The Rio Grande Cutthroat Trout Oncorhynchus clarkii virginalis (RGCT ) occupies just 12% of its ancestral range. As the southernmost subspecies of Cutthroat Trout, we expect a warming climate to bring additional stressors to RGCT populations, such as increased stream temperatures, reduced streamflows, and increased incidence of wildfire. We developed a Bayesian network (BN ) model using site‐specific data, empirical research, and expert knowledge to estimate the probability of persistence for each of the 121 remaining RGCT conservation populations and to rank the severity of the threats they face. These inputs quantified the genetic risks (e.g., inbreeding risk and hybridization risk), population demographics (disease risk, habitat suitability, and survival), and probability of stochastic disturbances (stream drying risk and wildfire risk) in an uncertain future. We also created stream temperature and base flow discharge models coupled with regionally downscaled climate projections to predict future abiotic conditions at short‐term (2040s) and long‐term (2080s) time horizons. In the absence of active management, we predicted a decrease in the average probability of population persistence from 0.53 (current) to 0.31 (2040s) and 0.26 (2080s). Only 11% of these populations were predicted to have a greater than 75% chance of persisting to the 2080s. Threat of invasion by nonnative trout had the strongest effect on population persistence. Of the 78 populations that are already invaded or lacking complete barriers, 60% were estimated to be extirpated by 2080 and the remainder averaged only a 10% chance of persistence. In contrast, the effects of increased stream temperatures were predicted to affect the future persistence of only 9% of the 121 RGCT populations remaining, as most have been restricted to high‐elevation habitats that are cold enough to buffer against some stream warming. Our BN model provides a framework for evaluating threats and will be useful to guide management actions that are likely to provide the most benefit for long‐term conservation.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10320","usgsCitation":"Zeigler, M.P., Rogers, K., Roberts, J., Todd, A., and Fausch, K., 2019, Predicting persistence of Rio Grande Cutthroat Trout populations in an uncertain future: North American Journal of Fisheries Management, v. 39, no. 5, p. 819-848, https://doi.org/10.1002/nafm.10320.","productDescription":"30 p.","startPage":"819","endPage":"848","ipdsId":"IP-080586","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":376949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.677001953125,\n 33.578014746143985\n ],\n [\n -103.7548828125,\n 33.578014746143985\n ],\n [\n -103.7548828125,\n 38.47079371120379\n ],\n [\n -107.677001953125,\n 38.47079371120379\n ],\n [\n -107.677001953125,\n 33.578014746143985\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-08-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeigler, Mathew P.","contributorId":91006,"corporation":false,"usgs":true,"family":"Zeigler","given":"Mathew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":794698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogers, Kevin B.","contributorId":220104,"corporation":false,"usgs":false,"family":"Rogers","given":"Kevin B.","affiliations":[],"preferred":false,"id":794699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":794673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Andrew atodd@usgs.gov","contributorId":149790,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew","email":"atodd@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":794700,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fausch, Kurt D. 0000-0001-5825-7560","orcid":"https://orcid.org/0000-0001-5825-7560","contributorId":198488,"corporation":false,"usgs":false,"family":"Fausch","given":"Kurt D.","affiliations":[],"preferred":false,"id":794701,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215168,"text":"70215168 - 2019 - Phytoplankton community structure response to groundwater-borne nutrients in the inland bays, Delaware","interactions":[],"lastModifiedDate":"2020-10-09T12:48:32.877319","indexId":"70215168","displayToPublicDate":"2019-08-15T07:46:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Phytoplankton community structure response to groundwater-borne nutrients in the inland bays, Delaware","docAbstract":"To determine the impacts of groundwater-borne nutrients on phytoplankton biomass and community structure, we conducted a series of mesocosm experiments in the Inland Bays of Delaware. Four treatments were tested, including mesocosms coupled directly to submarine groundwater seepage, mesocosms with the addition of pumped submarine groundwater, mesocosms with the addition of phosphate, and control mesocosms with no nutrient addition. We measured chlorophyll a concentrations as a proxy for overall biomass and used genetic sequencing techniques to characterize the phytoplankton community structure. Groundwater carried a high N load to the estuary with NO3- up to 295 µmol l-1 and NH4+ up to 55 µmol l-1. As a result, treatment mesocosms had elevated NO3- and NH4+, while control mesocosms were relatively low in nutrients. In June, the highest chlorophyll a concentrations occurred in mesocosms attached to seepage meters after 3.5 d, with significant differences across all treatments. In August, groundwater-amended mesocosms reached the highest biomass concentrations, which peaked after 3 d. There were significant differences across all treatments, except control and phosphate-amended mesocosms which remained unchanged. Community sequence data showed that species assemblage was also impacted by availability of nutrients, with significant differences in community structure for mesocosms receiving nutrients vs. control mesocosms in both June and August experiments. Harmful algal species proliferated in high nutrient treatments, including Cylindrotheca closterium, Karlodinium veneficum, Nitzschia spp., and Heterocapsa spp. While the general relationship between nutrient supply and biomass production is well known, we demonstrate the role groundwater-borne nutrients and sediment processes play in shaping community structure in estuarine primary producers and in promoting harmful algal blooms.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps13012","usgsCitation":"Torre, D., Coyne, K., Kroeger, K.D., and York, J.K., 2019, Phytoplankton community structure response to groundwater-borne nutrients in the inland bays, Delaware: Marine Ecology Progress Series, v. 624, p. 51-63, https://doi.org/10.3354/meps13012.","productDescription":"12 p.","startPage":"51","endPage":"63","ipdsId":"IP-105254","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":379268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"624","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Torre, Daniel","contributorId":242900,"corporation":false,"usgs":false,"family":"Torre","given":"Daniel","email":"","affiliations":[{"id":48572,"text":"University of Delaware, School of Marine Science and Policy, Lewes, Delaware, 19958, USA","active":true,"usgs":false}],"preferred":false,"id":801059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coyne, Kathryn","contributorId":242901,"corporation":false,"usgs":false,"family":"Coyne","given":"Kathryn","email":"","affiliations":[{"id":48572,"text":"University of Delaware, School of Marine Science and Policy, Lewes, Delaware, 19958, USA","active":true,"usgs":false}],"preferred":false,"id":801060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":801061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"York, Joanna K.","contributorId":140023,"corporation":false,"usgs":false,"family":"York","given":"Joanna","email":"","middleInitial":"K.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":801062,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207595,"text":"70207595 - 2019 - Predicting surf zone injuries along the Delaware coast using a Bayesian network","interactions":[],"lastModifiedDate":"2019-12-30T16:30:44","indexId":"70207595","displayToPublicDate":"2019-08-14T16:28:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Predicting surf zone injuries along the Delaware coast using a Bayesian network","docAbstract":"Personnel at Beebe Healthcare in Lewes, Delaware, collected surf zone injury (SZI) data for eight summer seasons from 2010 through 2017. Data include, but are not limited to, time of injury, gender, age, and activity. More than 2000 SZI events, including 196 spinal injuries and 6 fatalities, occurred at the five most populated beaches along the 25 miles of Atlantic-fronting coast. SZI are predominantly wave related incidents associated with wading (50.1%), body surfing (18.4%), and body boarding (13.3%). The episodic nature of SZI indicate the importance of linking the environmental conditions and human behavior in the surf zone to predict days with high injury rates. Higher order statistics are necessary to effectively consider all associated factors related to SZI. Two Bayesian networks (BN) were constructed to model SZI and predict changes in injury rate (proportion of injuries to bathers) and injury likelihood (probability of at least one injury occurrence) on an hourly basis. The models incorporate environmental data collected by weather stations, wave gauges, and researcher personnel on the beach. The models include prior (e.g., historic) information to infer relationships between provided parameters. Sensitivity analysis determined the most influential parameters related to injury rates were significant wave height, foreshore slope, and water temperature. Exposure parameters (e.g., air temperature) influenced the number of people in the water, resulting in strong correlation between injury likelihood and the related meteorological conditions (variance reduction > 0.4%). Log likelihood ratio (LLR) scores indicate the network predicts SZI likelihood during any specified hour with more skill than prior predictions with the best performing model improving prediction 69.1% of the time (LLR = 69.1%). An alternative BN predicting injury rate performed worse with the prior probability model out predicting the injury rate network (positive LLR = 36.7%). Issues persist with predicting SZI that have an LLR ≪ -1 (< 5% of 2017 injuries) and occur in conditions different than when most other SZI occur. Better understanding of SZI will improve awareness techniques to both educate beachgoers and assist beach patrol decision making during high risk conditions.","language":"English","publisher":"Springer","doi":"10.1007/s11069-019-03697-y","usgsCitation":"Doelp, M., Puleo, J., and Plant, N.G., 2019, Predicting surf zone injuries along the Delaware coast using a Bayesian network: Natural Hazards, v. 98, no. 2, p. 379-401, https://doi.org/10.1007/s11069-019-03697-y.","productDescription":"22 p.","startPage":"379","endPage":"401","ipdsId":"IP-100096","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":370880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"98","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Doelp, Matthew","contributorId":221558,"corporation":false,"usgs":false,"family":"Doelp","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":778659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puleo, Jack A.","contributorId":108287,"corporation":false,"usgs":true,"family":"Puleo","given":"Jack A.","affiliations":[],"preferred":false,"id":778660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":778661,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204836,"text":"70204836 - 2019 - Petrology and geochemistry of migrated hydrocarbons associated with the Albert Formation oil shale in New Brunswick, Canada","interactions":[],"lastModifiedDate":"2019-08-19T15:53:11","indexId":"70204836","displayToPublicDate":"2019-08-14T15:35:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1709,"text":"Fuel","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochemistry of migrated hydrocarbons associated with the Albert Formation oil shale in New Brunswick, Canada","docAbstract":"Samples of the Carboniferous oil shale of the Albert Formation in New Brunswick, Canada, were examined using reflected white and fluorescence light microscopy, Rock-Eval pyrolysis, and ICP-MS (for elements). The presence of fractured filled solid bitumen in contact with, and within the Albert Formation oil shale, particularly in fractures at the right angle to the bedding of oil shale indicated that migrated oil had enough force to overcome the tensil strength of oil shale matrix, and penetrating the oil shale. Migrating fluid also caused thermal alteration of the oil shale matrix, as evident by the presence primary bitumen and oil droplets. The evidence of oil migration included the presence of solid bitumen and crystalline carbonates in contact with the immature oil shale. The low permeability oil shale acted as a seal/aquitard and created a diagenetic ‘front’ by reducing/slowing the advance of migrating oil, resulting in the formation of a reaction zone. Oil droplets were found in this reaction zone. Albertite was the only solid bitumen reported in the Albert Mine area previously. However, the present study found that migrated solid bitumen consisted of both soluble solid bitumen types such as gilsonite and glance-pitch, and non-soluble solid bitumen such as wurtzilite and albertite. The high hydrocarbon yield of oil shales in the Albert Mine area was due to the presence of various solid bitumen types associated with the oil shale and possibly slight thermal alteration that the oil shale experienced when it came in contact with migrating oil. The variation of Th/K ratio and TOC (wt%) indicates that most of oil shales from the Albert Mine area and within the vicinity of oil migration have higher content of TOC (17-25 wt%) as compared to the other Albert oil shales ( TOC=<10 %). The oil shales examined in this study were immature to marginally mature and had a wide range of hydrocarbon yield (2-213 L/Tonne). The highest hydrocarbon yield range (66-199 L/Tonne) was associated with oil shale outcrop samples collected in the Albert Mine itself, where the oil shale was heavily impregnated by migrated solid bitumen.","language":"English","publisher":"Elsevier","doi":"10.1016/j.fuel.2019.115922","usgsCitation":"Goodarzi, F., T. Gentzis, Karacan, C.O., H. Sanei, and Pederson, P., 2019, Petrology and geochemistry of migrated hydrocarbons associated with the Albert Formation oil shale in New Brunswick, Canada: Fuel, v. 256, 115922, 17 p., https://doi.org/10.1016/j.fuel.2019.115922.","productDescription":"115922, 17 p.","ipdsId":"IP-105975","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":366661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"New Brunswick","otherGeospatial":"Alberta Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.7366943359375,\n 45.49094569262732\n ],\n [\n -63.74267578125,\n 45.49094569262732\n ],\n [\n -63.74267578125,\n 46.33175800051563\n ],\n [\n -65.7366943359375,\n 46.33175800051563\n ],\n [\n -65.7366943359375,\n 45.49094569262732\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"256","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goodarzi, F.","contributorId":218201,"corporation":false,"usgs":false,"family":"Goodarzi","given":"F.","email":"","affiliations":[{"id":39778,"text":"FG & Partners Ltd","active":true,"usgs":false}],"preferred":false,"id":768678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"T. 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Sanei","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":768680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pederson, P.K.","contributorId":218204,"corporation":false,"usgs":false,"family":"Pederson","given":"P.K.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":768681,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216452,"text":"70216452 - 2019 - The Islands of Oceania – Political geography, biogeography, and terrestrial ecosystems","interactions":[],"lastModifiedDate":"2020-11-19T12:59:13.764691","indexId":"70216452","displayToPublicDate":"2019-08-14T10:52:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"The Islands of Oceania – Political geography, biogeography, and terrestrial ecosystems","docAbstract":"Humans are dependent upon ecosystems for the production of goods and services necessary for their well-being (Daily, 1997). As the service provider units (SPUs) for these benefits of nature (Anderson et al., 2015), ecosystems need to be managed in a way that maximizes their persistence on the planet. Part of that management effort includes knowing a) what the ecosystem types are, b) where they are located on the landscape and in the seascape, and c) what condition they are in. Mapping of ecosystem occurrences as the SPUs for ecosystems goods and services is therefore an important element of ecosystem accounting, an inherently spatial activity. Maps are also needed of the ecosystem accounting areas within which the accounting is conducted. Standardized maps of ecosystem accounting areas and terrestrial ecosystem SPUs have not previously been available for many islands of the Oceania region. We describe the availability of new island shorelines and ecosystems data for Oceania herein, and encourage consideration and evaluation of the data for ecosystem accounting and other applications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2019.100985","usgsCitation":"Sayre, R., Martin, M., Karagulle, D., Frye, C., Breyer, S., Wright, D., Butler, K., Van Graafeiland, K., and Maynard, S., 2019, The Islands of Oceania – Political geography, biogeography, and terrestrial ecosystems: Ecosystem Services, v. 39, 100985, 7 p., https://doi.org/10.1016/j.ecoser.2019.100985.","productDescription":"100985, 7 p.","ipdsId":"IP-110629","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":380602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 91.0546875,\n -47.27922900257082\n ],\n [\n 178.59375,\n -47.27922900257082\n ],\n [\n 178.59375,\n 21.94304553343818\n ],\n [\n 91.0546875,\n 21.94304553343818\n ],\n [\n 91.0546875,\n -47.27922900257082\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sayre, Roger 0000-0001-6703-7105","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":245011,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":805165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Madeline Thomas 0000-0002-2704-1879","orcid":"https://orcid.org/0000-0002-2704-1879","contributorId":240612,"corporation":false,"usgs":true,"family":"Martin","given":"Madeline Thomas","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":805167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karagulle, Deniz","contributorId":213676,"corporation":false,"usgs":false,"family":"Karagulle","given":"Deniz","email":"","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":805168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frye, Charlie","contributorId":191631,"corporation":false,"usgs":false,"family":"Frye","given":"Charlie","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":805169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breyer, Sean","contributorId":213678,"corporation":false,"usgs":false,"family":"Breyer","given":"Sean","affiliations":[{"id":38832,"text":"Esri","active":true,"usgs":false}],"preferred":false,"id":805170,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Dawn","contributorId":200268,"corporation":false,"usgs":false,"family":"Wright","given":"Dawn","affiliations":[],"preferred":false,"id":805171,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Butler, Kevin","contributorId":200270,"corporation":false,"usgs":false,"family":"Butler","given":"Kevin","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":805172,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Graafeiland, Keith","contributorId":200271,"corporation":false,"usgs":false,"family":"Van Graafeiland","given":"Keith","email":"","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. (ESRI), Redlands, CA","active":true,"usgs":false}],"preferred":false,"id":805166,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Maynard, Simone","contributorId":191652,"corporation":false,"usgs":false,"family":"Maynard","given":"Simone","email":"","affiliations":[],"preferred":false,"id":805173,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70203767,"text":"sir20195057 - 2019 - Paleoliquefaction field reconnaissance in eastern North Carolina—Is there evidence for large magnitude earthquakes between the central Virginia seismic zone and Charleston seismic zone?","interactions":[],"lastModifiedDate":"2019-08-15T09:08:37","indexId":"sir20195057","displayToPublicDate":"2019-08-14T10:45:00","publicationYear":"2019","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":"2019-5057","displayTitle":"Paleoliquefaction Field Reconnaissance in Eastern North Carolina—Is There Evidence for Large Magnitude Earthquakes Between the Central Virginia Seismic Zone and Charleston Seismic Zone?","title":"Paleoliquefaction field reconnaissance in eastern North Carolina—Is there evidence for large magnitude earthquakes between the central Virginia seismic zone and Charleston seismic zone?","docAbstract":"In June 2016, approximately 64 kilometers (km) of riverbank were examined along the Tar and Neuse Rivers near Tarboro and Kinston, North Carolina, for evidence of liquefaction-forming earthquakes. The study area is in the vicinity of the Grainger’s fault zone in eastern North Carolina. The Grainger’s fault zone is a fault zone in the inner Coastal Plain Province that has well-documented Paleogene and younger deformation of Cretaceous to Eocene strata. Low-magnitude earthquakes near the fault zone (for example, magnitude [M] 2.1 in 2013, 13 km south-southwest of Kinston) suggest larger earthquakes may have struck this region in the past. The study area is about equidistant from newly documented Holocene paleoliquefaction sites in the Central Virginia Seismic Zone (CVSZ) and liquefaction sites formed during the 1886 M7.1 Charleston, South Carolina earthquake. The northernmost Holocene paleoliquefaction features associated with the Charleston Seismic Zone (CSZ) are in Southport, North Carolina.
Conditions suitable for liquefaction were identified at 38 sites on both rivers, but only one site was classified as highly susceptible. Stratigraphy consists of Paleozoic gneiss; Cretaceous sandstone/shale; Paleocene mudstone/claystone to Eocene fossiliferous limestone; Quaternary unconsolidated, crossbedded sand and gravel; and Holocene alluvium. Three sets of stratigraphic conditions suitable for liquefaction—unconsolidated source sand beneath capping strata—were identified in detailed examinations at 105 sites: (1) Holocene alluvial sand beneath alluvial silt and clay beds; (2) Quaternary terrace sand beneath beds of silt and clay; and (3) Holocene alluvial sand or Quaternary terrace sand capped by clay-rich Bt soil horizons. Weathered and unconsolidated Cretaceous sand capped by a Bt soil horizon was identified at one site, but the weathered sand is likely too compacted to liquefy readily. One outcrop containing three small sand dikes, and four outcrops of soft-sediment deformation features—mostly load casts—were observed, but none of these features could be conclusively established as seismogenic. A few examples of pseudo-sand-dikes were also identified: sand-filled cypress root casts and pedogenic weathering fronts created the appearance of sand dikes and sills.
A comparable survey in 2015 of 119 km of riverbank exposures in the CVSZ yielded 19 paleoliquefaction sites of probable earthquake origin; these features formed from at least one M~6 earthquake in the past 6,000 years (6 ka). This survey in eastern North Carolina revealed no definitive paleoliquefaction features; earthquakes of sufficient magnitude to produce liquefaction likely have not affected this region during the Holocene.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195057","usgsCitation":"Carter, M.W., and McLaurin, B.T., 2019, Paleoliquefaction field reconnaissance in eastern North Carolina—Is there evidence for large magnitude earthquakes between the Central Virginia Seismic Zone and Charleston Seismic Zone?: U.S. Geological Survey Scientific Investigations Report 2019–5057, 54 p., https://doi.org/10.3133/sir20195057. ","productDescription":"vi, 54 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092950","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":366514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5057/coverthb.jpg"},{"id":366515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5057/sir20195057.pdf","text":"Report","size":"18.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5057"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.7607421875,\n 32.37996146435729\n ],\n [\n -74.50927734375,\n 32.37996146435729\n ],\n [\n -74.50927734375,\n 37.61423141542417\n ],\n [\n -79.7607421875,\n 37.61423141542417\n ],\n [\n -79.7607421875,\n 32.37996146435729\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
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The Big Chino subbasin is located in central-northwest Arizona in the transition zone between the Colorado Plateau and the Basin and Range Province. The controlled source audio-frequency magnetotelluric (CSAMT) geophysical method, a low-impact, non-intrusive, electrical resistance sounding technique, was used to evaluate the subsurface hydrogeology of the southern third of the Big Chino subbasin. The Big Chino subbasin is a northwest-trending, late Tertiary graben bordered by the Big Chino Fault along its northeast flank where there is as much as 1,100 meters of displacement. The main water-bearing stratigraphic unit of the basin is Tertiary alluvial-fill sediment. The Devonian Martin Formation provides water to wells near Drake and the Mississippian Redwall Limestone provides water to wells east of the basin and in the Paulden area.
The purpose of the CSAMT surveys was to improve the conceptual model of the aquifer by constraining the basin geometry and identifying stratigraphic units and their subsurface extents. CSAMT methods were used to map the subsurface along 100 kilometers (62 miles) of survey lines across the southern third of the subbasin. Of 21 survey lines, 14 were west of the town of Paulden and another 7 were east of Paulden. Data were cleaned and prepared for entry into Zonge SCS2D software and then inverted to provide a two-dimensional resistivity profile for each survey line. Final inversion models representing the best fit to measured data were compared to driller’s logs or borehole data where present.
Data from the CSAMT lines west and north of Paulden are consistent with thicker alluvial basin deposits that range from 100 meters thick to a few hundred meters thick. Data from the CSAMT lines east of Paulden are consistent with thinner alluvial and basalt deposits overlying Paleozoic Martin Formation and Redwall Limestone, Tapeats Sandstone, and Precambrian granite and schist.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195082","collaboration":"Prepared in cooperation with the City of Prescott, the Town of Prescott Valley, and Salt River Project","usgsCitation":"Macy, J.P., Gungle, B., and Mason, J.P., 2019, Characterization of Big Chino subbasin hydrogeology near Paulden, Arizona, using controlled source audio-frequency magnetotellursurveys: U.S. Geological Survey Scientific Investigations Report 2019–5082, 39 p., https://doi.org/10.3133/sir20195082.\nic ","productDescription":"vii, 39 p.","numberOfPages":"39","onlineOnly":"Y","ipdsId":"IP-098264","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":366547,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5082/sir20195082.pdf","text":"Report","size":"50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
From fine-scale foraging to broad-scale migration, animal movement is shaped by the distribution of resources. There is mounting evidence, however, that learning and memory also guide movement. Although migratory mammals commonly track resource waves, how resource tracking and memory guide long-distance migration has not been reconciled. We examined these hypotheses using movement data from four populations of migratory mule deer (n = 91). Spatial memory had an extraordinary influence on migration, affecting movement 2–28 times more strongly than tracking spring green-up or autumn snow depth. Importantly, with only an ability to track resources, simulated deer were unable to recreate empirical migratory routes. In contrast, simulated deer with memory of empirical routes used those routes and obtained higher foraging benefits. For migratory terrestrial mammals, spatial memory provides knowledge of where seasonal ranges and migratory routes exist, whereas resource tracking determines when to beneficially move within those areas.
Birds of prey are becoming increasingly common occupants of urbanized settings, but the comparative benefits or detriments they experience in urban environs compared to exurban areas are poorly understood. We examined the reproductive success and phenology of Mississippi Kites (Ictinia mississippiensis) nesting concurrently in urban and exurban areas in west Texas during the 2010–2012 and 2014 breeding seasons. Our objective was to better understand the reproductive advantages or disadvantages that kites may experience by nesting in urban areas rather than exurban areas. We calculated annual productivity, estimated daily survival rates of nests, and estimated hatch dates. Kites produced 0.52 fledglings per urban nesting attempt and 0.33 fledglings per exurban nesting attempt. We found no difference in the mean number of young that fledged from successful urban (1.06) and exurban (1.07) nests, but kites in urban areas had greater nesting success within years than those in exurban areas. Both heat and drought were associated with low productivity and success in both areas, but the urban landscape appears to have provided some buffer to their effects. These factors may have had direct (e.g., exposure) or indirect (e.g., negative influences on prey availability) influences on reproductive success. Counter to previous studies of urban raptors, we found that exurban kites nested significantly earlier than urban kites. This may be linked to differences in environmental conditions and prey availability between the areas. Our results suggest that urban areas provide a reproductive advantage for Mississippi Kites in terms of facilitating an overall higher nesting success, but this does not translate into increased productivity for successful pairs. Further, our data suggest that, although urban areas may buffer species from drought or heat, that buffer can be breached during severe conditions.
The use of data generated from long term monitoring efforts necessitates accurate authoritative source citations of those data to ensure credit for data collected, and accountability for the data quality to enable repeated retrieval of a given data set. Data sets used in published reports and articles are increasingly being considered objects that are required to be published and cited. Aggregating data into open access databases is becoming common and is the focus of the Coordinated Assessment for Salmon and Steelhead project (CA; https://www.pnamp.org/project/coordinated-assessments-for-salmon-and-steelhead; http://www.streamnet.org/data/coordinated-assessments/) and National Marine Fisheries Service, National Oceanic and Atmospheric Administration Salmon Population Summary (SPS; https://www.webapps.nwfsc.noaa.gov/apex/f?p=261:home:0) among others. Guidelines are needed for citing these long-term dynamic data sets that have many contributors. We explore best practices and provide recommendations for including robust metadata attributes within data sets to enable data publication and citation using the CA and SPS data repositories as case studies. From reviewing the current citations possible from the CA and the SPS we recommend at minimum that natural resource monitoring databases contain: metadata to identify organizations that generated the data; contact persons for each organization that contributes data to an aggregated data set; and that metadata be incorporated into databases to enable auto-generated citations that recognize all contributing organizations with time-stamped versions of the data delivered. Beyond those minimums, additional best practice recommendations include this suite of metadata elements that identify a given data set upon citation or publication: author(s); publication date; description of data; file format(s) of data - e.g. tiles, shapefile sets, images, text files; dates data were collected; locations where data were collected; producers/contributors to the data set version cited; date data set was downloaded; original data repository from which the data were obtained; version identifier to note significant change to a data set; and a persistent identifier that can be used to locate that version of the data.
","language":"English","publisher":"Pacific Northwest Aquatic Monitoring Partnership","usgsCitation":"Olson, S.J., Barnas, K.A., Williams, M., Wheaton, C., Banach, M., and Bayer, J.M., 2019, Citing aquatic monitoring data sets: Best practice recommendations for authoritative data citation, 38 p.","productDescription":"38 p.","ipdsId":"IP-096434","costCenters":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":367206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367184,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnamp.org/document/15001"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Olson, Sheryn J. 0000-0002-6751-9013","orcid":"https://orcid.org/0000-0002-6751-9013","contributorId":204736,"corporation":false,"usgs":true,"family":"Olson","given":"Sheryn","email":"","middleInitial":"J.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":770136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnas, Katie A","contributorId":218747,"corporation":false,"usgs":false,"family":"Barnas","given":"Katie","email":"","middleInitial":"A","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":770137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Margaret","contributorId":218748,"corporation":false,"usgs":false,"family":"Williams","given":"Margaret","email":"","affiliations":[{"id":39899,"text":"NOAA - Affiliate","active":true,"usgs":false}],"preferred":false,"id":770138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wheaton, Christopher","contributorId":218749,"corporation":false,"usgs":false,"family":"Wheaton","given":"Christopher","email":"","affiliations":[{"id":39900,"text":"PSMFC","active":true,"usgs":false}],"preferred":false,"id":770139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banach, Michael","contributorId":218750,"corporation":false,"usgs":false,"family":"Banach","given":"Michael","email":"","affiliations":[{"id":39900,"text":"PSMFC","active":true,"usgs":false}],"preferred":false,"id":770141,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bayer, Jennifer M. 0000-0001-9564-3110 jbayer@usgs.gov","orcid":"https://orcid.org/0000-0001-9564-3110","contributorId":3393,"corporation":false,"usgs":true,"family":"Bayer","given":"Jennifer","email":"jbayer@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":770140,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227931,"text":"70227931 - 2019 - Management regime and habitat response influence abundance of regal fritillary (Speyeria idalia) in tallgrass prairie","interactions":[],"lastModifiedDate":"2022-02-03T12:03:54.22088","indexId":"70227931","displayToPublicDate":"2019-08-13T15:14:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Management regime and habitat response influence abundance of regal fritillary (Speyeria idalia ) in tallgrass prairie","title":"Management regime and habitat response influence abundance of regal fritillary (Speyeria idalia) in tallgrass prairie","docAbstract":"The >2,570,000-ha Flint Hills ecoregion of Kansas, USA, harbors the largest remaining contiguous tract of tallgrass prairie in North America, a unique system, as the remainder of North America's tallgrass prairie has succumbed to development and conversion. Consequently, the loss and degradation of tallgrass prairie has reduced populations of many North American prairie-obligate species including the regal fritillary (Speyeria idalia) butterfly. Population abundance and occupied range of regal fritillary have declined >99%, restricting many populations to isolated, remnant patches of tallgrass prairie. Such extensive decline has resulted in consideration of the regal fritillary for protection under the Endangered Species Act. Although it is widely accepted that management practices such as fire, grazing, and haying are necessary to maintain prairie ecosystems, reported responses by regal fritillary to these management regimes have been ambiguous. We tested effects of prescribed fire across short, moderate, and long fire-return intervals as well as grazing and haying management treatments on regal fritillary density. We also tested the relative influence of habitat characteristics created by these management regimes by measuring density of an obligate host plant (Viola spp.) and canopy cover of woody vegetation, grasses, forbs/ferns, bare ground, and litter. We found density was at least 1.6 times greater in sites burned with a moderate fire-return interval vs. sites burned with short and long fire-return intervals. Overall management regardless of fire-return interval did not have an effect on density. Percent cover of grass had the strongest positive association, while percent cover of woody vegetation had the greatest negative effect on density. Our results indicate that patch-burning is a viable and perhaps even ideal management strategy for regal fritillary in tallgrass prairie landscapes. Additionally, these results elucidate the importance of fire, particularly when applied at moderate-return intervals to regal fritillary, and corroborate a growing suite of studies that suggest fire is perhaps not as detrimental to populations of regal fritillary as previously believed.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2845","usgsCitation":"McCullough, K., Albanese, G., Haukos, D.A., Ricketts, A., and Stratton, S., 2019, Management regime and habitat response influence abundance of regal fritillary (Speyeria idalia) in tallgrass prairie: Ecosphere, v. 10, no. 8, e02845, 18 p., https://doi.org/10.1002/ecs2.2845.","productDescription":"e02845, 18 p.","ipdsId":"IP-094927","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2845","text":"Publisher Index Page"},{"id":395312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Flint Hills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.18505859374999,\n 37.020098201368114\n ],\n [\n -96.3720703125,\n 36.96744946416934\n ],\n [\n -95.47119140625,\n 36.932330061503144\n ],\n [\n -95.47119140625,\n 39.80853604144591\n ],\n [\n -97.1630859375,\n 39.80853604144591\n ],\n [\n -97.18505859374999,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"8","noUsgsAuthors":false,"publicationDate":"2019-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"McCullough, K.","contributorId":273122,"corporation":false,"usgs":false,"family":"McCullough","given":"K.","email":"","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albanese, G.","contributorId":67722,"corporation":false,"usgs":true,"family":"Albanese","given":"G.","email":"","affiliations":[],"preferred":false,"id":832759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","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":832594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricketts, A.M.","contributorId":273124,"corporation":false,"usgs":false,"family":"Ricketts","given":"A.M.","email":"","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stratton, S.","contributorId":273125,"corporation":false,"usgs":false,"family":"Stratton","given":"S.","email":"","affiliations":[{"id":56426,"text":"fort riley","active":true,"usgs":false}],"preferred":false,"id":832761,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206000,"text":"70206000 - 2019 - Physicochemical models of effusive rhyolitic eruptions constrained with InSAR and DEM data: A case study of the 2011-2012 Cordon Caulle eruption","interactions":[],"lastModifiedDate":"2019-10-17T07:00:50","indexId":"70206000","displayToPublicDate":"2019-08-13T14:44:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Physicochemical models of effusive rhyolitic eruptions constrained with InSAR and DEM data: A case study of the 2011-2012 Cordon Caulle eruption","docAbstract":"The 9 month long 2011-2012 eruption of Cordon Caulle (Southern Andes, Chile) is the best instrumentally recorded rhyolitic eruption to date and the first time that the effusion of a rhyolitic flow has been observed in detail. We use Interferometric Synthetic Aperture Radar (InSAR), with time-lapse DEMs and numerical models to study the dynamics of coupled magma reservoir deflation and lava effusion. InSAR recorded ~2.2-2.5 m of deflation after the first three days of the eruption, which can be modeled using a spheroidal magma reservoir at a depth of ∼5 km, ∼20 km long, and with a pressure drop of ~20-30 MPa. The source is elongated in the NW-SE direction and its large dimensions imply a large plumbing system spanning neighboring volcanoes and active throughout the eruption, with a slight change halfway through the effusive phase. TanDEM-X DEMs record the extrusion of both the rhyolitic lava flow and the intrusion of a shallow laccolith around the eruptive vent, with a total volume of ~1.2 km3 DRE. The laccolith was emplaced during the first month of the eruption, during both the eruption explosive and effusive stages. Both the reservoir pressure drop and the extruded volume time series follow quasi-exponential trends, and can be explained by a model that couples the reservoir pres- sure decrease, time- and pressured ependent variations in the magma properties inside of the reservoir, and conduit flow. This model predicts both the temporal evolution and amplitude of both time series, and a magma compressibility of ∼10^−10 Pa−1, half the compressibility of the magma of the sub-Plinian explosive phase. Further, we estimate that the reservoir contained 1-3 wt.% dissolved H2O at the onset of lava effusion, with no exsolved CO2 and H2O in the reservoir throughout the eruption. This is in accord with a magma that was significantly degassed after the explosive phase. These remaining volatiles might have been responsible for magma fragmentation, consistent with the hybrid explosive and effusive style observed during the waning of the eruption.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2019.115736","usgsCitation":"Delgado, F., Julia Kubanek, Anderson, K.R., Paul Lundgren, and Pritchard, M.E., 2019, Physicochemical models of effusive rhyolitic eruptions constrained with InSAR and DEM data: A case study of the 2011-2012 Cordon Caulle eruption: Earth and Planetary Science Letters, v. 524, p. 1-14, https://doi.org/10.1016/j.epsl.2019.115736.","productDescription":"115736, 14p.","startPage":"1","endPage":"14","ipdsId":"IP-102193","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2019.115736","text":"Publisher Index Page"},{"id":368337,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0012821X19304285"},{"id":368348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"Cordón Caulle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.59765625,\n -42.779275360241904\n ],\n [\n -71.69677734375,\n -42.779275360241904\n ],\n [\n -71.69677734375,\n -41.4262531950727\n ],\n [\n -72.59765625,\n -41.4262531950727\n ],\n [\n -72.59765625,\n -42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"524","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Delgado, Francisco","contributorId":219817,"corporation":false,"usgs":false,"family":"Delgado","given":"Francisco","email":"","affiliations":[{"id":40075,"text":"Institute de Physique du Globe de Paris","active":true,"usgs":false}],"preferred":false,"id":773252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Julia Kubanek","contributorId":219818,"corporation":false,"usgs":false,"family":"Julia Kubanek","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":773253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":773251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paul Lundgren","contributorId":219819,"corporation":false,"usgs":false,"family":"Paul Lundgren","affiliations":[{"id":32904,"text":"Jet Propulsion Lab, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":773254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pritchard, Matthew E.","contributorId":219820,"corporation":false,"usgs":false,"family":"Pritchard","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":773255,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208120,"text":"70208120 - 2019 - Global positioning system tracking devices can decrease Greater Sage-Grouse survival","interactions":[],"lastModifiedDate":"2020-01-29T16:27:32","indexId":"70208120","displayToPublicDate":"2019-08-13T13:06:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Global positioning system tracking devices can decrease Greater Sage-Grouse survival","docAbstract":"Reliable demographic estimates hinge on the assumption that marking animals does not alter their behavior, reproduction, or survival. Violations can bias inference and are especially egregious for species of high conservation concern. Global positioning system (GPS) devices represent a recent technological advancement that has contributed greatly to avian ecological studies compared with traditionally used very high frequency (VHF) radio transmitters, but may affect demographic rates differently than VHF transmitters. We compared survival between VHF (necklace attachment) and GPS (rump-mounted attachment) devices from >1,100 Greater Sage-Grouse (Centrocercus urophasianus), a species of high conservation concern, across multiple populations within California and Nevada. We found lower survival for GPS-marked compared to VHF-marked sage-grouse across most sex, age, and seasonal comparisons. Estimates of annual survival for GPS-marked sage-grouse were 0.55–0.86 times that of VHF-marked birds with considerable variation among sex and age classes. Differences in survival could be attributed to features associated with GPS devices, including greater weight, position of attachment (e.g., rump-mount harness), and a semi-reflective solar panel. In a post hoc analysis, we evaluated additive and interactive effects between device type (GPS vs. VHF) and transmitter mass as a proportion of body mass (PBM). While the device type effect alone was the best model, the PBM interaction also had support. For GPS devices, survival decreased with increasing PBM, whereas PBM effects were not found for VHF. We attributed differences in PBM effect to placement of transmitters on sage-grouse, as weight of GPS devices was positioned rearward. This information can help managers and researchers weigh costs and benefits of GPS-based monitoring. Our results indicate demographic data collected from GPS devices should be interpreted with caution, and use of these devices should be tailored to specific ecological questions. Future research aimed at investigating behavioral impacts and GPS designs that reduce adverse impacts on survival would be beneficial.
","language":"English","publisher":"American Ornithological Society","doi":"10.1093/condor/duz032","usgsCitation":"Severson, J.P., Coates, P.S., Prochazka, B.G., Ricca, M.A., Casazza, M.L., and Delahunty, D.J., 2019, Global positioning system tracking devices can decrease Greater Sage-Grouse survival: The Condor, v. 121, no. 3, duz032, 15 p., https://doi.org/10.1093/condor/duz032.","productDescription":"duz032, 15 p.","ipdsId":"IP-106346","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":460307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz032","text":"Publisher Index Page"},{"id":371649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, 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Here, we provide an update on the state of the knowledge of OHC, and also include mercury, exposure and/or associated effects in key Arctic marine and terrestrial mammal and bird species as well as in fish by reviewing the literature published since the last AMAP assessment in 2010. We aimed at updating the knowledge of how single but also combined health effects are or can be associated to the exposure to single compounds or mixtures of OHCs. We also focussed on assessing both potential individual as well as population health impacts using population-specific exposure data post 2000. We have identified quantifiable effects on vitamin metabolism, immune functioning, thyroid and steroid hormone balances, oxidative stress, tissue pathology, and reproduction. As with the previous assessment, a wealth of documentation is available for biological effects in marine mammals and seabirds, and sentinel species such as the sledge dog and Arctic fox, but information for terrestrial vertebrates and fish remain scarce. While hormones and vitamins are thoroughly studied, oxidative stress, immunotoxic and reproductive effects need further investigation. Depending on the species and population, some OHCs and mercury tissue contaminant burdens post 2000 were observed to be high enough to exceed putative risk threshold levels that have been previously estimated for non-target species or populations outside the Arctic. In this assessment, we made use of risk quotient calculations to summarize the cumulative effects of different OHC classes and mercury for which critical body burdens can be estimated for wildlife across the Arctic. As our ultimate goal is to better predict or estimate the effects of OHCs and mercury in Arctic wildlife at the individual, population and ecosystem level, there remain numerous knowledge gaps on the biological effects of exposure in Arctic biota. These knowledge gaps include the establishment of concentration thresholds for individual compounds as well as for realistic cocktail mixtures that in fact indicate biologically relevant, and not statistically determined, health effects for specific species and subpopulations. Finally, we provide future perspectives on understanding Arctic wildlife health using new in vivo, in vitro, and in silico techniques, and provide case studies on multiple stressors to show that future assessments would benefit from significant efforts to integrate human health, wildlife ecology and retrospective and forecasting aspects into assessing the biological effects of OHC and mercury exposure in Arctic wildlife and fish.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.133792","usgsCitation":"Dietz, R., Letcher, R.J., Desforges, J., Eulaers, I., Sonne, C., Wilson, S., Andersen-Ranberg, E., Basu, N., Barst, B.D., Bustnes, J.O., Bytingsvik, J., Ciesielski, T.M., Drevnick, P.E., Gabrielsen, G.W., Haarr, A., Hylland, K., Jenssen, B.M., Levin, M., McKinney, M.A., Norregaard, R.D., Pedersen, K.E., Provencher, J., Styrishave, B., Tartu, S., Aars, J., Ackerman, J., Rosing-Asvid, A., Barrett, R., Bignert, A., Born, E.W., Branigan, M., Braune, B., Bryan, C.E., Dam, M., Eagles-Smith, C.A., Evans, M.S., Evans, T., Fisk, A.T., Gamberg, M., Gustavson, K., Hartman, C.A., Helander, B., Herzog, M.P., Hoekstra, P.F., Houde, M., Hoydal, K., Jackson, A., Kucklick, J., Lie, E., Loseto, L., Mallory, M.L., Miljeteig, C., Mosbech, A., Muir, D.C., Nielsen, S.T., Peacock, E., Pedro, S., Peterson, S.H., Polder, A., Riget, F.F., Roach, P., Saunes, H., Sinding, M.S., Skaare, J.U., Sondergaard, J., Stenson, G., Stern, G., Treu, G., Schuur, S.S., and Vikingsson, G., 2019, Current state of knowledge on biological effects from contaminants on arctic wildlife and fish: Science of the Total Environment, v. 696, 133792, 40 p., https://doi.org/10.1016/j.scitotenv.2019.133792.","productDescription":"133792, 40 p.","ipdsId":"IP-107367","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Biology, Norwegian University of Life Sciences","active":true,"usgs":false}],"preferred":false,"id":769112,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Riget, Frank F.","contributorId":218378,"corporation":false,"usgs":false,"family":"Riget","given":"Frank","email":"","middleInitial":"F.","affiliations":[{"id":39808,"text":"Aarhus University, Arctic Research Centre (ARC), Department of Bioscience","active":true,"usgs":false}],"preferred":false,"id":769113,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Roach, Pat","contributorId":218379,"corporation":false,"usgs":false,"family":"Roach","given":"Pat","email":"","affiliations":[{"id":39832,"text":"Aboriginal Affairs and Northern Development Canada","active":true,"usgs":false}],"preferred":false,"id":769114,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Saunes, 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for Zoo and Wildlife Research","active":true,"usgs":false}],"preferred":false,"id":769121,"contributorType":{"id":1,"text":"Authors"},"rank":68},{"text":"Schuur, Stacy S.","contributorId":218386,"corporation":false,"usgs":false,"family":"Schuur","given":"Stacy","email":"","middleInitial":"S.","affiliations":[{"id":39825,"text":"National Institute of Standards and Technology, Chemical Sciences Division, Hollings Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":769122,"contributorType":{"id":1,"text":"Authors"},"rank":69},{"text":"Vikingsson, Gisli","contributorId":218387,"corporation":false,"usgs":false,"family":"Vikingsson","given":"Gisli","email":"","affiliations":[{"id":39837,"text":"Marine and Freshwater Research Institute","active":true,"usgs":false}],"preferred":false,"id":769123,"contributorType":{"id":1,"text":"Authors"},"rank":70}]}} ,{"id":70204903,"text":"70204903 - 2019 - Adding invasive species bio-surveillance to the U.S. Geological Survey streamgage network","interactions":[],"lastModifiedDate":"2019-08-26T09:33:57","indexId":"70204903","displayToPublicDate":"2019-08-13T11:13:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Adding invasive species bio-surveillance to the U.S. Geological Survey streamgage network","docAbstract":"The costs of invasive species in the United States alone are estimated to exceed US$100 billion per year so a critical tactic in minimizing the costs of invasive species is the development of effective, early-detection systems. To this end, we evaluated the efficacy of adding environmental (e)DNA surveillance to the U.S. Geological Survey (USGS) streamgage network, which consists of > 8,200 streamgages nationwide systemically visited by USGS hydrologic technicians. Incorporating strategic eDNA sample collection during routine streamgage visits could provide early detection surveillance of aquatic invasive species with minimal additional cost. For this evaluation, USGS hydrologic technicians collected monthly eDNA water samples, May – September 2018, from streamgages downstream of reservoirs in the Columbia River Basin thought to be vulnerable to invasive dreissenid mussel (Dreissenidae spp.) establishment. We tested water samples for dreissenid mussel DNA and also for kokanee (Oncorhynchus nerka) and yellow perch (Perca flavescens) DNA; the two fishes were used to assess if streamgages are adequately located to provide early-detection eDNA surveillance of taxa known to be present in upstream reservoirs. No Columbia River Basin streamgage samples met our criteria for being scored as positive for dreissenid DNA. We did detect kokanee and yellow perch DNA at all streamgages downstream of reservoirs where these species are known to occur. Field collection, laboratory analyses, and personnel time required for collection of four eDNA samples at a streamgage site cost US$500 -US$600 (net). Given these results, incorporating eDNA biosurveillance into routine streamgage visits might decrease costs associated with an invasion since early detection maximizes the potential for eradication, containment, and mitigation.
","language":"English","publisher":"ESA","doi":"10.1002/ecs2.2843","usgsCitation":"Sepulveda, A.J., Schmidt, C., Amberg, J., Hutchins, P.R., Stratton, C., Mebane, C.A., Laramie, M., and Pilliod, D.S., 2019, Adding invasive species bio-surveillance to the U.S. Geological Survey streamgage network: Ecosphere, v. 10, no. 8, e02843, 17 p., https://doi.org/10.1002/ecs2.2843.","productDescription":"e02843, 17 p.","ipdsId":"IP-106819","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":460309,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2843","text":"Publisher Index Page"},{"id":366852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.33203125,\n 48.980216985374994\n ],\n [\n -115.927734375,\n 33.063924198120645\n ],\n [\n -105.64453124999999,\n 31.353636941500987\n ],\n [\n -93.42773437499999,\n 45.02695045318546\n ],\n [\n -93.42773437499999,\n 48.69096039092549\n ],\n [\n -125.33203125,\n 48.980216985374994\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-13","publicationStatus":"PW","contributors":{"authors":[{"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":768956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Christian 0000-0001-6842-0392","orcid":"https://orcid.org/0000-0001-6842-0392","contributorId":217710,"corporation":false,"usgs":true,"family":"Schmidt","given":"Christian","email":"","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":768958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutchins, Patrick R. 0000-0001-5232-0821 phutchins@usgs.gov","orcid":"https://orcid.org/0000-0001-5232-0821","contributorId":198337,"corporation":false,"usgs":true,"family":"Hutchins","given":"Patrick","email":"phutchins@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":768959,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stratton, Christian","contributorId":217711,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":768960,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768961,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768962,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768963,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204877,"text":"70204877 - 2019 - A generically parameterized model of lake eutrophication (GPLake) that links field-, lab- and model-based knowledge","interactions":[],"lastModifiedDate":"2019-08-21T10:31:44","indexId":"70204877","displayToPublicDate":"2019-08-13T10:22:39","publicationYear":"2019","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":"A generically parameterized model of lake eutrophication (GPLake) that links field-, lab- and model-based knowledge","docAbstract":"Worldwide, eutrophication is threatening lake ecosystems. To support lake management numerous eutrophication models have been developed. Diverse research questions in a wide range of lake ecosystems are addressed by these models. The established models are based on three key approaches: the empirical approach that employs field surveys, the theoretical approach in which models based on first principles are tested against lab experiments, and the process-based approach that uses parameters and functions representing detailed biogeochemical processes. These approaches have led to an accumulation of field-, lab- and model-based knowledge, respectively. Linking these sources of knowledge would benefit lake management by exploiting complementary information; however, the development of a simple tool that links these approaches was hampered by their large differences in scale and complexity. Here we propose a Generically Parameterized Lake eutrophication model (GPLake) that links field-, lab- and model-based knowledge and can be used to make a first diagnosis of lake water quality. We derived GPLake from consumer-resource theory by the principle that lacustrine phytoplankton is typically limited by two resources: nutrients and light. These limitations are captured in two generic parameters that shape the nutrient to chlorophyll-a relations. Next, we parameterized GPLake, using knowledge from empirical, theoretical, and process-based approaches. GPLake generic parameters were found to scale in a comparable manner across data sources. Finally, we show that GPLake can be applied as a simple tool that provides lake managers with a first diagnosis of the limiting factor and lake water quality, using only the parameters for lake depth, residence time and current nutrient loading. With this first-order assessment, lake managers can easily assess measures such as reducing nutrient load, decreasing residence time or changing depth before spending money on field-, lab- or model- experiments to support lake management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.133887","usgsCitation":"Chang, M., Teurlincx, S., DeAngelis, D.L., Janse, J.H., Troost, T.A., van Wijk, D., Mooij, W.M., and Janssen, A., 2019, A generically parameterized model of lake eutrophication (GPLake) that links field-, lab- and model-based knowledge: Science of the Total Environment, v. 695, 133887, 11 p., https://doi.org/10.1016/j.scitotenv.2019.133887.","productDescription":"133887, 11 p.","ipdsId":"IP-104765","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.133887","text":"Publisher Index Page"},{"id":366781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"695","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chang, Manqi","contributorId":218274,"corporation":false,"usgs":false,"family":"Chang","given":"Manqi","email":"","affiliations":[],"preferred":false,"id":768853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teurlincx, Sven","contributorId":218275,"corporation":false,"usgs":false,"family":"Teurlincx","given":"Sven","email":"","affiliations":[],"preferred":false,"id":768854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":768855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Janse, Jan H.","contributorId":215555,"corporation":false,"usgs":false,"family":"Janse","given":"Jan","email":"","middleInitial":"H.","affiliations":[{"id":39277,"text":"Dept. of Aquatic Ecology, Netherlands Institute of Ecology, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":768856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Troost, Tineke A.","contributorId":218276,"corporation":false,"usgs":false,"family":"Troost","given":"Tineke","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768857,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Wijk, Dianneke","contributorId":215557,"corporation":false,"usgs":false,"family":"van Wijk","given":"Dianneke","email":"","affiliations":[{"id":39277,"text":"Dept. of Aquatic Ecology, Netherlands Institute of Ecology, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":768858,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mooij, Wolf M.","contributorId":215556,"corporation":false,"usgs":false,"family":"Mooij","given":"Wolf","email":"","middleInitial":"M.","affiliations":[{"id":39277,"text":"Dept. of Aquatic Ecology, Netherlands Institute of Ecology, the Netherlands","active":true,"usgs":false}],"preferred":false,"id":768859,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Janssen, Annette B. G.","contributorId":200076,"corporation":false,"usgs":false,"family":"Janssen","given":"Annette B. G.","affiliations":[],"preferred":false,"id":768860,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204724,"text":"70204724 - 2019 - Tracking phosphorus and sediment sources and transport from fields and channels in Great Lakes Restoration Initiative priority watersheds","interactions":[],"lastModifiedDate":"2019-08-13T08:21:20","indexId":"70204724","displayToPublicDate":"2019-08-13T08:19:00","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Tracking phosphorus and sediment sources and transport from fields and channels in Great Lakes Restoration Initiative priority watersheds","docAbstract":"A multi-agency, integrated series of studies were initiated in 2017 under the Great Lakes Restoration Initiative (GLRI) by the U.S. Geological Survey, U.S. Forest Service, and the University of Minnesota to quantify the source, downstream travel time, and storage of particulate-bound phosphorus and sediment in agricultural tributaries to the Great Lakes. Of particular interest are contributions at the edge of field, channels, and riparian corridors. Results will be used to help identify upland and stream conservation practices that may reduce phosphorus and sediment inputs to the Great Lakes. The two study watersheds are the 50 km2 Black Creek in the Maumee River basin (Lake Erie) and the 90 km2 Plum Creek in the Lower Fox River basin (Lake Michigan). As part of other GLRI work, Black Creek and Plum Creek have existing, nested, edge-of-field studies in addition to phosphorus and sediment monitoring stations along their mainstems.\n\nSediment-source tracking provides a direct method to quantify suspended sediment, and consequently phosphorus, sources by identifying a minimal set of properties (or fingerprint) that uniquely defines each source of sediment in the basin. This fingerprint can then be used to apportion sources of sediment from agricultural fields as well as other uplands including developed areas, forests, and pastures. These methods can also help distinguish sediment from ditches, ravines and eroding slopes, and streambanks. Multiple tracking methods are being used and adapted for best results in these watersheds, including a suite of trace elements for overall source apportionment in addition to short-term fallout radionuclides beryllium-7 (7Be) and lead-210 (210Pb) for high-flow event-based transport on fields and in stream channels. Tile drain connectivity to the surface is also of interest, especially in the Black Creek watershed.\n\nPreliminary results from the overall source apportionment from analyses of streambed sediment and monthly suspended sediment in Plum Creek indicate that the proportion attributed to different land cover varied by season and events. Further data analyses are being conducted for examining event-based pathways on individual fields, while most basin-wide sampling was monthly. Results from both watersheds will help describe the variations in transport of particulate-bound phosphorus across both steep and gentle landscapes representative of the Great Lakes basin. (this is from IP-101450)","language":"English","publisher":"SEDHYD","collaboration":"US Forest Service, University of Minnesota, EPA","usgsCitation":"Williamson, T.N., Fitzpatrick, F.A., Karwan, D.L., Kolka, R.K., Dobrowolski, E.G., Blount, J.D., and Pawlowski, E.D., 2019, Tracking phosphorus and sediment sources and transport from fields and channels in Great Lakes Restoration Initiative priority watersheds, 13 p.","productDescription":"13 p.","ipdsId":"IP-104838","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":366492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366475,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_program&action=view.php&id=79&file=1/79.pdf"}],"country":"United States, Canada","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.46093749999999,\n 41.11246878918088\n ],\n [\n -75.5859375,\n 41.11246878918088\n ],\n [\n -75.5859375,\n 48.86471476180277\n ],\n [\n -92.46093749999999,\n 48.86471476180277\n ],\n [\n -92.46093749999999,\n 41.11246878918088\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":196543,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":768190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":768191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolka, Randall K.","contributorId":16150,"corporation":false,"usgs":false,"family":"Kolka","given":"Randall","email":"","middleInitial":"K.","affiliations":[{"id":13259,"text":"USDA Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":768192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobrowolski, Edward G. 0000-0001-9840-4609 edobrowo@usgs.gov","orcid":"https://orcid.org/0000-0001-9840-4609","contributorId":5555,"corporation":false,"usgs":true,"family":"Dobrowolski","given":"Edward","email":"edobrowo@usgs.gov","middleInitial":"G.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":768194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pawlowski, Ethan D.","contributorId":218062,"corporation":false,"usgs":false,"family":"Pawlowski","given":"Ethan","email":"","middleInitial":"D.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":768195,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205307,"text":"70205307 - 2019 - Epidemic growth rates and host movement patterns shape management performance for pathogen spillover at the wildlife-livestock interface","interactions":[],"lastModifiedDate":"2019-09-13T14:38:35","indexId":"70205307","displayToPublicDate":"2019-08-12T14:35:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3047,"text":"Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Epidemic growth rates and host movement patterns shape management performance for pathogen spillover at the wildlife-livestock interface","docAbstract":"Managing pathogen spillover at the wildlife–livestock interface is a key step towards improving global animal health, food security and wildlife conservation. However, predicting the effectiveness of management actions across host–pathogen systems with different life histories is an on-going challenge since data on intervention effectiveness are expensive to collect and results are system-specific. We developed a simulation model to explore how the efficacies of different management strategies vary according to host movement patterns and epidemic growth rates. The model suggested that fast-growing, fast-moving epidemics like avian influenza were best-managed with actions like biosecurity or containment, which limited and localized overall spillover risk. For fast-growing, slower-moving diseases like foot-and-mouth disease, depopulation or prophylactic vaccination were competitive management options. Many actions performed competitively when epidemics grew slowly and host movements were limited, and how management efficacy related to epidemic growth rate or host movement propensity depended on what objective was used to evaluate management performance. This framework offers one means of classifying and prioritizing responses to novel pathogen spillover threats, and evaluating current management actions for pathogens emerging at the wildlife–livestock interface.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2018.0343","usgsCitation":"Manlove, K., Sam, L., Borremans, B., Cassirer, E.F., Miller, R.S., Pepin, K., Besser, T.E., and Cross, P., 2019, Epidemic growth rates and host movement patterns shape management performance for pathogen spillover at the wildlife-livestock interface: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, v. 374, no. 1782, 20180343, https://doi.org/10.1098/rstb.2018.0343.","productDescription":"20180343","ipdsId":"IP-103606","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6711312","text":"Publisher Index Page"},{"id":367417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"374","issue":"1782","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Manlove, K.R. 0000-0002-7200-5236","orcid":"https://orcid.org/0000-0002-7200-5236","contributorId":218981,"corporation":false,"usgs":false,"family":"Manlove","given":"K.R.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":770820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sam, L.","contributorId":218982,"corporation":false,"usgs":false,"family":"Sam","given":"L.","email":"","affiliations":[],"preferred":false,"id":770821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borremans, B. 0000-0002-7779-4107","orcid":"https://orcid.org/0000-0002-7779-4107","contributorId":218983,"corporation":false,"usgs":false,"family":"Borremans","given":"B.","email":"","affiliations":[{"id":12763,"text":"University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":770822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cassirer, E. Frances","contributorId":198303,"corporation":false,"usgs":false,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":770826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, R. S.","contributorId":172739,"corporation":false,"usgs":false,"family":"Miller","given":"R.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":770823,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pepin, K. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":218984,"corporation":false,"usgs":false,"family":"Pepin","given":"K.","email":"","affiliations":[{"id":39647,"text":"USDA-APHIS","active":true,"usgs":false}],"preferred":false,"id":770824,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Besser, T. E. 0000-0003-0449-1989","orcid":"https://orcid.org/0000-0003-0449-1989","contributorId":215110,"corporation":false,"usgs":false,"family":"Besser","given":"T.","email":"","middleInitial":"E.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":770825,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Paul","contributorId":218980,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":770819,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204649,"text":"pp1814E - 2019 - Soil mineralogy and geochemistry along a north-south transect in Alaska and the relation to source-rock terrane","interactions":[{"subject":{"id":70204649,"text":"pp1814E - 2019 - Soil mineralogy and geochemistry along a north-south transect in Alaska and the relation to source-rock terrane","indexId":"pp1814E","publicationYear":"2019","noYear":false,"chapter":"E","displayTitle":"Soil Mineralogy and Geochemistry Along a North-South Transect in Alaska and the Relation to Source-Rock Terrane","title":"Soil mineralogy and geochemistry along a north-south transect in Alaska and the relation to source-rock terrane"},"predicate":"IS_PART_OF","object":{"id":70158938,"text":"pp1814 - 2015 - Studies by the U.S. Geological Survey in Alaska, Volume 15","indexId":"pp1814","publicationYear":"2015","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, Volume 15"},"id":1}],"isPartOf":{"id":70158938,"text":"pp1814 - 2015 - Studies by the U.S. Geological Survey in Alaska, Volume 15","indexId":"pp1814","publicationYear":"2015","noYear":false,"title":"Studies by the U.S. Geological Survey in Alaska, Volume 15"},"lastModifiedDate":"2019-08-13T14:05:15","indexId":"pp1814E","displayToPublicDate":"2019-08-12T13:50:50","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1814","chapter":"E","displayTitle":"Soil Mineralogy and Geochemistry Along a North-South Transect in Alaska and the Relation to Source-Rock Terrane","title":"Soil mineralogy and geochemistry along a north-south transect in Alaska and the relation to source-rock terrane","docAbstract":"Soils collected along a predominately north-south transect in Alaska were used to evaluate regional differences in the soil mineralogy and geochemistry in the context of a geotectonic framework for Alaska. The approximately 1,395-kilometer-long transect followed the Dalton, Elliott, and Richardson Highways from near Prudhoe Bay to Valdez. Sites were selected with a site spacing of approximately 10 road-kilometers; soil was sampled by soil horizon at 175 sites. Terrane boundaries were estimated from digitized versions of the lithotectonic terrane map of Alaska (Silberling and others, 1994). Terrane assignments for each site were based on the site’s distance along the transect. We also present data for 15 minerals or mineral groups and 58 elements, as well as total, inorganic, and organic carbon. Quantitative mineralogy of the mineral-soil horizons was characterized by X-ray diffraction. Elemental contents were determined by a combination of inductively coupled plasma-atomic emission spectrometry (ICP-AES) and inductively coupled plasma-mass spectrometry (ICP-MS) analysis following a multi-acid or sodium-sinter decomposition of the samples. Total carbon and carbonate carbon contents were determined using an automated carbon analyzer and coulometric titration, respectively; organic carbon content was obtained by calculating the difference between total and carbonate carbon. Mercury and selenium were analyzed using cold-vapor atomic absorption (CV-AA), and hydride-generation atomic absorption spectrometry (HG-AAS), respectively. The mineralogical and geochemical patterns from these soils are used to assess the relation between soil characteristics and the geology of surrounding terranes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1814E","usgsCitation":"Wang, B., Hults, C., Eberl, D., Woodruff, L., Cannon, W., and Gough, L., 2019, Soil mineralogy and geochemistry along a north-south transect in Alaska and the relation to source-rock terrane in Dumoulin, J.A., ed., Studies by the U.S. Geological Survey in Alaska, vol. 15: U.S. Geological Survey Professional Paper 1814–E, 27 p., https://doi.org/10.3133/pp1814E.","productDescription":"Report: v, 27 p.; 4 Appendixes","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092422","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":366450,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1814/e/pp1814e_appendix1.pdf","text":"Appendix 1","size":"964 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1814 Chapter E Appendix 1","linkHelpText":" — Summary Statisitics for Chemical Analyses of Soil Samples from the North-South Transect of Alaska"},{"id":366449,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1814/e/pp1814e.pdf","text":"Report","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1814 Chapter E"},{"id":366448,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1814/e/coverthb.jpg"},{"id":366451,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1814/e/pp1814e_appendix_2.pdf","text":"Appendix 2","size":"777 KB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1814 Chapter E Appendix 2","linkHelpText":" — Plots of mineral contents in soil samples from the upper and lower mineral soil horizons at sites along the north-south transect of 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Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
The interpretation of geophysical survey results to answer hydrologic, engineering, and geologic questions is critical to diverse problems for management of water, energy, and mineral resources. Although geophysical images provide valuable qualitative insight into subsurface architecture and conditions, translating geophysical images into quantitative information (e.g., saturation, concentration, and hydraulic properties) often involves substantial nonuniqueness and uncertainty owing to the limited resolution of geophysical imaging and uncertainty in petrophysical relations. We have developed a machine-learning approach to address these challenges in the context of a field-based investigation to map zones where a hydrocarbon plume was discharging to surface water at the National Crude Oil Spill Fate and Natural Attenuation Research Site in Bemidji, Minnesota, USA. The two-step approach combines multiple types of geophysical and direct information and effectively bypasses inversion and its associated assumptions. Integrating multifrequency electromagnetic induction, ground-penetrating radar, and fluid-sampling data, we first identify discharge zones and second estimate specific conductance versus depth. Compared with conventional inversion results, the machine-learning results (1) directly address the study objectives (delineating the discharge zones); (2) better extract depth-dependent information from the data, for which sensitivity diminishes rapidly with depth; and (3) quantify the uncertainty of the predictions (i.e., discharge versus nondischarge zones), rather than the uncertainty of the geophysical estimates (i.e., the standard error of estimation for the logarithm of electrical conductivity).
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2018-0690.1","usgsCitation":"Terry, N., Day-Lewis, F.D., Lane, J., Trost, J.J., and Bekins, B.A., 2019, Geophysical mapping of plume discharge to surface water at a crude oil spill site: Inversion versus machine learning: Geophysics, v. 84, no. 5, p. EN67-EN80, https://doi.org/10.1190/geo2018-0690.1.","productDescription":"14 p.","startPage":"EN67","endPage":"EN80","ipdsId":"IP-105187","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":370676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","otherGeospatial":"National Crude Oil Spill Fate and Natural Attenuation Research Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.0820,\n 47.5775\n ],\n [\n -95.0920,\n 47.5775\n ],\n [\n -95.0920,\n 47.5715\n ],\n [\n -95.0820,\n 47.5715\n ],\n [\n -95.0820,\n 47.5775\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":778454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":778455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":778456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":778457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":778458,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204911,"text":"70204911 - 2019 - Immediate effects of hurricanes on a diverse coral/mangrove ecosystem in the U.S. Virgin Islands and the potential for recovery","interactions":[],"lastModifiedDate":"2019-08-23T11:29:24","indexId":"70204911","displayToPublicDate":"2019-08-12T11:25:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Immediate effects of hurricanes on a diverse coral/mangrove ecosystem in the U.S. Virgin Islands and the potential for recovery","docAbstract":"Hurricanes Irma and Maria, two powerful storms that hit the U.S. Virgin Islands less than 2 weeks apart in September 2017, caused extensive damage to the natural resources on St. John. Damage was particularly severe in a unique mangrove/coral ecosystem in three bays within Virgin Islands Coral Reef National Monument, a National Park Service marine protected area. Many Red Mangrove (Rhizophora mangle) trees were uprooted and tossed into the sea, and the prop roots of others were stripped of corals, sponges and other marine life. No other mangrove area in the Caribbean is known to have so many scleractinian corals (about 30 species before the storms). Although many corals were overturned or buried in rubble, colonies of most of the species, including four that are listed as threatened under the U.S. Endangered Species Act, survived. Recovery of this ecosystem will depend on Red Mangrove propagules becoming established and producing prop roots to support rich marine life along with a canopy to provide the shade that was critical to the biodiversity that was present before the storms. Unlike in many situations where major disturbances reduce coral cover, the substrate that must be restored for full recovery to occur is a living substrate—the prop roots of the mangroves. Larvae of corals and sponges will need to recruit on to the roots. Future storms could hinder this process.
","language":"English","publisher":"MDPI - Molecular Diversity Preservation International","doi":"10.3390/d11080130","usgsCitation":"Rogers, C., 2019, Immediate effects of hurricanes on a diverse coral/mangrove ecosystem in the U.S. Virgin Islands and the potential for recovery: Diversity, v. 11, no. 8, 130, 10 p., https://doi.org/10.3390/d11080130.","productDescription":"130, 10 p.","ipdsId":"IP-102132","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460313,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d11080130","text":"Publisher Index Page"},{"id":366855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"US Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.81521606445312,\n 18.376682358161855\n ],\n [\n -64.79461669921875,\n 18.26978204979353\n ],\n [\n -64.67788696289062,\n 18.231960055191504\n ],\n [\n -64.61883544921875,\n 18.341490772004338\n ],\n [\n -64.67788696289062,\n 18.375379094031825\n ],\n [\n -64.81521606445312,\n 18.376682358161855\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Rogers, Caroline 0000-0001-9056-6961","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":218311,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":768979,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70204944,"text":"70204944 - 2019 - Eviction notice: Observation of a Common Tern (Sterna hirundo) usurping an active Least Tern (Sternula antillarum) Nest","interactions":[],"lastModifiedDate":"2019-08-27T07:48:53","indexId":"70204944","displayToPublicDate":"2019-08-12T11:14:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Eviction notice: Observation of a Common Tern (Sterna hirundo) usurping an active Least Tern (Sternula antillarum) nest","title":"Eviction notice: Observation of a Common Tern (Sterna hirundo) usurping an active Least Tern (Sternula antillarum) Nest","docAbstract":"Although nest usurpation is common in some species and orders of birds, usurpation has rarely been reported for Sterninae. We observed a Sterna hirundo (Common Tern) egg in an active Sternula antillarum(Least Tern) nest with a complete clutch in a mixed-species Sterninae colony in Chesapeake Bay, MD, in May 2018. Based on observations from a game camera following usurpation, Common Terns incubated the mixed-species clutch, with no further parental care provided by the usurped Least Tern. The clutch never hatched, as the Common Terns abandoned the nest prior to the hatching. While we suspect that Common Terns usurped the Least Tern nest, alternative scenarios may explain how the Common Tern egg was documented in a Least Tern nest.
","language":"English","publisher":"BioOne","doi":"10.1656/045.026.0313","usgsCitation":"Riggs, G.J., Sullivan, J.D., Harvey, K.M., Pappas, D.A., Wall, J.L., McGowan, P.C., Callahan, C.R., Koppie, C.A., and Prosser, D., 2019, Eviction notice: Observation of a Common Tern (Sterna hirundo) usurping an active Least Tern (Sternula antillarum) Nest: Northeastern Naturalist, v. 26, no. 3, p. 609-615, https://doi.org/10.1656/045.026.0313.","productDescription":"7 p.","startPage":"609","endPage":"615","ipdsId":"IP-101312","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":366912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay, Poplar Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.37523651123047,\n 38.78299298997704\n ],\n [\n -76.37969970703125,\n 38.78085193143006\n ],\n [\n -76.39154434204102,\n 38.766531949968076\n ],\n [\n -76.3908576965332,\n 38.75609127334412\n ],\n [\n -76.38347625732422,\n 38.744711873638536\n ],\n [\n -76.37918472290039,\n 38.74190021311252\n ],\n [\n -76.37077331542969,\n 38.74337300148123\n ],\n [\n -76.36184692382812,\n 38.74698789869036\n ],\n [\n -76.36425018310547,\n 38.7542171440524\n ],\n [\n -76.36819839477539,\n 38.75582354360097\n ],\n [\n -76.37369155883789,\n 38.754752614585676\n ],\n [\n -76.380558013916,\n 38.76479194327964\n ],\n [\n -76.36940002441406,\n 38.777372574181335\n ],\n [\n -76.37523651123047,\n 38.78299298997704\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riggs, Georgia J.","contributorId":218412,"corporation":false,"usgs":false,"family":"Riggs","given":"Georgia","email":"","middleInitial":"J.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":769197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":769198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Kayla M.","contributorId":218413,"corporation":false,"usgs":false,"family":"Harvey","given":"Kayla","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":769199,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pappas, Dimitri A.","contributorId":218414,"corporation":false,"usgs":false,"family":"Pappas","given":"Dimitri","email":"","middleInitial":"A.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":769200,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wall, Jennifer L.","contributorId":205845,"corporation":false,"usgs":false,"family":"Wall","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":769201,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":769202,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":769203,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koppie, Craig A.","contributorId":218415,"corporation":false,"usgs":false,"family":"Koppie","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":769204,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":218411,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":769196,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205208,"text":"70205208 - 2019 - Confronting models with data: The challenges of estimating disease spillover","interactions":[],"lastModifiedDate":"2019-09-06T10:33:08","indexId":"70205208","displayToPublicDate":"2019-08-12T10:29:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Confronting models with data: The challenges of estimating disease spillover","docAbstract":"For pathogens known to transmit across host species, strategic investment in disease control requires knowledge about where and when spillover transmission is likely. One approach to estimating spillover is to directly correlate observed spillover events with covariates. An alternative is to mechanistically combine information on host density, distribution, and pathogen prevalence to predict where and when spillover events are expected to occur. We use several case studies at the wildlife-livestock disease interface to highlight the challenges, and potential solutions, to estimating spatio-temporal variation in spillover risk. Datasets on multiple host species often do not align in space, time or resolution, and may have no estimates of observation error. Linking these datasets requires they be related to a common spatial and temporal resolution and appropriately propagating errors in predictions can be difficult. Hierarchical models are one potential solution, but for fine-resolution predictions at broad spatial scales many models become computationally challenging. Despite these limitations, the confrontation of mechanistic predictions with observed events is an important avenue for developing a better understanding of pathogen spillover. Systems where data have been collected at all levels in the spillover process are rare, or non-existent, and require investment and sustained effort across disciplines.","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2018.0435","usgsCitation":"Cross, P.C., Prosser, D., Ramey, A.M., Hanks, E.M., and Pepin, K., 2019, Confronting models with data: The challenges of estimating disease spillover: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 374, no. 1782, 20180435, https://doi.org/10.1098/rstb.2018.0435.","productDescription":"20180435","ipdsId":"IP-103613","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467373,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6711303","text":"Publisher Index Page"},{"id":367254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"374","issue":"1782","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":770369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":770370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":770371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanks, Ephraim M. 0000-0003-0345-7164","orcid":"https://orcid.org/0000-0003-0345-7164","contributorId":210840,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":770372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":770373,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205207,"text":"70205207 - 2019 - Ecological interventions to prevent and manage zoonotic pathogen spillover","interactions":[],"lastModifiedDate":"2019-09-06T10:28:45","indexId":"70205207","displayToPublicDate":"2019-08-12T10:21:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Ecological interventions to prevent and manage zoonotic pathogen spillover","docAbstract":"Spillover of a pathogen from a wildlife reservoir into a human or livestock host requires the pathogen to overcome a hierarchical series of barriers. Interventions aimed at one or more of these barriers may be able to prevent the occurrence of spillover. Here, we demonstrate how interventions that target the ecological context in which spillover occurs (i.e. ecological interventions) can complement conventional approaches like vaccination, treatment, disinfection and chemical control. Accelerating spillover owing to environmental change requires effective, affordable, durable and scalable solutions that fully harness the complex processes involved in cross-species pathogen spillover.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2018.0342","usgsCitation":"Sokolow, S., Nova, N., Pepin, K., Peel, A.J., Pulliam, J., Manlove, K.R., Cross, P., Becker, D., Plowright, R., McCallum, H., and De Leo, G.A., 2019, Ecological interventions to prevent and manage zoonotic pathogen spillover: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 374, no. 1782, 20180342, 10 p., https://doi.org/10.1098/rstb.2018.0342.","productDescription":"20180342, 10 p.","ipdsId":"IP-104035","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2018.0342","text":"Publisher Index Page"},{"id":367253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"374","issue":"1782","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sokolow, S. 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J.","contributorId":218823,"corporation":false,"usgs":false,"family":"Peel","given":"A.","email":"","middleInitial":"J.","affiliations":[{"id":7117,"text":"Griffith University","active":true,"usgs":false}],"preferred":false,"id":770362,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pulliam, J","contributorId":218824,"corporation":false,"usgs":false,"family":"Pulliam","given":"J","email":"","affiliations":[{"id":39919,"text":"Stellenbosch University","active":true,"usgs":false}],"preferred":false,"id":770366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":770363,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":218820,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":770358,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Becker, D.","contributorId":177951,"corporation":false,"usgs":false,"family":"Becker","given":"D.","email":"","affiliations":[],"preferred":false,"id":770364,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Plowright, RK","contributorId":149691,"corporation":false,"usgs":false,"family":"Plowright","given":"RK","email":"","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":770365,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCallum, Hamish","contributorId":174852,"corporation":false,"usgs":false,"family":"McCallum","given":"Hamish","affiliations":[],"preferred":false,"id":770367,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"De Leo, Giulio A.","contributorId":146323,"corporation":false,"usgs":false,"family":"De Leo","given":"Giulio","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":770368,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70204876,"text":"70204876 - 2019 - Patterns of resource allocation in a coastal marsh plant (Schoenoplectus americanus) along a sediment-addition gradient","interactions":[],"lastModifiedDate":"2019-10-09T09:48:01","indexId":"70204876","displayToPublicDate":"2019-08-12T10:11:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Patterns of resource allocation in a coastal marsh plant (Schoenoplectus americanus) along a sediment-addition gradient","title":"Patterns of resource allocation in a coastal marsh plant (Schoenoplectus americanus) along a sediment-addition gradient","docAbstract":"Reductions in sediment delivery to coastal marshes increase their vulnerability to relative sea-level rise. Sediment pulses from storm events and commercial dredge-spray operations (e.g., beneficial use) represent increasingly important sediment sources to otherwise sediment-deprived marshes. These sediments can stimulate plant growth by providing nutrient and elevation subsidies, with plant growth predicted to peak at intermediate sediment depths. Most sediment subsidy studies have compared plant responses among discrete sediment depths applied across a uniform marsh platform, and often assessed impacts in the years following sediment deposition. Less is known about the immediate effects of sediment additions on plant growth or the mechanisms driving differences in these responses along a sediment-addition gradient. To investigate immediate plant responses to sediment additions (i.e., within 6 months), we added sediment to Schoenoplectus americanus-dominated brackish marsh sods in a greenhouse setting. Sediment was added incrementally along a sediment addition gradient (0–20 cm) to 18 sods, which were placed in clear planting enclosures to permit monitoring of above- and below-ground responses and hydro-edaphic properties. Shoot production, which increased linearly along the sediment addition gradient, was the first observable response to sediment addition and was likely a result of apical dominance interruption. This trend continued throughout the study even as survival of those shoots declined with increasing sediment depth. At the end of the experiment, however, shoot biomass production was biphasic, responding favorably to sediment addition up to intermediate depths before collapsing at higher depths. While fine root production in sods was maximal at intermediate sediment addition levels, root production in new sediment layers was limited. There were limited differences observed for hydro-edaphic properties along the sediment addition gradient. Thus, plant resources are allocated to shoot production immediately following sediment addition at the expense of root colonization of new sediment layers, suggesting that, in certain conditions, sediment deposition can represent a stress rather than a subsidy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2019.106337","usgsCitation":"Temple, N.A., Grace, J.B., and Cherry, J., 2019, Patterns of resource allocation in a coastal marsh plant (Schoenoplectus americanus) along a sediment-addition gradient: Estuarine, Coastal and Shelf Science, v. 228, 106337, 8 p., https://doi.org/10.1016/j.ecss.2019.106337.","productDescription":"106337, 8 p.","ipdsId":"IP-106497","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467375,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2019.106337","text":"Publisher Index Page"},{"id":366780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Pearl River Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.63968276977539,\n 30.16880135639736\n ],\n [\n -89.57934379577637,\n 30.16880135639736\n ],\n [\n -89.57934379577637,\n 30.20619347851233\n ],\n [\n -89.63968276977539,\n 30.20619347851233\n ],\n [\n -89.63968276977539,\n 30.16880135639736\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"228","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Temple, Nigel A.","contributorId":218273,"corporation":false,"usgs":false,"family":"Temple","given":"Nigel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":768850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":768851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherry, Julia A","contributorId":150554,"corporation":false,"usgs":false,"family":"Cherry","given":"Julia A","affiliations":[{"id":33913,"text":"Univ. of Alabama, Tuscaloosa, AL","active":true,"usgs":false}],"preferred":false,"id":768852,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}