We are grateful for the thought-provoking and forward-looking commentaries (Dingemanse et al. 2022; Mabry 2022; Spiegel and Pinter-Wollman 2022; Vander Wal et al. 2022) in response to our meta-analysis of evidence for consistent among-individual differences in animals’ spatial behaviors (Stuber et al. 2022). A clear consensus is that our demonstration of the prevalence of repeatability across spatial behaviors, and taxa, is only the first step towards identifying the mechanisms and consequences of variation in spatial behavior. Here, we take the opportunity to emphasize key future directions pertaining to uncovering mechanisms, disentangling apparent personality from spatial constraints, and examining additional metrics of variation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/beheco/arac018","usgsCitation":"Stuber, E.F., Carlson, B., and Jesmer, B., 2022, Many avenues for spatial personality research: a response to comments on Stuber et al. (2022): Behavioral Ecology, v. 33, no. 3, p. 492-493, https://doi.org/10.1093/beheco/arac018.","productDescription":"2 p.","startPage":"492","endPage":"493","ipdsId":"IP-136443","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arac018","text":"Publisher Index Page"},{"id":430056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":903509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Ben","contributorId":338737,"corporation":false,"usgs":false,"family":"Carlson","given":"Ben","email":"","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":903510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett","contributorId":338738,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":903511,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70247365,"text":"70247365 - 2022 - Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure","interactions":[],"lastModifiedDate":"2023-07-31T11:09:59.450954","indexId":"70247365","displayToPublicDate":"2022-03-04T14:47:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure","docAbstract":"Magnetotelluric models spanning the Pacific–Australian Plate boundary in New Zealand’s South Island indicate a localized zone of low electrical resistivity that is spatially coincident with theductile mid-crustal part of the Alpine Fault Zone (AFZ). We explored the source of this anomaly bymeasuring the electrical properties of samples collected from surface outcrops approaching the AFZthat have accommodated a gradient of systematic strain and deformation conditions. We investigatedthe effects of tectonite fabric, fluid saturated pore/fracture networks and surface conductivity on the bulk electrical response and the anisotropy of resistivity measured under increasing confining pressures up to 200 MPa. We find that porosity and resistivity increase while porosity and the change in anisotropy of resistivity with confining pressure (δ (ρk/ρ⊥)/δ (peff)) decreases approaching theAFZ, indicating the electrical response is controlled by pore fluid conductivity and modified during progressive metamorphism. Conversely, Alpine mylonites exhibit relatively low resistivities at low porosities, and lower δ (ρk/ρ⊥)/δ (peff) than the schists. These findings indicate a transition in both the porosity distribution and electrical charge transport processes in rocks that have experienced progressive grain size reduction and mixing of phases during development of mylonitic fabrics due to creep shear strain within the AFZ.
","language":"English","publisher":"MDPI","doi":"10.3390/geosciences12030121","usgsCitation":"Kluge, K.E., Toy, V.G., and Lockner, D., 2022, Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure: Geosciences, v. 12, 121, 19 p., https://doi.org/10.3390/geosciences12030121.","productDescription":"121, 19 p.","ipdsId":"IP-132712","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448588,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences12030121","text":"Publisher Index Page"},{"id":435938,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91A6OMH","text":"USGS data release","linkHelpText":"Data from the manuscript: Electrical properties and anisotropy of schists and fault rocks from New Zealand’s Southern Alps under confining pressure"},{"id":419434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Southern Alps","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[173.02037,-40.91905],[173.24723,-41.332],[173.95841,-40.9267],[174.24759,-41.34916],[174.24852,-41.77001],[173.87645,-42.23318],[173.22274,-42.97004],[172.71125,-43.37229],[173.08011,-43.85334],[172.30858,-43.86569],[171.45293,-44.24252],[171.18514,-44.8971],[170.6167,-45.90893],[169.83142,-46.35577],[169.33233,-46.64124],[168.41135,-46.61994],[167.76374,-46.2902],[166.67689,-46.21992],[166.50914,-45.8527],[167.04642,-45.11094],[168.30376,-44.12397],[168.94941,-43.93582],[169.66781,-43.55533],[170.52492,-43.03169],[171.12509,-42.51275],[171.56971,-41.76742],[171.94871,-41.51442],[172.09723,-40.9561],[172.79858,-40.49396],[173.02037,-40.91905]]],[[[174.61201,-36.1564],[175.33662,-37.2091],[175.3576,-36.52619],[175.80889,-36.79894],[175.95849,-37.55538],[176.7632,-37.88125],[177.43881,-37.96125],[178.01035,-37.57982],[178.51709,-37.69537],[178.27473,-38.58281],[177.97046,-39.16634],[177.20699,-39.14578],[176.93998,-39.44974],[177.03295,-39.87994],[176.88582,-40.06598],[176.50802,-40.60481],[176.01244,-41.28962],[175.23957,-41.68831],[175.0679,-41.42589],[174.65097,-41.28182],[175.22763,-40.45924],[174.90016,-39.90893],[173.82405,-39.50885],[173.85226,-39.1466],[174.5748,-38.79768],[174.74347,-38.02781],[174.69702,-37.38113],[174.29203,-36.71109],[174.319,-36.53482],[173.841,-36.12198],[173.05417,-35.23713],[172.63601,-34.52911],[173.00704,-34.45066],[173.5513,-35.00618],[174.32939,-35.2655],[174.61201,-36.1564]]]]},\"properties\":{\"name\":\"New Zealand\"}}]}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Kluge, Katherine E","contributorId":317793,"corporation":false,"usgs":false,"family":"Kluge","given":"Katherine","email":"","middleInitial":"E","affiliations":[{"id":69160,"text":"Univ. of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":879333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toy, Virginia G.","contributorId":195078,"corporation":false,"usgs":false,"family":"Toy","given":"Virginia","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":879334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":261920,"corporation":false,"usgs":true,"family":"Lockner","given":"David A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":879332,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229369,"text":"70229369 - 2022 - Leveraging rangeland monitoring data for wildlife: From concept to practice","interactions":[],"lastModifiedDate":"2022-03-04T15:45:24.688257","indexId":"70229369","displayToPublicDate":"2022-03-04T09:31:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging rangeland monitoring data for wildlife: From concept to practice","docAbstract":"Available rangeland data, from field-measured plots to remotely sensed landscapes, provide much needed information for mapping and modeling wildlife habitats.
Better integration of wildlife habitat characteristics into rangeland monitoring schemes is needed for most rangeland wildlife species at varying spatial and temporal scales.
Here, we aim to stimulate use of and inspire ideas about rangeland monitoring data in the context of wildlife habitat modeling and species conservation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.09.005","usgsCitation":"Pilliod, D., Beck, J.L., Duchardt, C.J., Rachlow, J.L., and Veblen, K.E., 2022, Leveraging rangeland monitoring data for wildlife: From concept to practice: Rangelands, v. 44, no. 1, p. 87-98, https://doi.org/10.1016/j.rala.2021.09.005.","productDescription":"12 p.","startPage":"87","endPage":"98","ipdsId":"IP-125490","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.09.005","text":"Publisher Index Page"},{"id":396752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Utah, Wyoming","otherGeospatial":"Great 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To achieve this goal the TMDL requires the implementation of Best Management Practices (BMPs), which are accepted land management practices for reducing pollutant runoff to nearby bodies of water. While the TMDL requires that the necessary management actions be in place by 2025 to eventually reach targeted nutrient loads, the ability to detect an effect of BMPs while assuming that one has occurred (i.e. statistical power) is still not well understood. The goal of this study was to investigate the power and required timelines to detect nutrient reductions in streams and rivers as the result of BMP implementation at the Chesapeake Watershed scale. Power estimates were produced using SPAtially Referenced Regression On Watershed attributes (SPARROW) models, which offer a flexible statistical framework and were recently extended to allow for modeling multiple time steps. 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University","active":true,"usgs":false}],"preferred":false,"id":837243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, Richard","contributorId":219089,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":837262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomquist, Joel D. 0000-0002-0140-6534","orcid":"https://orcid.org/0000-0002-0140-6534","contributorId":215461,"corporation":false,"usgs":true,"family":"Blomquist","given":"Joel","middleInitial":"D.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Devereux, Olivia H.","contributorId":97238,"corporation":false,"usgs":true,"family":"Devereux","given":"Olivia","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":837245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions 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},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":837246,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837248,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":837247,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229392,"text":"70229392 - 2022 - Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","interactions":[],"lastModifiedDate":"2022-03-04T15:06:26.624931","indexId":"70229392","displayToPublicDate":"2022-03-04T08:56:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil","docAbstract":"The Alto Guaporé gold province, southwestern Amazon craton, contains gold deposits that have been mined since the beginning of the 18th century and these deposits, together, have modern-day, pre-mining gold resources of at least 1.8 Moz. The ore is associated with quartz vein systems along the southeastern part of the Aguapei belt, a ~35-km-wide and ~500-km-long, NNW-trending shear zone formed due to reactivation of a terrane-bounding suture. The Aguapei belt evolved by ca. 1150 to 1100 Ma rifting and deposition of siliciclastic sediments in an aulacogen basin, followed by deformation and low-grade metamorphism of the sedimentary sequences during 1100 to 900 Ma terrane collision along the craton margin. The deformation was characterized by a compressional regime until ca. 950 Ma and transition to a transpressional setting during the final 50 m.y.
The gold deposits are hosted in a variety of structures that are second-order to the main Aguapei shear zone. The Ernesto and Pau-a-Pique deposits are located ~40 km apart and at jogs along the Aguapei belt. They are marginal to pre-ore igneous rocks, with Ernesto hosted in the basal part of the metasedimentary Fortuna Formation that overlies tonalite and Pau-a-Pique at the contact between metasedimentary rocks and diorite. Three deformational phases comprise the compressional (D1 to D2) to transpressional (D3) tectonic events. In the Pau-a-Pique deposit and the deeper level of the Ernesto deposit, the ore-bearing veins are bedding parallel and follow D2 strike-slip and reverse fault zones, respectively. However, the veins formed during D3 reactivation of the older structures by an array of oblique accommodation faults. In contrast, ores at shallower levels of Ernesto, both in discordant and bedding-parallel veins, are hosted within a ~20-m-thick rigid metaconglomerate with associated dilation due to the structural complexity as sedimentary rocks of the Aguapei Group were folded around the dome-shaped roof of the pre-ore tonalite. The ores in both deposits, as well as in many other deposits of the province, are characterized by disseminated and vein-hosted pyrite. Gold occurs mainly as inclusions in the pyrite, with other hydrothermal phases comprising muscovite, Fe-Ti oxides, and minor apatite, chalcopyrite, and galena.
Fluid inclusion data, coupled with stable isotope geochemistry and geothermometry, indicate that gold precipitated from a low-salinity, CO2-rich fluid at ~300°C and ~2.5 kbar. The source for the fluid and gold was the interbedded pelites during devolatilization of the Aguapei Group sequence. The aqueous-carbonic fluid inclusions and the narrow range of δ18O values of quartz (12 ± 1‰) from many auriferous veins from the central part of the province represent a regional ore-forming fluid. The broad range of δD for hydrous minerals (–116 to –55‰) reflects influx of small amounts of meteoric water into the steeply dipping shear zones during postgold exhumation. The 40Ar/39Ar geochronology from hydrothermal muscovite indicates a widespread hydrothermal event along the belt between 928 and 920 Ma. Collectively, the geological, geochronological, and geochemical data suggest that metamorphic fluids migrated laterally into and then upward along the Aguapei belt and deposited gold in lower-order structures where strain gradients existed between lithounits. The province has many characteristics of large orogenic gold provinces worldwide and represents a highly prospective and underexplored target region for early Neoproterozoic gold, a time period that generally is not well endowed in gold ores.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.4852","usgsCitation":"de Melo, R.P., de Oliveira, M.A., Goldfarb, R.J., Johnson, C.A., Marsh, E.E., Xavier, R.P., de Oliveira, L.R., and Morgan, L.E., 2022, Early Neoproterozoic gold deposits of the Alto Guaporé province, southwestern Amazon craton, western Brazil: Economic Geology, v. 117, no. 1, p. 127-163, https://doi.org/10.5382/econgeo.4852.","productDescription":"37 p.","startPage":"127","endPage":"163","ipdsId":"IP-121052","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488405,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11449/222995","text":"External Repository"},{"id":396749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Alto Guaporé gold province, Amazon craton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -64.7314453125,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -20.756113874762068\n ],\n [\n -45.966796875,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -8.146242825034385\n ],\n [\n -64.7314453125,\n -20.756113874762068\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Melo, Rodrigo Prudente","contributorId":287985,"corporation":false,"usgs":false,"family":"de Melo","given":"Rodrigo","email":"","middleInitial":"Prudente","affiliations":[{"id":61677,"text":"Faculdade de Ciência e Tecnologia, Univ. Federal de Goiás, R. Mucuri S/N, Aparecida de Goiânia, GO, CEP 74968-755, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Oliveira, Marcos Aurelio Farias","contributorId":287986,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Marcos","email":"","middleInitial":"Aurelio Farias","affiliations":[{"id":61678,"text":"Instituto de Geociências e Ciências Exatas, Univ. Estadual Paulista, R. 24A 1515, Rio Claro, SP, CEP 13506-900, Brazil.","active":true,"usgs":false}],"preferred":false,"id":837255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldfarb, Richard J. goldfarb@usgs.gov","contributorId":210729,"corporation":false,"usgs":false,"family":"Goldfarb","given":"Richard","email":"goldfarb@usgs.gov","middleInitial":"J.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":837256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":837257,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marsh, Erin E. 0000-0001-5245-9532 emarsh@usgs.gov","orcid":"https://orcid.org/0000-0001-5245-9532","contributorId":1250,"corporation":false,"usgs":true,"family":"Marsh","given":"Erin","email":"emarsh@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837258,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xavier, Roberto Perez","contributorId":287987,"corporation":false,"usgs":false,"family":"Xavier","given":"Roberto","email":"","middleInitial":"Perez","affiliations":[{"id":61679,"text":"Departamento de Geologia e Recursos Naturais, Instituto de Geociências, Universidade de Campinas, Campinas, SP, CEP 13083-970, Brazil","active":true,"usgs":false}],"preferred":false,"id":837259,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de Oliveira, Leandro Rocha","contributorId":287988,"corporation":false,"usgs":false,"family":"de Oliveira","given":"Leandro","email":"","middleInitial":"Rocha","affiliations":[{"id":61680,"text":"Yamana Desenvolvimento Mineral, R. Ministro Orozimbo Nonato 272/19º andar, Belo Horizonte, MG, CEP 34006-053, Brazil","active":true,"usgs":false}],"preferred":false,"id":837260,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":837261,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229391,"text":"70229391 - 2022 - Adaptive monitoring in support of adaptive management in rangelands","interactions":[],"lastModifiedDate":"2022-03-04T15:51:02.822444","indexId":"70229391","displayToPublicDate":"2022-03-04T08:56:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive monitoring in support of adaptive management in rangelands","docAbstract":"Monitoring supports iterative learning about the effectiveness of management actions, information that can help managers plan future actions, facilitate decision-making, and improve outcomes.
Adaptive monitoring is the evolution of a monitoring program in response to new management questions; new or changing environmental or socioeconomic conditions, improved monitoring methods, models, and tools; and experience implementing the monitoring program.
Adaptive monitoring is connected to research and management through the exchange of data; analytical, methodological, and technological developments; information; and understanding.
We review recent advances in adaptive monitoring and discuss new opportunities for both the research and management communities to improve monitoring in the years ahead.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2021.07.003","usgsCitation":"McCord, S.E., and Pilliod, D., 2022, Adaptive monitoring in support of adaptive management in rangelands: Rangelands, v. 44, no. 1, p. 1-7, https://doi.org/10.1016/j.rala.2021.07.003.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-127736","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rala.2021.07.003","text":"Publisher Index Page"},{"id":396753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837253,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231766,"text":"70231766 - 2022 - Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","interactions":[],"lastModifiedDate":"2022-05-27T13:45:52.178121","indexId":"70231766","displayToPublicDate":"2022-03-04T08:40:56","publicationYear":"2022","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":"Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","title":"Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses","docAbstract":"Investigating the long-term fluctuations of the feeding ecology of megaherbivores such as sirenians is important, as any changes could be indicative of shifts in resource availability. The Indian River Lagoon (IRL), eastern Florida, USA, is a critical habitat for the Florida manatee (Trichechus manatus latirostris). However, the IRL has experienced a substantial decline in seagrass due to the persistence of several harmful algal blooms. Using microhistological analysis, we examined the diet of manatees over a discontinuous sampling period spanning over 38 years using stomach contents collected from carcasses recovered in the IRL. Samples collected between 2013–2015 (post-seagrass die-off, n = 90) were compared to archived stomach samples collected between 1977–1989 (pre-seagrass die-off, n = 103). Samples analyzed from 1977–1989 contained primarily seagrasses (61.7%), followed by algae (28.4%) and vascular plants (1.7%). In contrast, stomach samples from the post-seagrass die-off primarily contained algae (49.5%), followed by seagrasses (34%) and vascular plants (2.7%). Between 1977–1989 and 2013–2015, manatees in the IRL experienced a 44.9% decline in seagrass consumption, and a 74.3% increase in algal consumption. This dietary shift was not influenced by body length, a proxy of age, or sex. Our results indicate that the dietary shift experienced by manatees is due to the decline of available seagrass forage in the IRL, and highlight the dietary plasticity of manatees in the face of changes in resource availability. However, the individual health and population-level consequences of this dietary shift are unknown. An increase in mortality due to undetermined causes in this region since 2012 can be associated with deteriorating body conditions of manatees in the IRL, possibly resulting from a lack of seagrass diet. Future research should further investigate behavioral changes affecting manatees in relation to seagrass decline in the IRL, including the energetic costs of this dietary change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2022.107788","usgsCitation":"Allen, A.C., Beck, C., Sattelberger, D.C., and Kiszka, J.J., 2022, Evidence of a dietary shift by the Florida manatee (Trichechus manatus latirostris) in the Indian River Lagoon inferred from stomach content analyses: Estuarine, Coastal and Shelf Science, v. 268, 107788, 7 p., https://doi.org/10.1016/j.ecss.2022.107788.","productDescription":"107788, 7 p.","ipdsId":"IP-134570","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":401296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Indian River Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.26611328125,\n 27.176469131898898\n ],\n [\n -80.0738525390625,\n 27.244862521497282\n ],\n [\n -80.57373046875,\n 28.65203063036226\n ],\n [\n -80.85937499999999,\n 28.844673680771795\n ],\n [\n -80.9088134765625,\n 28.7965462417692\n ],\n [\n -80.7989501953125,\n 28.36723539252299\n ],\n [\n -80.4913330078125,\n 27.727298422724655\n ],\n [\n -80.37597656249999,\n 27.391278222579277\n ],\n [\n -80.26611328125,\n 27.176469131898898\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"268","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Aarin Conrad","contributorId":139671,"corporation":false,"usgs":false,"family":"Allen","given":"Aarin","email":"","middleInitial":"Conrad","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":843744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Cathy 0000-0002-5388-5418 cbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-5418","contributorId":168987,"corporation":false,"usgs":true,"family":"Beck","given":"Cathy","email":"cbeck@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":843745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sattelberger, Danielle C.","contributorId":292060,"corporation":false,"usgs":false,"family":"Sattelberger","given":"Danielle","email":"","middleInitial":"C.","affiliations":[{"id":62815,"text":"Environmental Resource Program, Florida Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":843746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiszka, Jeremy J.","contributorId":292061,"corporation":false,"usgs":false,"family":"Kiszka","given":"Jeremy","email":"","middleInitial":"J.","affiliations":[{"id":62816,"text":"Institute of Environment, Department of Biological Sciences, Florida International University","active":true,"usgs":false}],"preferred":false,"id":843747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255537,"text":"70255537 - 2022 - Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","interactions":[],"lastModifiedDate":"2024-06-21T11:53:57.84801","indexId":"70255537","displayToPublicDate":"2022-03-04T06:51:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2334,"text":"Journal of Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Stage-specific environmental correlates of reproductive success in Boreal Toads (Anaxyrus boreas boreas)","docAbstract":"Compensatory recruitment can facilitate the persistence of populations experiencing high adult mortality. Because early life-stages of many taxa, including amphibians, are difficult to mark and recapture, sources of variation in survival at these stages often are unknown, which creates barriers to improving in situ recruitment rates. We leveraged count data and open N-mixture models to examine the environmental factors associated with the hatching of egg clutches, tadpole survival, and probability of metamorphosis in Boreal Toads (Anaxyrus boreas boreas) that inhabit pastures leased for cattle grazing in western Wyoming, USA. We conducted weekly surveys and measured a suite of environmental variables at 20 breeding ponds during May–September 2018. The hatching of egg clutches was most strongly related to pond surface area, as clutches often desiccated at smaller ponds. Weekly tadpole survival was lowest in ponds with high abundance of aquatic predators. Predation did not preclude metamorphosis, which was more strongly associated with higher dissolved oxygen and vegetation cover. Cattle grazing reduced vegetation cover in and around breeding ponds, which resulted in lower levels of dissolved oxygen. Grazing-induced habitat changes are therefore likely to negatively influence tadpole metamorphosis both via indirect effects on dissolved oxygen, and direct effects on vegetation cover, which also serves as feeding sites and escape cover from predators. We demonstrate the success of three critical phases in early life-stage development (egg hatching, tadpole survival, metamorphosis) was associated with different environmental factors. The inclusion of stage-specific responses in demographic analyses is therefore critical for a thorough understanding of what limits populations.
The goal of the Louisiana Barrier Island Comprehensive Monitoring (BICM) program is to provide long-term data on coastal Louisiana for monitoring change and assisting in coastal management. This study (carried out under Coastal Protection and Restoration Authority contract number 2000339324, BICM2—Chenier TopoBathy DEM) builds upon the previous BICM physical assessment of the Chenier Plain region using bathymetric data from three periods (1930, 2007, and 2017) to develop digital elevation models for historical and current periods. In addition to bathymetric datasets, the study includes light detection and ranging elevation measurements along the coastline to produce elevation datasets for the 2007 and 2017 periods. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221014","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chenier Plain region bathymetric and topographic datasets: Methodology report: U.S. Geological Survey Open-File Report 2022–1014, 21 p., https://doi.org/10.3133/ofr20221014.","productDescription":"vii, 21 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122902","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501759,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112530.htm","linkFileType":{"id":5,"text":"html"}},{"id":396683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1014"},{"id":396682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1014/coverthb.jpg"},{"id":396685,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1014/images/"},{"id":396684,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.XML"},{"id":396704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221014/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chenier Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85620117187499,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.439597566602902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
We use a suite of historical earthquakes to quantitatively determine earthquake early warning (EEW) alert threshold strategies for a range of shaking intensity targets for EEW in the U.S. West Coast. The current method for calculating alert regions for the ShakeAlert EEW System does not take into account variabilities and uncertainties in shaking distribution. As a result, if the modified Mercalli intensity (MMI) level used to determine the extent of the alert region (the alert threshold) is the same as the target intensity threshold, the alert region will be too small to include all locations that require alerts even if earthquake source parameters are estimated accurately. Missed alerts can be reduced by using a lower alert threshold than the target threshold. This expands the alert region, increasing the number of precautionary alerts issued to people who experience shaking below the target level. We determine alert thresholds that optimize this tradeoff between missed and precautionary alerts for target thresholds of MMI 4.0-6.0 using a ShakeMap catalog of 143 M5.0-7.3 earthquakes as ground truth. We examine the quality of each alerting strategy relative to the target MMI, where we define alert quality metrics in terms of both the area and population alerted. Optimal alert thresholds maximize correct alerts while limiting most precautionary alerts to regions that are likely to still feel some shaking. We find these optimal alert thresholds also maximize warning times. This analysis presents a quantitative framework ShakeAlert can use to communicate alerting strategies and performance expectations to ShakeAlert users.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021EF002515","usgsCitation":"Saunders, J.K., Minson, S.E., and Baltay Sundstrom, A.S., 2022, How low should we alert? Quantifying intensity threshold alerting strategies for earthquake early warning in the United States: Earth's Future, v. 10, no. 3, e2021EF002515, 20 p., https://doi.org/10.1029/2021EF002515.","productDescription":"e2021EF002515, 20 p.","ipdsId":"IP-130454","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021ef002515","text":"Publisher Index Page"},{"id":482033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Saunders, Jessie Kate 0000-0001-5340-6715","orcid":"https://orcid.org/0000-0001-5340-6715","contributorId":290634,"corporation":false,"usgs":true,"family":"Saunders","given":"Jessie","email":"","middleInitial":"Kate","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229816,"text":"70229816 - 2022 - Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","interactions":[],"lastModifiedDate":"2022-03-18T14:39:48.68884","indexId":"70229816","displayToPublicDate":"2022-03-03T09:34:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations","docAbstract":"Conservation translocations are increasingly used to help recover imperiled species. However, success of establishing populations remains low, especially for amphibians. Identifying factors associated with translocation success can help increase efficiency and efficacy of recovery efforts. Since the 1990s, several captive and semi-captive facilities have produced Chiricahua Leopard Frogs (Rana chiricahuensis) to establish or augment wild populations in Arizona and New Mexico, USA. During this same time, personnel associated with several programs surveyed translocation and non-translocation sites for presence of amphibians. We used 25 years (1995–2019) of survey and translocation data for the federally threatened Chiricahua Leopard Frog to identify factors linked with population persistence. Our dataset included approximately 40,642 egg masses or animals translocated in 314 events to 115 distinct sites and > 5800 visual encounter surveys from 641 sites; 120 of these sites were also surveyed with environmental DNA methods in 2018. We used a hierarchical dynamic occupancy model that accounted for imperfect detection to identify patch- and landscape-level attributes associated with site occupancy, and then used predictions from that model to evaluate factors associated with population persistence at translocation sites. Across all sites, extinction probability for Chiricahua Leopard Frogs was higher in lotic (stream) than lentic (pond) habitats and when Western Tiger Salamanders (Ambystoma mavortium) were present. Restoration of sites specifically for frog conservation reduced extinction probability. Colonization of unoccupied sites increased moderately with increasing numbers of translocation sites within 2 km, indicating a benefit of translocation efforts beyond sites where frogs were stocked. At translocation sites, persistence was greater in lentic than lotic habitats and was negatively correlated with the proportion of years tiger salamanders were present. Increasing numbers of translocation events, especially of late-stage larvae, increased persistence. There was little difference in population persistence based on whether stock was from captive, semi-captive, or wild sources, but translocations during the dry season (January—July) succeeded more than those after the typical arrival of summer rains (August—December). Based on the number of years translocation sites were predicted to be occupied, 2 or more translocations produced, on average, a > 4-yr increase in predicted occupancy compared to sites without translocations. While translocations have increased the number of populations across the landscape, continued management of water availability and threats such as invasive predators and disease remain critical to recovery of the Chiricahua Leopard Frog.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2022.e02078","usgsCitation":"Hossack, B., Howell, P., Owens, A., Cobos, C., Goldberg, C.S., Hall, D.L., Hedwall, S., MacVean, S., McCaffery, M., McCall, A.H., Mosley, C., Oja, E.B., Rorabaugh, J.C., Sigafus, B., and Sredl, M.J., 2022, Identifying factors linked with persistence of reintroduced populations: Lessons learned from 25 years of amphibian translocations: Global Ecology and Conservation, v. 35, e02078, 22 p., https://doi.org/10.1016/j.gecco.2022.e02078.","productDescription":"e02078, 22 p.","ipdsId":"IP-135486","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":448603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2022.e02078","text":"Publisher Index Page"},{"id":397306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.35717773437499,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 31.325486676506983\n ],\n [\n -106.0400390625,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 35.10193405724606\n ],\n [\n -112.35717773437499,\n 31.325486676506983\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howell, Paige E.","contributorId":173495,"corporation":false,"usgs":false,"family":"Howell","given":"Paige E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":838452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Audrey K","contributorId":288932,"corporation":false,"usgs":false,"family":"Owens","given":"Audrey K","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobos, C","contributorId":288933,"corporation":false,"usgs":false,"family":"Cobos","given":"C","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldberg, Caren S.","contributorId":76879,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren","email":"","middleInitial":"S.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":838455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, David L.","contributorId":222395,"corporation":false,"usgs":false,"family":"Hall","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":838456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hedwall, Shaula","contributorId":288934,"corporation":false,"usgs":false,"family":"Hedwall","given":"Shaula","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":838457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"MacVean, Susi","contributorId":288935,"corporation":false,"usgs":false,"family":"MacVean","given":"Susi","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCaffery, Magnus","contributorId":288936,"corporation":false,"usgs":false,"family":"McCaffery","given":"Magnus","email":"","affiliations":[{"id":38107,"text":"Turner Endangered Species Fund","active":true,"usgs":false}],"preferred":false,"id":838459,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCall, A. Hunter","contributorId":288937,"corporation":false,"usgs":false,"family":"McCall","given":"A.","email":"","middleInitial":"Hunter","affiliations":[{"id":48661,"text":"Private","active":true,"usgs":false}],"preferred":false,"id":838460,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mosley, C","contributorId":288938,"corporation":false,"usgs":false,"family":"Mosley","given":"C","email":"","affiliations":[{"id":61907,"text":"AGFD","active":true,"usgs":false}],"preferred":false,"id":838461,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Oja, Emily Bea 0000-0002-8621-9665","orcid":"https://orcid.org/0000-0002-8621-9665","contributorId":261164,"corporation":false,"usgs":true,"family":"Oja","given":"Emily","email":"","middleInitial":"Bea","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":838462,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, James C.","contributorId":191978,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":838463,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":838464,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sredl, Michael J","contributorId":288939,"corporation":false,"usgs":false,"family":"Sredl","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":838465,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70229202,"text":"tm6A62 - 2022 - Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","interactions":[],"lastModifiedDate":"2022-03-03T17:29:27.921518","indexId":"tm6A62","displayToPublicDate":"2022-03-03T09:21:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"6-A62","displayTitle":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","title":"Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6","docAbstract":"This report describes the skeletal storage, compaction and subsidence (CSUB) package of MODFLOW 6. The CSUB package simulates the vertical compaction of compressible sediments and land subsidence. The package simulates groundwater storage changes and elastic compaction in coarse-grained aquifer sediments. The CSUB package also simulates groundwater storage changes and elastic and inelastic compaction in fne-grained, compressible interbeds, or in extensive confning units. The package can account for effective stress-dependent changes in storage properties. The CSUB package can also explicitly account for the contribution of water compressibility to groundwater storage changes.
Compaction of compressible sediments is formulated using Terzaghi’s elastoplastic model and assumes the total compaction is a small fraction of the total initial thickness of compressible sediments. Compaction is controlled by head or pore-pressure changes and overburden stress changes associated with water-table changes, and thus by effective stress changes within coarse-and fne-grained compressible sediments. If the stress in a compressible unit is less than the preconsolidation stress, compaction is elastic (recoverable). If the stress in a compressible sediment is greater than the preconsolidation stress, compaction is inelastic (irrecoverable) and permanent land subsidence occurs.
The propagation of head changes within fne-grained, compressible interbeds is represented numerically using a transient, one-dimensional (vertical) groundwater fow equation. This equation accounts for delayed release of water from storage or uptake of water into storage in the interbeds. Vertical hydraulic conductivity, elastic and inelastic skeletal specifc storage, and interbed thickness control the timing of interbed storage changes. Interbeds that are thin, have a relatively large vertical hydraulic conductivity, or relatively small specifc-storage values equilibrate quickly with heads/pore pressures in surrounding coarse-grained sediments and can be represented as no-delay interbeds that use the simulated groundwater head in a cell to calculate interbed compaction and do not need to be solved numerically using a vertically discretized interbed and the vertical groundwater fow equation.
In addition to the applicability to confned groundwater fow systems, several features of the CSUB package make it applicable to shallow, unconfned groundwater fow systems. Geostatic stress can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress. The porosity, void ratio, and thickness of shallow and deep coarse-grained aquifer sediments, fne-grained interbeds, and extensive confning units can vary in time based on calculated strain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A62","usgsCitation":"Hughes, J.D., Leake, S.A., Galloway, D.L., and White, J.T., 2022, Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6: U.S. Geological Survey Techniques and Methods, book 6, chap. A62, 57 p., https://doi.org/10.3133/tm6A62.","productDescription":"Report: vi, 57 p.; Software Release","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114536","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396667,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396668,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396669,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a62/coverthb.jpg"},{"id":396642,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"},{"id":396640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a62/tm6a62.pdf","text":"Report","size":"5.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A62"},{"id":396641,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A61","text":"Techniques and Methods 6-A61","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Transport Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
This report documents a new Groundwater Transport (GWT) Model for MODFLOW 6. The GWT Model simulates three-dimensional transport of a single chemical species in fowing groundwater based on a generalized control-volume fnite-difference approach. Although each GWT Model is only able to represent a single chemical species, multiple GWT Models may be invoked within a single MODFLOW 6 simulation to represent solute transport of multiple non-interacting chemical species. The GWT Model is designed to work with the Groundwater Flow (GWF) Model for MODFLOW 6, which simulates transient, three-dimensional groundwater fow. The version of the GWT model documented here must use the same spatial discretization used by the GWF Model; however, that spatial discretization can be represented by regular MODFLOW grids consisting of layers, rows, and columns, or by more general unstructured grids. The GWT Model simulates (1) advective transport, (2) the combined hydrodynamic dispersion processes of velocity-dependent mechanical dispersion and molecular diffusion, (3) adsorption and absorption (collectively referred to as sorption) of solutes by the aquifer matrix, (4) transfer between the mobile domain and one or more immobile domains, (5) frst-or zero-order solute decay or production, (6) mixing from groundwater sources and sinks, and (7) direct addition of solute mass. The GWT Model can also represent advective solute transport through advanced package features, such as streams, lakes, multi-aquifer wells, and the unsaturated zone. If the GWF Model application uses the Water Mover (MVR) Package to connect fow packages, then solute transport between these packages can also be represented. The transport processes described in this report have been implemented in a fully implicit manner and are solved in a system of equations using iterative numerical methods. The present version of the GWT Model for MODFLOW 6 does not have an option to calculate steady-state transport solutions; if a steady-state solution is required, then transient evolution of the solute must be represented using multiple time steps until no further changes in solute concentrations are detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6A61","usgsCitation":"Langevin, C.D., Provost, A.M., Panday, Sorab, and Hughes, J.D., 2022, Documentation for the MODFLOW 6 Groundwater Transport Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A61, 56 p., https://doi.org/10.3133/tm6A61.","productDescription":"Report: vi, 56 p.; Software Release","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120850","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":396637,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A62","text":"Techniques and Methods 6-A62","linkHelpText":"- Documentation for the Skeletal Storage, Compaction, and Subsidence (CSUB) Package of MODFLOW 6"},{"id":396666,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A57","text":"Techniques and Methods 6-A57","linkHelpText":"- Documentation for the MODFLOW 6 framework"},{"id":396665,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A56","text":"Techniques and Methods 6-A56","linkHelpText":"- Documentation for the “XT3D” option in the Node Property Flow (NPF) Package of MODFLOW 6"},{"id":396664,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A55","text":"Techniques and Methods 6-A55","linkHelpText":"- Documentation for the MODFLOW 6 Groundwater Flow Model"},{"id":396635,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/a61/coverthb2.jpg"},{"id":396636,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/a61/tm6a61.pdf","text":"Report","size":"3.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-A61"},{"id":396638,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/F76Q1VQV","text":"USGS software release","linkHelpText":"- MODFLOW 6: USGS Modular Hydrologic Model"}],"contact":"Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 411
Reston, VA 20192-0002
Coastal marshes are globally important, carbon dense ecosystems simultaneously maintained and threatened by sea-level rise. Warming temperatures may increase wetland plant productivity and organic matter accumulation, but temperature-modulated feedbacks between productivity and decomposition make it difficult to assess how wetlands and their thick, organic rich soils will respond to climate warming. Here, we actively increased aboveground plant-surface and below-ground soil temperatures in two marsh plant communities, and found that a moderate amount of warming (1.7°C above ambient temperatures) consistently maximized root growth, marsh elevation gain, and below-ground carbon accumulation. Marsh elevation loss observed at higher temperatures was associated with increased carbon mineralization and increased microtopographic heterogeneity, a potential early warning signal of marsh drowning. Maximized elevation and below-ground carbon accumulation for moderate warming scenarios uniquely suggest linkages between metabolic theory of individuals and landscape-scale ecosystem resilience and function, but our work indicates nonpermanent benefits as global temperatures continue to rise.
Deep learning (DL) models can accurately predict many hydrologic variables including streamflow and water temperature; however, these models have typically predicted hydrologic variables independently. This study explored the benefits of modeling two interdependent variables, daily average streamflow and daily average stream water temperature, together using multi-task DL. A multi-task scaling factor controlled the relative contribution of the auxiliary variable's error to the overall loss during training. Our experiments examined the improvement in prediction accuracy of the multi-task approach using paired streamflow and water temperature data from sites across the conterminous United States. Our results showed that for 56 out of 101 sites, the best performing multi-task models performed better overall than the single-task models in terms of Nash-Sutcliffe efficiency for predicting streamflow with single-site models. For 43 sites, the best multi-task, single-site models made no significant difference in predicting streamflow. The multi-task approach had a smaller effect when applied to a model trained with data from 101 sites together, significantly improving performance for only 17 sites. The multi-task scaling factor was consequential in determining to what extent the multi-task approach was beneficial. A naïve selection of this factor led to significantly worse-performing models for 3 of 101 sites when predicting streamflow as the primary variable, and 47 of 53 sites when predicting stream temperature as the primary variable. We conclude that a multi-task approach can make more accurate predictions by leveraging information from interdependent hydrologic variables, but only for some sites, variables, and model configurations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR030138","usgsCitation":"Sadler, J.M., Appling, A.P., Read, J., Oliver, S.K., Jia, X., Zwart, J.A., and Kumar, V., 2022, Multi-task deep learning of daily streamflow and water temperature: Water Resources Research, v. 58, no. 4, e2021WR030138, 18 p., https://doi.org/10.1029/2021WR030138.","productDescription":"e2021WR030138, 18 p.","ipdsId":"IP-129032","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":448611,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr030138","text":"Publisher Index Page"},{"id":386338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":817232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":817236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":817237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229180,"text":"70229180 - 2022 - Assessing mineral supply concentration from different perspectives through a case study of zinc","interactions":[],"lastModifiedDate":"2022-10-31T14:03:16.051554","indexId":"70229180","displayToPublicDate":"2022-03-02T11:25:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5502,"text":"Mineral Economics","onlineIssn":"2191-2211","printIssn":"2191-2203","active":true,"publicationSubtype":{"id":10}},"title":"Assessing mineral supply concentration from different perspectives through a case study of zinc","docAbstract":"Increasing demand for nonfuel mineral commodities has increased concerns regarding the reliability of their supplies. “Criticality” assessments over the past decade have attempted to capture this concern through a set of indicators, the most common of which quantifies the risk associated with market concentration by applying the Herfindahl-Hirschman Index (HHI) to the world production of a given commodity by country in a given year. Although this approach is useful, it inherently assumes that all of world production is available to the market and is thus potentially at risk. In this analysis, the HHI, as well as HHI weighted by country governance, is calculated for mined and refined zinc using the standard approach of using all world production data and comparing that to the HHI when using the best estimate of what is available to the world market. The results indicate that although the HHI of both mined and refined zinc world production has increased markedly over the past decade, the HHI for what is available to the market for mined and refined zinc has remained relatively constant and low, which is indicative of minimal supply risk. This is mainly owing to the fact that a large and increasing share of the world’s mined and refined zinc production comes from China, but that production supplies domestic consumption as well as small amounts of exports. As a result, the zinc materials that are available to the world market outside of China are produced by a relatively large and diverse set of countries. Although these analyses are specific to zinc, they are likely to be comparable for other commodities of which the largest producers are also the largest consumers and highlight the importance of examining different perspectives in criticality assessments.","language":"English","publisher":"Springer","doi":"10.1007/s13563-021-00291-2","usgsCitation":"Thomas, C.L., Nassar, N.T., and DeYoung, J., 2022, Assessing mineral supply concentration from different perspectives through a case study of zinc: Mineral Economics, v. 35, p. 6067-616, https://doi.org/10.1007/s13563-021-00291-2.","productDescription":"10 p.","startPage":"6067","endPage":"616","ipdsId":"IP-101409","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":448614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13563-021-00291-2","text":"Publisher Index Page"},{"id":396657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2022-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Christine L. 0000-0002-1391-6072","orcid":"https://orcid.org/0000-0002-1391-6072","contributorId":287564,"corporation":false,"usgs":false,"family":"Thomas","given":"Christine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":836874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nassar, Nedal T. 0000-0001-8758-9732 nnassar@usgs.gov","orcid":"https://orcid.org/0000-0001-8758-9732","contributorId":197864,"corporation":false,"usgs":true,"family":"Nassar","given":"Nedal","email":"nnassar@usgs.gov","middleInitial":"T.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":836875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeYoung, John H. Jr. jdeyoung@usgs.gov","contributorId":190728,"corporation":false,"usgs":true,"family":"DeYoung","given":"John H.","suffix":"Jr.","email":"jdeyoung@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":836925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228690,"text":"gip213 - 2022 - Visit the U.S. Geological Survey's National Water Dashboard","interactions":[],"lastModifiedDate":"2022-03-03T11:54:44.829334","indexId":"gip213","displayToPublicDate":"2022-03-02T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"213","displayTitle":"Visit the U.S. Geological Survey’s National Water Dashboard","title":"Visit the U.S. Geological Survey's National Water Dashboard","docAbstract":"The U.S. Geological Survey National Water Dashboard supplies critical information to decision makers, emergency managers, and the public during extreme hydrologic events (such as droughts and floods) and during normal hydrologic conditions. It informs decision making that can help protect lives and property before and during extreme hydrologic events. The National Water Dashboard draws upon the extensive site-specific hydrologic data housed in the U.S. Geological Survey National Water Information System database (https://doi.org/10.5066/F7P55KJN) and also links to the U.S. Geological Survey WaterAlert system, which provides users with instant and customized updates about water conditions. Overall, the National Water Dashboard is part of the U.S. Geological Survey's effort to respond to 21st century science needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip213","usgsCitation":"Miller, M.P., Burley, T.E., and McCallum, B.E., 2022, Visit the U.S. Geological Survey's National Water Dashboard: U.S. Geological Survey General Information Product 213, 2 p., https://doi.org/10.3133/gip213.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-127330","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":396097,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/213/coverthb.jpg"},{"id":396098,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/213/gip213.pdf","text":"Report","size":"319 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 213"}],"contact":"Associate Director, Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey National Water Dashboard supplies critical information to decision makers, emergency managers, and the public during extreme hydrologic events (such as droughts and floods) and during normal hydrologic conditions. It informs decision making that can help protect lives and property before and during extreme hydrologic events. The National Water Dashboard draws upon the extensive site-specific hydrologic data housed in the U.S. Geological Survey National Water Information System database (https://doi.org/10.5066/F7P55KJN) and also links to the U.S. Geological Survey WaterAlert system, which provides users with instant and customized updates about water conditions. Overall, the National Water Dashboard is part of the U.S. Geological Survey's effort to respond to 21st century science needs.
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Hydroclimate on ‘Uvea (Wallis et Futuna) is controlled by rainfall associated with the South Pacific Convergence Zone (SPCZ), the southern hemisphere's largest precipitation feature. To extend the short observational precipitation record, the hydrogen isotopic composition of the algal lipid biomarker dinosterol (δ2Hdinosterol) was measured in sediment cores from two volcanic crater lakes on ‘Uvea. The modern lakes differ morphologically and chemically but both contain freshwater within the photic zone, support phytoplankton communities inclusive of dinosterol-producing dinoflagellates, and experience identical climate conditions. δ2Hdinosterol values track lake water isotope ratios, ultimately controlled in the tropics by precipitation amount and evaporative enrichment. However, in 88-m-deep Lac Lalolalo a steadily decreasing trend in sedimentary δ2Hdinosterol values from −227‰ around year 988 CE to modern values as low as −303‰, suggests this lake's evolution from an active volcanic setting to the present system strongly influenced δ2Hdinosterol values. Although current hydrology and water isotope systematics may now reflect precipitation and evaporation in this lake, the interaction between these processes and large changes in basin morphology, geochemistry, and hydrology obstruct the recovery of a climate signal from Lac Lalolalo's sedimentary δ2Hdinosterol records. This work emphasizes the importance of site replication and the use of complementary climate reconstruction tools, especially when using molecular proxies that may be sensitive to more than one environmental parameter. Contrary to its neighbor, duplicate δ2Hdinosterol records from 23-m-deep Lac Lanutavake varied between −277‰ and −297‰ and indicate slightly drier conditions during the time-period known as the Medieval Climate Anomaly (MCA, 950–1250 CE). The δ2Hdinosterol signal in Lac Lanutavake was muted compared to published records from ‘Upolu (Samoa) and Efate (Vanuatu) indicating that ‘Uvea's location is not as sensitive to precipitation variability at sites farther from the SPCZ central axis. Lithogenic runoff proxies combined with δ2Hdinosterol support the interpretation of a relatively dry MCA on ‘Uvea, ‘Upolu, and Efate, potentially due to less intense precipitation, a contracted, or a more zonally oriented SPCZ.
The endangered mountain yellow-legged frog (Rana muscosa) has been reduced to <10 isolated populations in the wild. Due to frequent catastrophic events (floods, droughts, wildfires), the recent dynamics of these populations have been erratic, making the future of the species highly uncertain. In 2018, a recovery plan was developed to improve the species status by reducing the impacts of various threats (predation, disease, habitat destruction), as well as reinforcing wild populations through the reintroduction of captive-bred frogs. The short-term goal stated in this plan was to reach a minimum of 20 populations of 50 adults each (hereafter, the 20/50 target), before the species can be considered for downlisting from the U.S. Endangered Species Act. However, there is no guarantee that this 20/50 target will be sufficient to ensure the species persistence in the long run. Using 19 years of mark-recapture data, we estimated populations' demographic trends and assessed the viability of R. muscosa from a starting state of 20 populations of 50 adults each (i.e., the downlisting criteria). Our results reveal that, from this 20/50 state, the species has high chances of persistence only at a short time horizon (50 years). Moreover, >80% of populations would be extinct 50 years later. Therefore, the species will not be able to persist without implementation of the reintroduction program. We found that it is more important to increase the number of suitable sites occupied by R. muscosa than to simply reinforce or augment existing populations. Expanding the current distribution by establishing new populations at suitable sites, even after the “20 populations” mark has been reached, would increase the likelihood of the species' persistence in the longer term.
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2022 - Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York","interactions":[],"lastModifiedDate":"2026-04-02T19:34:37.460842","indexId":"sir20215086","displayToPublicDate":"2022-03-02T10:40:00","publicationYear":"2022","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":"2021-5086","displayTitle":"Hydrogeology of Aquifers Within the Fairport-Lyons Channel System and Adjacent Areas in Wayne, Ontario, and Seneca Counties, New York","title":"Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York","docAbstract":"A hydrogeologic investigation was undertaken by the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, within the areas shown in the Macedon, Palmyra, Newark, and Lyons 7.5-minute quadrangle maps that include parts of Wayne, Ontario, and Seneca Counties in New York. The most productive zone of aquifers within the study area is associated with the Fairport-Lyons glacial-stream channel (hereinafter referred to as the “Fairport-Lyons channel”) in southern Wayne County and adjacent areas. The Fairport-Lyons channel is a west-east-oriented bedrock channel that once served as the outlet for glacial Lake Dawson, which occupied the Genesee Valley near Rochester during the Pleistocene. The Fairport-Lyons channel and intersecting subsidiary channels are hereinafter referred to as the “Fairport-Lyons channel system.” Glacial meltwater eroded this shallow channel network into the underlying bedrock, and the channels subsequently filled with interlayered glaciofluvial sand and gravel and fine-grained lacustrine deposits. These sand and gravel deposits provide the only large supplies of groundwater in Wayne County under unconfined and confined conditions and serve a population of over 20,000 through a combination of domestic and municipal water supply wells. The largest reported well yield, 1,200 gallons per minute, is from an industrial supply well near Newark, N.Y. Much of the sand and gravel within the Fairport-Lyons channel system is generally thinly saturated; however, in three areas—near Macedon, Newark, and Lyons, N.Y.—the saturated thickness of the aquifer is sufficient to support groundwater yields adequate for municipal and industrial use, in part because of induced infiltration from the Erie Canal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215086","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Reynolds, R.J., Heisig, P.M., and Linsey, K.S., 2022, Hydrogeology of aquifers within the Fairport-Lyons channel system and adjacent areas in Wayne, Ontario, and Seneca Counties, New York: U.S. Geological Survey Scientific Investigations Report 2021–5086, 15 p., 2 pls., https://doi.org/10.3133/sir20215086.","productDescription":"Report v, 15 p.; 2 Plates: 36.00 x 24.00 inches and 36.00 x 60.00 inches; Data Release","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070043","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":502111,"rank":9,"type":{"id":36,"text":"NGMDB Index 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E–E'"},{"id":396440,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5086/sir20215086_plate01.pdf","text":"Plate 1","size":"63.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5086 Plate 1","linkHelpText":"- Surficial geologic map of the Fairport-Lyons channel-system aquifer and adjacent areas in Wayne, Ontario, and Seneca Counties, New York [layered pdf; to toggle layers, download the file (right-click and select \"Save link as...\") and open it with Adobe Acrobat Reader]"},{"id":396653,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215086/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":396445,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5086/images/"},{"id":396439,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N3JVAQ","text":"USGS data release","description":"USGS data 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New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Understanding recruitment dynamics is an essential part of effective fisheries management, whether the focus is on conservation, harvest policy development, or invasive species control. We developed a model that estimates lake-wide Ricker stock-recruitment relations for invasive sea lampreys (Petromyzon marinus) in each of the five Laurentian Great Lakes to inform future control efforts. We fit adult-to-adult models, taking advantage of a long time series of lake-wide, adult, sea lamprey abundance estimates. We incorporated proportional contributions at age for the stock as well as additional explanatory variables sea lamprey weight, as a surrogate for fecundity, and lampricide quantity applied, as a surrogate for anthropogenic mortality, to explain residual recruitment variability. The best model incorporated equal cohort contributions from the adult stock (that matured 5, 6, and 7 years prior to recruitment), a single productivity parameter (
Glen Torridon is a topographic trough located on the slope of Aeolis Mons, Gale crater, Mars. It corresponds to what was previously referred to as the “clay-bearing unit”, due to the relatively strong spectral signatures of clay minerals (mainly ferric smectites) detected from orbit. Starting in January 2019, the Curiosity rover explored Glen Torridon for more than 700 sols (Martian days). The objectives of this campaign included acquiring a detailed understanding of the geologic context in which the clay minerals were formed and determining the intensity of aqueous alteration experienced by the sediments. Here, we present the major-element geochemistry of the bedrock as analyzed by the ChemCam instrument. Our results reveal that the two main types of bedrock exposures identified in the lower part of Glen Torridon are associated with distinct chemical compositions (K-rich and Mg-rich), for which we are able to propose mineralogical interpretations. Moreover, the topmost stratigraphic member exposed in the region displays a stronger diagenetic overprint, especially at two locations close to the unconformable contact with the overlying Stimson formation, where the bedrock composition significantly deviates from the rest of Glen Torridon. Overall, the values of the Chemical Index of Alteration determined with ChemCam are elevated by Martian standards, suggesting the formation of clay minerals through open system weathering. However, there is no indication that the alteration was stronger than in some terrains previously visited by Curiosity, which in turn implies that the enhanced orbital signatures are mostly controlled by non-compositional factors.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JE007103","usgsCitation":"Dehouck, E., Cousin, A., Mangold, N., Frydenvang, J., Gasnault, O., Forni, O., Rapin, W., Gasda, P.J., Caravaca, G., David, G., Bedford, C.C., Lasue, J., Meslin, P., Rammelkamp, K., Desjardins, M., Le Mouelic, S., Thorpe, M.T., Fox, V.K., Bennett, K.A., Bryk, A., Lanza, N.L., Maurice, S., and Wiens, R.C., 2022, Bedrock geochemistry and alteration history of the clay-bearing Glen Torridon region of Gale crater, Mars: Journal of Geophysical Research E: Planets, v. 127, no. 12, e2021JE007103, 29 p., https://doi.org/10.1029/2021JE007103.","productDescription":"e2021JE007103, 29 p.","ipdsId":"IP-134173","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":448627,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021je007103","text":"External 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mussels","interactions":[],"lastModifiedDate":"2025-08-28T14:09:03.594606","indexId":"70270788","displayToPublicDate":"2022-03-02T09:01:08","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-141-2022","title":"Brook Floater restoration: Identifying locations to reintroduce or augment populations with propagated mussels","docAbstract":"In February 2020, we held a workshop where we sought to identify where states should reintroduce or augment brook floater to minimize the probability of extinction within a state. We focused on Massachusetts and Connecticut, two states with only a few, small populations still extant, that likely need population restoration to prevent statewide extirpation. We identified that restoration actions aimed at redundancy (number of populations), representation (number of occupied basins), and resiliency (population size) were constrained by resource availability such as limited broodstock , staff time, and budgets. Optimal restoration locations depended on habitat conditions, the status (viability) of nearby mussel populations, population size (number of individuals), and the location within watersheds; all important considerations in addressing population persistence. Restoration actions also accounted for the risk of disease transmission among mussels and fish, and the genetic health and diversity of mussel populations. The workshop identified the multiple, compounding uncertainties related to population restoration, identified information gaps critical to decision making, and charted a path forward to make decisions given uncertainties. The optimization approach developed can be used to select specific watersheds for restoration in any state, province, or region and can easily be adapted as new information becomes available.
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