The Midcontinent Rift System (MRS) is expressed geophysically by a semi-linear, regional gravity high that trends across the Midcontinent and Great Lakes region of North America. The gravity high is interrupted by two prominent, semi-circular gravity lows, which have been interpreted from modeling and seismic-reflection sections as basement highs of Archean granite (Allen et al., 1997). One is centered southwest of Isle Royale in western Lake Superior (Grand Marais ridge) and the other over Bayfield Peninsula (White’s Ridge). Allen et al. (1997) suggest that the Archean granite highs were pre-rift features that remained high while lava basins of the MRS subsided adjacent to them. Hart et al. (1994) questioned the presence of granitic rocks underlying Grand Marais ridge (GMR) because heat flow measurements there are much lower than is typical for Archean granitic upper crust. They argued that the region must instead be underlain by rocks of low radiogenic heat production, such as gabbro, extending to at least 15 km depth. However, gabbro has high densities and would not produce the observed gravity low. Thus, the geophysical observations appear contradictory.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology: Proceedings 2021","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute of Lake Superior Geology","usgsCitation":"Grauch, V.J., and Heller, S.J., 2021, Integration of geophysical evidence suggests that anorthosite composes a significant portion of Grand Marais ridge, an inferred basement high in western Lake Superior, in Institute on Lake Superior Geology: Proceedings 2021, v. 67, p. 29-30.","productDescription":"2 p.","startPage":"29","endPage":"30","ipdsId":"IP-128430","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":387398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387391,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/items/show/3063"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.340576171875,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.56170075451973\n ],\n [\n -89.26391601562499,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.96785877999251\n ],\n [\n -90.340576171875,\n 47.56170075451973\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.01074218749999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 46.76244305208004\n ],\n [\n -90.28564453124999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 47.249406957888446\n ],\n [\n -91.01074218749999,\n 46.76244305208004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grauch, V. J. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":152256,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":819754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heller, Samuel J. 0000-0002-6579-5620 sheller@usgs.gov","orcid":"https://orcid.org/0000-0002-6579-5620","contributorId":201350,"corporation":false,"usgs":true,"family":"Heller","given":"Samuel","email":"sheller@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819755,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222466,"text":"70222466 - 2021 - Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","interactions":[],"lastModifiedDate":"2021-07-30T14:22:37.638537","indexId":"70222466","displayToPublicDate":"2021-05-31T09:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Field Evaluation of an Improved Solid TFM Formulation for Use in Treating Small Tributary Streams","title":"Field evaluation of an improved solid TFM formulation for use in treating small tributary streams","docAbstract":"A solid lampricide formulation containing 23% 3-trifluoromethyl-4-nitrophenol (TFM) as the active ingredient was developed in the mid-1980s for use in small tributaries of dendritic streams during routine treatments to kill larval sea lamprey. This TFM bar formulation was designed to use a matrix of commercially prepared surfactants that would dissolve and slowly release their TFM payload over an 8–10-hour period. Although this formulation has proven useful, several matrix surfactants have been discontinued, resulting in the need to reformulate the TFM bar multiple times. Maintaining acceptable performance of the TFM bars while reformulating has been challenging. As a result, an experimental surfactant-free tableted TFM formulation was developed as a potential TFM bar replacement. Release of TFM from the tablet formulation was evaluated in four independent experimental applications made over varied substrates in three small tributaries of the Ford River (Delta County, Michigan). For each tributary, TFM release from tablets was modeled using exponential decay curves and the time required to release 25, 50, 75 and 90% of the TFM tablets was calculated. Differences in water-quality properties were detected using one-way analysis of variance tests, and post-hoc Tukey Honest Significant Difference tests were used to determine which water-quality properties differed among the trials. The influences of water temperature and water velocity on the release of TFM from the tablets has been previously reported; however, in this study substrate type also appeared to be an indicator of TFM release. In this study the performance of the TFM tablets appeared acceptable; however, it may be beneficial to conduct additional investigations to determine storage stability and handling durability as well as to identify potential challenges with mass production.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Luoma, J.A., Robertson, N., Schueller, J., Schloesser, N., Johnson, T., Severson, T.J., Meulemans, M.J., and Muelemans, E., 2021, Field evaluation of an improved solid TFM formulation for use in treating small tributary streams, 21 p.","productDescription":"21 p.","ipdsId":"IP-127807","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":387600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387559,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/pubs/pdfs/research/reports/2020_LUO_760150.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Nicholas","contributorId":237024,"corporation":false,"usgs":false,"family":"Robertson","given":"Nicholas","email":"","affiliations":[{"id":18886,"text":"Northland College","active":true,"usgs":false}],"preferred":false,"id":820121,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schueller, Justin R. 0000-0002-7102-3889","orcid":"https://orcid.org/0000-0002-7102-3889","contributorId":213527,"corporation":false,"usgs":true,"family":"Schueller","given":"Justin","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schloesser, Nicholas 0000-0002-3815-5302","orcid":"https://orcid.org/0000-0002-3815-5302","contributorId":237025,"corporation":false,"usgs":true,"family":"Schloesser","given":"Nicholas","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820123,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Todd 0000-0003-2152-8528","orcid":"https://orcid.org/0000-0003-2152-8528","contributorId":261519,"corporation":false,"usgs":true,"family":"Johnson","given":"Todd","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820124,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820125,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meulemans, Matthew J 0000-0003-4584-8737","orcid":"https://orcid.org/0000-0003-4584-8737","contributorId":261521,"corporation":false,"usgs":true,"family":"Meulemans","given":"Matthew","email":"","middleInitial":"J","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820126,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muelemans, Erica","contributorId":261523,"corporation":false,"usgs":false,"family":"Muelemans","given":"Erica","email":"","affiliations":[{"id":52865,"text":"Northland College, Ashland, WI","active":true,"usgs":false}],"preferred":false,"id":820127,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223180,"text":"70223180 - 2021 - Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","interactions":[],"lastModifiedDate":"2021-08-17T14:13:12.185743","indexId":"70223180","displayToPublicDate":"2021-05-31T09:03:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5856,"text":"Regional Protocol Framework","active":true,"publicationSubtype":{"id":1}},"title":"Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts","docAbstract":"Alaska provides habitat for 143 species of landbirds that occur regularly in the state, about half of which breed predominantly north of the border between the contiguous United States and Canada. The road-based North American Breeding Bird Survey (BBS) provides some data on population trends in Alaska, but most northern populations are inadequately monitored by this program because of a paucity of roads. To remedy this deficiency, Boreal Partners in Flight developed the Alaska Landbird Monitoring Survey (ALMS) to monitor breeding populations of landbirds in off-road areas of Alaska in tandem with data collected from the roadside BBS. The primary objective of ALMS is to monitor long-term population trends of landbirds and other species that can be monitored by diurnal point counts during the breeding season, including many shorebirds and aquatic birds. A secondary objective is to estimate landbird densities by habitat, which can be used to model avian distribution and abundance across Alaska. ALMS is a collaborative program whereby agencies and other entities conduct standardized surveys of breeding birds and their habitats on the lands they manage and then contribute the data to the U.S. Geological Survey Alaska Science Center for storage and analysis.
The short-term implementation goal of ALMS is to monitor birds systematically within each of 100 randomly selected survey blocks, thereby matching the number of BBS surveys conducted in each of Alaska's five Bird Conservation Regions (BCRs). Each block has a mini-grid of 15−25 points that are surveyed biennially, with half of the blocks surveyed in alternating years. Survey blocks are stratified by accessibility and cost-effectiveness. Refuges may opt to limit sites to those accessible by foot, vehicle, boat, or fixed-wing aircraft, as these can be surveyed more inexpensively and reliably over time. Observers survey each point within a survey block for birds using a 10-min point count once per summer on a biennial basis. They collect corresponding habitat data during the first visit and at subsequent 10-year intervals or whenever a disturbance (e.g., fire, wind) has caused a significant change. USGS analyzes ALMS data jointly with BBS data to test for differences between off-road and roadside areas and to increase power to detect statewide trends. Additional blocks can be surveyed in areas that are more difficult and expensive to access as resources become available in the future. Long-term monitoring enables detection of change in bird populations in relation to fire, disease and insect damage, resource development, climate-related change, and other landscape-level disturbances across Alaska. Results from ALMS can also help prioritize conservation and research towards species before they become endangered and require expensive recovery programs.
","language":"English","publisher":"U.S. Fish & Wildlife Service","usgsCitation":"Handel, C.M., Matsuoka, S.M., Cady, M.N., and Granfors, D.A., 2021, Alaska landbird montoring survey: Alaska regional protocol framework for monitoring landbirds using point counts: Regional Protocol Framework, vi, 66 p.","productDescription":"vi, 66 p.","ipdsId":"IP-113748","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":387999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387969,"type":{"id":15,"text":"Index Page"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/114719"}],"country":"United States","state":"Alaska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-141.0007667541504,69.64681951728146],[-141.064453125,69.80172356231073],[-141.767578125,69.96043926902489],[-142.734375,70.1478274118401],[-143.26171875,70.25945200030638],[-144.99755859375,70.1925497583889],[-146.14013671875,70.21487465331137],[-147.43652343749997,70.32613725493573],[-148.40332031249997,70.51024068514326],[-149.47998046875,70.63448406630856],[-149.85351562499997,70.63448406630856],[-150.64453125,70.59802116106809],[-151.611328125,70.61261423801925],[-151.8310546875,70.7724429742589],[-152.02880859375,70.90226826757711],[-152.666015625,71.0098110139634],[-153.52294921875,71.05979781529196],[-154.31396484375,70.95969716686398],[-154.70947265625,71.20191973293133],[-155.41259765625,71.3219146980122],[-156.46728515625,71.45515260247822],[-157.10449218749997,71.34301347171373],[-157.58789062499997,71.21607526596131],[-157.91748046875,70.99550574822297],[-158.62060546875,70.9883492241249],[-159.30175781249997,70.98119010476937],[-159.98291015625,70.94535555009823],[-160.51025390625,70.73622993891799],[-160.90576171875,70.58341752317065],[-161.5869140625,70.45150843439349],[-161.78466796875,70.45885925640687],[-162.5537109375,70.34092679475283],[-163.05908203125,70.09552886456429],[-163.388671875,69.81689109911446],[-163.564453125,69.51914693717981],[-164.02587890625,69.15474044269264],[-164.90478515625,69.03714171275197],[-165.69580078124997,68.97416358340674],[-166.26708984375,69.01354605132325],[-166.376953125,68.80004113882613],[-166.66259765624997,68.5443150407769],[-167.1240234375,68.39918004344189],[-166.61865234375,68.17155518732503],[-166.5087890625,67.99110834539984],[-165.87158203125,67.8672645403614],[-164.61914062499997,67.47492238478702],[-164.24560546874997,67.23806155909902],[-164.091796875,67.02458758377148],[-163.10302734375,66.87834504307976],[-163.05908203125,66.73990169639414],[-162.66357421875,66.58321725728175],[-162.333984375,66.48697584176404],[-162.3779296875,66.34632215978135],[-163.2568359375,66.31103501145373],[-163.19091796875,66.55700652350038],[-163.76220703124997,66.73990169639414],[-164.46533203125,66.69647781801481],[-165.30029296875,66.55700652350038],[-166.1572265625,66.41674787052298],[-166.9482421875,66.24916310923315],[-167.3876953125,66.01801815922045],[-168.42041015625,65.56754970214311],[-168.02490234375,65.33017791526855],[-167.45361328125,65.18303007291382],[-166.9921875,64.86760781632728],[-166.7724609375,64.49172504435471],[-165.69580078124997,64.24459476798195],[-164.59716796875,64.29229248039543],[-164.13574218749997,64.26368374017731],[-163.49853515625,64.18724867664994],[-162.5537109375,64.27322328178595],[-161.82861328124997,64.24459476798195],[-161.52099609375,63.93737246791484],[-163.125,63.68524808030715],[-163.93798828125,63.41119772365924],[-164.5751953125,63.32254947641308],[-165.41015625,63.15435519659187],[-165.78369140625,62.75472592723178],[-166.26708984375,62.42090322195164],[-166.5966796875,62.155240711732425],[-166.48681640625,61.616843178481375],[-166.2451171875,61.23853141060282],[-165.849609375,60.8663124746226],[-166.5966796875,60.56537850464181],[-167.34375,60.468050120874615],[-167.80517578125,60.20707506634915],[-167.8271484375,60.09771842541544],[-167.89306640624997,59.93300042374631],[-167.03613281249997,59.712097173322924],[-166.640625,59.61221219518693],[-165.95947265624997,59.60109549032134],[-165.47607421874997,59.74532608213611],[-165.10253906249997,59.95501026206206],[-164.794921875,59.987997631212224],[-164.72900390624997,59.7563950493563],[-164.46533203125,59.54545678424146],[-163.8720703125,59.54545678424146],[-163.14697265625,59.60109549032134],[-162.26806640625,59.62332522313024],[-162.20214843749997,59.17592824927136],[-162.35595703125,58.81374171570782],[-162.57568359375,58.6769376725869],[-162.09228515625,58.39019698411526],[-161.455078125,58.39019698411526],[-160.68603515625,58.44773280389084],[-160.1806640625,58.516651799363785],[-159.71923828125,58.58543569119917],[-159.43359375,58.47072082411973],[-159.08203125,58.33256713195789],[-158.55468749999997,58.286395482881034],[-158.44482421874997,58.619777025081675],[-157.60986328125,58.52812515905843],[-158.00537109375,58.00809779306888],[-158.48876953125,57.468589192089354],[-159.49951171875,56.84897198026975],[-161.0595703125,56.389583525613055],[-164.9267578125,54.97761367069628],[-165.9814453125,54.470037612805754],[-168.55224609375,53.73571574532637],[-173.232421875,52.92215137976296],[-175.62744140624997,52.3755991766591],[-177.86865234375,52.13348804077147],[-178.9453125,50.98609893339354],[-178.00048828125,51.440312757160115],[-176.8359375,51.467696956223364],[-175.36376953125,51.7406361640977],[-171.826171875,52.119998657638156],[-167.62939453124997,52.9883372533954],[-166.728515625,53.186287573913305],[-165.9375,53.553362785528094],[-165.30029296875,53.76170183021049],[-164.3115234375,54.149567212540525],[-163.89404296875,54.29088164657006],[-163.3447265625,54.18815548107151],[-162.26806640625,54.07228265560388],[-162.09228515625,54.3549556895541],[-161.89453125,54.7246201949245],[-161.0595703125,54.80068486732233],[-160.400390625,54.67383096593114],[-159.19189453125,54.61025498157912],[-159.14794921875,55.07836723201515],[-158.79638671875,55.429013452407396],[-157.58789062499997,55.825973254619015],[-155.7421875,55.541064956111036],[-154.62158203125,56.01066647040695],[-153.47900390625,56.43820369358165],[-151.45751953125,57.397624055000456],[-151.4794921875,58.07787626787517],[-151.45751953125,58.75680543225761],[-149.74365234374997,59.38917842312835],[-148.51318359375,59.63443457494949],[-146.689453125,59.355596110016315],[-144.51416015625,59.75086102411168],[-144.3109130859375,59.87239799228177],[-143.8330078125,59.968758992382334],[-143.0694580078125,60.031929699115615],[-141.5533447265625,59.842055288480076],[-140.9051513671875,59.68160832698723],[-140.020751953125,59.478568831926395],[-139.1693115234375,59.234986238722],[-138.82873535156247,59.09138238455909],[-138.3233642578125,58.96983560365735],[-138.1146240234375,58.862064179600374],[-138.076171875,58.722598828043374],[-136.9775390625,58.19387126497797],[-136.56005859375,57.7862326105289],[-135.966796875,57.33838126552897],[-136.03271484375,57.052681978717494],[-135.81298828125,56.92099675839107],[-134.571533203125,55.8845546603819],[-134.2034912109375,55.56592203025787],[-133.8958740234375,55.263468250921285],[-133.7530517578125,55.06264118216743],[-133.6102294921875,54.64523407607479],[-133.2421875,54.635697306063854],[-130.6171417236328,54.70637513489091],[-130.62950134277344,54.72422365048395],[-130.62606811523438,54.73651472417763],[-130.65765380859375,54.762274228176494],[-130.62950134277344,54.78247406031503],[-130.5663299560547,54.79237225560392],[-130.49697875976562,54.82877675365454],[-130.42282104492188,54.87423625974835],[-130.34591674804688,54.91569803760518],[-130.27244567871094,54.97288463122321],[-130.18661499023438,55.062247951730015],[-130.18043518066406,55.091729515360875],[-130.15090942382812,55.12393783348962],[-130.14747619628906,55.14160209881279],[-130.10284423828125,55.19219635238084],[-129.97169494628906,55.28146181651345],[-129.97581481933594,55.30022902025666],[-130.02044677734375,55.33890835596374],[-130.0396728515625,55.45043679812318],[-130.0884246826172,55.496749338303694],[-130.12825012207028,55.58144971869657],[-130.10971069335938,55.68223010941079],[-130.14816284179688,55.71473455012689],[-130.15296936035156,55.7649857705176],[-130.12550354003906,55.80475427021683],[-130.0843048095703,55.82134464477078],[-130.00465393066406,55.90573012454021],[-130.00465393066406,55.9130425993163],[-130.0190734863281,55.912657766599715],[-130.00259399414062,56.00605986001467],[-130.10421752929688,56.12297419573329],[-130.24635314941406,56.09693875609652],[-130.3479766845703,56.12794955397159],[-130.42556762695312,56.14134155069025],[-130.4674530029297,56.24373146827144],[-130.55740356445312,56.249454174583384],[-130.5677032470703,56.25479459547735],[-130.62400817871094,56.2685236855868],[-130.78262329101562,56.36715174252849],[-131.08612060546875,56.40668363558357],[-131.16989135742188,56.44883107459549],[-131.473388671875,56.551913918713375],[-131.58119201660156,56.61204220477141],[-131.8352508544922,56.59843662755775],[-131.85997009277344,56.702620872371355],[-131.89979553222656,56.75347577609789],[-131.87232971191406,56.805765643008264],[-132.12432861328122,56.87374615531272],[-132.0467376708984,57.04521234171931],[-132.3687744140625,57.09149987857074],[-132.2472381591797,57.211056900559335],[-132.3680877685547,57.347273783306676],[-132.55210876464844,57.49516565182901],[-132.65853881835938,57.61562391374733],[-132.75466918945312,57.69680911844304],[-132.8693389892578,57.83853792318956],[-133.06983947753906,58.00082136594698],[-133.17283630371094,58.15404059343076],[-133.34518432617188,58.27628739957773],[-133.45985412597656,58.38731772556939],[-133.37608337402344,58.430481925680034],[-133.70567321777344,58.611194853078764],[-133.83956909179685,58.730440812979516],[-134.25979614257812,58.861354043320055],[-134.3360137939453,58.92414471817596],[-134.3140411376953,58.962755708753306],[-134.4060516357422,58.978683427688686],[-134.38133239746094,59.03878841190553],[-134.44656372070312,59.08820785301446],[-134.48501586914062,59.13121539881386],[-134.56329345703125,59.130510792073984],[-134.67933654785156,59.191757369765085],[-134.70130920410156,59.24973478117606],[-134.95742797851562,59.279914277804906],[-135.02883911132812,59.34649517787861],[-134.9897003173828,59.3877798237848],[-135.10093688964844,59.42622028594434],[-135.07827758789062,59.45275367774563],[-135.0274658203125,59.47473269180728],[-135.03021240234375,59.564245132658975],[-135.11810302734372,59.62367244601488],[-135.15586853027344,59.625061301654334],[-135.2190399169922,59.6632323288228],[-135.23345947265625,59.69650975428769],[-135.252685546875,59.69789559656873],[-135.36048889160156,59.73598378851403],[-135.4779052734375,59.79821644465919],[-135.94894409179688,59.6632323288228],[-136.1927032470703,59.63998787256213],[-136.34788513183594,59.60109549032134],[-136.25038146972656,59.56633207991906],[-136.24076843261716,59.55972296971678],[-136.24076843261716,59.52387204745182],[-136.3066864013672,59.46461714320982],[-136.36642456054688,59.4496126517294],[-136.47628784179688,59.46566371970234],[-136.46804809570312,59.28552611855346],[-136.49620056152344,59.27465233689575],[-136.4900207519531,59.26096748461385],[-136.5840911865234,59.166075318301345],[-136.8285369873047,59.16009179641602],[-136.8793487548828,59.13544273484683],[-137.28240966796875,59.0009698708429],[-137.449951171875,58.908900972391415],[-137.52548217773438,58.906418795609426],[-137.5000762939453,58.985760051467075],[-137.54127502441406,59.10478272378236],[-137.60787963867188,59.24376590151355],[-138.62617492675778,59.76746035005358],[-138.66600036621094,59.80961318716828],[-138.6797332763672,59.84481485969105],[-138.70582580566406,59.90650046741583],[-139.05258178710938,59.994179105518434],[-139.19952392578125,60.08950200748712],[-139.0711212158203,60.3187885497516],[-139.07386779785156,60.35243208301854],[-139.69253540039062,60.33544473468298],[-139.97955322265625,60.181818669034776],[-140.4595184326172,60.30858669066228],[-140.5199432373047,60.22003701633967],[-141.00128173828125,60.3058656567224],[-141.0007667541504,69.64681951728146]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-173.07586669921875,60.72157115165579],[-173.155517578125,60.69469537287745],[-173.15277099609375,60.64356945377967],[-173.08135986328125,60.61123754937553],[-173.04016113281247,60.58157148491742],[-173.08135986328125,60.53972302275651],[-173.089599609375,60.511343283202464],[-173.05938720703125,60.4788788301667],[-172.98248291015625,60.468050120874615],[-172.94677734374997,60.43689744859958],[-172.8424072265625,60.403001945865476],[-172.78472900390625,60.373144671593685],[-172.7105712890625,60.329667021005825],[-172.6611328125,60.3187885497516],[-172.5897216796875,60.309266913738156],[-172.49908447265625,60.31606836555203],[-172.4139404296875,60.3187885497516],[-172.35076904296875,60.3187885497516],[-172.30682373046872,60.29021531318375],[-172.2381591796875,60.29021531318375],[-172.17498779296875,60.30518536282736],[-172.2381591796875,60.333745513303114],[-172.34527587890625,60.378575303227215],[-172.364501953125,60.40164539086417],[-172.43041992187497,60.40571488624096],[-172.4798583984375,60.39757538658664],[-172.57598876953125,60.41249624776229],[-172.6556396484375,60.43689744859958],[-172.77374267578122,60.4788788301667],[-172.83416748046875,60.50052541051131],[-172.89459228515625,60.550527811064846],[-172.8863525390625,60.588316165776824],[-172.91656494140625,60.62606036274505],[-172.98797607421875,60.658377412327326],[-173.01544189453125,60.69469537287745],[-173.07586669921875,60.72157115165579]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-171.650390625,63.809167882566385],[-171.793212890625,63.82128765261384],[-171.80419921875,63.73147780336167],[-171.8426513671875,63.65601144183318],[-171.8865966796875,63.54365806976644],[-171.859130859375,63.42594585479083],[-171.7877197265625,63.34966546248425],[-171.62841796875,63.32501562217765],[-171.474609375,63.28306240110864],[-171.353759765625,63.29540792564745],[-171.2548828125,63.33980806067484],[-171.1395263671875,63.38413977217118],[-171.002197265625,63.389061297647125],[-170.760498046875,63.34966546248425],[-170.57373046875,63.32501562217765],[-170.41992187499997,63.27812271092345],[-170.343017578125,63.1989725264735],[-170.3594970703125,63.156835740093236],[-170.2496337890625,63.156835740093236],[-170.145263671875,63.156835740093236],[-170.0408935546875,63.14194929585152],[-169.9090576171875,63.087300267152735],[-169.8321533203125,63.03753005973634],[-169.7991943359375,62.990169510232555],[-169.8101806640625,62.95522304515911],[-169.74975585937497,62.922735326966595],[-169.617919921875,62.91523303947614],[-169.54650878906247,62.9502272814474],[-169.4915771484375,62.97270150065472],[-169.508056640625,62.99765260346662],[-169.4970703125,63.04251090966805],[-169.43664550781247,63.08978654472616],[-169.34326171874997,63.11712157280328],[-169.178466796875,63.13946747896222],[-169.1070556640625,63.14443090047572],[-168.958740234375,63.104699747121074],[-168.760986328125,63.112153479825004],[-168.67309570312497,63.203925767041305],[-168.662109375,63.26576978358972],[-168.7115478515625,63.3348780927218],[-168.92578125,63.366907787681754],[-169.07958984374997,63.366907787681754],[-169.25537109375,63.37183226679281],[-169.420166015625,63.376755901872734],[-169.5245361328125,63.389061297647125],[-169.6124267578125,63.43331707559086],[-169.705810546875,63.46278300222105],[-169.8211669921875,63.46523712749102],[-169.947509765625,63.48976680530999],[-170.0079345703125,63.59011870211632],[-170.0958251953125,63.658448979940175],[-170.2386474609375,63.704722429433225],[-170.4638671875,63.73390885572919],[-170.5902099609375,63.721751503619956],[-170.7659912109375,63.6779417467744],[-171.2164306640625,63.648697570849286],[-171.474609375,63.6779417467744],[-171.54052734375,63.75334975181205],[-171.650390625,63.809167882566385]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-170.40618896484375,57.022794415389725],[-170.3155517578125,57.043718234032625],[-170.22216796875,57.119841130872615],[-170.1947021484375,57.14518072479997],[-170.11505126953125,57.18985535714817],[-170.08209228515625,57.227042992549855],[-170.07110595703125,57.271618718194446],[-170.189208984375,57.23893512461504],[-170.2386474609375,57.22852971878346],[-170.32928466796875,57.22852971878346],[-170.3704833984375,57.22406936030381],[-170.49407958984375,57.20473490715757],[-170.41992187499997,57.12878649751151],[-170.364990234375,57.11387635258491],[-170.42266845703125,57.06910989239133],[-170.46112060546875,57.033257797376066],[-170.40618896484375,57.022794415389725]]]}},{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-169.8321533203125,56.62904228542147],[-169.8211669921875,56.60486209416893],[-169.7991943359375,56.586716786451156],[-169.71405029296875,56.565536245992064],[-169.71405029296875,56.551913918713375],[-169.63165283203125,56.51707901932375],[-169.56024169921875,56.515563731608296],[-169.5025634765625,56.553427752820355],[-169.43115234375,56.58369172128337],[-169.43664550781247,56.626020608371924],[-169.56024169921875,56.63055303322322],[-169.6783447265625,56.62450967912138],[-169.8321533203125,56.62904228542147]]]}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":821281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matsuoka, Steven M. 0000-0001-6415-1885 smatsuoka@usgs.gov","orcid":"https://orcid.org/0000-0001-6415-1885","contributorId":184173,"corporation":false,"usgs":true,"family":"Matsuoka","given":"Steven","email":"smatsuoka@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":821282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cady, Melissa N.","contributorId":173930,"corporation":false,"usgs":false,"family":"Cady","given":"Melissa","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":821283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Granfors, Diane A.","contributorId":174567,"corporation":false,"usgs":false,"family":"Granfors","given":"Diane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":821284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221725,"text":"70221725 - 2021 - Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide","interactions":[],"lastModifiedDate":"2021-12-10T16:36:17.553183","indexId":"70221725","displayToPublicDate":"2021-05-31T07:50:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide","docAbstract":"Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13777","usgsCitation":"Noss, R., Cartwright, J.M., Estes, D., Witsell, T., Elliott, G., Adams, D.S., Albrecht, M.A., Boyles, R., Comer, P., Doffitt, C., Hill, J.G., Hunter, W.C., Knapp, W.M., Marshall, M., Singhurst, J.R., Tracey, C., Walck, J.L., and Weakley, A., 2021, Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide: Conservation Biology, v. 35, no. 6, p. 1715-1724, https://doi.org/10.1111/cobi.13777.","productDescription":"10 p.","startPage":"1715","endPage":"1724","ipdsId":"IP-122143","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":452069,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/cobi.13777","text":"External Repository"},{"id":386890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Noss, Reed","contributorId":260710,"corporation":false,"usgs":false,"family":"Noss","given":"Reed","affiliations":[{"id":52646,"text":"Florida Institute for Conservation Science","active":true,"usgs":false}],"preferred":false,"id":818519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes, Dwayne","contributorId":260711,"corporation":false,"usgs":false,"family":"Estes","given":"Dwayne","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witsell, Theo","contributorId":258187,"corporation":false,"usgs":false,"family":"Witsell","given":"Theo","email":"","affiliations":[],"preferred":false,"id":818522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, Gregg","contributorId":260712,"corporation":false,"usgs":false,"family":"Elliott","given":"Gregg","email":"","affiliations":[{"id":52648,"text":"Southeastern Grasslands Initiative","active":true,"usgs":false}],"preferred":false,"id":818523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Daniel S. 0000-0001-9695-0577","orcid":"https://orcid.org/0000-0001-9695-0577","contributorId":258189,"corporation":false,"usgs":false,"family":"Adams","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":818524,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Albrecht, Matthew A. 0000-0002-1079-1630","orcid":"https://orcid.org/0000-0002-1079-1630","contributorId":213559,"corporation":false,"usgs":false,"family":"Albrecht","given":"Matthew","email":"","middleInitial":"A.","affiliations":[{"id":38790,"text":"Missouri Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":818525,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyles, Ryan 0000-0001-9272-867X","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":221983,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":818526,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Comer, Patrick","contributorId":191654,"corporation":false,"usgs":false,"family":"Comer","given":"Patrick","affiliations":[],"preferred":false,"id":818527,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Doffitt, Chris","contributorId":258191,"corporation":false,"usgs":false,"family":"Doffitt","given":"Chris","email":"","affiliations":[],"preferred":false,"id":818528,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hill, JoVonn G. 0000-0002-1892-7117","orcid":"https://orcid.org/0000-0002-1892-7117","contributorId":258193,"corporation":false,"usgs":false,"family":"Hill","given":"JoVonn","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":818529,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hunter, William C.","contributorId":258194,"corporation":false,"usgs":false,"family":"Hunter","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":818530,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Knapp, Wesley M. 0000-0002-5289-5649","orcid":"https://orcid.org/0000-0002-5289-5649","contributorId":258195,"corporation":false,"usgs":false,"family":"Knapp","given":"Wesley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":818531,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Marshall, Mike","contributorId":260713,"corporation":false,"usgs":false,"family":"Marshall","given":"Mike","affiliations":[{"id":52649,"text":"U.S Fish and Wildlife Service; Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":818532,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Singhurst, Jason R.","contributorId":258196,"corporation":false,"usgs":false,"family":"Singhurst","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":818533,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tracey, Christopher","contributorId":260714,"corporation":false,"usgs":false,"family":"Tracey","given":"Christopher","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":818534,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Walck, Jeffrey L. 0000-0002-8518-9900","orcid":"https://orcid.org/0000-0002-8518-9900","contributorId":258197,"corporation":false,"usgs":false,"family":"Walck","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":818535,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Weakley, Alan 0000-0003-2093-3767","orcid":"https://orcid.org/0000-0003-2093-3767","contributorId":197982,"corporation":false,"usgs":false,"family":"Weakley","given":"Alan","email":"","affiliations":[],"preferred":false,"id":818536,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70239001,"text":"70239001 - 2021 - Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model","interactions":[],"lastModifiedDate":"2022-12-20T13:15:41.956204","indexId":"70239001","displayToPublicDate":"2021-05-31T07:14:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12986,"text":"Spectrochimica Acta B","active":true,"publicationSubtype":{"id":10}},"title":"Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model","docAbstract":"We report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.
Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the potential to estimate surface flow velocities from satellite video of a large, sediment-laden river in Alaska via particle image velocimetry (PIV). In this setting, naturally occurring sediment boil vortices produced distinct water surface features that could be tracked from frame to frame as they were advected by the flow, obviating the need to introduce artificial tracer particles. In this study, we refined an end-to-end workflow that involved stabilization and geo-referencing, image preprocessing, PIV analysis with an ensemble correlation algorithm, and post-processing of PIV output to filter outliers and scale and geo-reference velocity vectors. Applying these procedures to image sequences extracted from satellite video allowed us to produce high resolution surface velocity fields; field measurements of depth-averaged flow velocity were used to assess accuracy. Our results confirmed the importance of preprocessing images to enhance contrast and indicated that lower frame rates (e.g., 0.25 Hz) lead to more reliable velocity estimates because longer capture intervals allow more time for water surface features to translate several pixels between frames, given the relatively coarse spatial resolution of the satellite data. Although agreement between PIV-derived velocity estimates and field measurements was weak (R2 = 0.39) on a point-by-point basis, correspondence improved when the PIV output was aggregated to the cross-sectional scale. For example, the correspondence between cross-sectional maximum velocities inferred via remote sensing and measured in the field was much stronger (R2 = 0.76), suggesting that satellite video could play a role in measuring river discharge. Examining correlation matrices produced as an intermediate output of the PIV algorithm yielded insight on the interactions between image frame rate and sensor spatial resolution, which must be considered in tandem. Although further research and technological development are needed, measuring surface flow velocities from satellite video could become a viable tool for streamflow monitoring in certain fluvial environments.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2021.652213","usgsCitation":"Legleiter, C.J., and Kinzel, P.J., 2021, Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river: Frontiers in Water, v. 3, 652213, 20 p., https://doi.org/10.3389/frwa.2021.652213.","productDescription":"652213, 20 p.","ipdsId":"IP-125455","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":452077,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2021.652213","text":"Publisher Index Page"},{"id":436332,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZY5LK1","text":"USGS data release","linkHelpText":"Satellite video and field measurements of flow velocity acquired from the Tanana River in Alaska and used for particle image velocimetry (PIV)"},{"id":386020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Nenana","otherGeospatial":"Tanana River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.21218872070312,\n 64.53486288126804\n ],\n [\n -148.92929077148438,\n 64.53486288126804\n ],\n [\n -148.92929077148438,\n 64.61387025268262\n ],\n [\n -149.21218872070312,\n 64.61387025268262\n ],\n [\n -149.21218872070312,\n 64.53486288126804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":816651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":816652,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220871,"text":"sir20205057 - 2021 - Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","interactions":[],"lastModifiedDate":"2021-05-28T19:21:03.271116","indexId":"sir20205057","displayToPublicDate":"2021-05-28T11:11:37","publicationYear":"2021","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":"2020-5057","displayTitle":"Flood-Inundation Maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","title":"Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019","docAbstract":"Digital flood-inundation maps for a 4.6-mile reach of the Blue River near Red Bridge Road in Kansas City, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the City of Kansas City, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 06893195, Blue River at Red Bridge Road, Kansas City, Mo. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the Johnson County, Kansas, StormWatch Automated Local Elevation in Real Time Flood Warning System at https://www.stormwatch.com.
Flood profiles were computed for the Blue River reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relations at the upstream USGS streamgage 06893150, Blue River at Blue Ridge Boulevard Extension, Kansas City, Mo., and the downstream streamgage 06893500, Blue River at Kansas City, Mo.
The hydraulic model was then used to compute 37 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 11 ft, or near bankfull, to 47 ft at the reference streamgage 06893195. The upper stage for the map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) in the model reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model with a maximum 10-centimeter vertical root mean square error and 4.0-ft horizontal resolution to delineate the area flooded at each water level.
The availability of these maps, along with real-time internet information regarding current stage from the USGS streamgage, will help guide emergency management personnel and residents in flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and any postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205057","collaboration":"Prepared in cooperation with the City of Kansas City, Missouri","usgsCitation":"Heimann, D.C., Voss, J.D., and Rydlund, P.H., Jr., 2021, Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5057, 14 p., https://doi.org/10.3133/sir20205057.","productDescription":"Report: vi, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-117597","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385983,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90MH291","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets for the flood-inundation study of the Blue River near Red Bridge Road, Kansas City, Missouri, 2019"},{"id":385984,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":385981,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5057/coverthb.jpg"},{"id":385982,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5057/sir20205057.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5057"}],"country":"United States","state":"Kansas, Missouri","otherGeospatial":"Blue River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.83333,\n 38.8333\n ],\n [\n -94.45,\n 38.8333\n ],\n [\n -94.45,\n 39.1666\n ],\n [\n -94.833333,\n 39.1666\n ],\n [\n -94.833333,\n 38.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba in Canada and the State of North Dakota in the United States. Greater than average snowpack during the winter of 2010–11, along with record-setting rains in May and June 2011, resulted in historically unprecedented flooding in the Souris River Basin. The severity of the 2011 flood led the United States and Canada to request a review of the operating plan for any improvements of reservoir operations and flood control measures in the basin, and the Souris River Basin Task Force was formed. The International Souris River Study Board was then formed in 2017 to carry out the recommendations of the Souris River Basin Task Force laid out in a plan of study. To support the International Souris River Study Board, the U.S. Geological Survey (USGS), in cooperation with the North Dakota State Water Commission and the International Joint Commission, used the previously developed unregulated and regulated streamflow models and data for stochastic streamflow in the Souris River Basin to characterize climate and streamflow and support selection of streamflow traces based on their characterization. Components of the original stochastic hydrology models and their outputs were used in this phase of the study to (1) characterize historical and stochastic climate and streamflow for the Souris River Basin, (2) disaggregate monthly stochastic streamflow spatially and temporally to meet the needs of the U.S. Army Corps of Engineers, Hydrologic Engineering Center, Reservoir System Simulation model for the Souris River Basin, and (3) discuss selection of disaggregated streamflow traces (simulations) using the characteristics of climate and streamflow. A trace is a time series of a stochastic variable such as streamflow, potential evapotranspiration, or precipitation.
To characterize climate conditions, precipitation, potential evapotranspiration (PET), and moisture deficit for the Souris River Basin and individual points at Rafferty, Grant Devine, and Lake Darling Reservoirs were determined annually and seasonally. The annual basin (November 1–October 31) precipitation for the 50-percent nonexceedance probability is 452 millimeters (mm). Spring (March–May) is the wettest season, followed by summer (June–August), fall (September–November), and winter (December–February). Annual moisture deficit was largest at Lake Darling Reservoir, followed by Rafferty Reservoir, and then Grant Devine Reservoir.
Annual maximum monthly mean streamflow was determined for the Souris River below Rafferty Reservoir, Saskatchewan (Canadian streamgage 05NB036); Long Creek near Noonan (above Boundary Reservoir), North Dakota (USGS streamgage 05113600); Moose Mountain Creek near Oxbow, Saskatchewan (Canadian streamgage 05ND004); the Souris River near Sherwood, N. Dak. (USGS streamgage 05114000); the Des Lacs River at Foxholm, N. Dak. (USGS streamgage 05116500); and the Souris River above Minot, N. Dak. (USGS streamgage 05117500). When the seasonal maximum monthly mean streamflows are evaluated in contrast to annual maximum monthly mean streamflows separated by their seasonal occurrence, summer months of annual maximum monthly mean streamflows have a higher 50-percent exceedance probability of streamflow compared to annual maximum monthly mean streamflows that occur in spring, seasonal maximum monthly mean streamflows that occur in spring, and seasonal maximum monthly mean streamflows that occur in summer. When annual maximum monthly mean streamflows in summer are compared to annual maximum monthly mean streamflows in spring, they are consistently higher in streamflow but occur in less than 4.2 percent of years. Evaluation of whether the annual maximum monthly mean streamflows that occur in summer can be described as a separate population from annual maximum monthly mean streamflows that occur in spring was outside the scope of this study, and the summer and spring annual maximum monthly mean streamflows were not tested for statistical differences in mean or variance. Further investigation of seasonal weather patterns that induce flooding could lead to a better understanding of the seasonal differences in flooding.
Long-term hydrologic drought was characterized by evaluating multiyear mean streamflow. Shorter averaging periods have greater streamflow variability than longer periods and hence have a wider range of values. As the averaging period is extended to a longer period, the variability of mean streamflow decreases, and the more extreme streamflow volumes seen in shorter averaging periods cannot be sustained. Stochastic streamflow time series were disaggregated spatially and temporally for use in a HEC–ResSim model. The combination of monthly and daily stochastic streamflow data was used to select traces with qualities that could be used to test alternatives focused on water supply, summer flooding, and apportionment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215044","collaboration":"Prepared in cooperation with the North Dakota State Water Commission and the International Joint Commission","usgsCitation":"Gregory, A., and Galloway, J.M., 2021, Characterization of historical and stochastically generated climate and streamflow conditions in the Souris River Basin, United States and Canada: U.S. Geological Survey Scientific Investigations Report 2021–5044, 36 p., https://doi.org/10.3133/sir20215044.","productDescription":"Report: viii, 36 p.; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-120682","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":386014,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":386011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5044/coverthb.jpg"},{"id":386012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5044/sir20215044.pdf","text":"Report","size":"5.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021—5044"},{"id":386013,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93AOWFL","text":"USGS data release","linkHelpText":"Historical and stochastically generated climate and streamflow data for the Souris River Basin, United States and Canada"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Souris River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.55859375,\n 46.6795944656402\n ],\n [\n -98.0859375,\n 50.12057809796008\n ],\n [\n -101.25,\n 51.67255514839674\n ],\n [\n -107.138671875,\n 53.48804553605622\n ],\n [\n -108.6328125,\n 50.958426723359935\n ],\n [\n -102.568359375,\n 48.22467264956519\n ],\n [\n -99.66796875,\n 46.98025235521883\n ],\n [\n -97.55859375,\n 46.6795944656402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Martian surface conditions are cold and dry, unfavorable for liquid water, yet steep slopes display young and currently active features suggestive of wet processes. These include recurring slope lineae and slope streaks, gully landforms, and small lobate features. Wet origins for these features would imply surprising amounts of liquid water at the surface. However, detailed observations of the morphology and activity of these features have demonstrated that dry processes, some of them unique to the Martian environment, can account for all of them. This reconciles the contradiction between physics and geomorphology and provides a self-consistent model of a Martian surface that is very active today despite having negligible volumes of liquid water.
In Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsidence and SLR must be balanced by an adequate sediment supply. This study used an ensemble of plausible future scenarios to predict potential climate change impacts on suspended-sediment discharge (Qss) from fluvial sources. Streamflow was simulated using a deterministic water-balance model, and Qss was computed using statistical sediment-transport models. Changes relative to a baseline period (1981–2010) were used to assess climate impacts. For local basins that discharge directly to the bay, the ensemble means projected increases in Qss of 27% for the mid-century (2040–2069) and 58% for the end-of-century (2070–2099). For the Eel River, a regional sediment source that discharges sediment-laden plumes to the coastal margin, the ensemble means projected increases in Qss of 53% for the mid-century and 99% for the end-of-century. Climate projections of increased precipitation and streamflow produced amplified increases in the regional sediment supply that may partially or wholly mitigate sediment demand caused by the combined effects of subsidence and SLR. This finding has important implications for coastal resiliency. Coastal regions with an increasing sediment supply may be more resilient to SLR. In a broader context, an increasing sediment supply from fluvial sources has global relevance for communities threatened by SLR that are increasingly building resiliency to SLR using sediment-based solutions that include regional sediment management, beneficial reuse strategies, and marsh restoration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-00938-x","usgsCitation":"Curtis, J., Flint, L.E., Stern, M.A., Lewis, J., and Klein, R.D., 2021, Amplified impact of climate change on fine-sediment delivery to a subsiding coast, Humboldt Bay, California: Estuaries and Coasts, v. 44, p. 2173-2193, https://doi.org/10.1007/s12237-021-00938-x.","productDescription":"21 p.","startPage":"2173","endPage":"2193","ipdsId":"IP-102755","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452090,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-021-00938-x","text":"Publisher Index Page"},{"id":436333,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UBENK","text":"USGS data release","linkHelpText":"Daily Basin Characterization Model (BCM) archive for Humboldt Bay/Eel River"},{"id":386195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.49707031249999,\n 39.53793974517623\n ],\n [\n -123.96972656249999,\n 39.53793974517623\n ],\n [\n -123.96972656249999,\n 41.41801503608022\n ],\n [\n -124.49707031249999,\n 41.41801503608022\n ],\n [\n -124.49707031249999,\n 39.53793974517623\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2021-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Curtis, Jennifer 0000-0001-7766-994X","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":212727,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Jack","contributorId":189105,"corporation":false,"usgs":false,"family":"Lewis","given":"Jack","email":"","affiliations":[],"preferred":false,"id":816915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klein, Randy D.","contributorId":259269,"corporation":false,"usgs":false,"family":"Klein","given":"Randy","email":"","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":816916,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221343,"text":"70221343 - 2021 - Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary","interactions":[],"lastModifiedDate":"2021-06-11T12:05:22.631939","indexId":"70221343","displayToPublicDate":"2021-05-28T07:04:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3331,"text":"San Francisco Estuary and Watershed Science","active":true,"publicationSubtype":{"id":10}},"title":"Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary","docAbstract":"Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can be responsible for detecting or not detecting biological trends. The SmeltCam is an imaging apparatus developed as a potential sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, California, to reduce handling stress on sensitive species like the Delta Smelt (Hypomesus transpacificus). Although believed to be a reliable alternative to closed cod-end trawling surveys, no formal test of sampling efficiency has been implemented using the SmeltCam. We used a paired deployment of the SmeltCam and a conventional closed cod-end trawl within the Napa River and San Pablo Bay, a Bayesian binomial N-mixture model, and data simulations to determine the sampling efficiency of both deployed gear types to capture a Delta Smelt surrogate (Northern Anchovy, Engraulis mordax) and to test potential bias in our modeling framework. We found that retention efficiency—a component of detection efficiency that estimates the probability a fish is retained by the gear, conditional on gear contact—was slightly higher using the SmeltCam (mean = 0.58) than the conventional trawl (mean = 0.47, Probability SmeltCam retention efficiency > trawl retention efficiency = 94%). We also found turbidity did not affect the SmeltCam’s retention efficiency, although total fish density during an individual tow improved the trawl’s retention efficiency. Simulations also showed the binomial model was accurate when model assumptions were met. Collectively, our results suggest the SmeltCam to be a reliable alternative to sampling with conventional trawling gear, but future tests are needed to confirm whether the SmeltCam is as reliable when applied to taxa other than Northern Anchovy over a greater range of conditions.
","language":"English","publisher":"University of California","doi":"10.15447/sfews.2021v19iss2art6","usgsCitation":"Huntsman, B., Feyrer, F.V., and Young, M.J., 2021, Use of the smeltCam as an efficient fish sampling alternative within the San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 19, no. 2, 16 p., https://doi.org/10.15447/sfews.2021v19iss2art6.","productDescription":"16 p.","ipdsId":"IP-123894","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":452096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2021v19iss2art6","text":"Publisher Index Page"},{"id":386410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.57421875,\n 36.84446074079564\n ],\n [\n -121.86035156249999,\n 36.84446074079564\n ],\n [\n -121.86035156249999,\n 39.40224434029275\n ],\n [\n -123.57421875,\n 39.40224434029275\n ],\n [\n -123.57421875,\n 36.84446074079564\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239051,"text":"70239051 - 2021 - Predicting light regime controls on primary productivity across CONUS river networks","interactions":[],"lastModifiedDate":"2022-12-22T13:03:46.202793","indexId":"70239051","displayToPublicDate":"2021-05-28T06:54:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Predicting light regime controls on primary productivity across CONUS river networks","docAbstract":"Solar radiation is a fundamental driver of ecosystem productivity, but widespread estimates of light available for primary producers in rivers are lacking. We developed a model to predict light available for river primary producers and used it to estimate river primary production across the contiguous United States (CONUS). Successively accounting for riparian and water column processes improved predictions of primary production as a function of light. We calculated the ratio of river width to riparian tree height and used this metric to predict whether riparian zones or water column processes most limit productivity for over 2 million reaches. Water column processes limited productivity for 50% of the nation's river length and 80% of its surface area, with variations across ecoregions related to riparian forest cover. Our findings facilitate large-scale predictions of stream and river ecosystem productivity, as well as understanding the processes controlling productivity across networks.
The topography of Mt. Etna, Italy, is subjected to continuous modifications depending on intensity and magnitude of eruptions that frequently occur at the volcano summit and flanks. In order to make high-resolution maps of morphological changes and accurately calculate the overall volume of the erupted products (e.g., lava flows, tephra fall out, scoriae cones) in ten years, we have compared the altimetry models of Mt. Etna derived from 2005 Airborne Laser Scanning data and 2015 Pleiades stereo satellite imagery. Both models cover a common area of 400 km2 with spatial resolution of 2 m and comparable vertical accuracy (RMSE < 0.8 m). The results show that the area most affected by the erupted products is the mid-upper portion of the volcano with an altitude ranging from 1300 m to more than 3300 m a.s.l., value reached at the summit of the North East crater. In particular, this portion changes dramatically in the eastern sector due to the birth and growth of the New South-East Crater, the invasion of dozens of lava flows in the Valle del Bove, and the formation of the 2014 scoriae cones and lava field at the base of the North-East Crater. The total volume of products erupted in the investigated period results in 284.3±15.8 x 106 m3 with a yearly average volume of 28.4 x 106 m3/y comparable with the previous decades. In addition, the products emitted by the 2014 sub-terminal eruption are mapped and quantified including, for the first time, the volume of the 2014 scoriae cones generated on the eastern flank of North-East Crater This study demonstrates how a rigorous comparison between digital elevation models derived from different remote sensing techniques produce high accurate mapping and quantifications of morphological changes applicable for worldwide active volcanoes. This allows to quantify volumes and areas of erupted products reducing the error estimations, a crucial point to provide precise data often used as key parameters for many volcanic hazard studies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2021.102369","usgsCitation":"Bisson, M., Spinetti, C., Andronico, D., Palaseanu-Lovejoy, M., Buongiorno, M.F., Alexandrov, O., and Cecere, T., 2021, Ten years of volcanic activity at Mt Etna: High-resolution mapping and accurate quantification of the morphological changes by Pleiades and Lidar data: International Journal of Applied Earth Observations and Geoinformation, v. 102, 102369, 11 p., https://doi.org/10.1016/j.jag.2021.102369.","productDescription":"102369, 11 p.","ipdsId":"IP-121404","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":452102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2021.102369","text":"Publisher Index Page"},{"id":386026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Mt. Etna, Sicily","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.849395751953125,\n 37.62402129571883\n ],\n [\n 15.137786865234377,\n 37.62402129571883\n ],\n [\n 15.137786865234377,\n 37.85859141570558\n ],\n [\n 14.849395751953125,\n 37.85859141570558\n ],\n [\n 14.849395751953125,\n 37.62402129571883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bisson, Marina 0000-0002-7104-9210","orcid":"https://orcid.org/0000-0002-7104-9210","contributorId":221724,"corporation":false,"usgs":false,"family":"Bisson","given":"Marina","email":"","affiliations":[{"id":40408,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, via Della Faggiola, Pisa, 56126, Italy","active":true,"usgs":false}],"preferred":false,"id":816657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spinetti, Claudia 0000-0002-1861-5666","orcid":"https://orcid.org/0000-0002-1861-5666","contributorId":221725,"corporation":false,"usgs":false,"family":"Spinetti","given":"Claudia","email":"","affiliations":[{"id":40409,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione ONT, via di Vigna Murata, Roma, 00143, Italy","active":true,"usgs":false}],"preferred":false,"id":816658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andronico, Daniele 0000-0002-8333-1547","orcid":"https://orcid.org/0000-0002-8333-1547","contributorId":259163,"corporation":false,"usgs":false,"family":"Andronico","given":"Daniele","email":"","affiliations":[{"id":52323,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo","active":true,"usgs":false}],"preferred":false,"id":816659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":816660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buongiorno, Maria Fabrizia 0000-0002-6095-6974","orcid":"https://orcid.org/0000-0002-6095-6974","contributorId":221726,"corporation":false,"usgs":false,"family":"Buongiorno","given":"Maria","email":"","middleInitial":"Fabrizia","affiliations":[{"id":40409,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Sezione ONT, via di Vigna Murata, Roma, 00143, Italy","active":true,"usgs":false}],"preferred":false,"id":816661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexandrov, Oleg","contributorId":167662,"corporation":false,"usgs":false,"family":"Alexandrov","given":"Oleg","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":816662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cecere, Thomas 0000-0001-5254-8404 tcecere@usgs.gov","orcid":"https://orcid.org/0000-0001-5254-8404","contributorId":221727,"corporation":false,"usgs":true,"family":"Cecere","given":"Thomas","email":"tcecere@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":816663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229737,"text":"70229737 - 2021 - Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model","interactions":[],"lastModifiedDate":"2022-03-16T16:11:47.02032","indexId":"70229737","displayToPublicDate":"2021-05-27T11:06:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model","docAbstract":"Fishery managers often rely on forecasts of future population abundance to set allowable harvest quotas or exploitation rates. While there has been substantial research devoted to identifying environmental factors that can predict recruitment for individual populations, such correlations often degrade over time, thereby limiting their utility for management. Conversely, examining multiple populations at once to detect shared, spatially structured patterns can offer insights into their recruitment dynamics that are advantageous for forecasting. Here, we develop a population dynamics model for natural origin coho salmon (Oncorhynchus kisutch) stocks in Washington State that leverages spatial and temporal autocorrelation in marine survival to improve one-year-ahead forecasts of adult returns. Executed in a Bayesian hierarchical integrated modelling framework, our spatiotemporal approach incorporates multiple data types and shares information among stocks to estimate key biological parameters that are informative for forecasting. Retrospective evaluation of one-year-ahead forecast skill indicated that the spatiotemporal integrated population model (ST-IPM) outperformed existing forecasts of Washington State coho salmon returns by 25–38 % on average. Moreover, the ST-IPM estimates parameters that were previously non-identifiable for many stocks, and propagates uncertainty from multiple contributing data sources into model forecasts. Our results add to a growing body of work demonstrating the utility of spatiotemporal and integrated approaches for modelling population dynamics, and the framework developed here has broad applications to the assessment and management of coho salmon in Washington State and elsewhere throughout their range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2021.106014","usgsCitation":"DeFilippo, L.B., Buehrens, T., Scheuerell, M.D., Kendall, N.W., and Schindler, D.E., 2021, Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model: Fisheries Research, v. 242, 106014, 12 p., https://doi.org/10.1016/j.fishres.2021.106014.","productDescription":"106014, 12 p.","ipdsId":"IP-129173","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2021.106014","text":"Publisher Index Page"},{"id":397172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.626757,48.288991],[-122.620748,48.282961],[-122.623779,48.269431],[-122.652639,48.265081],[-122.66921,48.240614],[-122.668385,48.223967],[-122.628352,48.222467],[-122.606406,48.208262],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571853,48.102143],[-122.54512,48.05255],[-122.513994,48.059077],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.358812,47.93742],[-122.376837,47.923703],[-122.380497,47.904023],[-122.397349,47.912401],[-122.431035,47.914732],[-122.445519,47.930226],[-122.44076,47.951845],[-122.446682,47.963155],[-122.47266,47.988449],[-122.501257,47.987089],[-122.521219,47.972997],[-122.546824,47.967215],[-122.552053,47.973644],[-122.542924,47.996404],[-122.58178,48.010386],[-122.607342,48.030992],[-122.593621,48.0472],[-122.594922,48.056318],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.677337,48.154587],[-122.693084,48.181509],[-122.763042,48.215342],[-122.770045,48.224395],[-122.752563,48.260061],[-122.732022,48.279425],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664928,48.374823],[-122.664659,48.401508],[-122.634991,48.404244],[-122.63582,48.395128],[-122.609715,48.411565],[-122.60198,48.409907],[-122.595351,48.3972],[-122.585038,48.395166],[-122.585162,48.353304],[-122.551334,48.342138],[-122.506568,48.310041],[-122.505828,48.297677],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460027,47.48686],[-122.433385,47.46643],[-122.439415,47.458633],[-122.437656,47.407424],[-122.395054,47.399277],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.469702,47.344623],[-122.493122,47.330253],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.497862,47.475915],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.644901,48.691389],[-122.618225,48.670721],[-122.609576,48.645018],[-122.635299,48.651846],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.722262,48.731624],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.028091,48.973943],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.804869,48.595932],[-122.801096,48.585425],[-122.770349,48.558106],[-122.788503,48.530393],[-122.787347,48.523012],[-122.777467,48.517799],[-122.779124,48.508911],[-122.817912,48.483888],[-122.81973,48.458843],[-122.803521,48.428748],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.913888,48.443231],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.067675,48.479497],[-123.119451,48.492576],[-123.141478,48.505291],[-123.163234,48.529544],[-123.16147,48.547618],[-123.176266,48.562131],[-123.173061,48.579086],[-123.184941,48.58697],[-123.197754,48.586216],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.098462,48.612834],[-123.101552,48.59782],[-123.074611,48.591816],[-123.048403,48.569216],[-123.015046,48.560821],[-122.987296,48.561895],[-122.98611,48.569984],[-122.995026,48.578162],[-123.016647,48.580244],[-123.034101,48.591767],[-123.023433,48.599477],[-123.04653,48.61149],[-123.048652,48.621002],[-123.023495,48.634001],[-123.009924,48.655064],[-122.949116,48.693398],[-122.942367,48.706723],[-122.894599,48.71503],[-122.833124,48.698173],[-122.800267,48.67962],[-122.743049,48.661991],[-122.755031,48.649512],[-122.792147,48.633502],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.186076,48.684917],[-123.14799,48.668001],[-123.106165,48.633473],[-123.134956,48.63724],[-123.215917,48.669352],[-123.237148,48.683466],[-123.236567,48.68895],[-123.212892,48.689713],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.007511,48.718863],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.03636,48.69008],[-123.070427,48.699971],[-123.040179,48.717296],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.610841,48.561146],[-122.578856,48.54813],[-122.572967,48.529028],[-122.599948,48.536904],[-122.635738,48.526021],[-122.649256,48.528769],[-122.654342,48.537956],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.694672,48.596602],[-122.670638,48.568812],[-122.68944,48.543903],[-122.722407,48.540606],[-122.73048,48.565602],[-122.73944,48.573893],[-122.739898,48.583949],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.676796,48.610055],[-122.699266,48.621115]]],[[[-122.334524,48.018916],[-122.321721,48.019977],[-122.303455,48.005603],[-122.326115,48.010295],[-122.334524,48.018916]]],[[[-122.418268,47.320614],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.361336,47.481421],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.370167,47.583087],[-122.342937,47.59122],[-122.339513,47.599113],[-122.344937,47.60912],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.393248,47.701602],[-122.38044,47.709119],[-122.37314,47.729219],[-122.382641,47.749119],[-122.380241,47.758519],[-122.396422,47.777927],[-122.394944,47.803318],[-122.33595,47.852306],[-122.328546,47.897917],[-122.311927,47.923703],[-122.307048,47.949117],[-122.249007,47.959507],[-122.230046,47.970917],[-122.226346,47.976417],[-122.232391,47.987713],[-122.224979,48.016626],[-122.231761,48.029876],[-122.281087,48.049793],[-122.326119,48.092877],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.372492,48.193022],[-122.395499,48.228551],[-122.433767,48.23655],[-122.449605,48.232598],[-122.45371,48.228859],[-122.449513,48.214736],[-122.441731,48.211776],[-122.45493,48.196639],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.358375,48.056133],[-122.377114,48.057568],[-122.400692,48.085255],[-122.4675,48.130353],[-122.489986,48.120617],[-122.512031,48.133931],[-122.53722,48.183745],[-122.538916,48.209683],[-122.530996,48.249821],[-122.503786,48.257045],[-122.480925,48.251706],[-122.463962,48.270541],[-122.406516,48.25183],[-122.395328,48.257187],[-122.392058,48.269628],[-122.371693,48.287839],[-122.408718,48.326413],[-122.442678,48.337934],[-122.475529,48.359912],[-122.507437,48.364666],[-122.533452,48.383409],[-122.539449,48.39719],[-122.554536,48.40604],[-122.558403,48.426758],[-122.551221,48.439465],[-122.557298,48.444438],[-122.575254,48.443333],[-122.581607,48.429244],[-122.61448,48.41488],[-122.649839,48.408526],[-122.674158,48.424726],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.664623,48.478128],[-122.689121,48.476849],[-122.700603,48.457632],[-122.712322,48.464143],[-122.712981,48.47879],[-122.701644,48.497622],[-122.684521,48.509123],[-122.671386,48.50398],[-122.606961,48.522152],[-122.599951,48.520946],[-122.598469,48.512169],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.46967,48.474975],[-122.483501,48.49243],[-122.485288,48.528106],[-122.498463,48.556206],[-122.504428,48.564775],[-122.531978,48.568644],[-122.534719,48.574246],[-122.495904,48.575927],[-122.478431,48.559303],[-122.44456,48.570115],[-122.425271,48.599522],[-122.448702,48.622624],[-122.46425,48.625717],[-122.500308,48.656163],[-122.519172,48.713095],[-122.495301,48.737328],[-122.490401,48.751128],[-122.510902,48.757728],[-122.535803,48.776128],[-122.567498,48.779185],[-122.596844,48.771492],[-122.637146,48.735708],[-122.626287,48.72093],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.630422,48.696625],[-122.673472,48.733082],[-122.647443,48.773998],[-122.646777,48.785011],[-122.693683,48.804475],[-122.699303,48.789063],[-122.709815,48.786205],[-122.709169,48.817829],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.821631,48.941369],[-122.817226,48.95597],[-122.774276,48.991038],[-122.756318,48.996881],[-122.75802,49.002357],[-121.751252,48.997399],[-117.032351,48.999188],[-117.042623,47.761223],[-117.039813,46.425425],[-117.034696,46.418318],[-117.046915,46.379577],[-117.062785,46.365287],[-117.062748,46.353624],[-117.055983,46.345531],[-117.023844,46.335976],[-117.020663,46.314793],[-116.986688,46.296662],[-116.991134,46.276342],[-116.966742,46.256923],[-116.955264,46.23088],[-116.965841,46.203417],[-116.92187,46.167808],[-116.950276,46.123464],[-116.955263,46.102237],[-116.976957,46.09667],[-116.982479,46.089389],[-116.978938,46.080007],[-116.957372,46.075449],[-116.942656,46.061],[-116.91718,45.996575],[-118.987129,45.999855],[-119.027056,45.969134],[-119.12612,45.932859],[-119.19553,45.92787],[-119.25715,45.939926],[-119.322509,45.933183],[-119.364396,45.921605],[-119.450256,45.917354],[-119.487829,45.906307],[-119.524632,45.908605],[-119.571584,45.925456],[-119.600549,45.919581],[-119.623393,45.905639],[-119.669877,45.856867],[-119.772927,45.845578],[-119.802655,45.84753],[-119.907461,45.828135],[-119.965744,45.824365],[-120.07015,45.785152],[-120.141352,45.773152],[-120.170453,45.761951],[-120.210754,45.725951],[-120.282156,45.72125],[-120.40396,45.699249],[-120.482362,45.694449],[-120.505863,45.700048],[-120.559465,45.738348],[-120.591166,45.746547],[-120.634968,45.745847],[-120.68937,45.715847],[-120.855674,45.671545],[-120.895575,45.642945],[-120.913476,45.640045],[-120.943977,45.656445],[-120.983478,45.648344],[-121.06437,45.652549],[-121.084933,45.647893],[-121.120064,45.623134],[-121.117052,45.618117],[-121.145534,45.607886],[-121.183841,45.606441],[-121.196556,45.616689],[-121.200367,45.649829],[-121.215779,45.671238],[-121.33777,45.704949],[-121.372574,45.703111],[-121.401739,45.692887],[-121.423592,45.69399],[-121.462849,45.701367],[-121.499153,45.720846],[-121.533106,45.726541],[-121.631167,45.704657],[-121.668362,45.705082],[-121.707358,45.694809],[-121.735104,45.694039],[-121.811304,45.706761],[-121.867167,45.693277],[-121.901855,45.670716],[-121.900858,45.662009],[-121.908267,45.654399],[-121.935149,45.644169],[-121.955734,45.643559],[-121.963547,45.632784],[-121.983038,45.622812],[-122.044374,45.609516],[-122.101675,45.583516],[-122.183695,45.577696],[-122.2017,45.564141],[-122.266701,45.543841],[-122.331502,45.548241],[-122.352802,45.569441],[-122.380302,45.575941],[-122.438674,45.563585],[-122.548149,45.596768],[-122.675008,45.618039],[-122.76381,45.657138],[-122.774511,45.680437],[-122.760108,45.734413],[-122.761451,45.759163],[-122.769532,45.780583],[-122.795605,45.81],[-122.785026,45.867699],[-122.81151,45.912725],[-122.806193,45.932416],[-122.813998,45.960984],[-122.837638,45.98082],[-122.856158,46.014469],[-122.878092,46.031281],[-122.884478,46.06028],[-122.904119,46.083734],[-122.962681,46.104817],[-123.004233,46.133823],[-123.041297,46.146351],[-123.115904,46.185268],[-123.166414,46.188973],[-123.280166,46.144843],[-123.371433,46.146372],[-123.430847,46.181827],[-123.427629,46.229348],[-123.474844,46.267831],[-123.501245,46.271004],[-123.547659,46.259109],[-123.547636,46.265595],[-123.613544,46.259988],[-123.669501,46.266832],[-123.679125,46.272502],[-123.680574,46.296025],[-123.700764,46.305278],[-123.724273,46.301161],[-123.727913,46.289661],[-123.741478,46.290274],[-123.766682,46.273499],[-123.806139,46.283588],[-123.875525,46.239787],[-123.919581,46.251217],[-123.954353,46.277001],[-123.974509,46.303063],[-124.001264,46.31326],[-124.020551,46.315737],[-124.029924,46.308312],[-124.044018,46.275925],[-124.060961,46.278761],[-124.080671,46.267239],[-124.064624,46.326899],[-124.057425,46.409315],[-124.057024,46.493338],[-124.068655,46.634879],[-124.062715,46.642582],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.050842,46.617421],[-124.023566,46.582559],[-124.031737,46.496375],[-124.026032,46.462978],[-123.990615,46.463019],[-123.99268,46.488617],[-123.983688,46.498542],[-123.968044,46.473497],[-123.943667,46.477197],[-123.921192,46.507731],[-123.896703,46.522665],[-123.894254,46.537028],[-123.920247,46.567343],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.87668,46.730657],[-123.898641,46.750205],[-123.916371,46.741322],[-123.91285,46.730647],[-123.916874,46.726739],[-123.948683,46.725369],[-123.968564,46.736106],[-123.974994,46.733391],[-123.979655,46.724658],[-123.966886,46.705184],[-123.994242,46.707929],[-124.003458,46.702337],[-124.063117,46.733664],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.110641,46.91252],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.046344,46.893972],[-124.01366,46.90363],[-123.985082,46.921916],[-123.957493,46.921261],[-123.86018,46.948556],[-123.898245,46.971927],[-123.939214,46.969739],[-123.959185,46.981759],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.017035,47.011717],[-124.026345,47.030187],[-124.065856,47.04114],[-124.122057,47.04165],[-124.141517,47.035142],[-124.151288,47.021112],[-124.138035,46.970959],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.25359,47.30248],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.336724,47.415996],[-124.355955,47.545698],[-124.382215,47.632302],[-124.412106,47.691199],[-124.425195,47.738434],[-124.453927,47.765334],[-124.47657,47.769671],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.67083,47.982366],[-124.682157,48.035987],[-124.696542,48.069274],[-124.695114,48.087096],[-124.687101,48.098657],[-124.733174,48.163393],[-124.731746,48.169997],[-124.704153,48.184422],[-124.696111,48.198599],[-124.690389,48.219745],[-124.705031,48.238774],[-124.684677,48.255228],[-124.676319,48.295143],[-124.665908,48.299324],[-124.65894,48.331057],[-124.670072,48.341341],[-124.696703,48.349748],[-124.727022,48.371101],[-124.731828,48.381157],[-124.716947,48.389776],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.250882,48.264773],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.880068,48.160621],[-123.858821,48.154273],[-123.778122,48.155466],[-123.728736,48.1628],[-123.71835,48.158713],[-123.702743,48.166783],[-123.651408,48.156952],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.288265,48.121036],[-123.239129,48.118217],[-123.21719,48.127203],[-123.1644,48.165894],[-123.133445,48.177276],[-123.143229,48.156633],[-123.116479,48.150208],[-123.085154,48.127137],[-123.06621,48.120469],[-123.038727,48.081138],[-122.979413,48.09594],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.918602,48.058238],[-122.877641,48.047025],[-122.849273,48.053808],[-122.857727,48.065774],[-122.878255,48.076072],[-122.882013,48.100779],[-122.876282,48.110877],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.778466,48.106135],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.698465,48.103102],[-122.68724,48.101662],[-122.69222,48.087081],[-122.682264,48.042723],[-122.668942,48.032026],[-122.669868,48.017217],[-122.686898,48.008305],[-122.70184,48.016106],[-122.723374,48.008095],[-122.718082,47.987739],[-122.701294,47.972979],[-122.6788,47.96793],[-122.676215,47.958743],[-122.68445,47.939593],[-122.657722,47.931156],[-122.651063,47.920985],[-122.655085,47.905058],[-122.646494,47.894771],[-122.610341,47.887343],[-122.631857,47.874815],[-122.63636,47.866186],[-122.69376,47.868002],[-122.681602,47.850405],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.880462,47.720643],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.917103,47.620743],[-122.856611,47.649615],[-122.804498,47.653363],[-122.754186,47.671612],[-122.740159,47.736228],[-122.722686,47.748827],[-122.714801,47.768176],[-122.690562,47.778372],[-122.682015,47.800882],[-122.623192,47.836199],[-122.608105,47.856728],[-122.573672,47.857582],[-122.573098,47.874081],[-122.588235,47.912923],[-122.620316,47.931553],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.527593,47.905882],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.485214,47.804128],[-122.495346,47.79704],[-122.495458,47.786692],[-122.471402,47.765965],[-122.470333,47.757109],[-122.471844,47.749819],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.53094,47.704814],[-122.511196,47.708715],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.500357,47.617816],[-122.49824,47.598242],[-122.493933,47.588963],[-122.479089,47.583654],[-122.518367,47.57408],[-122.543118,47.556326],[-122.546611,47.52355],[-122.52305,47.524],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.575985,47.32642],[-122.547521,47.285344],[-122.578211,47.254804],[-122.589454,47.227618],[-122.602541,47.217506],[-122.611464,47.2181],[-122.668571,47.270449],[-122.697378,47.283969],[-122.671256,47.343774],[-122.632463,47.376394],[-122.671486,47.366876],[-122.725738,47.33047],[-122.74525,47.297158],[-122.749621,47.276408],[-122.718124,47.250045],[-122.648941,47.214531],[-122.641802,47.205013],[-122.673925,47.174675],[-122.691771,47.141958],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.816633,47.276457],[-122.799025,47.289306],[-122.796646,47.341654],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.84586,47.298405],[-122.863732,47.270221],[-122.856171,47.233788],[-122.838298,47.208353],[-122.858735,47.167955],[-122.852046,47.164359],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.650634,47.132738],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.561957,47.244099],[-122.527586,47.291531],[-122.547747,47.316403],[-122.533338,47.31662],[-122.471652,47.277321],[-122.4442,47.266723],[-122.429605,47.269707],[-122.409199,47.288556],[-122.444635,47.300421],[-122.418268,47.320614]]]]},\"properties\":{\"name\":\"Washington\",\"nation\":\"USA \"}}]}","volume":"242","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeFilippo, Lukas B.","contributorId":288622,"corporation":false,"usgs":false,"family":"DeFilippo","given":"Lukas","email":"","middleInitial":"B.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":838141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buehrens, Thomas W.","contributorId":288623,"corporation":false,"usgs":false,"family":"Buehrens","given":"Thomas W.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":838142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Neala W.","contributorId":288624,"corporation":false,"usgs":false,"family":"Kendall","given":"Neala","email":"","middleInitial":"W.","affiliations":[{"id":61815,"text":"wafg","active":true,"usgs":false}],"preferred":false,"id":838143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schindler, Daniel E.","contributorId":288625,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":838144,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220879,"text":"70220879 - 2021 - Appendix C: Central sands lakes study technical report: Modeling documentation","interactions":[],"lastModifiedDate":"2021-05-27T14:04:05.646141","indexId":"70220879","displayToPublicDate":"2021-05-27T08:51:14","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":8761,"text":"Wisconsin DNR Technical Report","active":true,"publicationSubtype":{"id":2}},"title":"Appendix C: Central sands lakes study technical report: Modeling documentation","docAbstract":"This report provides the necessary documentation of the numerical models developed for the Central Sands Lake study in central Wisconsin and will be included as a technical appendix in the report to the Wisconsin State Legislature by the Wisconsin Department of Natural Resources (WDNR) in response to 2017 Wisconsin Act 10. This legislation directed WDNR to determine whether existing and potential groundwater withdrawals are causing or are likely to cause significant reduction of mean seasonal water levels at Pleasant Lake, Long Lake, and Plainfield Lake (s. 281.34(7m)(2)(b), Wis. Stats.) in Waushara County, Wisconsin. To evaluate the potential hydrologic connection between groundwater withdrawals and the nearby study lakes, hydrologic models were created that focused on the lakes of interest and yet were large enough to cover a broad enough region to extend to the major hydrologic boundaries of the natural flow system. The areas near the lakes require finer-scale grid discretization (or spacing) to better represent the lakes and streams in the model, but also need to cover a large enough area to include the groundwater withdrawal locations that have the potential to cause reduction in water levels in the lakes. To accomplish these goals, three groundwater models were created: a regional model extending to major hydrologic boundaries; and two inset models, inheriting boundaries from the regional model but focused near the lakes. Each of the inset models, in turn, included a detailed area close to the lakes surrounded by an area at the same spatial scale as the regional model (Figure 1).
To support WDNR in evaluating the connection between groundwater withdrawals and lake levels, a representative time period was required over which to compare land use with and without irrigated agriculture and for WDNR to evaluate potential lake stage and flux changes related to irrigated agriculture. WDNR chose the climate period of 1981-2018 to be representative of a typical period and provided two land use scenarios—one with no irrigated agriculture and one with assumed crop rotations similar to current conditions—to simulate with groundwater models to, then, compare lake responses with. As a result, simulations over this climate record are not intended to recreate the history of 1981-2018 because land use changed over that time. These runs are, instead, intended to provide a basis on which to compare land use with and without irrigation-related groundwater withdrawals based on the current arrangement of land use and a varied climatic record. Groundwater withdrawals focused on irrigated-agriculture-related water use because greater than 95% of groundwater withdrawal in the two inset models around the study lakes is for irrigated agriculture water use.
The period of 2012-2018 was used for parameter estimation (synonymously referred to as “history matching”) for the groundwater models. This time period was chosen because it includes the most complete water use records to simulate groundwater withdrawals. History matching was performed using groundwater elevations, lake stages, and streamflow observations over the 2012-2018 time period and processed observations derived from those raw data.
Climatic data were incorporated into the model using a soil-water balance approach. A soil water balance model was constructed at the scale of the regional groundwater model to both calculate recharge based on land use and climate, and in the long-term climate-period runs, to estimate water use required by irrigated agriculture to apply as well boundary conditions in the groundwater model in the absence of reported water use values over that period.
","language":"English","publisher":"Wisconsin Department of Natural Resources","usgsCitation":"Fienen, M., Haserodt, M.J., Leaf, A.T., and Westenbroek, S., 2021, Appendix C: Central sands lakes study technical report: Modeling documentation: Wisconsin DNR Technical Report, ix, 137 p.","productDescription":"ix, 137 p.","ipdsId":"IP-127829","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":386002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385990,"type":{"id":15,"text":"Index Page"},"url":"https://dnr.wisconsin.gov/topic/Wells/HighCap/CSLStudy.html"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Central Sands region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.78851318359375,\n 43.58834891179792\n ],\n [\n -89.29962158203125,\n 43.57641143300888\n ],\n [\n -89.219970703125,\n 43.75919263886012\n ],\n [\n -89.54132080078125,\n 44.471031231561845\n ],\n [\n -89.7967529296875,\n 44.41808794374846\n ],\n [\n -89.85443115234375,\n 44.33367180085156\n ],\n [\n -89.98901367187499,\n 44.11125397357155\n ],\n [\n -90.01373291015625,\n 44.03232064275081\n ],\n [\n -89.96978759765625,\n 43.878097874251736\n ],\n [\n -89.8187255859375,\n 43.71156424665851\n ],\n [\n -89.78851318359375,\n 43.58834891179792\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","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":true,"id":816549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westenbroek, Stephen, M. 0000-0002-6284-8643","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":206429,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen, M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816550,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230038,"text":"70230038 - 2021 - Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest","interactions":[],"lastModifiedDate":"2022-03-29T18:57:47.258287","indexId":"70230038","displayToPublicDate":"2021-05-27T08:35:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest","docAbstract":"Assemblages of fossil plant remains have been widely used to reconstruct past climatic conditions, usually through the application of methods that involve either finding vegetation analogues on the modern landscape (and using the modern associated climatic values as the basis for an estimate) or using the modern climatic ranges of individual taxa in an assemblage to determine the range of a given climate variable that would allow these plant taxa to live together. Although these approaches are relatively straightforward, it is difficult to assess the uncertainties associated with each approach, particularly in regard to their application to plant macrofossil assemblages. To explore the uncertainty that may arise from inaccuracy and imprecision in climate reconstructions and from ecological considerations we used variants of both approaches to estimate climate from two data sets of modern vegetation assemblages from the southwestern United States: (1) 1752 gridded “virtual plant assemblages” based on plant range maps that provide uniform spatial coverage of the presence or absence of major woody plant taxa across the study area; and (2) 43 modern packrat (Neotoma spp.) midden presence-absence assemblages that are similar to fossil midden assemblages. By comparing observed and estimated climate values, we evaluated the quality of the climate estimates, identified sources of uncertainty, and characterized the nature and magnitude of the effects of these uncertainties on the climate estimates.
Uncertainties in estimating climate from vegetation assemblages arise because any given plant taxon (or assemblage) must have the resiliency to survive a range of climatic variability, and because of the strong intercorrelations among climatic variables in the modern climate data. Additional sources of uncertainty in climate estimates from plant assemblages include: (1) the modern climate and plant distribution data that are selected as the basis for estimation; (2) the particular quantitative approach that is used to estimate climate; (3) the sufficiency of the number of taxa in the analysis for providing an unbiased representation of the vegetation community as it existed for each time period in the analysis; and, (4) the location of the assemblage on the climatic and environmental gradients in the calibration data set for each climate variable under consideration.
We conclude that vegetation assemblages can provide valid and reproducible estimates of climatic variables and that the primary trends and mapped patterns in the observed climate data can be reconstructed from such estimates. However, many factors may affect the quality of an estimate from a given plant assemblage, including aspects of data selection, data adequacy, methodologies, and the location of the assemblage site relative to gradients in the base climate data. It is particularly difficult to accurately estimate extreme values in the observed climate data, because estimated values from either end of an observed climate gradient necessarily “move toward the middle” of the gradient. In addition, the interval chosen to represent modern climate (here we used 1961 to 1990) may have a large impact on the size of the estimated difference between modern and past climate at a given site.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2021.106880","usgsCitation":"Thompson, R.S., Anderson, K., Pelltier, R.T., Strickland, L.E., Shafer, S., and Bartlein, P.J., 2021, Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest: Quaternary Science Reviews, v. 262, 106880, 27 p., https://doi.org/10.1016/j.quascirev.2021.106880.","productDescription":"106880, 27 p.","ipdsId":"IP-100351","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436335,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CKCP22","text":"USGS data release","linkHelpText":"Data release for Assessing the Uncertainties in Climatic Estimates Based on Vegetation Assemblages: Examples from Modern Vegetation Assemblages in the American Southwest"},{"id":397596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Texas, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.3046875,\n 29.84064389983441\n ],\n [\n -104.765625,\n 32.32427558887655\n ],\n [\n -106.435546875,\n 35.71083783530009\n ],\n [\n -106.787109375,\n 37.75334401310656\n ],\n [\n -107.666015625,\n 40.38002840251183\n ],\n [\n -111.4013671875,\n 40.51379915504413\n ],\n [\n -112.32421875,\n 42.09822241118974\n ],\n [\n -119.970703125,\n 42.06560675405716\n ],\n [\n -121.86035156249999,\n 41.83682786072714\n ],\n [\n -119.970703125,\n 38.54816542304656\n ],\n [\n -119.267578125,\n 36.24427318493909\n ],\n [\n -116.103515625,\n 32.54681317351514\n ],\n [\n -114.5654296875,\n 32.54681317351514\n ],\n [\n -111.005859375,\n 31.42866311735861\n ],\n [\n -108.28125,\n 31.316101383495624\n ],\n [\n -108.19335937499999,\n 31.914867503276223\n ],\n [\n -106.435546875,\n 31.87755764334002\n ],\n [\n -104.67773437499999,\n 30.107117887092357\n ],\n [\n -103.84277343749999,\n 29.305561325527698\n ],\n [\n -103.35937499999999,\n 29.075375179558346\n ],\n [\n -102.83203125,\n 29.19053283229458\n ],\n [\n -102.3046875,\n 29.84064389983441\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"262","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Katherine H 0000-0003-2677-6109","orcid":"https://orcid.org/0000-0003-2677-6109","contributorId":289266,"corporation":false,"usgs":false,"family":"Anderson","given":"Katherine H","affiliations":[{"id":62090,"text":"Institute of Arctic and Alpine Research, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":838828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pelltier, Richard T. 0000-0001-8322-7961 rtpelltier@usgs.gov","orcid":"https://orcid.org/0000-0001-8322-7961","contributorId":4683,"corporation":false,"usgs":true,"family":"Pelltier","given":"Richard","email":"rtpelltier@usgs.gov","middleInitial":"T.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838829,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strickland, Laura E. 0000-0002-1958-7273 lstrickland@usgs.gov","orcid":"https://orcid.org/0000-0002-1958-7273","contributorId":4682,"corporation":false,"usgs":true,"family":"Strickland","given":"Laura","email":"lstrickland@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838830,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838831,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":838832,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238937,"text":"70238937 - 2021 - Ten simple rules for productive lab meetings","interactions":[],"lastModifiedDate":"2022-12-19T14:19:07.541434","indexId":"70238937","displayToPublicDate":"2021-05-27T08:12:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Ten simple rules for productive lab meetings","docAbstract":"The aim of this article is to delineate 10 simple rules on how to achieve productive lab meetings. We use the term “meeting” interchangeably to represent both the single meeting event and the overarching concept of the recurring meeting. In this article we speak from our experience, as a lab group at the University of Massachusetts that meets regularly (Fig 1). Although the rules are mostly tailored toward academic or research institution settings, insights can be gained for other contexts. We believe these rules are applicable across a diverse set of labs and lab structures. For example, while many members of our current lab have remained constant for many years, the lab composition has changed as various undergraduate students, graduate students, postdoctoral fellow, visiting professors, and other faculty have joined and/or moved on. Throughout these experiences, lab rules, presented in modified form here, proved flexible and adaptable enough to be useful in helping guide productive lab meetings. Note that this article is written for principal investigator/s (PI), students, postdocs, and other lab members; it takes the whole lab group to succeed. The key to planning productive lab meetings boils down to discussing and determining as a team the answers to why, who, what, where, when, and how: Why are lab meetings important for the functioning of the lab? Who will participate? What will be the focus of lab meetings? When and where should the lab meetings occur? How should each meeting be structured and carried out so that the goals and objectives of the lab and its participants are met?
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pcbi.1008953","usgsCitation":"Golden, N., Devarajan, K., Balantic, C., Drake, J., Hallworth, M.T., and Morelli, T.L., 2021, Ten simple rules for productive lab meetings: PLOS Computational Biology, v. 17, no. 5, e1008953, 13 p., https://doi.org/10.1371/journal.pcbi.1008953.","productDescription":"e1008953, 13 p.","ipdsId":"IP-125473","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":452113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1008953","text":"Publisher Index Page"},{"id":410702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-27","publicationStatus":"PW","contributors":{"editors":[{"text":"Schwartz, Russell","contributorId":300129,"corporation":false,"usgs":false,"family":"Schwartz","given":"Russell","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":859459,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Golden, Nigel","contributorId":300012,"corporation":false,"usgs":false,"family":"Golden","given":"Nigel","email":"","affiliations":[{"id":65000,"text":"University of Massachusetts, Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":859268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devarajan, Kadambari","contributorId":236828,"corporation":false,"usgs":false,"family":"Devarajan","given":"Kadambari","email":"","affiliations":[],"preferred":false,"id":859269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balantic, Cathleen","contributorId":275317,"corporation":false,"usgs":false,"family":"Balantic","given":"Cathleen","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":859270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, Joseph","contributorId":300015,"corporation":false,"usgs":false,"family":"Drake","given":"Joseph","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":859271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hallworth, Michael T.","contributorId":213805,"corporation":false,"usgs":false,"family":"Hallworth","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":38879,"text":"National Zoological Park, Migratory Bird Center","active":true,"usgs":false}],"preferred":false,"id":859272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":859273,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221154,"text":"70221154 - 2021 - Transient disease dynamics across ecological scales","interactions":[],"lastModifiedDate":"2022-01-06T17:10:13.809411","indexId":"70221154","displayToPublicDate":"2021-05-27T08:12:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3592,"text":"Theoretical Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Transient disease dynamics across ecological scales","docAbstract":"Analyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.
A disconnect between scientific research and environmental management communities can be a detriment to both. In the case of Great Lakes coastal ecosystems, which are inherently complex and subject to uncertain effects of future climatic, environmental, and anthropogenic drivers, greater collaboration could be beneficial to their sustainability. We capture the challenges and opportunities identified by a scientist/decision-maker co-production workshop focused on the future environmental quality of Great Lakes coastal wetlands. We explain our path through the stakeholder workshop process, our challenges in translating meeting outcomes into actionable items, and lessons learned to bridge gaps between scientists and decision-makers. Additionally, we determine topics and directions identified by decision-makers that can be modeled with existing technologies and others that require further research. These topics may be incorporated into future research efforts and could serve as a shortlist of research priorities that were identified by decision-makers working with coastal wetland issues. Based on lessons learned during and after the workshop, we provide suggestions for bridging the gap between researchers and decision-makers, including sustained engagement between these groups and improved interaction through the beginning, duration, and end of research and/or management efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.04.018","usgsCitation":"Weinstein, C.B., Bourgeau-Chavez, L., Martin, S.L., Currie, W.S., Grantham, K., Hamlin, Q.F., Hyndman, D.W., Kowalski, K., Martina, J.P., and Pearsall, D., 2021, Enhancing Great Lakes coastal ecosystems research by initiating engagement between scientists and decision-makers: Journal of Great Lakes Research, v. 47, no. 4, p. 1235-1240, https://doi.org/10.1016/j.jglr.2021.04.018.","productDescription":"6 p.","startPage":"1235","endPage":"1240","ipdsId":"IP-125315","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":387990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","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 -75.5419921875,\n 44.08758502824516\n ],\n [\n -77.3876953125,\n 44.33956524809713\n ],\n [\n -78.92578124999999,\n 44.08758502824516\n ],\n [\n -82.353515625,\n 42.58544425738491\n ],\n [\n -81.123046875,\n 43.866218006556394\n ],\n [\n -81.123046875,\n 44.37098696297173\n ],\n [\n -79.5849609375,\n 44.5278427984555\n ],\n [\n -79.62890625,\n 45.089035564831036\n ],\n [\n -81.1669921875,\n 46.28622391806706\n ],\n [\n -84.0673828125,\n 46.649436163350245\n ],\n [\n -85.517578125,\n 48.22467264956519\n ],\n [\n -87.0556640625,\n 49.18170338770663\n ],\n [\n -90.3076171875,\n 48.60385760823255\n ],\n [\n -92.94433593749999,\n 46.76996843356982\n ],\n [\n -91.7578125,\n 46.40756396630067\n ],\n [\n -88.72558593749999,\n 46.9502622421856\n ],\n [\n -88.330078125,\n 46.558860303117164\n ],\n [\n -86.8359375,\n 46.28622391806706\n ],\n [\n -85.517578125,\n 46.5286346952717\n ],\n [\n -85.0341796875,\n 46.164614496897094\n ],\n [\n -87.099609375,\n 45.920587344733654\n ],\n [\n -88.41796875,\n 44.5278427984555\n ],\n [\n -87.890625,\n 44.33956524809713\n ],\n [\n -87.978515625,\n 43.004647127794435\n ],\n [\n -87.71484375,\n 41.77131167976407\n ],\n [\n -86.572265625,\n 41.705728515237524\n ],\n [\n -85.8251953125,\n 43.068887774169625\n ],\n [\n -85.9130859375,\n 44.43377984606822\n ],\n [\n -84.72656249999999,\n 45.460130637921004\n ],\n [\n -83.8037109375,\n 44.933696389694674\n ],\n [\n -83.935546875,\n 43.77109381775651\n ],\n [\n -83.84765625,\n 43.29320031385282\n ],\n [\n -83.056640625,\n 43.89789239125797\n ],\n [\n -82.79296874999999,\n 42.94033923363181\n ],\n [\n -83.583984375,\n 41.77131167976407\n ],\n [\n -83.056640625,\n 41.07935114946899\n ],\n [\n -81.2109375,\n 41.376808565702355\n ],\n [\n -78.31054687499999,\n 42.65012181368022\n ],\n [\n -76.2451171875,\n 43.48481212891603\n ],\n [\n -75.5419921875,\n 44.08758502824516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weinstein, Charlotte B.","contributorId":260518,"corporation":false,"usgs":false,"family":"Weinstein","given":"Charlotte","email":"","middleInitial":"B.","affiliations":[{"id":34530,"text":"Michigan Tech Research Institute","active":true,"usgs":false}],"preferred":false,"id":821246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bourgeau-Chavez, Laura 0000-0001-7127-279X","orcid":"https://orcid.org/0000-0001-7127-279X","contributorId":220963,"corporation":false,"usgs":false,"family":"Bourgeau-Chavez","given":"Laura","email":"","affiliations":[{"id":34530,"text":"Michigan Tech Research Institute","active":true,"usgs":false}],"preferred":false,"id":821247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, S. L.","contributorId":264243,"corporation":false,"usgs":false,"family":"Martin","given":"S.","email":"","middleInitial":"L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":821248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Currie, W. S.","contributorId":264245,"corporation":false,"usgs":false,"family":"Currie","given":"W.","email":"","middleInitial":"S.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":821249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grantham, K.","contributorId":264247,"corporation":false,"usgs":false,"family":"Grantham","given":"K.","email":"","affiliations":[{"id":54411,"text":"Southeast Michigan Council of Governments","active":true,"usgs":false}],"preferred":false,"id":821250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamlin, Q. F.","contributorId":264248,"corporation":false,"usgs":false,"family":"Hamlin","given":"Q.","email":"","middleInitial":"F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":821251,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hyndman, David W","contributorId":264249,"corporation":false,"usgs":false,"family":"Hyndman","given":"David","email":"","middleInitial":"W","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":821252,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":821253,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Martina, J. P.","contributorId":264250,"corporation":false,"usgs":false,"family":"Martina","given":"J.","email":"","middleInitial":"P.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":821254,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pearsall, D.","contributorId":264252,"corporation":false,"usgs":false,"family":"Pearsall","given":"D.","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":821255,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223137,"text":"70223137 - 2021 - Impact of SST and surface waves on Hurricane Florence (2018): A coupled modeling investigation","interactions":[],"lastModifiedDate":"2021-09-21T13:11:40.385044","indexId":"70223137","displayToPublicDate":"2021-05-27T07:58:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3735,"text":"Weather and Forecasting","active":true,"publicationSubtype":{"id":10}},"title":"Impact of SST and surface waves on Hurricane Florence (2018): A coupled modeling investigation","docAbstract":"Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir-Simpson Category 4 to Category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere-ocean-wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by oceanwaves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r=0.89) and strength (r=0.95) coming from the fully-coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean andwave features to the model further modified the fluxes due to more realistic cooling beneath the stormwhich in turn modified the precipitation field. Our experiments highlight significant differences in how air-sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.
Forests are a significant CO2 sink. However, CO2 sequestration in forests is radiatively offset by emissions of nitrous oxide (N2O), a potent greenhouse gas, from forest soils. Reforestation, an important strategy for mitigating climate change, has focused on maximizing CO2 sequestration in plant biomass without integrating N2O emissions from soils. Although nitrogen (N)-fixing trees are often recommended for reforestation because of their rapid growth on N-poor soil, they can stimulate significant N2O emissions from soils. Here, we first used a field experiment to show that a N-fixing tree (Robinia pseudoacacia) initially mitigated climate change more than a non-fixing tree (Betula nigra). We then used our field data to parameterize a theoretical model to investigate these effects over time. Under lower N supply, N-fixers continued to mitigate climate change more than non-fixers by overcoming N limitation of plant growth. However, under higher N supply, N-fixers ultimately mitigated climate change less than non-fixers by enriching soil N and stimulating N2O emissions from soils. These results have implications for reforestation, suggesting that N-fixing trees are more effective at mitigating climate change at lower N supply, whereas non-fixing trees are more effective at mitigating climate change at higher N supply.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.3414","usgsCitation":"Kou-Giesbrecht, S., Funk, J.L., Perakis, S.S., Wolf, A.A., and Menge, D., 2021, N supply mediates the radiative balance of N2O emissions and CO2 sequestration driven by N-fixing vs. non-fixing trees: Ecology, v. 102, no. 8, e03414, 8 p., https://doi.org/10.1002/ecy.3414.","productDescription":"e03414, 8 p.","ipdsId":"IP-123004","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":452122,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3414","text":"Publisher Index Page"},{"id":387284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Black Rock Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.0584945678711,\n 41.3791271230665\n ],\n [\n -73.99017333984375,\n 41.3791271230665\n ],\n [\n -73.99017333984375,\n 41.41737138589576\n ],\n [\n -74.0584945678711,\n 41.41737138589576\n ],\n [\n -74.0584945678711,\n 41.3791271230665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kou-Giesbrecht, Sian 0000-0002-4086-0561","orcid":"https://orcid.org/0000-0002-4086-0561","contributorId":261258,"corporation":false,"usgs":false,"family":"Kou-Giesbrecht","given":"Sian","email":"","affiliations":[{"id":52786,"text":"Columbia U","active":true,"usgs":false}],"preferred":false,"id":819602,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Jennifer L.","contributorId":260668,"corporation":false,"usgs":false,"family":"Funk","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":819603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":819604,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolf, Amelia A.","contributorId":190685,"corporation":false,"usgs":false,"family":"Wolf","given":"Amelia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":819605,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":819606,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221849,"text":"70221849 - 2021 - Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales","interactions":[],"lastModifiedDate":"2021-07-12T17:45:19.948532","indexId":"70221849","displayToPublicDate":"2021-05-26T12:41:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales","docAbstract":"Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.107822","usgsCitation":"Coffer, M.M., Schaeffer, B., Salls, W.B., Urquhart, E., Loftin, K.A., Stumpf, R.P., Werdell, P.J., and Darling, J., 2021, Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales: Ecological Indicators, v. 128, 107822, 12 p., https://doi.org/10.1016/j.ecolind.2021.107822.","productDescription":"107822, 12 p.","ipdsId":"IP-126524","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":452125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.107822","text":"Publisher Index Page"},{"id":387135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coffer, Megan M. 0000-0003-3188-4729","orcid":"https://orcid.org/0000-0003-3188-4729","contributorId":260857,"corporation":false,"usgs":false,"family":"Coffer","given":"Megan","email":"","middleInitial":"M.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaeffer, Blake 0000-0001-9794-3977","orcid":"https://orcid.org/0000-0001-9794-3977","contributorId":245603,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salls, Wilson B. 0000-0001-7505-0828","orcid":"https://orcid.org/0000-0001-7505-0828","contributorId":260858,"corporation":false,"usgs":false,"family":"Salls","given":"Wilson","email":"","middleInitial":"B.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urquhart, Erin 0000-0001-7141-9499","orcid":"https://orcid.org/0000-0001-7141-9499","contributorId":260859,"corporation":false,"usgs":false,"family":"Urquhart","given":"Erin","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":818983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":818984,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stumpf, Richard P. 0000-0001-5531-6860","orcid":"https://orcid.org/0000-0001-5531-6860","contributorId":222357,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard","email":"","middleInitial":"P.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werdell, P. Jeremy 0000-0002-3592-0152","orcid":"https://orcid.org/0000-0002-3592-0152","contributorId":222358,"corporation":false,"usgs":false,"family":"Werdell","given":"P.","email":"","middleInitial":"Jeremy","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":818986,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Darling, John A. 0000-0002-4776-9533","orcid":"https://orcid.org/0000-0002-4776-9533","contributorId":260860,"corporation":false,"usgs":false,"family":"Darling","given":"John A.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818987,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221214,"text":"70221214 - 2021 - Seismic wave propagation and basin amplification in the Wasatch Front, Utah","interactions":[],"lastModifiedDate":"2021-11-01T15:26:45.377797","indexId":"70221214","displayToPublicDate":"2021-05-26T08:16:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Seismic wave propagation and basin amplification in the Wasatch Front, Utah","docAbstract":"Ground‐motion analysis of more than 3000 records from 59 earthquakes, including records from the March 2020
The Mississippi embayment encompasses about 100,000 square miles and covers parts of eight States. In 2016, the U.S. Geological Survey began updating previous work for a part of the embayment known as the Mississippi Alluvial Plain to support informed water use and agricultural policy in the region. Groundwater, water use, economic, and other related models are being combined with field surveys and observations to create a quantitative framework for evaluating regional groundwater withdrawals and their effects on long-term water availability in the Mississippi Alluvial Plain.
As part of this effort, the U.S. Geological Survey’s Soil-Water-Balance code (version 2.0) is being used to model potential groundwater recharge and irrigation water use, as necessary inputs to the long-term groundwater modeling efforts. The Soil-Water-Balance code is designed to estimate the distribution and timing of net infiltration leaving the root zone. Soil-Water-Balance makes use of gridded datasets of elevation, soils, land use (including specific crop types), and daily weather datasets to calculate other components of the root-zone water balance, including soil moisture, reference, actual evapotranspiration, snowfall, snowmelt, and canopy interception. Parameters on plant height and growing-season water needs are used to estimate crop-water demand and potential irrigation water use.
This report documents the initial construction, calibration, and application of a Soil-Water-Balance model of the Mississippi Embayment Regional Aquifer Study area for simulations running from 1915 to 2017. Further refinements of the model calibration for an expanded model area are planned.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211008","programNote":"Water Availability and Use Science Program","usgsCitation":"Westenbroek, S.M., Nielsen, M.G., and Ladd, D.E., 2021, Initial estimates of net infiltration and irrigation from a soil-water-balance model of the Mississippi Embayment Regional Aquifer Study Area: U.S. Geological Survey Open-File Report 2021-1008, 29 p., https://doi.org/10.3133/ofr20211008.","productDescription":"Report: v, 29 p.; 2 Data Releases","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-108908","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385921,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U484X5","text":"USGS data release","description":"USGS data release","linkHelpText":"OFR 2021–1008 MODEL OUTPUT—Soil-Water-Balance net infiltration and irrigation water use output datasets for the Mississippi Embayment Regional Aquifer System, 1915 to 2018"},{"id":385920,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PBR8O","text":"USGS data release","description":"USGS data release","linkHelpText":"OFR 2021–1008 MODEL ARCHIVE—Soil-Water-Balance model developed to simulate net infiltration and irrigation water use for the Mississippi Embayment Regional Aquifer System, 1915 to 2018"},{"id":385919,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1008/ofr20211008.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1008"},{"id":385918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1008/coverthb.jpg"}],"country":"United States","state":"Alabama, Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi Embayment Regional Aquifer Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.6044921875,\n 37.16031654673677\n ],\n [\n -90.4833984375,\n 36.527294814546245\n ],\n [\n -91.2744140625,\n 35.71083783530009\n ],\n [\n -91.7138671875,\n 35.31736632923788\n ],\n [\n -92.4169921875,\n 35.02999636902566\n ],\n [\n -93.3837890625,\n 34.59704151614417\n ],\n [\n -94.0869140625,\n 33.578014746143985\n ],\n [\n -94.1748046875,\n 32.69486597787505\n ],\n [\n -93.6474609375,\n 31.690781806136822\n ],\n [\n -92.94433593749999,\n 31.50362930577303\n ],\n [\n -91.93359375,\n 31.42866311735861\n ],\n [\n -91.14257812499999,\n 31.541089879585808\n ],\n [\n -89.7802734375,\n 31.316101383495624\n ],\n [\n -88.5498046875,\n 30.86451022625836\n ],\n [\n -87.3193359375,\n 31.203404950917395\n ],\n [\n -87.5390625,\n 31.80289258670676\n ],\n [\n -88.5498046875,\n 32.69486597787505\n ],\n [\n -88.505859375,\n 33.8339199536547\n ],\n [\n -88.5498046875,\n 34.59704151614417\n ],\n [\n -88.3740234375,\n 35.60371874069731\n ],\n [\n -88.5498046875,\n 36.94989178681327\n ],\n [\n -89.6044921875,\n 37.16031654673677\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562