"United States","volume":"104","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-08-19","publicationStatus":"PW","scienceBaseUri":"542bb80ee4b0abfb4c8096ac","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":502360,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70127470,"text":"70127470 - 2014 - Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest","interactions":[],"lastModifiedDate":"2017-01-18T11:30:03","indexId":"70127470","displayToPublicDate":"2014-09-30T09:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest","docAbstract":"A warming climate influences boreal forest productivity, dynamics, and disturbance regimes. We used ecosystem models and 250 m satellite Normalized Difference Vegetation Index (NDVI) data averaged over the growing season (GSN) to model current, and estimate future, ecosystem performance. We modeled Expected Ecosystem Performance (EEP), or anticipated productivity, in undisturbed stands over the 2000–2008 period from a variety of abiotic data sources, using a rule-based piecewise regression tree. The EEP model was applied to a future climate ensemble A1B projection to quantify expected changes to mature boreal forest performance. Ecosystem Performance Anomalies (EPA), were identified as the residuals of the EEP and GSN relationship and represent performance departures from expected performance conditions. These performance data were used to monitor successional events following fire. Results suggested that maximum EPA occurs 30–40 years following fire, and deciduous stands generally have higher EPA than coniferous stands. Mean undisturbed EEP is projected to increase 5.6% by 2040 and 8.7% by 2070, suggesting an increased deciduous component in boreal forests. Our results contribute to the understanding of boreal forest successional dynamics and its response to climate change. This information enables informed decisions to prepare for, and adapt to, climate change in the Yukon River Basin forest.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Multidisciplanary Digital Publishing Institute","doi":"10.3390/rs6109145","usgsCitation":"Wylie, B.K., Rigge, M.B., Brisco, B., Mrnaghan, K., Rover, J.R., and Long, J., 2014, Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest: Remote Sensing, v. 6, no. 10, p. 9145-9169, https://doi.org/10.3390/rs6109145.","productDescription":"25 p.","startPage":"9145","endPage":"9169","ipdsId":"IP-057217","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6109145","text":"Publisher Index Page"},{"id":294612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294611,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/rs6109145"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -164.8,61.55 ], [ -164.8,66.62 ], [ -141.0,66.62 ], [ -141.0,61.55 ], [ -164.8,61.55 ] ] ] } } ] }","volume":"6","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-09-26","publicationStatus":"PW","scienceBaseUri":"542bb80ce4b0abfb4c809689","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":502327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","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":502328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":502332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mrnaghan, Kevin","contributorId":21092,"corporation":false,"usgs":true,"family":"Mrnaghan","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":502331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":502329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":502330,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70127549,"text":"70127549 - 2014 - Characterizing recent and projecting future potential patterns of mountain pine beetle outbreaks in the Southern Rocky Mountains","interactions":[],"lastModifiedDate":"2014-10-02T09:50:27","indexId":"70127549","displayToPublicDate":"2014-09-30T09:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing recent and projecting future potential patterns of mountain pine beetle outbreaks in the Southern Rocky Mountains","docAbstract":"The recent widespread mountain pine beetle (MPB) outbreak in the Southern Rocky Mountains presents an opportunity to investigate the relative influence of anthropogenic, biologic, and physical drivers that have shaped the spatiotemporal patterns of the outbreak. The aim of this study was to quantify the landscape-level drivers that explained the dynamic patterns of MPB mortality, and simulate areas with future potential MPB mortality under projected climate-change scenarios in Grand County, Colorado, USA. The outbreak patterns of MPB were characterized by analysis of a decade-long Landsat time-series stack, aided by automatic attribution of change detected by the Landsat-based Detection of Trends in Disturbance and Recovery algorithm (LandTrendr). The annual area of new MPB mortality was then related to a suite of anthropogenic, biologic, and physical predictor variables under a general linear model (GLM) framework. Data from years 2001–2005 were used to train the model and data from years 2006–2011 were retained for validation. After stepwise removal of non-significant predictors, the remaining predictors in the GLM indicated that neighborhood mortality, winter mean temperature anomaly, and residential housing density were positively associated with MPB mortality, whereas summer precipitation was negatively related. The final model had an average area under the curve (AUC) of a receiver operating characteristic plot value of 0.72 in predicting the annual area of new mortality for the independent validation years, and the mean deviation from the base maps in the MPB mortality areal estimates was around 5%. The extent of MPB mortality will likely expand under two climate-change scenarios (RCP 4.5 and 8.5) in Grand County, which implies that the impacts of MPB outbreaks on vegetation composition and structure, and ecosystem functioning are likely to increase in the future.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2014.09.012","usgsCitation":"Liang, L., Hawbaker, T., Chen, Y., Zhu, Z., and Gong, P., 2014, Characterizing recent and projecting future potential patterns of mountain pine beetle outbreaks in the Southern Rocky Mountains: Applied Geography, v. 55, p. 165-175, https://doi.org/10.1016/j.apgeog.2014.09.012.","productDescription":"11 p.","startPage":"165","endPage":"175","numberOfPages":"11","ipdsId":"IP-055165","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":472739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeog.2014.09.012","text":"Publisher Index Page"},{"id":294606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294594,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeog.2014.09.012"}],"country":"United States","state":"Colorado","county":"Grand County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.653,39.6841 ], [ -106.653,40.4863 ], [ -105.6261,40.4863 ], [ -105.6261,39.6841 ], [ -106.653,39.6841 ] ] ] } } ] }","volume":"55","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542bb80ae4b0abfb4c809669","chorus":{"doi":"10.1016/j.apgeog.2014.09.012","url":"http://dx.doi.org/10.1016/j.apgeog.2014.09.012","publisher":"Elsevier BV","authors":"Liang Lu, Hawbaker Todd J., Chen Yanlei, Zhu Zhiliang, Gong Peng","journalName":"Applied Geography","publicationDate":"12/2014","auditedOn":"3/22/2016","publiclyAccessibleDate":"9/19/2014"},"contributors":{"authors":[{"text":"Liang, Lu","contributorId":72714,"corporation":false,"usgs":true,"family":"Liang","given":"Lu","affiliations":[],"preferred":false,"id":502387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":502384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Yanlei","contributorId":18276,"corporation":false,"usgs":true,"family":"Chen","given":"Yanlei","email":"","affiliations":[],"preferred":false,"id":502385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhi-Liang","contributorId":70726,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","affiliations":[],"preferred":false,"id":502386,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gong, Peng","contributorId":102393,"corporation":false,"usgs":true,"family":"Gong","given":"Peng","affiliations":[],"preferred":false,"id":502388,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70127471,"text":"70127471 - 2014 - Can mercury in fish be reduced by water level management? Evaluating the effects of water level fluctuation on mercury accumulation in yellow perch (Perca flavescens)","interactions":[],"lastModifiedDate":"2014-09-30T09:43:19","indexId":"70127471","displayToPublicDate":"2014-09-30T09:42:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Can mercury in fish be reduced by water level management? Evaluating the effects of water level fluctuation on mercury accumulation in yellow perch (Perca flavescens)","docAbstract":"Mercury (Hg) contamination of fisheries is a major concern for resource managers of many temperate lakes. Anthropogenic Hg contamination is largely derived from atmospheric deposition within a lake’s watershed, but its incorporation into the food web is facilitated by bacterial activity in sediments. Temporal variation in Hg content of fish (young-of-year yellow perch) in the regulated lakes of the Rainy–Namakan complex (on the border of the United States and Canada) has been linked to water level (WL) fluctuations, presumably through variation in sediment inundation. As a result, Hg contamination of fish has been linked to international regulations of WL fluctuation. Here we assess the relationship between WL fluctuations and fish Hg content using a 10-year dataset covering six lakes. Within-year WL rise did not appear in strongly supported models of fish Hg, but year-to-year variation in maximum water levels (∆maxWL) was positively associated with fish Hg content. This WL effect varied in magnitude among lakes: In Crane Lake, a 1 m increase in ∆maxWL from the previous year was associated with a 108 ng increase in fish Hg content (per gram wet weight), while the same WL change in Kabetogama was associated with only a 5 ng increase in fish Hg content. In half the lakes sampled here, effect sizes could not be distinguished from zero. Given the persistent and wide-ranging extent of Hg contamination and the large number of regulated waterways, future research is needed to identify the conditions in which WL fluctuations influence fish Hg content.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecotoxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10646-014-1296-5","usgsCitation":"Larson, J.H., Maki, R., Knights, B.C., and Gray, B.R., 2014, Can mercury in fish be reduced by water level management? Evaluating the effects of water level fluctuation on mercury accumulation in yellow perch (Perca flavescens): Ecotoxicology, v. 23, no. 8, p. 1555-1563, https://doi.org/10.1007/s10646-014-1296-5.","productDescription":"9 p.","startPage":"1555","endPage":"1563","ipdsId":"IP-050898","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":294603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294576,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-014-1296-5"}],"country":"Canada;United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.203689,48.299689 ], [ -93.203689,48.631628 ], [ -92.453285,48.631628 ], [ -92.453285,48.299689 ], [ -93.203689,48.299689 ] ] ] } } ] }","volume":"23","issue":"8","noUsgsAuthors":false,"publicationDate":"2014-08-19","publicationStatus":"PW","scienceBaseUri":"542bb809e4b0abfb4c809664","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":502335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":100111,"corporation":false,"usgs":true,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":502336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":502334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":502333,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70125456,"text":"ofr20141202 - 2014 - Landbird trends in national parks of the North Coast and Cascades Network, 2005-12","interactions":[],"lastModifiedDate":"2017-11-22T16:02:41","indexId":"ofr20141202","displayToPublicDate":"2014-09-29T13:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1202","title":"Landbird trends in national parks of the North Coast and Cascades Network, 2005-12","docAbstract":"

National parks in the North Coast and Cascades Network (NCCN) can fulfill vital roles as refuges for bird species dependent on late-successional forest conditions and as reference sites for assessing the effects of land-use and land-cover changes on bird populations throughout the larger Pacific Northwest region. Additionally, long-term monitoring of landbirds throughout the NCCN provides information that can inform decisions about important management issues in the parks, including visitor impacts, fire management, and the effects of introduced species. In 2005, the NCCN began implementing a network-wide Landbird Monitoring Project as part of the NPS Inventory and Monitoring Program. In this report, we discuss 8-year trends (2005–12) of bird populations in the NCCN, based on a sampling framework of point counts established in three large wilderness parks (Mount Rainier, North Cascades, and Olympic National Parks), 7-year trends at Lewis and Clark National Historical Park (sampled in 2006, 2008, 2010, and 2012), and 5-year trends at San Juan Islands National Historical Park (sampled in 2007, 2009, and 2011). Our analysis encompasses a fairly short time span for this long-term monitoring program. The first 2 years of the time series (2005 and 2006) were implemented as part of a limited pilot study that included only a small subset of the transects. The subsequent 6 years (2007–12) represent just a single cycle through 5 years of alternating panels of transects in the large parks, with the first of five alternating panels revisited for the first time in 2012. Of 204 transects that comprise the six sampling panels in the large parks, only 68 (one-third) have thus been eligible for revisit surveys (34 during every year after 2005, and an additional 34 only in 2012) and can contribute to our current trend estimates. We therefore initiated the current analysis with a primary goal of testing our analytical procedures rather than detecting trends that might be strong enough to drive conservation or management decisions in the parks or elsewhere. We expect that aggregated trend detection results may change substantially over the next several years, as the number of transects with revisit histories triples and the spatial dispersion of transects contributing to trend estimates also improves greatly. In the meantime, caution should be exercised in interpreting the importance of trends, as individual years can have very large influences on the direction and magnitude of trends in a time series of such limited duration (and limited numbers of repeat visits at the small parks). Nevertheless, we estimated trends for 43 species at Mount Rainier National Park, 53 species at North Cascades National Park Complex, and 41 species at Olympic National Park. Of 137 park-species combinations (including combined-park analyses), we found 16 significant decreases (12 percent) and five significant increases (4 percent).

\n
\n

We identify several limitations of the current analytical framework for trend assessment but suggest that the overall sampling design is strong and amenable to analysis by more recently developed model-based methods. These could provide a more flexible framework for examining trends and other population parameters of interest, as well as testing hypotheses that relate the distribution and abundance of species to environmental covariates. A model-based approach would allow for modeling various components of the detection process and analyzing observations (detection process), population state (occupancy, population size, density), and change (trend, local extinction and colonization rates turnover) simultaneously. Finally, we also evaluate operational aspects of NCCN Landbird Monitoring Project, and conclude that our robust, multi-party partnership is successfully implementing the project as it was envisioned.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141202","collaboration":"Prepared in cooperation with the National Park Service and The Institute for Bird Populations","usgsCitation":"Saracco, J., Holmgren, A.L., Wilkerson, R.L., Siegel, R.B., Kuntz, R.C., Jenkins, K.J., Happe, P.J., Boetsch, J.R., and Huff, M.H., 2014, Landbird trends in national parks of the North Coast and Cascades Network, 2005-12: U.S. Geological Survey Open-File Report 2014-1202, Report: v, 36 p.; 2 Appendixes, https://doi.org/10.3133/ofr20141202.","productDescription":"Report: v, 36 p.; 2 Appendixes","numberOfPages":"43","onlineOnly":"Y","temporalStart":"2005-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-055491","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":294582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141202.jpg"},{"id":294574,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1202/"},{"id":294586,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1202/pdf/ofr2014-1202.pdf"},{"id":294596,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1202/downloads/ofr2014-1202_appendix3.pdf"},{"id":294595,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2014/1202/downloads/ofr2014-1202_appendix2.pdf"}],"country":"Canada;United States","state":"British Columbia;Oregon;Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.88,45.8608 ], [ -124.88,49.3817 ], [ -120.6473,49.3817 ], [ -120.6473,45.8608 ], [ -124.88,45.8608 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"542a66afe4b01535cb427272","contributors":{"authors":[{"text":"Saracco, James F.","contributorId":23680,"corporation":false,"usgs":true,"family":"Saracco","given":"James F.","affiliations":[],"preferred":false,"id":501458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holmgren, Amanda L.","contributorId":40914,"corporation":false,"usgs":true,"family":"Holmgren","given":"Amanda","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkerson, Robert L.","contributorId":56320,"corporation":false,"usgs":true,"family":"Wilkerson","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":501463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siegel, Rodney B.","contributorId":37019,"corporation":false,"usgs":true,"family":"Siegel","given":"Rodney","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":501460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kuntz, Robert C. II","contributorId":83213,"corporation":false,"usgs":true,"family":"Kuntz","given":"Robert","suffix":"II","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":501465,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":501457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Happe, Patricia J.","contributorId":50983,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":501462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boetsch, John R.","contributorId":36236,"corporation":false,"usgs":true,"family":"Boetsch","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":501459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huff, Mark H.","contributorId":73296,"corporation":false,"usgs":true,"family":"Huff","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":501464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}