Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.05.016","usgsCitation":"Ellefsen, K.J., and Smith, D., 2016, Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model: Applied Geochemistry, v. 75, p. 200-210, https://doi.org/10.1016/j.apgeochem.2016.05.016.","productDescription":"11 p.","startPage":"200","endPage":"210","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073180","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":324600,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":470811,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2016.05.016","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 37\n ],\n [\n -107,\n 41\n ],\n [\n -102,\n 41\n ],\n [\n -102,\n 37\n ],\n [\n -107,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e345e4b07dd077c5fcab","contributors":{"authors":[{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":629166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":629167,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171068,"text":"70171068 - 2016 - On the sustainability of inland fisheries: Finding a future for the forgotten","interactions":[],"lastModifiedDate":"2018-04-24T13:51:53","indexId":"70171068","displayToPublicDate":"2016-06-29T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":698,"text":"Ambio","active":true,"publicationSubtype":{"id":10}},"title":"On the sustainability of inland fisheries: Finding a future for the forgotten","docAbstract":"At present, inland fisheries are not often a national or regional governance priority and as a result, inland capture fisheries are undervalued and largely overlooked. As such they are threatened in both developing and developed countries. Indeed, due to lack of reliable data, inland fisheries have never been part of any high profile global fisheries assessment and are notably absent from the Sustainable Development Goals. The general public and policy makers are largely ignorant of the plight of freshwater ecosystems and the fish they support, as well as the ecosystem services generated by inland fisheries. This ignorance is particularly salient given that the current emphasis on the food-water-energy nexus often fails to include the important role that inland fish and fisheries play in food security and supporting livelihoods in low-income food deficit countries. Developing countries in Africa and Asia produce about 11 million tonnes of inland fish annually, 90 % of the global total. The role of inland fisheries goes beyond just kilocalories; fish provide important micronutrients and essentially fatty acids. In some regions, inland recreational fisheries are important, generating much wealth and supporting livelihoods. The following three key recommendations are necessary for action if inland fisheries are to become a part of the food-water-energy discussion: invest in improved valuation and assessment methods, build better methods to effectively govern inland fisheries (requires capacity building and incentives), and develop approaches to managing waters across sectors and scales. Moreover, if inland fisheries are recognized as important to food security, livelihoods, and human well-being, they can be more easily incorporated in regional, national, and global policies and agreements on water issues. Through these approaches, inland fisheries can be better evaluated and be more fully recognized in broader water resource and aquatic ecosystem planning and decision-making frameworks, enhancing their value and sustainability for the future.
","language":"English","publisher":"Springer","doi":"10.1007/s13280-016-0787-4","usgsCitation":"Cooke, S., Allison, E.H., Beard, Arlinghaus, R., Arthington, A., Bartley, D., Cowx, I.G., Fuentevilla, C., Leonard, N.J., Lorenzen, K., Lynch, A., Nguyen, V., Youn, S., Tayor, W.W., and Welcomme, R., 2016, On the sustainability of inland fisheries: Finding a future for the forgotten: Ambio, v. 45, no. 7, p. 753-764, https://doi.org/10.1007/s13280-016-0787-4.","productDescription":"12 p.","startPage":"753","endPage":"764","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069471","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":470812,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s13280-016-0787-4","text":"External Repository"},{"id":324593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-16","publicationStatus":"PW","scienceBaseUri":"5774e349e4b07dd077c5fccc","chorus":{"doi":"10.1007/s13280-016-0787-4","url":"http://dx.doi.org/10.1007/s13280-016-0787-4","publisher":"Springer Nature","authors":"Cooke Steven J., Allison Edward H., Beard T. 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Methods for collecting and detectingCoccidioides in soil samples are currently in use by several laboratories; however, a method utilizing current air sampling technologies has not been formally demonstrated for the capture of airborne arthroconidia. In this study, we collected air/dust samples at two sites (Site A and Site B) in the endemic region of Tucson, Arizona, and tested a variety of air samplers and membrane matrices. We then employed a single-tube nested qPCR assay for molecular detection. At both sites, numerous soil samples (n = 10 at Site A and n = 24 at Site B) were collected and Coccidioides was detected in two samples (20%) at Site A and in eight samples (33%) at Site B. Of the 25 air/dust samples collected at both sites using five different air sampling methods, we detected Coccidioides in three samples from site B. All three samples were collected using a high-volume sampler with glass-fiber filters. In this report, we describe these methods and propose the use of these air sampling and molecular detection strategies for environmental surveillance of Coccidioides.
","language":"English","publisher":"Oxford Journals","doi":"10.1093/mmy/myw022","usgsCitation":"Chow, N.A., Griffin, D.W., Barker, B.M., Loparev, V.N., and Litvintseva, A.P., 2016, Molecular detection of airborne Coccidioides in Tucson, Arizona: Medical Mycology, v. 54, no. 6, p. 584-592, https://doi.org/10.1093/mmy/myw022.","productDescription":"9 p.","startPage":"584","endPage":"592","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068272","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/mmy/myw022","text":"Publisher Index Page"},{"id":324591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","city":"Tucson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.2200927734375,\n 32.01273389791075\n ],\n [\n -111.2200927734375,\n 32.45183828577544\n ],\n [\n -110.70098876953125,\n 32.45183828577544\n ],\n [\n -110.70098876953125,\n 32.01273389791075\n ],\n [\n -111.2200927734375,\n 32.01273389791075\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-03","publicationStatus":"PW","scienceBaseUri":"5774e347e4b07dd077c5fcba","contributors":{"authors":[{"text":"Chow, Nancy A.","contributorId":168323,"corporation":false,"usgs":false,"family":"Chow","given":"Nancy","email":"","middleInitial":"A.","affiliations":[{"id":25255,"text":"USCDC","active":true,"usgs":false}],"preferred":false,"id":625479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":625478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barker, Bridget M.","contributorId":168324,"corporation":false,"usgs":false,"family":"Barker","given":"Bridget","email":"","middleInitial":"M.","affiliations":[{"id":25256,"text":"Translational Genomics Research Institute","active":true,"usgs":false}],"preferred":false,"id":625480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loparev, Vladimir N.","contributorId":168325,"corporation":false,"usgs":false,"family":"Loparev","given":"Vladimir","email":"","middleInitial":"N.","affiliations":[{"id":25255,"text":"USCDC","active":true,"usgs":false}],"preferred":false,"id":625481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Litvintseva, Anastasia P.","contributorId":168326,"corporation":false,"usgs":false,"family":"Litvintseva","given":"Anastasia","email":"","middleInitial":"P.","affiliations":[{"id":25255,"text":"USCDC","active":true,"usgs":false}],"preferred":false,"id":625482,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174210,"text":"70174210 - 2016 - Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids","interactions":[],"lastModifiedDate":"2016-06-29T15:30:05","indexId":"70174210","displayToPublicDate":"2016-06-29T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids","docAbstract":"Pesticide presence in streams is a potential threat to Endangered Species Act listed salmonids in the Hood River basin, Oregon, a primarily forested and agricultural basin. Two types of passive samplers, polar organic chemical integrative samplers (POCIS) and semipermeable membrane devices (SPMDs), were simultaneously deployed at four sites in the basin during Mar. 2011–Mar. 2012 to measure the presence of pesticides, polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs). The year-round use of passive samplers is a novel approach and offers several new insights. Currently used pesticides and legacy contaminants, including many chlorinated pesticides and PBDEs, were present throughout the year in the basin’s streams. PCBs were not detected. Time-weighted average water concentrations for the 2-month deployment periods were estimated from concentrations of chemicals measured in the passive samplers. Currently used pesticide concentrations peaked during spring and were detected beyond their seasons of expected use. Summed concentrations of legacy contaminants in Neal Creek were highest during July–Sept., the period with the lowest streamflows. Endosulfan was the only pesticide detected in passive samplers at concentrations exceeding Oregon or U.S. Environmental Protection Agency water-quality thresholds. A Sensitive Pesticide Toxicity Index (SPTI) was used to estimate the relative acute potential toxicity among sample mixtures. The acute potential toxicity of the detected mixtures was likely greater for invertebrates than for fish and for all samples in Neal Creek compared to Rogers Creek, but the indices appear to be low overall (<0.1). Endosulfans and pyrethroid insecticides were the largest contributors to the SPTIs for both sites. SPTIs of some discrete (grab) samples from the basin that were used for comparison exceeded 0.1 when some insecticides (azinphos methyl, chlorpyrifos, malathion) were detected at concentrations near or exceeding acute water-quality thresholds. Early life stages and adults of several sensitive fish species, including salmonids, are present in surface waters of the basin throughout the year, including during periods of peak estimated potential toxicity. Based on these data, direct toxicity to salmonids from in-stream pesticide exposure is unlikely, but indirect impacts (reduced fitness due to cumulative exposures or negative impacts to invertebrate prey populations) are unknown.
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","language":"English","publisher":"University of Chicago Press","doi":"10.1086/687843","usgsCitation":"Lynch, D.T., and Magoulick, D.D., 2016, Effects of pulse and press drying disturbance on benthic stream communities: Freshwater Science, v. 35, no. 3, p. 998-1009, https://doi.org/10.1086/687843.","productDescription":"12 p. ","startPage":"998","endPage":"1009","ipdsId":"IP-059893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":336737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba8e4b01ccd5500bb1d","contributors":{"authors":[{"text":"Lynch, Dustin T.","contributorId":145645,"corporation":false,"usgs":false,"family":"Lynch","given":"Dustin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":680399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":673765,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70177751,"text":"70177751 - 2016 - The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)","interactions":[],"lastModifiedDate":"2018-08-08T10:25:00","indexId":"70177751","displayToPublicDate":"2016-06-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)","docAbstract":"Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.
","language":"English","publisher":"Pergamon Press","doi":"10.1016/j.marpolbul.2016.02.076","usgsCitation":"Slonecker, E.T., Jones, D.K., and Pellerin, B.A., 2016, The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM): Marine Pollution Bulletin, v. 107, no. 2, p. 518-527, https://doi.org/10.1016/j.marpolbul.2016.02.076.","productDescription":"10 p.","startPage":"518","endPage":"527","ipdsId":"IP-069654","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470815,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2016.02.076","text":"Publisher Index Page"},{"id":438605,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7125QQM","text":"USGS data release","linkHelpText":"CDOM/fDOM and Landsat 8 Comparisons"},{"id":330242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5809d7c4e4b0f497e78fca62","chorus":{"doi":"10.1016/j.marpolbul.2016.02.076","url":"http://dx.doi.org/10.1016/j.marpolbul.2016.02.076","publisher":"Elsevier BV","authors":"Slonecker E. Terrence, Jones Daniel K., Pellerin Brian A.","journalName":"Marine Pollution Bulletin","publicationDate":"6/2016","auditedOn":"3/21/2016","publiclyAccessibleDate":"3/4/2016"},"contributors":{"authors":[{"text":"Slonecker, E. Terrence 0000-0002-5793-0503 tslonecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":168591,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"tslonecker@usgs.gov","middleInitial":"Terrence","affiliations":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":651634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":651653,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175475,"text":"70175475 - 2016 - Increased water deficit decreases Douglas fir growth throughout western US forests","interactions":[],"lastModifiedDate":"2016-08-26T11:04:58","indexId":"70175475","displayToPublicDate":"2016-06-28T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Increased water deficit decreases Douglas fir growth throughout western US forests","docAbstract":"Changes in tree growth rates can affect tree mortality and forest feedbacks to the global carbon cycle. As air temperature increases, evaporative demand also increases, increasing effective drought in forest ecosystems. Using a spatially comprehensive network of Douglas-fir (Pseudotsuga menziesii) chronologies from 122 locations that experience distinctly different climate in the western United States, we show that increased temperature decreases growth via vapor pressure deficit (VPD) across all latitudes. Under an ensemble of global circulation models, we project an increase in both the mean VPD associated with the lowest growth extremes and the probability of exceeding these VPD values. As temperature continues to increase in future decades, we can expect deficit-related stress to increase and consequently Douglas-fir growth to decrease throughout its US range.
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The seasonal variations of natural attenuation were investigated through measurements of surficial CO2 effluxes, shallow soil CO2 radiocarbon contents, subsurface gas concentrations, soil temperature, and volumetric water contents during a 2-yr period. Surficial CO2 effluxes varied seasonally, with peak values of total soil respiration (TSR) occurring in the late spring and summer. Efflux and radiocarbon data indicated that the fractional contributions of natural soil respiration (NSR) and contaminant soil respiration (CSR) to TSR varied seasonally. The NSR dominated in the spring and summer, and CSR dominated in the fall and winter. Subsurface gas concentrations also varied seasonally, with peak values of CO2 and CH4 occurring in the fall and winter. Vadose zone temperatures and subsurface CO2 concentrations revealed a correlation between contaminant respiration and temperature. A time lag of 5 to 7 mo between peak subsurface CO2 concentrations and peak surface efflux is consistent with travel-time estimates for subsurface gas migration. Periods of frozen soils coincided with depressed surface CO2 effluxes and elevated CO2 concentrations, pointing to the temporary presence of an ice layer that inhibited gas transport. Quantitative reactive transport simulations demonstrated aspects of the conceptual model developed from field measurements. Overall, results indicated that source-zone natural attenuation (SZNA) rates and gas transport processes varied seasonally and that the average annual SZNA rate estimated from periodic surface efflux measurements is 60% lower than rates determined from measurements during the summer.
","language":"English","publisher":"Soil Science Society of America","publisherLocation":"Fitchburg, WI","doi":"10.2136/vzj2015.09.0125","usgsCitation":"Sihota, N.J., Trost, J.J., Bekins, B., Berg, A.M., Delin, G.N., Mason, B.E., Warren, E., and Mayer, K.U., 2016, Seasonal Variability in Vadose zone biodegradation at a crude oil pipeline rupture site: Vadose Zone Journal, v. 15, no. 5, 14 p., https://doi.org/10.2136/vzj2015.09.0125.","productDescription":"14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057205","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":324558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"577391a7e4b07657d1a88bd8","contributors":{"authors":[{"text":"Sihota, Natasha J.","contributorId":46431,"corporation":false,"usgs":true,"family":"Sihota","given":"Natasha","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bekins, Barbara 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":139407,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berg, Andrew M. 0000-0001-9312-240X aberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9312-240X","contributorId":5642,"corporation":false,"usgs":true,"family":"Berg","given":"Andrew","email":"aberg@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delin, Geoffrey N. 0000-0001-7991-6158 delin@usgs.gov","orcid":"https://orcid.org/0000-0001-7991-6158","contributorId":2610,"corporation":false,"usgs":true,"family":"Delin","given":"Geoffrey","email":"delin@usgs.gov","middleInitial":"N.","affiliations":[{"id":5063,"text":"Central Water Science Field Team","active":true,"usgs":true}],"preferred":true,"id":638905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mason, Brent E. bmason@usgs.gov","contributorId":5196,"corporation":false,"usgs":true,"family":"Mason","given":"Brent","email":"bmason@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638906,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warren, Ean ewarren@usgs.gov","contributorId":1351,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638907,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mayer, K. Ulrich","contributorId":151069,"corporation":false,"usgs":false,"family":"Mayer","given":"K.","email":"","middleInitial":"Ulrich","affiliations":[{"id":18176,"text":"Department of Earth and Ocean Science, University of British Columbia, Vancouver, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":638908,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170462,"text":"70170462 - 2016 - Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014)","interactions":[],"lastModifiedDate":"2019-12-14T06:31:12","indexId":"70170462","displayToPublicDate":"2016-06-28T16:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014)","docAbstract":"Remote sensing has proven a useful way of evaluating long-term trends in vegetation “greenness” through the use of vegetation indices like Normalized Differences Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In particular, analyses of greenness trends have been performed for large areas (continents, for example) in an attempt to understand vegetation response to climate. These studies have been most often used coarse resolution sensors like Moderate Resolution Image Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR). However, trends in greenness are also important at more local scales, particularly in and around cities as vegetation offers a variety of valuable ecosystem services ranging from minimizing air pollution to mitigating urban heat island effects. To explore the ability to monitor greenness trends in and around cities, this paper presents a new way for analyzing greenness trends based on all available Landsat 5, 7, and 8 images and applies it to Guangzhou, China. This method is capable of including the effects of land cover change in the evaluation of greenness trends by separating the effects of abrupt and gradual changes, and providing information on the timing of greenness trends.
\nAn assessment of the consistency of surface reflectance from Landsat 8 with past Landsat sensors indicates biases in the visible bands of Landsat 8, especially the blue band. Landsat 8 NDVI values were found to have a larger bias than the EVI values; therefore, EVI was used in the analysis of greenness trends for Guangzhou. In spite of massive amounts of development in Guangzhou from 2000 to 2014, greenness was found to increase, mostly as a result of gradual change. Comparison of the greening magnitudes estimated from the approach presented here and a Simple Linear Trend (SLT) method indicated large differences for certain time intervals as the SLT method does not include consideration for abrupt land cover changes. Overall, this analysis demonstrates the importance of considering land cover change when analyzing trends in greenness from satellite time series in areas where land cover change is common.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.03.036","usgsCitation":"Zhu, Z., Fu, Y., Woodcock, C., Olofsson, P., Vogelmann, J., Holden, C., Wang, M., Dai, S., and Yu, Y., 2016, Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014): Remote Sensing of Environment, v. 185, p. 243-257, https://doi.org/10.1016/j.rse.2016.03.036.","productDescription":"15 p.","startPage":"243","endPage":"257","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068963","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470818,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2016.03.036","text":"Publisher Index Page"},{"id":324550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","city":"Guangzhou","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 112.5,\n 21.453068633086783\n ],\n [\n 116.71874999999999,\n 21.453068633086783\n ],\n [\n 116.71874999999999,\n 26.86328062676624\n ],\n [\n 112.5,\n 26.86328062676624\n ],\n [\n 112.5,\n 21.453068633086783\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"185","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a6e4b07657d1a88bd0","contributors":{"authors":[{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":627309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fu, Yingchun","contributorId":172520,"corporation":false,"usgs":false,"family":"Fu","given":"Yingchun","email":"","affiliations":[],"preferred":false,"id":641108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodcock, Curtis","contributorId":166666,"corporation":false,"usgs":false,"family":"Woodcock","given":"Curtis","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":641109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olofsson, Pontus","contributorId":131007,"corporation":false,"usgs":false,"family":"Olofsson","given":"Pontus","email":"","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":641110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":127752,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":641111,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holden, Christopher","contributorId":172521,"corporation":false,"usgs":false,"family":"Holden","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":641112,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Min","contributorId":145692,"corporation":false,"usgs":false,"family":"Wang","given":"Min","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":641113,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, Shu","contributorId":172522,"corporation":false,"usgs":false,"family":"Dai","given":"Shu","email":"","affiliations":[],"preferred":false,"id":641114,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yu, Yang","contributorId":172524,"corporation":false,"usgs":false,"family":"Yu","given":"Yang","email":"","affiliations":[],"preferred":false,"id":641115,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170411,"text":"70170411 - 2016 - Spatiotemporal patterns of mercury accumulation in lake sediments of western North America","interactions":[],"lastModifiedDate":"2018-08-09T12:04:23","indexId":"70170411","displayToPublicDate":"2016-06-28T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal patterns of mercury accumulation in lake sediments of western North America","docAbstract":"For the Western North America Mercury Synthesis, we compiled mercury records from 165 dated sediment cores from 138 natural lakes across western North America. Lake sediments are accepted as faithful recorders of historical mercury accumulation rates, and regional and sub-regional temporal and spatial trends were analyzed with descriptive and inferential statistics. Mercury accumulation rates in sediments have increased, on average, four times (4×) from 1850 to 2000 and continue to increase by approximately 0.2 μg/m2 per year. Lakes with the greatest increases were influenced by the Flin Flon smelter, followed by lakes directly affected by mining and wastewater discharges. Of lakes not directly affected by point sources, there is a clear separation in mercury accumulation rates between lakes with no/little watershed development and lakes with extensive watershed development for agricultural and/or residential purposes. Lakes in the latter group exhibited a sharp increase in mercury accumulation rates with human settlement, stabilizing after 1950 at five times (5×) 1850 rates. Mercury accumulation rates in lakes with no/little watershed development were controlled primarily by relative watershed size prior to 1850, and since have exhibited modest increases (in absolute terms and compared to that described above) associated with (regional and global) industrialization. A sub-regional analysis highlighted that in the ecoregion Northwestern Forest Mountains, <1% of mercury deposited to watersheds is delivered to lakes. Research is warranted to understand whether mountainous watersheds act as permanent sinks for mercury or if export of “legacy” mercury (deposited in years past) will delay recovery when/if emissions reductions are achieved.
Mercury (Hg) is considered a contaminant of global concern for coastal environments due to its toxicity, widespread occurrence in sediment, and bioaccumulation in tissue. Coastal New Jersey, USA, is characterized by shallow bays and wetlands that provide critical habitat for wildlife but share space with expanding urban landscapes. This study was designed as an assessment of the magnitude and distribution of Hg in coastal New Jersey sediments and critical species using publicly available data to highlight potential data gaps. Mercury concentrations in estuary sediments can exceed 2 μg/g and correlate with concentrations of other metals. Based on existing data, the concentrations of Hg in mussels in southern New Jersey are comparable to those observed in other urbanized Atlantic Coast estuaries. Lack of methylmercury data for sediments, other media, and tissues are data gaps needing to be filled for a clearer understanding of the impacts of Hg inputs to the ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.027","usgsCitation":"Ng, K., Szabo, Z., Reilly, P.A., Barringer, J., and Smalling, K., 2016, An assessment of mercury in estuarine sediment and tissue in Southern New Jersey using public domain data: Marine Pollution Bulletin, v. 107, no. 1, p. 22-35, https://doi.org/10.1016/j.marpolbul.2016.04.027.","productDescription":"14 p.","startPage":"22","endPage":"35","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069013","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":470819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2016.04.027","text":"Publisher Index Page"},{"id":324536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7015380859375,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 39.24714385893248\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a2e4b07657d1a88bbe","contributors":{"authors":[{"text":"Ng, Kara","contributorId":169541,"corporation":false,"usgs":false,"family":"Ng","given":"Kara","email":"","affiliations":[{"id":25560,"text":"The City College of New York, Division of Science","active":true,"usgs":false}],"preferred":false,"id":629961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barringer, Julia jbarring@usgs.gov","contributorId":169542,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia","email":"jbarring@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. ","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169127,"text":"70169127 - 2016 - Hemidactylus parvimaculatus (Sri Lankan spotted house gecko)","interactions":[],"lastModifiedDate":"2016-07-17T23:05:34","indexId":"70169127","displayToPublicDate":"2016-06-28T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Hemidactylus parvimaculatus (Sri Lankan spotted house gecko)","docAbstract":"USA: LOUISIANA: St. Tammany Parish: private property ca. 4 km S of Abita Springs, E of State Hwy 59, and N of Interstate 12 (30.44000°N, 90.02000°W; WGS 84). 18 August 2013. Brad M. Glorioso. Verified by David Heckard. Florida Museum of Natural History (UF 176422, photo voucher). New parish record. This species was first reported in the Americas in the vicinity of Audubon Zoo in New Orleans, Louisiana (Heckard et al. 2013. IRCF Reptiles & Amphibians 20:192–196). This is the third report of this species in Louisiana (Heckard et al. 2013, op. cit.; Borgardt 2015. Herpetol. Rev. 46:217), and is now documented from Orleans, Jefferson, and St. Tammany parishes in southeast Louisiana. The individual was located at night, ca. 10 m from a dwelling on the forest floor amid a downed picket fence, which was resting atop a thick layer of pine needles. There are H. turcicus at the property, but this individual was recognized as unusual, and many photos were taken before releasing the animal. It was not until much later that it was determined to be H. parvimaculatus. The origin of this individual is unknown, as the owners of this 1.62-ha property are elderly and do not keep any pets. Subsequent casual searches have not turned up any new individuals. I thank David Heckard for his help with identification and discussion of this species in Louisiana.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Glorioso, B.M., 2016, Hemidactylus parvimaculatus (Sri Lankan spotted house gecko): Herpetological Review, v. 47, no. 1, p. 81-81.","productDescription":"1 p.","startPage":"81","endPage":"81","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071143","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":319094,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/publications/journals/herpetological-review/"}],"volume":"47","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a5e4b07657d1a88bca","contributors":{"authors":[{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":623127,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70169031,"text":"70169031 - 2016 - The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA","interactions":[],"lastModifiedDate":"2025-05-13T16:48:37.177037","indexId":"70169031","displayToPublicDate":"2016-06-28T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA","docAbstract":"Low-relief environments like the Florida Coastal Everglades (FCE) have complicated hydrologic systems where surface water and groundwater processes are intimately linked yet hard to separate. Fluid exchange within these lowhydraulic-gradient systems can occur across broad spatial and temporal scales, with variable contributions to material transport and transformation. Identifying and assessing the scales at which these processes operate is essential for accurate evaluations of how these systems contribute to global biogeochemical cycles. The distribution of 222Rn and 223,224,226Ra have complex spatial patterns along the Shark River Slough estuary (SRSE), Everglades, FL. High-resolution time-series measurements of 222Rn activity, salinity, and water level were used to quantify processes affecting radon fluxes out of the mangrove forest over a tidal cycle. Based on field data, tidal pumping through an extensive network of crab burrows in the lower FCE provides the best explanation for the high radon and fluid fluxes. Burrows are irrigated during rising tides when radon and other dissolved constituents are released from the mangrove soil. Flushing efficiency of the burrows—defined as the tidal volume divided by the volume of burrows— estimated for the creek drainage area vary seasonally from 25 (wet season) to 100 % (dry season) in this study. The tidal pumping of the mangrove forest soil acts as a significant vector for exchange between the forest and the estuary. Processes that enhance exchange of O2 and other materials across the sediment-water interface could have a profound impact on the environmental response to larger scale processes such as sea level rise and climate change. Compounding the material budgets of the SRSE are additional inputs from groundwater from the Biscayne Aquifer, which were identified using radium isotopes. Quantification of the deep groundwater component is not obtainable, but isotopic data suggest a more prevalent signal in the dry season. These findings highlight the important role that both tidal- and seasonal-scale forcings play on groundwater movement in low-gradient hydrologic systems.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-016-0079-z","usgsCitation":"Smith, C.G., Price, R.M., Swarzenski, P.W., and Stalker, J.C., 2016, The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA: Estuaries and Coasts, v. 39, no. 6, p. 1600-1616, https://doi.org/10.1007/s12237-016-0079-z.","productDescription":"17 p.","startPage":"1600","endPage":"1616","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067122","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3482666015625,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.175116531621764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-26","publicationStatus":"PW","scienceBaseUri":"577391a8e4b07657d1a88bdc","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":622616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Rene M.","contributorId":52880,"corporation":false,"usgs":true,"family":"Price","given":"Rene","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":622617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":622618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stalker, Jeremy C.","contributorId":167541,"corporation":false,"usgs":false,"family":"Stalker","given":"Jeremy","email":"","middleInitial":"C.","affiliations":[{"id":24739,"text":"Jacksonville State University","active":true,"usgs":false}],"preferred":false,"id":622619,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174228,"text":"70174228 - 2016 - Genetic reconstruction of a bullfrog invasion to elucidate vectors of introduction and secondary spread","interactions":[],"lastModifiedDate":"2016-08-04T15:20:25","indexId":"70174228","displayToPublicDate":"2016-06-28T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genetic reconstruction of a bullfrog invasion to elucidate vectors of introduction and secondary spread","docAbstract":"Reconstructing historical colonization pathways of an invasive species is critical for uncovering factors that determine invasion success and for designing management strategies. The American bullfrog (Lithobates catesbeianus) is endemic to eastern North America, but now has a global distribution and is considered to be one of the worst invaders in the world. In Montana, several introduced populations have been reported, but little is known of their sources and vectors of introduction and secondary spread. We evaluated the genetic composition of introduced populations at local (Yellowstone River floodplain) and regional (Montana and Wyoming) scales in contrast to native range populations. Our objectives were to (1) estimate the number of introductions, (2) identify probable native sources, (3) evaluate genetic variation relative to sources, and (4) characterize properties of local- and regional-scale spread. We sequenced 937 bp of the mitochondrial cytochrome b locus in 395 tadpoles collected along 100 km of the Yellowstone River, from three additional sites in MT and a proximate site in WY. Pairwise ΦST revealed high divergence among nonnative populations, suggesting at least four independent introductions into MT from diverse sources. Three cyt b haplotypes were identical to native haplotypes distributed across the Midwest and Great Lakes regions, and AMOVA confirmed the western native region as a likely source. While haplotype (Hd = 0.69) and nucleotide diversity (π = 0.005) were low in introduced bullfrogs, the levels of diversity did not differ significantly from source populations. In the Yellowstone, two identified haplotypes implied few introduction vectors and a significant relationship between genetic and river distance was found. Evidence for multiple invasions and lack of subsequent regional spread emphasizes the importance of enforcing legislation prohibiting bullfrog importation and the need for continuing public education to prevent transport of bullfrogs in MT. 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\"}}]}","volume":"6","issue":"15","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-28","publicationStatus":"PW","scienceBaseUri":"57779430e4b07dd077c905de","chorus":{"doi":"10.1002/ece3.2278","url":"http://dx.doi.org/10.1002/ece3.2278","publisher":"Wiley-Blackwell","authors":"Kamath Pauline L., Sepulveda Adam J., Layhee Megan","journalName":"Ecology and Evolution","publicationDate":"6/28/2016"},"contributors":{"authors":[{"text":"Kamath, Pauline L. pkamath@usgs.gov","contributorId":4517,"corporation":false,"usgs":true,"family":"Kamath","given":"Pauline","email":"pkamath@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":641437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":641436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Layhee, Megan J. 0000-0003-1359-1455 mlayhee@usgs.gov","orcid":"https://orcid.org/0000-0003-1359-1455","contributorId":3955,"corporation":false,"usgs":true,"family":"Layhee","given":"Megan","email":"mlayhee@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":641438,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170667,"text":"70170667 - 2016 - Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations","interactions":[],"lastModifiedDate":"2016-11-09T10:11:38","indexId":"70170667","displayToPublicDate":"2016-06-28T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations","docAbstract":"Supraglacial rivers on the Greenland ice sheet (GrIS) transport large volumes of surface meltwater toward the ocean, yet have received relatively little direct research. This study presents field observations of channel width, depth, velocity, and water surface slope for nine supraglacial channels on the southwestern GrIS collected between 23 July and 20 August, 2012. Field sites are located up to 74 km inland and span 494-1485 m elevation, and contain measured discharges larger than any previous in situ study: from 0.006 to 23.12 m3/s in channels 0.20 to 20.62 m wide. All channels were deeply incised with near vertical banks, and hydraulic geometry results indicate that supraglacial channels primarily accommodate greater discharges by increasing velocity. Smaller streams had steeper water surface slopes (0.74-8.83%) than typical in terrestrial settings, yielding correspondingly high velocities (0.40-2.60 m/s) and Froude numbers (0.45-3.11) with supercritical flow observed in 54% of measurements. Derived Manning's n values were larger and more variable than anticipated from channels of uniform substrate, ranging from 0.009 to 0.154 with a mean value of 0.035 +/- 0.027 despite the absence of sediment, debris, or other roughness elements. Ubiquitous micro-depressions in shallow sections of the channel bed may explain some of these roughness values. However, we find that other, unobserved sources of flow resistance likely contributed to these elevated n values: future work should explicitly consider additional sources of flow resistance beyond bed roughness in supraglacial channels. We conclude that hydraulic modelling for these channels must allow for both sub- and supercritical flow, and most importantly must refrain from assuming that all ice-substrate channels exhibit similar hydraulic behavior, especially for Froude numbers and Manning's n. Finally, this study highlights that further theoretical and empirical work on supraglacial channel hydraulics is necessary before broad scale understanding of ice sheet hydrology can be achieved. This article is protected by copyright. All rights reserved.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3977","usgsCitation":"Gleason, C.J., Smith, L., Chu, V.W., Legleiter, C.J., Pitcher, L.H., Overstreet, B.T., Rennermalm, A.K., Forster, R.R., and Yang, K., 2016, Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations: Earth Surface Processes and Landforms, v. 41, no. 14, p. 2111-2122, https://doi.org/10.1002/esp.3977.","productDescription":"12 p.","startPage":"2111","endPage":"2122","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075253","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":324508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-46.76379,82.62796],[-43.40644,83.22516],[-39.89753,83.18018],[-38.62214,83.54905],[-35.08787,83.64513],[-27.10046,83.51966],[-20.84539,82.72669],[-22.69182,82.34165],[-26.51753,82.29765],[-31.9,82.2],[-31.39646,82.02154],[-27.85666,82.13178],[-24.84448,81.78697],[-22.90328,82.09317],[-22.07175,81.73449],[-23.16961,81.15271],[-20.62363,81.52462],[-15.76818,81.91245],[-12.77018,81.71885],[-12.20855,81.29154],[-16.28533,80.58004],[-16.85,80.35],[-20.04624,80.17708],[-17.73035,80.12912],[-18.9,79.4],[-19.70499,78.75128],[-19.67353,77.63859],[-18.47285,76.98565],[-20.03503,76.94434],[-21.67944,76.62795],[-19.83407,76.09808],[-19.59896,75.24838],[-20.66818,75.15585],[-19.37281,74.29561],[-21.59422,74.22382],[-20.43454,73.81713],[-20.76234,73.46436],[-22.17221,73.30955],[-23.56593,73.30663],[-22.31311,72.62928],[-22.29954,72.18409],[-24.27834,72.59788],[-24.79296,72.3302],[-23.44296,72.08016],[-22.13281,71.46898],[-21.75356,70.66369],[-23.53603,70.471],[-24.30702,70.85649],[-25.54341,71.43094],[-25.20135,70.75226],[-26.36276,70.22646],[-23.72742,70.18401],[-22.34902,70.12946],[-25.02927,69.2588],[-27.74737,68.47046],[-30.67371,68.12503],[-31.77665,68.12078],[-32.81105,67.73547],[-34.20196,66.67974],[-36.35284,65.9789],[-37.04378,65.93768],[-38.37505,65.69213],[-39.81222,65.45848],[-40.66899,64.83997],[-40.68281,64.13902],[-41.1887,63.48246],[-42.81938,62.68233],[-42.41666,61.90093],[-42.86619,61.07404],[-43.3784,60.09772],[-44.7875,60.03676],[-46.26364,60.85328],[-48.26294,60.85843],[-49.23308,61.40681],[-49.90039,62.38336],[-51.63325,63.62691],[-52.14014,64.27842],[-52.27659,65.1767],[-53.66166,66.09957],[-53.30161,66.8365],[-53.96911,67.18899],[-52.9804,68.35759],[-51.47536,68.72958],[-51.08041,69.14781],[-50.87122,69.9291],[-52.01358,69.57492],[-52.55792,69.42616],[-53.45629,69.28363],[-54.68336,69.61003],[-54.75001,70.28932],[-54.35884,70.82131],[-53.43131,70.83576],[-51.39014,70.56978],[-53.10937,71.20485],[-54.00422,71.54719],[-55,71.40654],[-55.83468,71.65444],[-54.71819,72.58625],[-55.32634,72.95861],[-56.12003,73.64977],[-57.32363,74.71026],[-58.59679,75.09861],[-58.58516,75.51727],[-61.26861,76.10238],[-63.39165,76.1752],[-66.06427,76.13486],[-68.50438,76.06141],[-69.66485,76.37975],[-71.40257,77.00857],[-68.77671,77.32312],[-66.76397,77.37595],[-71.04293,77.63595],[-73.297,78.04419],[-73.15938,78.43271],[-69.37345,78.91388],[-65.7107,79.39436],[-65.3239,79.75814],[-68.02298,80.11721],[-67.15129,80.51582],[-63.68925,81.21396],[-62.23444,81.3211],[-62.65116,81.77042],[-60.28249,82.03363],[-57.20744,82.19074],[-54.13442,82.19962],[-53.04328,81.88833],[-50.39061,82.43883],[-48.00386,82.06481],[-46.59984,81.98595],[-44.523,81.6607],[-46.9007,82.19979],[-46.76379,82.62796]]]},\"properties\":{\"name\":\"Greenland\"}}]}","volume":"41","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-10","publicationStatus":"PW","scienceBaseUri":"577391a2e4b07657d1a88bc0","contributors":{"authors":[{"text":"Gleason, Colin J.","contributorId":169003,"corporation":false,"usgs":false,"family":"Gleason","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Laurence C.","contributorId":169004,"corporation":false,"usgs":false,"family":"Smith","given":"Laurence C.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chu, Vena W.","contributorId":169005,"corporation":false,"usgs":false,"family":"Chu","given":"Vena","email":"","middleInitial":"W.","affiliations":[{"id":12626,"text":"Department of Geography, University of California, Berkeley, CA 94720, USA","active":true,"usgs":false}],"preferred":false,"id":628026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":628023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitcher, Lincoln H.","contributorId":169006,"corporation":false,"usgs":false,"family":"Pitcher","given":"Lincoln","email":"","middleInitial":"H.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overstreet, Brandon T. 0000-0001-7845-6671","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":63257,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":628028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rennermalm, Asa K.","contributorId":169007,"corporation":false,"usgs":false,"family":"Rennermalm","given":"Asa","email":"","middleInitial":"K.","affiliations":[{"id":25395,"text":"Department of Geography, Rutgers University, New Brunswick","active":true,"usgs":false}],"preferred":false,"id":628029,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Forster, Richard R.","contributorId":169008,"corporation":false,"usgs":false,"family":"Forster","given":"Richard","email":"","middleInitial":"R.","affiliations":[{"id":25396,"text":"Department of Geography, University of Utah","active":true,"usgs":false}],"preferred":false,"id":628030,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yang, Kang","contributorId":169009,"corporation":false,"usgs":false,"family":"Yang","given":"Kang","email":"","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628031,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70173795,"text":"70173795 - 2016 - Geographic distribution of genetic diversity in populations of Rio Grande Chub Gila pandora","interactions":[],"lastModifiedDate":"2016-09-06T13:53:35","indexId":"70173795","displayToPublicDate":"2016-06-28T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Geographic distribution of genetic diversity in populations of Rio Grande Chub Gila pandora","docAbstract":"In the southwestern United States (US), the Rio Grande chub (Gila pandora) is state-listed as a fish species of greatest conservation need and federally listed as sensitive due to habitat alterations and competition with non-native fishes. Characterizing genetic diversity, genetic population structure, and effective number of breeders will assist with conservation efforts by providing a baseline of genetic metrics. Genetic relatedness within and among G. pandora populations throughout New Mexico was characterized using 11 microsatellite loci among 15 populations in three drainage basins (Rio Grande, Pecos, Canadian). Observed heterozygosity (HO) ranged from 0.71–0.87 and was similar to expected heterozygosity (0.75–0.87). Rio Ojo Caliente (Rio Grande) had the highest allelic richness (AR = 15.09), while Upper Rio Bonito (Pecos) had the lowest allelic richness (AR = 6.75). Genetic differentiation existed among all populations with the lowest genetic variation occurring within the Pecos drainage. STRUCTURE analysis revealed seven genetic clusters. Populations of G. pandora within the upper Rio Grande drainage (Rio Ojo Caliente, Rio Vallecitos, Rio Pueblo de Taos) had high levels of admixture with Q-values ranging from 0.30–0.50. In contrast, populations within the Pecos drainage (Pecos River and Upper Rio Bonito) had low levels of admixture (Q = 0.94 and 0.87, respectively). Estimates of effective number of breeders (N b ) varied from 6.1 (Pecos: Upper Rio Bonito) to 109.7 (Rio Grande: Rio Peñasco) indicating that populations in the Pecos drainage are at risk of extirpation. In the event that management actions are deemed necessary to preserve or increase genetic diversity of G. pandora, consideration must be given as to which populations are selected for translocation.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-016-0845-2","usgsCitation":"Galindo, R., Wilson, W., and Caldwell, C.A., 2016, Geographic distribution of genetic diversity in populations of Rio Grande Chub Gila pandora: Conservation Genetics, v. 17, no. 5, p. 1081-1091, https://doi.org/10.1007/s10592-016-0845-2.","productDescription":"11 p.","startPage":"1081","endPage":"1091","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064386","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah,","otherGeospatial":"Southwest United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.18945312500001,\n 42.00032514831621\n ],\n [\n -111.02783203125,\n 42.01665183556825\n ],\n [\n -111.005859375,\n 40.9964840143779\n ],\n [\n -102.01904296874999,\n 41.0130657870063\n ],\n [\n -102.041015625,\n 37.03763967977139\n ],\n [\n -103.0078125,\n 36.98500309285596\n ],\n [\n -103.07373046875,\n 32.02670629333614\n ],\n [\n -106.435546875,\n 31.728167146023935\n ],\n [\n -108.19335937499999,\n 31.784216884487385\n ],\n [\n -108.21533203125,\n 31.29732799140429\n ],\n [\n -111.09374999999999,\n 31.3348710339506\n ],\n [\n -114.78515624999999,\n 32.56533316084101\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -117.1142578125,\n 32.56533316084101\n ],\n [\n -120.62988281249999,\n 33.97980872872457\n ],\n [\n -124.29931640625,\n 39.01064750994083\n ],\n [\n -124.56298828125001,\n 40.26276066437183\n ],\n [\n -124.18945312500001,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-06","publicationStatus":"PW","scienceBaseUri":"577391a4e4b07657d1a88bc6","contributors":{"authors":[{"text":"Galindo, Rene","contributorId":172385,"corporation":false,"usgs":false,"family":"Galindo","given":"Rene","email":"","affiliations":[],"preferred":false,"id":640497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Wade","contributorId":103554,"corporation":false,"usgs":true,"family":"Wilson","given":"Wade","affiliations":[],"preferred":false,"id":640496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638372,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173940,"text":"70173940 - 2016 - Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-07-22T13:39:59","indexId":"70173940","displayToPublicDate":"2016-06-28T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico","docAbstract":"Shelf-margin carbonate mounds in water depths of 116–135 m in the eastern Gulf of Mexico along the central west Florida shelf were investigated using swath bathymetry, side-scan sonar, sub-bottom imaging, rock dredging, and submersible dives. These enigmatic structures, known to fisherman as the “Sticky Grounds”, trend along slope, are 5–15 m in relief with base diameters of 5–30 m, and suggest widespread potential for mesophotic reef habitat along the west Florida outer continental shelf. Possible origins are sea-level lowstand coral patch reefs, oyster reefs, or perhaps more recent post-lowstand biohermal development. Rock dredging recovered bioeroded carbonate-rock facies comprised of bored and cemented bioclastics. Rock sample components included calcified worm tubes, pelagic sediment, and oysters normally restricted to brackish nearshore areas. Several reef sites were surveyed at the Sticky Grounds during a cruise in August 2010 with the R/V Seward Johnson using the Johnson-Sea-Link II submersible to ground truth the swath-sonar maps and to quantify and characterize the benthic habitats, benthic macrofauna, fish populations, and coral/sponge cover. This study characterizes for the first time this mesophotic reef ecosystem and associated fish populations, and analyzes the interrelationships of the fish assemblages, benthic habitats and invertebrate biota. These highly eroded rock mounds provide extensive hard-bottom habitat for reef invertebrate species as well as essential fish habitat for reef fish and commercially/recreationally important fish species. The extent and significance of associated living resources with these bottom types is particularly important in light of the 2010 Deepwater Horizon oil spill in the northeastern Gulf and the proximity of the Loop Current. Mapping the distribution of these mesophotic-depth ecosystems is important for quantifying essential fish habitat and describing benthic resources. These activities can improve ecosystem management and planning of future oil and gas activities in this outer continental shelf region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2016.06.015","usgsCitation":"Locker, S., Reed, J.K., Farrington, S., Harter, S., Hine, A.C., and Dunn, S., 2016, Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico: Continental Shelf Research, v. 125, p. 71-87, https://doi.org/10.1016/j.csr.2016.06.015.","productDescription":"17 p.","startPage":"71","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070404","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470821,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2016.06.015","text":"Publisher Index Page"},{"id":324506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.044921875,\n 30.06909396443887\n ],\n [\n -85.4296875,\n 29.420460341013133\n ],\n [\n -84.4189453125,\n 29.573457073017593\n ],\n [\n -83.935546875,\n 29.38217507514529\n ],\n [\n -83.4521484375,\n 28.76765910569123\n ],\n [\n -83.27636718749999,\n 28.033197847676377\n ],\n [\n -82.3974609375,\n 26.509904531413927\n ],\n [\n -82.08984375,\n 25.760319754713887\n ],\n [\n -82.6611328125,\n 25.284437746983055\n ],\n [\n -84.0234375,\n 24.886436490787712\n ],\n [\n -84.9462890625,\n 25.363882272740256\n ],\n [\n -86.0009765625,\n 26.27371402440643\n ],\n [\n -87.14355468749999,\n 26.902476886279807\n ],\n [\n -88.4619140625,\n 27.21555620902969\n ],\n [\n -89.912109375,\n 27.176469131898898\n ],\n [\n -91.4501953125,\n 26.86328062676624\n ],\n [\n -93.33984375,\n 26.745610382199022\n ],\n [\n -94.04296874999999,\n 26.745610382199022\n ],\n [\n -94.4384765625,\n 27.644606381943326\n ],\n [\n -94.4384765625,\n 28.613459424004414\n ],\n [\n -94.21875,\n 29.036960648558267\n ],\n [\n -92.5048828125,\n 28.9600886880068\n ],\n [\n -91.3623046875,\n 28.76765910569123\n ],\n [\n -89.47265625,\n 28.729130483430154\n ],\n [\n -88.59374999999999,\n 29.036960648558267\n ],\n [\n -88.06640625,\n 29.53522956294847\n ],\n [\n -87.0556640625,\n 29.6880527498568\n ],\n [\n -86.044921875,\n 30.06909396443887\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a4e4b07657d1a88bc8","contributors":{"authors":[{"text":"Locker, Stanley D. slocker@usgs.gov","contributorId":5906,"corporation":false,"usgs":true,"family":"Locker","given":"Stanley D.","email":"slocker@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":639634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, John K.","contributorId":172114,"corporation":false,"usgs":false,"family":"Reed","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":639635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrington, Stephanie","contributorId":172115,"corporation":false,"usgs":false,"family":"Farrington","given":"Stephanie","email":"","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":639636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harter, Stacey","contributorId":172116,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","affiliations":[{"id":12555,"text":"NOAA Fisheries – Beaufort Laboratory, Beaufort, NC","active":true,"usgs":false}],"preferred":false,"id":639637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hine, Albert C.","contributorId":87580,"corporation":false,"usgs":true,"family":"Hine","given":"Albert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunn, Shane","contributorId":172117,"corporation":false,"usgs":false,"family":"Dunn","given":"Shane","email":"","affiliations":[{"id":7149,"text":"College of Marine Science, University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":639639,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70168946,"text":"70168946 - 2016 - High concentrations of manganese and sulfur in deposits on Murray Ridge, Endeavour Crater, Mars","interactions":[],"lastModifiedDate":"2018-11-08T17:09:01","indexId":"70168946","displayToPublicDate":"2016-06-28T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"High concentrations of manganese and sulfur in deposits on Murray Ridge, Endeavour Crater, Mars","docAbstract":"Mars Reconnaissance Orbiter HiRISE images and Opportunity rover observations of the ~22 km wide Noachian age Endeavour Crater on Mars show that the rim and surrounding terrains were densely fractured during the impact crater-forming event. Fractures have also propagated upward into the overlying Burns formation sandstones. Opportunity’s observations show that the western crater rim segment, called Murray Ridge, is composed of impact breccias with basaltic compositions, as well as occasional fracture-filling calcium sulfate veins. Cook Haven, a gentle depression on Murray Ridge, and the site where Opportunity spent its sixth winter, exposes highly fractured, recessive outcrops that have relatively high concentrations of S and Cl, consistent with modest aqueous alteration. Opportunity’s rover wheels serendipitously excavated and overturned several small rocks from a Cook Haven fracture zone. Extensive measurement campaigns were conducted on two of them: Pinnacle Island and Stuart Island. These rocks have the highest concentrations of Mn and S measured to date by Opportunity and occur as a relatively bright sulfate-rich coating on basaltic rock, capped by a thin deposit of one or more dark Mn oxide phases intermixed with sulfate minerals. We infer from these unique Pinnacle Island and Stuart Island rock measurements that subsurface precipitation of sulfate-dominated coatings was followed by an interval of partial dissolution and reaction with one or more strong oxidants (e.g., O2) to produce the Mn oxide mineral(s) intermixed with sulfate-rich salt coatings. In contrast to arid regions on Earth, where Mn oxides are widely incorporated into coatings on surface rocks, our results demonstrate that on Mars the most likely place to deposit and preserve Mn oxides was in fracture zones where migrating fluids intersected surface oxidants, forming precipitates shielded from subsequent physical erosion.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2016-5599","usgsCitation":"Arvidson, R.E., Squyres, S.W., Morris, R., Knoll, A.H., Gellert, R., Clark, B., Catalano, J.G., Jolliff, B.L., McLennan, S.M., Herkenhoff, K.E., VanBommel, S., Mittelfehldt, D.W., Grotzinger, J., Guinness, E.A., Johnson, J., Bell, J.F., Farrand, W., Stein, N., Fox, V.K., Golombek, M., Hinkle, M.A., Calvin, W.M., and de Souza, P.A., 2016, High concentrations of manganese and sulfur in deposits on Murray Ridge, Endeavour Crater, Mars: American Mineralogist, v. 101, no. 6, p. 1389-1405, https://doi.org/10.2138/am-2016-5599.","productDescription":"17 p.","startPage":"1389","endPage":"1405","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069984","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":470822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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III","contributorId":12737,"corporation":false,"usgs":true,"family":"Bell","given":"James","suffix":"III","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":623020,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Farrand, William H.","contributorId":167514,"corporation":false,"usgs":false,"family":"Farrand","given":"William H.","affiliations":[{"id":24736,"text":"Space Science Institute, Boulder, Colo.","active":true,"usgs":false}],"preferred":false,"id":623021,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Stein, Nathan","contributorId":167651,"corporation":false,"usgs":false,"family":"Stein","given":"Nathan","affiliations":[{"id":24730,"text":"Department of Earth and Planetary Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":623022,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Fox, Valerie K.","contributorId":167652,"corporation":false,"usgs":false,"family":"Fox","given":"Valerie","email":"","middleInitial":"K.","affiliations":[{"id":24730,"text":"Department of Earth and Planetary Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":623023,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Golombek, Matthew P.","contributorId":93180,"corporation":false,"usgs":true,"family":"Golombek","given":"Matthew P.","affiliations":[],"preferred":false,"id":623024,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Hinkle, Margaret A. G.","contributorId":167653,"corporation":false,"usgs":false,"family":"Hinkle","given":"Margaret","email":"","middleInitial":"A. G.","affiliations":[{"id":24730,"text":"Department of Earth and Planetary Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":623025,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Calvin, Wendy M.","contributorId":93508,"corporation":false,"usgs":true,"family":"Calvin","given":"Wendy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":623026,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"de Souza, Paulo A. 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Here, the first in situ images of the black coral Schizopathes sp. (Anthozoa: Antipatharia) in the deep western Indian Ocean have been obtained from remotely operated vehicle video footage and time-lapse photography. In these images, there appears to be an association with the cusk eel Bassozetus (Family: Ophidiidae). In the primary observation, chance encounters revealed the fish interacted with the anitpatharian on multiple occasions over several days. Subsequent time-lapse camera footage showed the fish remained almost exclusively underneath the antipatharian for the duration of a 30-h deployment. Excursions from the cover of the antipatharian were for less than 2 min. The primary observation is supported by two similar encounters in the same region. Observed reduction in the tail-beat frequency of the fish under the antipatharian suggests reduced energy requirements for the ophidiid in this position. The observations demonstrate the role that even individual coral colonies play as a source of three-dimensional structure, providing habitat heterogeneity in the deep sea.","language":"English","publisher":"Springer","doi":"10.1007/s12526-016-0516-z","usgsCitation":"Gates, A.R., Morris, K., Jones, D.O., and Sulak, K.J., 2016, An association between a cusk eel (Bassozetus sp.) and a black coral (Schizopathes sp.) in the deep western Indian Ocean: Marine Biodiversity Records, v. 47, no. 3, p. 971-977, https://doi.org/10.1007/s12526-016-0516-z.","productDescription":"7 p.","startPage":"971","endPage":"977","ipdsId":"IP-069269","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470826,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1007/s12526-016-0516-z>).","text":"External Repository"},{"id":372677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Indian Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 55.1953125,\n -41.244772343082076\n ],\n [\n 112.5,\n -41.244772343082076\n ],\n [\n 112.5,\n 10.833305983642491\n ],\n [\n 55.1953125,\n 10.833305983642491\n ],\n [\n 55.1953125,\n -41.244772343082076\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gates, Andrew R.","contributorId":222788,"corporation":false,"usgs":false,"family":"Gates","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":40603,"text":"National Oceanography Centre, University of Southampton Waterfront Campus","active":true,"usgs":false}],"preferred":false,"id":783187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Kirsty","contributorId":222789,"corporation":false,"usgs":false,"family":"Morris","given":"Kirsty","email":"","affiliations":[{"id":40603,"text":"National Oceanography Centre, University of Southampton Waterfront Campus","active":true,"usgs":false}],"preferred":false,"id":783188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Daniel O.B.","contributorId":222790,"corporation":false,"usgs":false,"family":"Jones","given":"Daniel","email":"","middleInitial":"O.B.","affiliations":[{"id":40603,"text":"National Oceanography Centre, University of Southampton Waterfront Campus","active":true,"usgs":false}],"preferred":false,"id":783189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sulak, Kenneth J. 0000-0002-4795-9310 ksulak@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-9310","contributorId":2217,"corporation":false,"usgs":true,"family":"Sulak","given":"Kenneth","email":"ksulak@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":783186,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170928,"text":"sir20165050 - 2016 - Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois","interactions":[],"lastModifiedDate":"2024-09-18T14:34:15.573847","indexId":"sir20165050","displayToPublicDate":"2016-06-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5050","displayTitle":"Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois","title":"Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois","docAbstract":"This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.
The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.
This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant.
The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted annual maximum peak discharge records by streamgage are provided at https://doi.org/10.3133/sir20165050 for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165050","collaboration":"Prepared in cooperation with the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., Veilleux, A.G., O’Shea, P.S., Sharpe, J.B., Soong, D.T., and Ishii, A.L., 2016, Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois (ver. 3.0, June 2021): U.S. Geological Survey Scientific Investigations Report 2016–5050, 50 p. with appendix, https://doi.org/10.3133/sir20165050.","productDescription":"Report: x, 51 p.; Tables; Companion Files; Version History","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072125","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":386876,"rank":13,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5050/versionHist.txt","text":"Version History","size":"20.7 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016–5050 Version History"},{"id":386859,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_13.csv","text":"Table 13","size":"4.33 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 13","linkHelpText":"— Components of variance of prediction for the selected spatial regression equations in this study in northeastern Illinois"},{"id":386858,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_08.csv","text":"Table 8","size":"2.36 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 8","linkHelpText":"— Quantile regression coefficients from temporal analysis of 117 streamgages in northeastern Illinois and adjacent states, as a function of annual exceedance probability"},{"id":386856,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_04.csv","text":"Table 4","size":"9.96 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 4","linkHelpText":"— Segment information for 181 U.S. Geological Survey streamgages used in this study, northeastern Illinois and adjacent states"},{"id":386855,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_03.csv","text":"Table 3","size":"7.02 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 3","linkHelpText":"— Spatially averaged basin characteristics considered for developing spatial regression equations in this study in northeastern Illinois"},{"id":386854,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_02.csv","text":"Table 2","size":"104 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 2","linkHelpText":"— Estimated peak discharge quantiles for 181 streamgages in northeastern Illinois and adjacent states, at selected exceedance probabilities"},{"id":386853,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_01.csv","text":"Table 1","size":"29.2 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 1","linkHelpText":"— U.S. Geological Survey streamgages used in this study in northeastern Illinois and adjacent states"},{"id":386852,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050.pdf","text":"Report","size":"6.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5050"},{"id":324328,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_Links_To_Files.html","text":"Annual maximum peak discharge and associated urban fraction and precipitation values by streamgage","size":"29 kB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2016–5050 Supplemental Graphs and Tables"},{"id":386861,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_tables.xlsx","text":"Tables 1 through 4, 6, 8 and 13 and Table 1–1","size":"673 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5050 Tables"},{"id":386860,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_appendix_table_1.1.csv","text":"Table 1.1","size":"7.58 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 1.1","linkHelpText":"— Skew statistics at streamgages used in the development of the regional skew model in this study in northeastern Illinois"},{"id":386857,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_06.csv","text":"Table 6","size":"345 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 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U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
The jaguar is the largest Neotropical felid and the only extant representative of the genus Panthera in the Americas. In recorded history, the jaguars range has extended from the Southern United States, throughout Mexico, to Central and South America, and they occupy a wide variety of habitats. A previous jaguar genetic study found high historical levels of gene flow among jaguar populations over broad areas but did not include any samples of jaguar from the States of Arizona, United States, or Sonora, Mexico. Arizona and Sonora have been part of the historical distribution of jaguars; however, poaching and habitat fragmentation have limited their distribution until they were declared extinct in the United States and endangered in Sonora. Therefore, a need was apparent to have this northernmost (Arizona/Sonora) jaguar population included in an overall jaguar molecular taxonomy and genetic diversity analyses. In this study, we used molecular genetic markers to examine diversity and taxonomy for jaguars in the Northwestern Jaguar Recovery Unit (NJRU; Sonora, Sinaloa, and Jalisco, Mexico; and southern Arizona and New Mexico, United States) relative to jaguars in other parts of the jaguar range (Central and South America). The objectives of this study were to:
Leader, Arizona Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
325 Biosciences East
Tucson, Arizona 85721
http://www.coopunits.org/Arizona/
Much remains unknown about the genetic status and population connectivity of high-elevation and high-latitude freshwater invertebrates, which often persist near snow and ice masses that are disappearing due to climate change. Here we report on the conservation genetics of the meltwater stonefly Lednia tumana (Ricker) of Montana, USA, a cold-water obligate species. We sequenced 1530 bp of mtDNA from 116 L. tumana individuals representing “historic” (>10 yr old) and 2010 populations. The dominant haplotype was common in both time periods, while the second-most-common haplotype was found only in historic samples, having been lost in the interim. The 2010 populations also showed reduced gene and nucleotide diversity and increased genetic isolation. We found lower genetic diversity in L. tumana compared to two other North American stonefly species, Amphinemura linda (Ricker) and Pteronarcys californica Newport. Our results imply small effective sizes, increased fragmentation, limited gene flow, and loss of genetic variation among contemporary L. tumana populations, which can lead to reduced adaptive capacity and increased extinction risk. This study reinforces concerns that ongoing glacier loss threatens the persistence of L. tumana, and provides baseline data and analysis of how future environmental change could impact populations of similar organisms.
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The study period was divided into six time intervals between 1973 and 2011. Forest land cover was the source of 40% or more of the new urban land in 35 of the 84 ecoregions located within the CONUS. In 11 of these ecoregions this threshold exceeded in every time interval. When the percent of change, forest to urban, was compared to the percent of forest in each ecoregion, 58 ecoregions had a greater percent of change and, in six of those, change occurred in every time interval. Annual rates of forest to urban land cover change of 0.2% or higher occurred in 12 ecoregions at least once and in one ecoregion in all intervals. There were three ecoregions where the above conditions were met for nearly every time interval. Even though only a small number of the ecoregions were heavily impacted by forest loss to urban development within the CONUS, the ecosystem services provided by undeveloped forest land cover need to be quantified more completely to better inform future regional land management.
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