{"pageNumber":"125","pageRowStart":"3100","pageSize":"25","recordCount":46644,"records":[{"id":70239772,"text":"70239772 - 2023 - Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","interactions":[],"lastModifiedDate":"2025-05-14T17:36:22.285243","indexId":"70239772","displayToPublicDate":"2023-01-18T06:52:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">Quantifying seepage losses from unlined irrigation canals is necessary to improve water use and conservation. The use of heat as a tracer is widely used in quantifying seepage rates across the sediment–water interface. In this study, field observations and two-dimensional numerical models were used to simulate seepage losses during the 2018 and 2019 irrigation season in the Truckee Canal system. Nineteen transects were instrumented with temperature probes and stage recording devices for inverse modeling to derive seepage flux and volumetric losses over the 39&nbsp;km length of canal. The numerical models for each transect were calibrated and validated using the two-year dataset. Soil zones and observation data were used in each numerical model to help guide calibration of vertical and lateral heat and fluid fluxes. Model simulations were used to derive multivariable regression equations that consider stage, temperature, and hydraulic gradient. The results demonstrate the value of long-term datasets that illustrate the seasonality of groundwater levels, siltation, stage, and temperature on seepage rates. Seepage rates estimated by the numerical models range from 0.16 to 4.6&nbsp;m<sup>3</sup>/d m<sup>−1</sup>. Total annual volumetric losses estimated for 2018 and 2019 were 1.6&nbsp;×&nbsp;10<sup>-2</sup><span>&nbsp;</span>to 1.2&nbsp;×&nbsp;10<sup>-2</sup><span>&nbsp;</span>km<sup>3</sup>, respectively. The seepage losses estimated by this study account for 32&nbsp;% to 41&nbsp;% of the inflow volumes. Regression models were able to reproduce seepage time-series simulated by the numerical models reasonably well. In arid environments, water diverted into irrigation canals may be influenced by seasonal variations in temperature sufficient to influence the water accounting of conveyed surface flows.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129117","usgsCitation":"Naranjo, R.C., Smith, D., and Lindenbach, E.J., 2023, Incorporating temperature into seepage loss estimates for a large unlined irrigation canal: Journal of Hydrology, v. 617, no. C, 129117, 15 p.; Data Release, https://doi.org/10.1016/j.jhydrol.2023.129117.","productDescription":"129117, 15 p.; Data Release","ipdsId":"IP-096517","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":412069,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":435498,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P971LB6C","text":"USGS data release","linkHelpText":"Supplemental data and documentation of VS2DH seepage models: Incorporating temperature into seepage loss estimates for a large irrigation canal"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.6447610565691,\n              39.4835481422399\n            ],\n            [\n              -119.6447610565691,\n              38.96460925429065\n            ],\n            [\n              -118.63993876134998,\n              38.96460925429065\n            ],\n            [\n              -118.63993876134998,\n              39.4835481422399\n            ],\n            [\n              -119.6447610565691,\n              39.4835481422399\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"617","issue":"C","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David 0000-0002-9543-800X","orcid":"https://orcid.org/0000-0002-9543-800X","contributorId":169280,"corporation":false,"usgs":true,"family":"Smith","given":"David","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":861906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lindenbach, Evan J.","contributorId":263642,"corporation":false,"usgs":false,"family":"Lindenbach","given":"Evan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":861907,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70239766,"text":"70239766 - 2023 - Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex","interactions":[],"lastModifiedDate":"2023-05-25T15:38:17.243989","indexId":"70239766","displayToPublicDate":"2023-01-18T06:50:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Here we determine how traditional morphometrics (TM) compares with geometric morphometrics (GM) in discriminating among morphologies of four forms of ciscoes of the<span>&nbsp;</span><i>Coregonus artedi</i><span>&nbsp;</span>complex collected from Lake Huron. One of the forms comprised two groups of the same deepwater cisco separated by capture depth, whereas the other three forms were shallow-water ciscoes. Our three groups of shallow-water ciscoes were better separated (3% versus 19% overlap) in Principle Component Analysis (PCA) with TM data than with GM data incorporating semilandmarks (evenly spaced nonhomologous landmarks used to bridge between widely separated homologous landmarks). Our two deepwater cisco groups, comprising a putatively single form collected from different depths, separated more in PCAs with GM data (33% overlap) than in PCAs with TM data (66% overlap), an anomaly caused by greater decompression of the swimbladder and deformation of the body wall in the group captured at greater depths. Separation of the two deepwater cisco groups captured at different depths was not affected by the removal of semilandmarks. Assignment of forms using canonical variate analysis (CVA) accurately assigned 86% of individuals using TM data, 98% of individuals using GM data incorporating semilandmarks, and 100% of individuals using GM data without semilandmarks. However, we considered assignments from the same form of deepwater cisco into separate groups as misassignments resulting from different capture depths, which reduced the accuracy of assignments with GM data to 66% with semilandmarks. Our study implies that TM will continue to have an important role in morphological discrimination within<span>&nbsp;</span><i>Coregonus</i><span>&nbsp;</span>and other fishes similarly shaped.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10403","usgsCitation":"Martin, B.E., O’Malley, B., Eshenroder, R.E., Kao, Y., Olds, C., O’Brien, T.P., and Davis, C.L., 2023, Comparison of traditional and geometric morphometrics using Lake Huron ciscoes of the Coregonus artedi complex: Transactions of the American Fisheries Society, v. 152, no. 3, p. 296-309, https://doi.org/10.1002/tafs.10403.","productDescription":"14 p.","startPage":"296","endPage":"309","ipdsId":"IP-143472","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":498958,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10403","text":"Publisher Index Page"},{"id":412068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.7705078125,\n              45.81348649679973\n            ],\n            [\n              -84.4189453125,\n              45.5679096098613\n            ],\n            [\n              -83.81469726562499,\n              45.390735154248894\n            ],\n            [\n              -83.507080078125,\n              45.166547157856016\n            ],\n            [\n              -83.38623046875,\n              44.73892994307368\n            ],\n            [\n              -83.507080078125,\n              44.315987905196906\n      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       45.98169518512228\n            ],\n            [\n              -84.6826171875,\n              46.11132565729796\n            ],\n            [\n              -84.7705078125,\n              45.81348649679973\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"152","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Benjamin E","contributorId":301031,"corporation":false,"usgs":false,"family":"Martin","given":"Benjamin","email":"","middleInitial":"E","affiliations":[{"id":13451,"text":"Univ. of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":861807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Malley, Brian 0000-0001-5035-3080 bomalley@usgs.gov","orcid":"https://orcid.org/0000-0001-5035-3080","contributorId":216560,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshenroder, Randy E","contributorId":301032,"corporation":false,"usgs":false,"family":"Eshenroder","given":"Randy","email":"","middleInitial":"E","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":861809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kao, Yu-Chun 0000-0001-5552-909X ykao@usgs.gov","orcid":"https://orcid.org/0000-0001-5552-909X","contributorId":192240,"corporation":false,"usgs":true,"family":"Kao","given":"Yu-Chun","email":"ykao@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olds, Chris","contributorId":218041,"corporation":false,"usgs":false,"family":"Olds","given":"Chris","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":861811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":861812,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davis, Chris L.","contributorId":264659,"corporation":false,"usgs":false,"family":"Davis","given":"Chris","email":"","middleInitial":"L.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":861813,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70239823,"text":"70239823 - 2023 - Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models","interactions":[],"lastModifiedDate":"2023-09-06T16:04:00.742929","indexId":"70239823","displayToPublicDate":"2023-01-17T09:12:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models","docAbstract":"<p><span>Non-native species maps are important tools for understanding and managing biological invasions. We demonstrate a novel approach to extend presence modeling to map fractional cover (FC) of non-native yellow sweet clover&nbsp;</span><i>Melilotus officinalis</i><span>&nbsp;in the Northern Great Plains, USA. We used ensembles of MaxEnt models to map FC across landscapes from satellite imagery trained from regional aerial imagery that was trained by local unmanned aerial vehicle (UAV) imagery. Clover cover from field surveys and classified UAV imagery were nearly identical (</span><i>n</i><span>&nbsp;=&nbsp;22,&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;0.99). Two classified UAV images provided training data to map clover presence with MaxEnt and National Agricultural Imagery Program (NAIP) aerial imagery. We binned cover predictions from NAIP imagery within each Sentinel-2 pixel into eight cover classes to create pure (100%) and FC (20%–95%) training data and modeled each class separately using MaxEnt and Sentinel-2 imagery. We mapped pure clover with one classification threshold and compared its performance to 15 candidate maps that included FC predictions outside pure predictions. Each FC map represented alternative combinations of five MaxEnt thresholds and three approaches to assign cover to pixels with multiple predictions from the FC ensemble. Evaluations of performance with independent datasets revealed maps including FC corresponded to field (</span><i>n</i><span>&nbsp;=&nbsp;32,&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;range: 0.39–0.68) and UAV (</span><i>n</i><span>&nbsp;=&nbsp;20,&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;range: 0.61–0.84) data better than pure clover maps (</span><i>R</i><sup>2</sup><span>&nbsp;=&nbsp;0.15 and 0.31, respectively). Overall, the pure clover map predicted 3.2% cover, whereas the three best performing FC maps predicted 6.6%–8.0% cover. Including FC predictions increased accuracy and cover predictions which can improve ecological understanding of invasions. Our method allows efficient FC mapping for vegetative species discernible in UAV imagery and may be especially useful for mapping rare, irruptive or patchily distributed species with poor representation in field data, which challenges landscape-level mapping.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rse2.325","usgsCitation":"Preston, T.M., Johnston, A.N., Ebenhoch, K.G., and Diehl, R.H., 2023, Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models: Remote Sensing in Ecology and Conservation, v. 9, no. 4, p. 512-526, https://doi.org/10.1002/rse2.325.","productDescription":"15 p.","startPage":"512","endPage":"526","ipdsId":"IP-135782","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":444792,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.325","text":"Publisher Index Page"},{"id":435499,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91X4EPQ","text":"USGS data release","linkHelpText":"Fractional cover estimates of sweet clover derived from UAV, aerial, and Sentinel-2 imagery for central Montana and northwest South Dakota, 2019"},{"id":412216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, South Dakota","county":"Butte County, Harding County, Musselshell County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-108.6276,46.7487],[-108.5911,46.7491],[-108.5699,46.7489],[-108.5494,46.7486],[-108.5163,46.7481],[-108.4991,46.7483],[-108.4772,46.7489],[-108.4567,46.7491],[-108.3586,46.7503],[-108.3373,46.7509],[-108.2618,46.7524],[-108.2399,46.7525],[-108.2187,46.7526],[-108.1981,46.7532],[-108.1763,46.7533],[-107.8833,46.7568],[-107.878,46.7571],[-107.8276,46.7566],[-107.8279,46.7502],[-107.8221,46.7455],[-107.8162,46.7444],[-107.8164,46.7394],[-107.8118,46.7375],[-107.8101,46.7306],[-107.8155,46.7279],[-107.8295,46.7254],[-107.829,46.7218],[-107.8212,46.7184],[-107.8287,46.7126],[-107.819,46.7083],[-107.8238,46.7038],[-107.8186,46.7],[-107.811,46.693],[-107.8043,46.6942],[-107.8026,46.6873],[-107.7955,46.6835],[-107.7957,46.6784],[-107.7998,46.6758],[-107.802,46.6707],[-107.7983,46.6643],[-107.8024,46.6602],[-107.8044,46.6607],[-107.8082,46.6631],[-107.8111,46.659],[-107.8073,46.6539],[-107.8153,46.6522],[-107.8217,46.6413],[-107.8224,46.639],[-107.8152,46.638],[-107.8148,46.6325],[-107.8184,46.6243],[-107.829,46.6231],[-107.8298,46.6204],[-107.8188,46.6147],[-107.8367,46.5976],[-107.7971,46.5954],[-107.7986,46.495],[-107.7781,46.4951],[-107.7829,46.3948],[-107.9102,46.3931],[-107.9299,46.3935],[-107.9299,46.3779],[-107.947,46.3773],[-107.9482,46.3649],[-107.9693,46.3644],[-107.9712,46.3493],[-107.9915,46.3502],[-107.9901,46.335],[-108.0099,46.3358],[-108.0112,46.3171],[-108.0116,46.3065],[-108.0254,46.3068],[-108.0266,46.2761],[-108.0271,46.2624],[-108.0896,46.2626],[-108.1113,46.263],[-108.131,46.2628],[-108.3197,46.2632],[-108.3195,46.2504],[-108.3622,46.2502],[-108.3627,46.2351],[-108.3838,46.2354],[-108.4035,46.2352],[-108.4033,46.2196],[-108.4035,46.1949],[-108.4032,46.1812],[-108.4037,46.1665],[-108.4035,46.1528],[-108.4035,46.1326],[-108.5301,46.1327],[-108.5518,46.133],[-108.6574,46.1331],[-108.7782,46.1328],[-108.7778,46.2762],[-108.7988,46.2765],[-108.7993,46.3072],[-108.8211,46.307],[-108.822,46.3216],[-108.8325,46.3222],[-108.8318,46.3511],[-108.8423,46.3517],[-108.8419,46.3668],[-108.8636,46.3666],[-108.8634,46.3781],[-108.8642,46.4509],[-108.8846,46.4525],[-108.8856,46.4915],[-108.9074,46.4918],[-108.906,46.5775],[-108.9912,46.5775],[-108.9902,46.622],[-109.0101,46.6209],[-109.0104,46.6649],[-109.0094,46.7378],[-109.0091,46.7516],[-108.9038,46.7504],[-108.8647,46.7504],[-108.817,46.7507],[-108.7567,46.75],[-108.7382,46.7497],[-108.6958,46.7496],[-108.6276,46.7487]]],[[[-102.9587,45.2128],[-102.958,45.1251],[-102.9581,45.0388],[-102.9576,44.7781],[-102.9589,44.69],[-102.9653,44.6898],[-102.966,44.6036],[-103.1861,44.6039],[-103.2066,44.6039],[-103.3273,44.6042],[-103.4467,44.6053],[-103.5666,44.6044],[-103.8156,44.6048],[-103.8258,44.6023],[-103.8256,44.5982],[-103.8234,44.5937],[-103.8324,44.5939],[-103.8309,44.5889],[-103.8373,44.5888],[-103.8384,44.586],[-103.8417,44.5877],[-103.8464,44.5913],[-103.8533,44.5884],[-103.8567,44.5915],[-103.8641,44.5854],[-103.8702,44.5925],[-103.884,44.5985],[-103.8883,44.5952],[-103.8934,44.5942],[-103.8973,44.595],[-103.9018,44.5954],[-103.9061,44.5916],[-103.9053,44.5889],[-103.9105,44.5892],[-103.9144,44.59],[-103.9179,44.5849],[-103.9262,44.5838],[-103.9344,44.5799],[-103.9396,44.5812],[-103.9446,44.5783],[-103.9454,44.5819],[-103.9511,44.5808],[-103.9549,44.5789],[-103.9671,44.5791],[-103.9761,44.5811],[-103.9813,44.5814],[-103.983,44.5777],[-103.9997,44.5773],[-104.0183,44.5773],[-104.0229,44.5799],[-104.035,44.5782],[-104.0399,44.574],[-104.0457,44.5734],[-104.0564,44.5717],[-104.0571,44.9818],[-104.0571,44.9987],[-104.0397,44.9986],[-104.0399,45.0602],[-104.0402,45.1563],[-104.0403,45.169],[-104.0403,45.1774],[-104.0403,45.1832],[-104.0406,45.2143],[-104.041,45.2639],[-104.0425,45.5572],[-104.0426,45.5736],[-104.0424,45.6245],[-104.0425,45.6437],[-104.0425,45.6578],[-104.0425,45.6656],[-104.0426,45.6717],[-104.0426,45.6835],[-104.0433,45.7735],[-104.0434,45.7951],[-104.0435,45.8098],[-104.0437,45.8405],[-104.0439,45.8799],[-104.0441,45.9063],[-104.0443,45.9438],[-102.9956,45.944],[-102.9425,45.944],[-102.9445,45.8189],[-102.9439,45.7311],[-102.955,45.7318],[-102.9558,45.5584],[-102.9565,45.4711],[-102.9539,45.3852],[-102.9578,45.3851],[-102.9605,45.2982],[-102.9587,45.2128]]]]},\"properties\":{\"name\":\"Musselshell\",\"state\":\"MT\"}}]}","volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebenhoch, Kyle Gregory 0000-0001-7046-5557","orcid":"https://orcid.org/0000-0001-7046-5557","contributorId":299946,"corporation":false,"usgs":true,"family":"Ebenhoch","given":"Kyle","email":"","middleInitial":"Gregory","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":862050,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240165,"text":"70240165 - 2023 - Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River","interactions":[],"lastModifiedDate":"2023-01-31T13:13:29.009178","indexId":"70240165","displayToPublicDate":"2023-01-17T07:11:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River","docAbstract":"<div class=\"article-section__content en main\"><p>Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non-contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes as input images acquired from an airplane and involves orthorectification, frame overlap analysis, image enhancement, particle image velocimetry (PIV), and aggregation of the resulting velocity vectors onto a prediction grid. We also use new metrics to quantify the agreement between image-derived and field-measured velocity vectors in terms of both orientation and magnitude. The potential of MARV was evaluated using data from two Alaskan rivers: a large, highly turbid channel and its smaller, clearer tributary. Sediment boil vortices on the mainstem provided natural features trackable via PIV and estimated velocities corresponded closely with field measurements (<i>R</i><sup>2</sup><span>&nbsp;</span>up to 0.911). We compared an exhaustive approach that evaluates overlap for all frame combinations to a simpler rolling window implementation and found that the more efficient algorithm did not compromise accuracy. Sensitivity analysis suggested that the method was robust to window parameterization. Comparing PIV output from different flying heights and imaging systems indicated that larger pixels led to higher accuracy and that a more advanced dual-camera system provided superior performance. Results from the tributary were less encouraging, presumably due to a lack of trackable features in visible images. Testing across a range of rivers is needed to assess the generality of MARV.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR033822","usgsCitation":"Legleiter, C.J., Kinzel, P.J., Laker, M., and Conaway, J., 2023, Moving Aircraft River Velocimetry (MARV): Framework and proof-of-concept on the Tanana River: Water Resources Research, v. 59, no. 2, e2022WR033822, 29 p., https://doi.org/10.1029/2022WR033822.","productDescription":"e2022WR033822, 29 p.","ipdsId":"IP-145891","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488772,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022wr033822","text":"Publisher Index Page"},{"id":435500,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P968OENT","text":"USGS data release","linkHelpText":"Digital orthophotos and field measurements of flow velocity from the Tanana and Nenana Rivers, Alaska, from August 2021 (ver. 2.0, June 2024)"},{"id":412495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-30","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":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":862816,"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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","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":862817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laker, Mark","contributorId":298315,"corporation":false,"usgs":false,"family":"Laker","given":"Mark","email":"","affiliations":[{"id":64530,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":862818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conaway, Jeff 0000-0002-3036-592X","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":214226,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeff","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":862819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70241042,"text":"70241042 - 2023 - The San Francisco Estuary, USA as a reference section for an Anthropocene series","interactions":[],"lastModifiedDate":"2023-05-12T14:55:36.358251","indexId":"70241042","displayToPublicDate":"2023-01-17T06:57:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13447,"text":"The Anthropocene Review","active":true,"publicationSubtype":{"id":10}},"title":"The San Francisco Estuary, USA as a reference section for an Anthropocene series","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>A San Francisco Estuary core was analysed at high resolution to assess its component stratigraphic signatures of the Anthropocene in the form of non-native species, Hg, spheroidal carbonaceous particles, δ<sup>13</sup>C<sub>org</sub>, δ<sup>15</sup>N, radiogenic materials, and heavy metals. Time series analysis of the core using Ti data provides a chronology to depth 167 cm into the 1960s. Below this, to depth 230 cm, the lowermost part of the core may extend to the 1950s or potentially a little earlier. The earliest anthropogenic marker recorded in the core is the excursion in Hg (beginning at 190 cm) which may denote the early 1960s and is the closest stratigraphic marker in the core to the proposed mid-20th century timing for the onset of the Anthropocene. Biostratigraphical signatures of non-native species arriving in the 1970s–1980s are widespread key markers and are significant tools for the correlation of Anthropocene deposits across the estuary. The absence of signals that indicate pre-1950s deposits precludes the use of the core to mark the Holocene–Anthropocene boundary. However, the core provides an important reference section to demonstrate the palaeontological distinctiveness of Anthropocene series deposits.</div></div></div>","language":"English","publisher":"Sage Publications","doi":"10.1177/20530196221147607","usgsCitation":"Himson, S.J., Williams, M., Zalasiewicz, J., Waters, C.N., McGann, M., England, R., Jaffe, B.E., Boom, A., Holmes, R., Sampson, S., Pye, C., Berrio, J.C., Tyrrell, G., Wilkinson, I.P., Rose, N., Gaca, P., and Cundy, A., 2023, The San Francisco Estuary, USA as a reference section for an Anthropocene series: The Anthropocene Review, v. 10, no. 1, p. 87-115, https://doi.org/10.1177/20530196221147607.","productDescription":"29 p.","startPage":"87","endPage":"115","ipdsId":"IP-143287","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444795,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/20530196221147607","text":"Publisher Index Page"},{"id":413760,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.98898796525978,\n              38.33835510273127\n            ],\n            [\n              -122.98898796525978,\n              37.192468321934456\n            ],\n            [\n              -121.49548160296686,\n              37.192468321934456\n            ],\n            [\n              -121.49548160296686,\n              38.33835510273127\n            ],\n            [\n              -122.98898796525978,\n              38.33835510273127\n            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UK","active":true,"usgs":false}],"preferred":false,"id":865807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waters, Colin N.","contributorId":297463,"corporation":false,"usgs":false,"family":"Waters","given":"Colin","email":"","middleInitial":"N.","affiliations":[{"id":40148,"text":"University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":169540,"corporation":false,"usgs":true,"family":"McGann","given":"Mary","email":"mmcgann@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":865809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"England, Richard","contributorId":302908,"corporation":false,"usgs":false,"family":"England","given":"Richard","email":"","affiliations":[{"id":65578,"text":"School of Geography, Geology and the Environment, University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":865811,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boom, Arnoud","contributorId":302909,"corporation":false,"usgs":false,"family":"Boom","given":"Arnoud","email":"","affiliations":[{"id":65578,"text":"School of Geography, Geology and the Environment, University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865812,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Holmes, Rachael","contributorId":297462,"corporation":false,"usgs":false,"family":"Holmes","given":"Rachael","email":"","affiliations":[{"id":40148,"text":"University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865813,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sampson, Sue","contributorId":302910,"corporation":false,"usgs":false,"family":"Sampson","given":"Sue","email":"","affiliations":[{"id":65578,"text":"School of Geography, Geology and the Environment, University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865814,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pye, Cerin","contributorId":302911,"corporation":false,"usgs":false,"family":"Pye","given":"Cerin","email":"","affiliations":[{"id":65578,"text":"School of Geography, Geology and the Environment, University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865815,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Berrio, Juan Carlos","contributorId":297468,"corporation":false,"usgs":false,"family":"Berrio","given":"Juan","email":"","middleInitial":"Carlos","affiliations":[{"id":40148,"text":"University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865816,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tyrrell, Genevieve","contributorId":302912,"corporation":false,"usgs":false,"family":"Tyrrell","given":"Genevieve","email":"","affiliations":[{"id":65578,"text":"School of Geography, Geology and the Environment, University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865817,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wilkinson, Ian P.","contributorId":297469,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":40148,"text":"University of Leicester, UK","active":true,"usgs":false}],"preferred":false,"id":865818,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rose, Neil","contributorId":289606,"corporation":false,"usgs":false,"family":"Rose","given":"Neil","affiliations":[],"preferred":false,"id":865819,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gaca, Pawel","contributorId":302913,"corporation":false,"usgs":false,"family":"Gaca","given":"Pawel","email":"","affiliations":[{"id":65579,"text":"Ocean and Earth Science, National Oceanography Centre Southampton, UK","active":true,"usgs":false}],"preferred":false,"id":865820,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Cundy, Andrew","contributorId":302914,"corporation":false,"usgs":false,"family":"Cundy","given":"Andrew","affiliations":[{"id":65579,"text":"Ocean and Earth Science, National Oceanography Centre Southampton, UK","active":true,"usgs":false}],"preferred":false,"id":865821,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70248758,"text":"70248758 - 2023 - A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping","interactions":[],"lastModifiedDate":"2023-09-20T11:50:04.288946","indexId":"70248758","displayToPublicDate":"2023-01-17T06:44:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping","docAbstract":"<div class=\"html-p\">Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers; thus, many small-scale site-specific models had to be created to cover the landscape at the national scale. The present work aims to develop a large-scale surface fuel identification model using a custom deep learning framework that can ingest multimodal data. Specifically, we use deep learning to extract information from multispectral signatures, high-resolution imagery, and biophysical climate and terrain data in a way that facilitates their end-to-end training on labeled data. A multi-layer neural network is used with spectral and biophysical data, and a convolutional neural network backbone is used to extract the visual features from high-resolution imagery. A Monte Carlo dropout mechanism was also devised to create a stochastic ensemble of models that can capture classification uncertainties while boosting the prediction performance. To train the system as a proof-of-concept, fuel pseudo-labels were created by a random geospatial sampling of existing fuel maps across California. Application results on independent test sets showed promising fuel identification performance with an overall accuracy ranging from 55% to 75%, depending on the level of granularity of the included fuel types. As expected, including the rare—and possibly less consequential—fuel types reduced the accuracy. On the other hand, the addition of high-resolution imagery improved classification performance at all levels.</div>","language":"English","publisher":"MDPI","doi":"10.3390/fire6020036","usgsCitation":"Alipour, M., La Puma, I.P., Picotte, J., Shamsei, K., Rowell, E., Watts, A., Kosovic, B., Ebrahimian, H., and Taciroglu, E., 2023, A multimodal data fusion and deep learning framework for large-scale wildfire surface fuel mapping: Fire, v. 6, no. 2, 36, 25 p., https://doi.org/10.3390/fire6020036.","productDescription":"36, 25 p.","ipdsId":"IP-148036","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":444798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire6020036","text":"Publisher Index Page"},{"id":420970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0003-1992-6033","orcid":"https://orcid.org/0000-0003-1992-6033","contributorId":329857,"corporation":false,"usgs":false,"family":"Ebrahimian","given":"Hamed","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":883474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Taciroglu, Erugrul 0000-0001-9618-1210","orcid":"https://orcid.org/0000-0001-9618-1210","contributorId":329858,"corporation":false,"usgs":false,"family":"Taciroglu","given":"Erugrul","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":883475,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70239912,"text":"70239912 - 2023 - Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa","interactions":[],"lastModifiedDate":"2023-01-25T12:39:26.054546","indexId":"70239912","displayToPublicDate":"2023-01-17T06:35:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13280,"text":"Environmental Science and Technology: Water","active":true,"publicationSubtype":{"id":10}},"title":"Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0030\">In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018–2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2023.161672","usgsCitation":"Bradley, P., Kolpin, D., Thompson, D.A., Romanok, K., Smalling, K., Breitmeyer, S.E., Cardon, M.C., Cwiertny, D.M., Evans, N., Field, R.W., Focazio, M.J., Freeman, L.E., Givens, C.E., Gray, J.L., Hager, G.L., Hladik, M.L., Hoffman, J.N., Jones, R.R., Kanagy, L.K., Lane, R.F., McCleskey, R., Medgyesi, D., Medlock-Kakaley, E., Meppelink, S., Meyer, M., Stavreva, D.A., and Ward, M.H., 2023, Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa: Environmental Science and Technology: Water, v. 868, 161672, 11 p., https://doi.org/10.1016/j.scitotenv.2023.161672.","productDescription":"161672, 11 p.","ipdsId":"IP-134194","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":444805,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2023.161672","text":"Publisher Index Page"},{"id":435501,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IYT37H","text":"USGS data release","linkHelpText":"Target-Chemical Concentrations, Exposure Activity Ratios, and Bioassay Results for Assessment of Mixed-Organic/Inorganic Chemical Exposures in Northeast Iowa Private-Well Tapwater, 2018"},{"id":412305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.12228849222048,\n              42.99050594750622\n            ],\n            [\n              -93.12228849222048,\n              41.09871525515322\n            ],\n            [\n              -89.9156424790619,\n              41.09871525515322\n            ],\n            [\n              -89.9156424790619,\n              42.99050594750622\n            ],\n            [\n              -93.12228849222048,\n              42.99050594750622\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. 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,{"id":70239727,"text":"70239727 - 2023 - Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","interactions":[],"lastModifiedDate":"2023-01-16T19:30:15.171651","indexId":"70239727","displayToPublicDate":"2023-01-16T13:25:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","docAbstract":"Subaqueous clinoforms are an important yet underappreciated shelf feature. Their origins are typically associated with subaerial deltas but recent work has identified similar features in settings without a significant fluvial source. These other studies have shown that such subaqueous clinoforms, also known as infralittoral prograding wedges (IPWs), are created largely by wave-induced processes. This study uses geophysical, sedimentological, and radiocarbon data to determine the sedimentary characteristics and genesis of a shore-parallel subaqueous clinoform developed far from any significant river on the central California continental shelf; a feature known locally as the Cross Hosgri Slope. Sediment cores through the feature reveal that it is composed of beds with an erosive base, followed by a thin coarsening upward sequence of shelly fine sands transitioning to a fining upward sequence marked by alternating parallel and ripple cross laminated very fine sands. The deposit is often capped by fine silts that are commonly interbedded with thin very fine sand beds. Radiocarbon dating of shells within the cores paired with seismic profiles indicate the subaqueous clinoform initiated progradation ~7 ka, nucleating on an older Younger Dryas relict shoreface. We suggest the CHS was created by winter-storm waves mobilizing sands in water depths up to ~ 70 m that transitioned into wave-supported gravity flows. The wave-supported gravity flows traveled downslope to water depths of up to ~85 m, corresponding to the foot of the subaqueous clinoform.  They did not travel beyond this depth as wave influence at these depths is negligible and the shelf slope is insufficient to maintain movement of the load alone. Our work suggests that wave-supported gravity flows can entrain very fine sands and silts and build subaqueous clinoforms, even in the absence of a significant river source. Furthermore, we provide a facies model for sandy wave-supported gravity flow deposits.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2022.106977","usgsCitation":"Medri, E., Simms, A.R., Kluesner, J., Johnson, S., Nishenko, S., Greene, H.G., and Conrad, J.E., 2023, Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf: Marine Geology, v. 456, 106977, 13 p., https://doi.org/10.1016/j.margeo.2022.106977.","productDescription":"106977, 13 p.","ipdsId":"IP-144443","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/62t4p940","text":"Publisher Index Page"},{"id":411965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.56611710043825,\n              36.61947594158909\n            ],\n            [\n              -123.56611710043825,\n              34.32371030361945\n            ],\n            [\n              -119.09307635415979,\n              34.32371030361945\n            ],\n            [\n              -119.09307635415979,\n              36.61947594158909\n            ],\n            [\n              -123.56611710043825,\n              36.61947594158909\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"456","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Medri, Elisa","contributorId":300974,"corporation":false,"usgs":false,"family":"Medri","given":"Elisa","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":861657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":52887,"corporation":false,"usgs":true,"family":"Simms","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":861658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":221270,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nishenko, Stuart P.","contributorId":82219,"corporation":false,"usgs":true,"family":"Nishenko","given":"Stuart P.","affiliations":[],"preferred":false,"id":861661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":861662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70239723,"text":"70239723 - 2023 - Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","interactions":[],"lastModifiedDate":"2023-01-16T18:55:39.202204","indexId":"70239723","displayToPublicDate":"2023-01-16T12:45:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","docAbstract":"Terminal channels were historically a common feature of tidal delta ecosystems but have become increasingly rare as landscapes have been modified. Tidal hydrodynamics are a defining feature in tidal terminal channel ecosystems from which native aquatic communities have evolved. However, few studies have explored the relationship between fish community structure and hydrodynamics in these tidal terminal channel ecosystems. We sampled fish communities throughout a network of terminal channels within the northeasternmost region of the San Francisco Estuary to determine the relationship between fish community structure and hydrodynamics within these environments. We collected two years (2017 and 2018) of fish community samples using gill nets and analyzed data using multivariate community analyses and count models. We found metrics of fish diversity and counts of native fishes to be greatest upstream (farthest from tidal influence) of the tidal excursion within terminal channels. Counts of non-native fishes were less affected by this hydrodynamic feature of terminal channels and more tightly correlated to local habitat conditions (e.g., water temperature, depth). Our results suggest that channel hydrodynamics plays a role in structuring fish communities within terminal channels, particularly native fishes. These results indicate that hydrodynamics in tidal delta ecosystems may be able to be altered in ways that benefit native fishes without the cost of water pumping.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4339","usgsCitation":"Huntsman, B., Young, M.J., Feyrer, F.V., Stumpner, P., Brown, L.R., and Burau, J.R., 2023, Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta: Ecosphere, v. 14, no. 1, e4339, 18 p., https://doi.org/10.1002/ecs2.4339.","productDescription":"e4339, 18 p.","ipdsId":"IP-139147","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":444812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4339","text":"Publisher Index Page"},{"id":411962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cache Slough Complex, San Francisco Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.69932887248329,\n              38.24856975517184\n            ],\n            [\n              -121.67220637492461,\n              38.24776088323978\n            ],\n            [\n              -121.71752497844034,\n              38.3229474560282\n            ],\n            [\n              -121.80987879924118,\n              38.31217280176293\n            ],\n            [\n              -121.77760646037407,\n              38.28495967449561\n            ],\n            [\n              -121.72713801554991,\n              38.28064774752275\n            ],\n            [\n              -121.69932887248329,\n              38.24856975517184\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-13","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":861635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":861636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":861637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Larry R. 0000-0001-6702-4531","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":269405,"corporation":false,"usgs":false,"family":"Brown","given":"Larry","email":"","middleInitial":"R.","affiliations":[{"id":55970,"text":"USGS CAWSC (not in system - posthumous)","active":true,"usgs":false}],"preferred":false,"id":861639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861640,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239726,"text":"70239726 - 2023 - Enhancements to population monitoring of Yellowstone grizzly bears","interactions":[],"lastModifiedDate":"2023-01-16T18:08:30.013759","indexId":"70239726","displayToPublicDate":"2023-01-16T12:00:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Enhancements to population monitoring of Yellowstone grizzly bears","docAbstract":"<p><span>In the Greater Yellowstone Ecosystem, counts of female grizzly bears (</span><i>Ursus arctos</i><span>) with cubs-of-the-year (females with cubs) from systematic aerial surveys and opportunistic ground sightings are combined with demographic data to derive annual population estimates. We addressed 2 limitations to the monitoring approach. As part of a rule set, a conservative distance of&nbsp;</span><i>&gt;</i><span>30 km currently is used as a threshold to assign sightings to unique females with cubs, resulting in underestimation bias. Using telemetry locations of females with cubs collected during 1997–2019, we created 1,000 data sets for each of 5 levels of simulated number of females with cubs, simulated sightings by selecting among these locations, and evaluated the classification performance of alternative distance criteria (12–30 km). Under all scenarios, 12–16-km criteria maximized classification performance and minimized estimation bias; the 16-km criterion was optimal for current conditions and sampling efforts. Our second objective was to test generalized additive models (GAMs) as a flexible trend analysis technique. We simulated 1,000 time series for each of 10 scenarios (10, 15, and 20% decline over periods of 5, 10, and 15 yrs, plus stability), applied GAMs, and assessed metrics associated with the posterior distribution of the instantaneous rate of change. We detected declines among&nbsp;</span><i>&gt;</i><span>99.6% of replicates under the 15 and 20% decline scenarios and in 84.7–94.7% of replicates under the 10% decline scenario. From decline onset to first detection, periods ranged from 3.7 (20% decline over 5 yrs) to 11.1 (10% decline over 15 yrs), with 3.9–8.8 years mean duration of detection events. The GAM approach allows detection of directional changes in population trend, including early warning metrics, and stabilization after such changes. Retrospective application of the 16-km distance criterion and GAMs resulted in higher population estimates and growth rates than are reported using current methods.</span></p>","language":"English","publisher":"International Association for Bear Research and Management","doi":"10.2192/URSUS-D-22-00002.2","usgsCitation":"van Manen, F.T., Ebinger, M., Costello, C., Bjornlie, D., Clapp, J., Thompson, D., Haroldson, M.A., Frey, K.L., Hendricks, C., Nicholson, J., Gunther, K.A., Wilmot, K.R., Cooley, H., Fortin-Noreus, J., Hnilicka, P., and Tyers, D.B., 2023, Enhancements to population monitoring of Yellowstone grizzly bears: Ursus, v. 33, e17, 19 p., https://doi.org/10.2192/URSUS-D-22-00002.2.","productDescription":"e17, 19 p.","ipdsId":"IP-137270","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":444815,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2192/ursus-d-22-00002.2","text":"Publisher Index Page"},{"id":411958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.06216250119708,\n              45.005442783577365\n            ],\n            [\n              -111.05388206352849,\n              43.99158796485162\n            ],\n            [\n              -110.88275301837602,\n              44.04716331869298\n            ],\n            [\n              -110.79994864168938,\n              44.08682810596011\n            ],\n            [\n              -110.62881959653659,\n              44.134390765324724\n            ],\n   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]\n}","volume":"33","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":861641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebinger, Michael","contributorId":300973,"corporation":false,"usgs":false,"family":"Ebinger","given":"Michael","affiliations":[{"id":35211,"text":"Montana Department of Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":861642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":861643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":861644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clapp, Justin","contributorId":256932,"corporation":false,"usgs":false,"family":"Clapp","given":"Justin","email":"","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":861645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Daniel","contributorId":225736,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","affiliations":[{"id":13584,"text":"Natural Resources Canada, Canadian Forest Service","active":true,"usgs":false}],"preferred":false,"id":861646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":861647,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Frey, Kevin L.","contributorId":124580,"corporation":false,"usgs":false,"family":"Frey","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":5125,"text":"Montana Fish Wildlife and Parks, Bear Management Office, 1400 South 19th Avenue, Bozeman, MT 59718","active":true,"usgs":false}],"preferred":false,"id":861648,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hendricks, Curtis","contributorId":256933,"corporation":false,"usgs":false,"family":"Hendricks","given":"Curtis","email":"","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":861649,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nicholson, Jeremy M.","contributorId":256934,"corporation":false,"usgs":false,"family":"Nicholson","given":"Jeremy M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":861650,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":861651,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wilmot, Katharine R.","contributorId":244265,"corporation":false,"usgs":false,"family":"Wilmot","given":"Katharine","email":"","middleInitial":"R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":861652,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cooley, Hilary","contributorId":205414,"corporation":false,"usgs":false,"family":"Cooley","given":"Hilary","affiliations":[],"preferred":false,"id":861653,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fortin-Noreus, Jennifer","contributorId":200746,"corporation":false,"usgs":false,"family":"Fortin-Noreus","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":861654,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hnilicka, Pat","contributorId":289731,"corporation":false,"usgs":false,"family":"Hnilicka","given":"Pat","affiliations":[],"preferred":false,"id":861655,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tyers, Daniel B.","contributorId":124587,"corporation":false,"usgs":false,"family":"Tyers","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":5129,"text":"U.S. Forest Service, 2327 University Way, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":861656,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70240433,"text":"70240433 - 2023 - Influence of fine-scale habitat characteristics on sage-grouse nest site selection and nest survival varies by mesic and xeric site conditions","interactions":[],"lastModifiedDate":"2023-03-31T15:19:27.088033","indexId":"70240433","displayToPublicDate":"2023-01-16T06:54:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Influence of fine-scale habitat characteristics on sage-grouse nest site selection and nest survival varies by mesic and xeric site conditions","docAbstract":"<p class=\"chapter-para\">Resource managers and scientists across western U.S. agencies seek methodologies for identifying environmental attributes important to both wildlife conservation and broad-scale land stewardship. The Greater Sage-Grouse (<i>Centrocercus urophasianus</i>; hereafter, sage-grouse) exemplifies a species in need of this broad-scale approach given widespread population declines that have resulted from loss and degradation of habitat from natural and anthropogenic disturbances. These include agricultural land conversion, conifer expansion, energy development, and wildfire coupled with ecological conversion by invasive plants such as cheatgrass (<i>Bromus tectorum</i>). Development of habitat assessments and conservation actions for sage-grouse benefit from studies that link demographic responses to habitat selection patterns. To address this, we examined nest survival of sage-grouse in relation to fine-scale habitat patterns (i.e., field-based habitat measurements) that influenced nest site selection, using data from nests of telemetered females at 17 sites over 6 years in Nevada and northeastern California, USA. Importantly, sites spanned mesic and xeric average precipitation conditions that contributed substantially to vegetation community structure across cold desert ecosystems of the North American Great Basin. Vegetative cover immediately surrounding sage-grouse nests was important for both nest site selection and nest survival, but responses varied between mesic and xeric sites. For example, while taller perennial grasses were selected at xeric sites, we found no evidence of selection for perennial grass at mesic sites, indicating a functional response to availability of habitat features between hydrographic regions. Furthermore, perennial grass height and forb height both had positive effects on nest survival at xeric sites, but we found varying effects at mesic sites. We emphasize that precipitation conditions driving ecosystem productivity vary regionally among sagebrush communities, shaping vegetation structure and suitable habitat conditions for nesting sage-grouse.</p>","language":"English","publisher":"American Ornithological Society","doi":"10.1093/ornithapp/duac052","usgsCitation":"Brussee, B.E., Coates, P.S., O’Neil, S.T., Ricca, M.A., Dudko, J.E., Espinosa, S.P., Gardner, S.C., Casazza, M.L., and Delehanty, D.J., 2023, Influence of fine-scale habitat characteristics on sage-grouse nest site selection and nest survival varies by mesic and xeric site conditions: Ornithological Applications, v. 125, no. 1, duac052, 15 p., https://doi.org/10.1093/ornithapp/duac052.","productDescription":"duac052, 15 p.","ipdsId":"IP-123231","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444825,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duac052","text":"Publisher Index Page"},{"id":435505,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EWKWJ3","text":"USGS data release","linkHelpText":"Code to Examine How the Influence of Fine-Scale Habitat Characteristics on Greater Sage-Grouse (Centrocercus urophasianus) Nest Site Selection and Nest Survival Varies by Mesic and Xeric Site Conditions version 1.0"},{"id":435504,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JJ747B","text":"USGS data release","linkHelpText":"Influence of microhabitat characteristics on sage-grouse nest site selection and nest survival depends on ecological site potential"},{"id":412804,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dudko, Jonathan E.","contributorId":210049,"corporation":false,"usgs":false,"family":"Dudko","given":"Jonathan","email":"","middleInitial":"E.","affiliations":[{"id":38059,"text":"Idaho State U","active":true,"usgs":false}],"preferred":false,"id":863779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":863780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863782,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863783,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70239758,"text":"70239758 - 2023 - Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California","interactions":[],"lastModifiedDate":"2023-01-18T14:25:55.153483","indexId":"70239758","displayToPublicDate":"2023-01-15T08:20:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California","docAbstract":"<p><span>In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail (</span><i>Anas acuta</i><span>), Green-winged Teal (</span><i>Anas crecca</i><span>), and Northern Shoveler (</span><i>Anas clypeata</i><span>), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4367","usgsCitation":"Conlisk, E.E., Byrd, K.B., Matchett, E., Lorenz, A., Casazza, M.L., Golet, G.H., Reynolds, M.D., Sesser, K.A., and Reiter, M.E., 2023, Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California: Ecosphere, v. 14, e4367, 19 p., https://doi.org/10.1002/ecs2.4367.","productDescription":"e4367, 19 p.","ipdsId":"IP-144890","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":444827,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4367","text":"Publisher Index Page"},{"id":412024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.81873286495954,\n              35.04394124445325\n            ],\n            [\n              -118.8570190310794,\n              36.52123291574787\n            ],\n            [\n              -120.23927537042829,\n              37.988003366747364\n            ],\n            [\n              -121.61872476287942,\n              40.10174582877633\n            ],\n            [\n              -121.96284031570764,\n              40.846007013038246\n            ],\n            [\n              -123.06491347085935,\n              40.526780450482676\n         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E.","contributorId":301022,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":861775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":861776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":861777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":861778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":861779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golet, Gregory H.","contributorId":89844,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":861780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reynolds, Mark D.","contributorId":301023,"corporation":false,"usgs":false,"family":"Reynolds","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":861781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sesser, Kristin A.","contributorId":215294,"corporation":false,"usgs":false,"family":"Sesser","given":"Kristin","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":861782,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reiter, Matthew E. 0000-0002-0587-786X","orcid":"https://orcid.org/0000-0002-0587-786X","contributorId":271031,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":56258,"text":"Point Blue","active":true,"usgs":false}],"preferred":false,"id":861783,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70239957,"text":"70239957 - 2023 - Elevation-based probabilistic mapping of irregularly flooded wetlands along the northern Gulf of Mexico coast","interactions":[],"lastModifiedDate":"2023-03-28T15:05:16.75939","indexId":"70239957","displayToPublicDate":"2023-01-14T07:17:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Elevation-based probabilistic mapping of irregularly flooded wetlands along the northern Gulf of Mexico coast","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0060\">Irregularly flooded wetlands are found above the mean high water tidal datum and are exposed to tides and saltwater less frequently than daily. These wetlands provide important ecosystem services, such as providing habitat for fish and wildlife, enhancing water quality, ameliorating flooding impacts, supporting coastal food webs, and protecting upslope areas from erosion. Mapping irregularly flooded wetlands is challenging given their expansive coverage and dynamic nature. Furthermore, coastal wetlands are expected to change over the coming century due to sea-level rise and changes in the frequency and intensity of extreme storms. Consequently, coastal managers need baseline information on the spatial distribution of wetlands along with efficient and repeatable methods for observing changes. In this study, we used coastal wetlands from existing land use land cover data, best available lidar-derived digital elevation models, and Monte Carlo simulations to incorporate elevation uncertainty to create a probabilistic map of irregularly flooded wetlands along the northern Gulf of Mexico coast (USA). Our approach integrated findings from a review of coastal wetland elevation error in lidar datasets and an analysis of spatial autocorrelations of wetland elevation. We found a positive correlation (<i>r</i>&nbsp;=&nbsp;0.563,<span>&nbsp;</span><i>p</i>&nbsp;&lt;&nbsp;0.0001) when comparing the probability estimated from a digital elevation model and in situ elevation observations. The differences in probability had a mean bias error of −0.04 (i.e., digital elevation model-based probability tends to be slightly lower), a mean absolute error of 0.20, and a root mean square error of 0.26. Beyond this overall validation, we explored error metrics for land cover classes and lidar collection details. To quantify areal coverage of the probabilistic output, we classified the probability values into equal bins using an interval of 0.33. The areal coverage of the lowest probability bin (“unlikely”; probability ≤0.33) was separated into the upper and lower portions of the irregularly flooded wetland zone. Of the coastal wetlands along the northern Gulf of Mexico coast about 38% were classified as unlikely and low with the greatest coverage in south Louisiana and the Everglades and around 33% were classified as unlikely and high with the greatest coverage in the Everglades and Texas. The relative coverage within the highest probability bin (“likely”; probability &gt;0.66) covered around 13%, with the greatest coverage in south Florida, south Louisiana, and Texas. The framework developed in this study can be transferred to other coastal wetland areas and updated to observe changes with sea-level rise.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2023.113451","usgsCitation":"Enwright, N., Cheney, W.C., Evans, K., Thurman, H., Woodrey, M.S., Fournier, A., Gesch, D.B., Pitchford, J.L., Stoker, J.M., and Medeiros, S.C., 2023, Elevation-based probabilistic mapping of irregularly flooded wetlands along the northern Gulf of Mexico coast: Remote Sensing of Environment, v. 287, 113451, 14 p.; 2 Data Releases, https://doi.org/10.1016/j.rse.2023.113451.","productDescription":"113451, 14 p.; 2 Data Releases","ipdsId":"IP-145605","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444832,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2023.113451","text":"Publisher Index Page"},{"id":412358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":414818,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q2592L","linkFileType":{"id":5,"text":"html"}},{"id":414817,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MLO26U","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Gulf of Mexico coastline","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.54653474928946,\n              25.576920146584584\n            ],\n            [\n              -81.71016757208815,\n              27.94557824049396\n            ],\n            [\n              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-83.19961758527069,\n              28.027782531007816\n            ],\n            [\n              -82.26871132703153,\n              26.621878442379753\n            ],\n            [\n              -81.43089569461618,\n              24.945510858029138\n            ],\n            [\n              -80.68617068802521,\n              25.07205491218268\n            ],\n            [\n              -80.54653474928946,\n              25.576920146584584\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"287","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Enwright, Nicholas 0000-0002-7887-3261","orcid":"https://orcid.org/0000-0002-7887-3261","contributorId":202164,"corporation":false,"usgs":true,"family":"Enwright","given":"Nicholas","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":862506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheney, Wyatt C.","contributorId":301249,"corporation":false,"usgs":false,"family":"Cheney","given":"Wyatt","email":"","middleInitial":"C.","affiliations":[{"id":65344,"text":"Cheney Consulting under contract to the U.S. Geological Survey, Wetland and Aquatic Research Center","active":true,"usgs":false}],"preferred":false,"id":862507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Kristine O.","contributorId":301250,"corporation":false,"usgs":false,"family":"Evans","given":"Kristine O.","affiliations":[{"id":65345,"text":"Quantitative Ecology and Spatial Technologies (QuEST) Lab, Department of Wildlife, Fisheries and Aquaculture, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":862508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurman, Hana R. 0000-0001-7097-5362","orcid":"https://orcid.org/0000-0001-7097-5362","contributorId":294346,"corporation":false,"usgs":false,"family":"Thurman","given":"Hana R.","affiliations":[{"id":63558,"text":"Cherokee Nation System Solutions, contracted to the U.S. Geological Survey, Wetland and Aquatic Research Center","active":true,"usgs":false}],"preferred":false,"id":862509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woodrey, Mark S.","contributorId":259212,"corporation":false,"usgs":false,"family":"Woodrey","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":862510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fournier, Auriel 0000-0002-8530-9968","orcid":"https://orcid.org/0000-0002-8530-9968","contributorId":261669,"corporation":false,"usgs":false,"family":"Fournier","given":"Auriel","email":"","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":862511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":862512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pitchford, Jonathan L.","contributorId":301251,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":862513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":862514,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Medeiros, Stephen C.","contributorId":166892,"corporation":false,"usgs":false,"family":"Medeiros","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":24567,"text":"UCF","active":true,"usgs":false}],"preferred":false,"id":862515,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70239566,"text":"pp1877 - 2023 - Hydrogeology, land-surface subsidence, and documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) model, southeast Texas, 1897–2018","interactions":[],"lastModifiedDate":"2026-02-18T22:23:41.870989","indexId":"pp1877","displayToPublicDate":"2023-01-13T11:33:47","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1877","displayTitle":"Hydrogeology, Land-Surface Subsidence, and Documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) Model, Southeast Texas, 1897–2018","title":"Hydrogeology, land-surface subsidence, and documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) model, southeast Texas, 1897–2018","docAbstract":"<h1>Executive Summary</h1><p class=\"Citation\"><span>As a part of the Texas Water Development Board groundwater availability modeling program, the U.S. Geological Survey developed the Gulf Coast Land Subsidence and Groundwater-Flow model (hereinafter, the “GULF model”) and ensemble to simulate groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system (the study area) in Texas from predevelopment (1897) through 2018. Since the publication of a previous groundwater model for the greater Houston area in 2012, there have been changes to the distribution of groundwater withdrawals and advances in modeling tools. To reflect these changes and to simulate more recent conditions, the GULF model was developed in cooperation with the Harris-Galveston and Fort Bend Subsidence Districts to provide an updated Groundwater Availability Model.</span></p><p class=\"Citation\"><span>Since the early 1900s, most of the groundwater withdrawals in the study area have been from three of the hydrogeologic units that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers and, more recently, from the Catahoula confining unit. Withdrawals from these hydrogeologic units are used for municipal supply, commercial and industrial use, and irrigation purposes. Withdrawals of large quantities of groundwater in the greater Houston area have caused widespread groundwater-level declines in the Chicot, Evangeline, and Jasper aquifers of more than 300 feet (ft). Early development of the aquifer system, which began before 1900, resulted in nearly 50 percent of the eventual historical groundwater-level minimums having been reached as early as 1946 in some areas. These groundwater-level declines led to more than 9 ft of land-surface subsidence—historically in central and southeastern Harris County and Galveston County, but more recently in northern, northwestern, and western Harris County, Montgomery County, and northern Fort Bend County—from depressurization and compaction of clay and silt layers interbedded in the aquifer sediments.</span></p><p class=\"Citation\"><span>In a generalized conceptual model of the Gulf Coast aquifer system, water enters the groundwater system in topographically high outcrops of the hydrogeologic units in the northwestern part of the aquifer system. Groundwater that does not discharge to streams flows to intermediate and deep zones of the aquifer system southeastward of the outcrop areas where it is discharged by wells and by upward leakage in topographically low areas near the coast. The uppermost parts of the aquifer system, which include outcrop areas, are under water-table (unconfined) conditions where the groundwater is not confined under pressure. As depth increases in the aquifer system and interbedded clay and silt layers accumulate, water-table conditions evolve into confined conditions where the groundwater is under pressure.</span></p><p class=\"Citation\"><span>Groundwater flow and land-surface subsidence in the GULF model and ensemble were simulated by using MODFLOW 6 with the Skeletal Storage, Compaction, and Subsidence package. The model consists of six layers, one for each of the five hydrogeologic units in the northern part of the Gulf Coast aquifer system and a surficial top layer that includes part of each hydrogeologic unit. Transient groundwater flow was simulated during 1897–2018 by using a combination of multiyear, annual, and monthly stress periods. An initial steady-state stress period was configured to represent predevelopment mean annual inflows and outflows. The subsidence package used in the GULF model and ensemble uses a head-based subsidence formulation that simulates the delayed drainage response from clay and silt sediment to changes in groundwater levels.</span></p><p class=\"Citation\"><span>The GULF model and ensemble were history matched to groundwater-level observations at selected wells, land-surface subsidence at benchmarks, aquifer compaction at borehole extensometers, and vertical displacement from Global Positioning System stations. A Bayesian framework was used to represent uncertainty in modeled parameters and simulated outputs of interest. History matching and uncertainty quantification were performed by using a Monte Carlo approach enabled through iterative ensemble smoother software to produce an ensemble of models fit to historical data. The iterative ensemble smoother substantially reduced the computational demand of parameter estimation by approximating the first-order relation between model inputs and outputs, thereby allowing 183,207 adjustable parameters to be used for history matching at a relatively low computational and time cost.</span></p><p class=\"Citation\"><span>The history-matched parameter values are within the ranges of previously published values and agree with the current understanding of the spatial and temporal patterns of parameter uncertainty for the Gulf Coast aquifer system. A good agreement between the observed (or estimated) and simulated groundwater levels, land-surface subsidence, compaction, and vertical displacement was obtained across the modeled area based on qualitative and quantitative comparisons. Ensemble mean annual groundwater-flow rates to the Chicot, Evangeline, Jasper aquifers and Catahoula confining unit were 0.0–0.49 inch (in.), 0.09–0.33 in., 0.01–0.07 in., and 0.01–0.05 in., respectively. GULF model mean annual groundwater-flow rates to the Chicot, Evangeline, and Jasper aquifers and Catahoula confining unit were 0.31 in., 0.19 in., 0.03 in., and 0.03 in., respectively.</span></p><p class=\"Citation\"><span>The GULF-model-simulated recharge to the outcrop area was the largest inflow (75 percent), and recharge to other areas was 25 percent of the model inflow. The simulated outflows included (1) net surface-water/groundwater exchange with study area streams (50 percent), (2) groundwater use (49 percent), and (3) net surface-water/groundwater exchange with the Gulf of Mexico (1 percent). The sum of the simulated values of the outflows (1,041,973 acre-feet per year [acre-ft/yr]) and the elastic expansion of the fine-grained sediment and numerical solver error (339 acre-ft/yr) minus the inflows (654,172 acre-ft/yr) represents the reduction of storage from the Gulf Coast aquifer system (388,140 acre-ft/yr). Most of the storage depletion is caused by the long-term groundwater-level declines that have resulted primarily in inelastic compaction.</span></p><p class=\"Citation\"><span>The GULF model was used to estimate Jasper aquifer compaction at selected benchmarks in Montgomery County and northern Harris County, which are the primary locations of Jasper aquifer groundwater use. Simulated Jasper aquifer compaction in northern Harris County was between 0.2 and 0.5 ft, or between about 5 and 16 percent of simulated subsidence at the benchmark locations. Simulated Jasper aquifer compaction in Montgomery County was between 0.8 and 1.2 ft, or between about 33 and 57 percent of simulated subsidence at the benchmark locations.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1877","issn":"ISSN 2330-7102","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District and the Fort Bend Subsidence District","usgsCitation":"Ellis, J.H., Knight, J.E., White, J.T., Sneed, M., Hughes, J.D., Ramage, J.K., Braun, C.L., Teeple, A., Foster, L., Rendon, S.H., and Brandt, J., 2023, Hydrogeology, land-surface subsidence, and documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) model, southeast Texas, 1897–2018 (ver. 1.1, November 2023): U.S. Geological Survey Professional Paper 1877, 425 p., https://doi.org/10.3133/pp1877.","productDescription":"Report: xx, 425 p., 8 Appendixes; Data Release","numberOfPages":"450","onlineOnly":"Y","ipdsId":"IP-127938","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":500160,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114230.htm","linkFileType":{"id":5,"text":"html"}},{"id":422702,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/pp1877/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":411889,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XM8A1P","text":"USGS Data Release","linkHelpText":"MODFLOW 6 model and ensemble used in the simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, 1897–2018"},{"id":422705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/pp1877/coverthb2.jpg"},{"id":411888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1877/pp1877.pdf","text":"Report","size":"184 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.54245107965883,\n              31.199747848944256\n            ],\n            [\n              -96.33297842340923,\n              30.997489619299927\n            ],\n            [\n              -96.79440420465926,\n              30.136679255787612\n            ],\n            [\n              -96.02536123590899,\n              28.551820525825022\n            ],\n            [\n              -95.36068838434645,\n              28.86498475853952\n            ],\n            [\n              -94.72348135309639,\n              29.28746086219381\n            ],\n            [\n              -94.65207022028405,\n              29.402380282489133\n            ],\n            [\n              -94.23458975153387,\n              29.574516044800063\n            ],\n            [\n              -93.82809561090883,\n              29.670020494605353\n            ],\n            [\n              -93.89401357965892,\n              29.803574466610613\n            ],\n            [\n              -93.6907665093464,\n              30.05113045792723\n            ],\n            [\n              -93.67428701715903,\n              30.307554456695556\n            ],\n            [\n              -93.6687938530968,\n              30.563309394138372\n            ],\n            [\n              -93.49301260309677,\n              30.841976559030968\n            ],\n            [\n              -93.4765331109094,\n              31.077503645282718\n            ],\n            [\n              -93.54245107965883,\n              31.199747848944256\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","edition":"Version 1.0: January 13, 2023; Version 1.1: November 28, 2023","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/ot-water\" href=\"https://www.usgs.gov/centers/ot-water\">Oklahoma-Texas Water Science Center</a> <br>U.S. Geological Survey <br>1505 Ferguson Lane <br>Austin, TX 78754-4501&nbsp;<br></p><p><a data-mce-href=\"../\" href=\"../\">Contact Pubs Warehouse</a><br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Hydrogeology</li><li>Land-Surface Subsidence</li><li>Simulation of Groundwater Flow and Land-Surface Subsidence</li><li>Model Uses, Limitations, and Assumptions</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Model Grid Construction</li><li>Appendix 2. Groundwater Use</li><li>Appendix 3. Predevelopment to Early Development Groundwater-Level Measurements</li><li>Appendix 4. Climate Stations In and Near the Gulf Coast Aquifer System Study Area</li><li>Appendix 5. Historical Subsidence Contour Maps</li><li>Appendix 6. Global Navigation Satellite System Survey Uncertainty</li><li>Appendix 7. Model Temporal Discretization, History Matching, and Uncertainty Analysis with PESTPP-IES</li><li>Appendix 8. Groundwater Model Observations and Water Budgets</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-01-13","revisedDate":"2023-11-28","noUsgsAuthors":false,"publicationDate":"2023-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, J.H. 0000-0001-7161-3136 jellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7161-3136","contributorId":196287,"corporation":false,"usgs":true,"family":"Ellis","given":"J.H.","email":"jellis@usgs.gov","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Jacob E. 0000-0003-0271-9011 jknight@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-9011","contributorId":5143,"corporation":false,"usgs":true,"family":"Knight","given":"Jacob","email":"jknight@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sneed, Michelle 0000-0002-8180-382X","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":214186,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":861628,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramage, Jason K. 0000-0001-8014-2874 jkramage@usgs.gov","orcid":"https://orcid.org/0000-0001-8014-2874","contributorId":3856,"corporation":false,"usgs":true,"family":"Ramage","given":"Jason","email":"jkramage@usgs.gov","middleInitial":"K.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861629,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Braun, Christopher L. 0000-0002-5540-2854 clbraun@usgs.gov","orcid":"https://orcid.org/0000-0002-5540-2854","contributorId":925,"corporation":false,"usgs":true,"family":"Braun","given":"Christopher","email":"clbraun@usgs.gov","middleInitial":"L.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861630,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":193061,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861631,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Foster, Linzy K. 0000-0002-7373-7017","orcid":"https://orcid.org/0000-0002-7373-7017","contributorId":259186,"corporation":false,"usgs":true,"family":"Foster","given":"Linzy","email":"","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861632,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rendon, Samuel H. 0000-0001-5589-0563 srendon@usgs.gov","orcid":"https://orcid.org/0000-0001-5589-0563","contributorId":197178,"corporation":false,"usgs":true,"family":"Rendon","given":"Samuel H.","email":"srendon@usgs.gov","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":861633,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brandt, Justin T. 0000-0002-9397-6824 jbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":157,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"jbrandt@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861634,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70255224,"text":"70255224 - 2023 - Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish","interactions":[],"lastModifiedDate":"2024-06-14T16:00:03.261943","indexId":"70255224","displayToPublicDate":"2023-01-13T10:52:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish","docAbstract":"<p><span>Differences in the life history pathways (LHPs) of juvenile animals are often associated with differences in demographic rates in later life stages. For migratory animals, different LHPs often result in animals from the same population occupying distinct habitats subjected to different environmental drivers. Understanding how demographic rates differ among animals expressing different LHPs may reveal fitness trade-offs that drive the expression of alternative LHPs and enable better prediction of population dynamics in a changing environment. To understand how demographic outcomes and their relationships with environmental variables differ among animals with different LHPs, we analyzed a long-term (2006–2021) mark–recapture dataset for Chinook salmon (</span><i>Oncorhynchus tshawytscha</i><span>) from the Wenatchee River, Washington, USA. Distinct LHPs represented in this population include either remaining in the natal stream until emigrating to the ocean as a 1-year-old (natal-reach rearing) or emigrating from the natal stream and rearing in downstream habitats for several months before completing the emigration to the ocean as a 1-year-old (downstream rearing). We found that downstream-rearing fish emigrated to the ocean 19 days earlier on average and returned as adults from the ocean at higher rates. We detected a positive correlation between rate of return from the ocean by downstream-rearing fish and coastal upwelling in their spring of outmigration, whereas for natal-reach-rearing fish we detected a positive correlation with sea surface temperature during their first marine summer. Different responses to environmental variability should lead to asynchrony in adult abundance among juvenile LHPs. A higher proportion of downstream-rearing fish returned at younger ages compared with natal-reach-rearing fish, which contributed to variability in age at reproduction and greater mixing across generations. Our results demonstrate how diversity in juvenile LHPs is associated with heterogeneity in demographic rates during subsequent life stages, which can in turn affect variance in aggregate population abundance and response to environmental change. Our findings underscore the importance of considering life history diversity in demographic analyses and provide insights into the effects of life history diversity on population dynamics and trade-offs that contribute to the maintenance of life history diversity.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4366","usgsCitation":"Sorel, M.H., Murdoch, A.R., Zabel, R.W., Jorgensen, J.C., Kamphaus, C.M., and Converse, S.J., 2023, Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish: Ecosphere, v. 14, no. 1, e4366, 14 p., https://doi.org/10.1002/ecs2.4366.","productDescription":"e4366, 14 p.","ipdsId":"IP-141079","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4366","text":"Publisher Index Page"},{"id":430212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Wenatchee River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.2,\n              48.2\n            ],\n            [\n              -121.2,\n              47.4\n            ],\n            [\n              -120.2,\n              47.4\n            ],\n            [\n              -120.2,\n              48.2\n            ],\n            [\n              -121.2,\n              48.2\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sorel, Mark H.","contributorId":171739,"corporation":false,"usgs":false,"family":"Sorel","given":"Mark","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":903770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murdoch, Andrew R.","contributorId":339213,"corporation":false,"usgs":false,"family":"Murdoch","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":903771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zabel, Richard W.","contributorId":272049,"corporation":false,"usgs":false,"family":"Zabel","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":903772,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgensen, Jeffrey C.","contributorId":339208,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":903773,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kamphaus, Cory M.","contributorId":339215,"corporation":false,"usgs":false,"family":"Kamphaus","given":"Cory","email":"","middleInitial":"M.","affiliations":[{"id":39287,"text":"Yakama Nation Fisheries","active":true,"usgs":false}],"preferred":false,"id":903774,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":903775,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239358,"text":"sir20225099 - 2023 - Recent history of glacial lake outburst floods, analysis of channel changes, and development of a two-dimensional flow and sediment transport model of the Snow River near Seward, Alaska","interactions":[],"lastModifiedDate":"2026-02-23T19:23:26.079763","indexId":"sir20225099","displayToPublicDate":"2023-01-12T09:48:28","publicationYear":"2023","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":"2022-5099","displayTitle":"Recent History of Glacial Lake Outburst Floods, Analysis of Channel Changes, and Development of a Two-Dimensional Flow and Sediment Transport Model of the Snow River near Seward, Alaska","title":"Recent history of glacial lake outburst floods, analysis of channel changes, and development of a two-dimensional flow and sediment transport model of the Snow River near Seward, Alaska","docAbstract":"<p><span>Snow Lake, a glacially dammed lake on the Snow Glacier near Seward, Alaska, drains rapidly every 14 months–3 years, causing flooding along the Snow River. Highway, railroad, and utility infrastructure on the lower Snow River floodplain is vulnerable to flood damage. Historical hydrology, geomorphology, and two-dimensional hydraulic and sediment transport modeling were used to assess the flood risks from Snow Lake outburst floods. Floods have become more frequent, peaked more rapidly, and have had generally higher peaks over the last 20 years as the Snow Glacier has thinned, translating to a greater potential for flood damage. Rapidly shifting channel locations and the occasional introduction of large volumes of debris to the river also threaten infrastructure on the floodplain and in the channel. An assessment of the historical channel planform between 1951 and 2019 showed that there have been more and less stable segments along the lower Snow River and that channel migration has generally been toward the east. An analysis of floodplain elevations using 2008 light detection and ranging (lidar) showed that the main channel is relatively high compared to floodplain channels that carry floodwaters along the railroad grade, so that once the main channel banks are overtopped water rapidly disperses throughout the floodplain. A two-dimensional flow and sediment transport model was developed, and its simulation results were compared to three past outburst floods from 2007, 2017, and 2019. Despite the complex floodplain and channel geometry, coarse resolution of the mesh, and sediment input data, the model successfully simulated areas of observed scour along the railroad grade and at the guidebank to the highway bridge. The modeled water-surface elevations generally replicated peak elevations recorded at a streamgage in the middle of the model domain and at pressure transducers installed on the floodplain and main channel, although there were discrepancies on the rising limb and some locations had a poorer fit than others. A model of a hypothetical check flood, approximately 150 percent of the largest recorded outburst flood, was developed to provide hydraulic variables to use when planning for infrastructure upgrades.</span><span><br></span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225099","collaboration":"Prepared in cooperation with the Alaska Railroad Corporation and the Alaska Department of Transportation and Public Facilities and the Alaska Department of Transportation and Public Facilities","usgsCitation":"Beebee, R.A., 2022, Recent history of glacial lake outburst floods, analysis of channel changes, and development of a two-dimensional flow and sediment transport model of the Snow River near Seward, Alaska: U.S. Geological Survey Scientific Investigations Report 2022–5099, 39 p., https://doi.org/10.3133/sir20225099.","productDescription":"vi, 39 p.","onlineOnly":"Y","ipdsId":"IP-128851","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":490414,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VVQH9D","text":"USGS data release","linkHelpText":"Water Surfaces Elevations During an Outburst Flood from Pressure Transducers at Snow River, Alaska, 2019"},{"id":435509,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X2YE9O","text":"USGS data release","linkHelpText":"GIS and Hydraulic Model data in Support of a Geomorphic and Hydraulic Assessment of Glacial Outburst Floods on the Snow River near Seward, Alaska"},{"id":411681,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5099/coverthb2.jpg"},{"id":411685,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5099/sir20225099.XML"},{"id":411684,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5099/images"},{"id":411683,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225099/full","text":"Report","description":"SIR 2022-5099"},{"id":411682,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5099/sir20225099.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5099"},{"id":500453,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114227.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","city":"Seward","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -149.59345352902176,\n              60.45612040349263\n            ],\n            [\n              -149.59345352902176,\n              60.128459300361044\n            ],\n            [\n              -149.14199122584208,\n              60.128459300361044\n            ],\n            [\n              -149.14199122584208,\n              60.45612040349263\n            ],\n            [\n              -149.59345352902176,\n              60.45612040349263\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Flood History</li><li>Geomorphic Setting and Human Environment</li><li>Channel Change, Geomorphology, and Debris Recruitment Analysis Methods</li><li>Analysis Results</li><li>Hydraulic and Sediment Transport Modeling</li><li>Results</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2023-01-12","noUsgsAuthors":false,"publicationDate":"2023-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Beebee, Robin A. 0000-0002-2976-7294 rbeebee@usgs.gov","orcid":"https://orcid.org/0000-0002-2976-7294","contributorId":5778,"corporation":false,"usgs":true,"family":"Beebee","given":"Robin","email":"rbeebee@usgs.gov","middleInitial":"A.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":861254,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70239770,"text":"70239770 - 2023 - Taxonomic identity, biodiversity, and antecedent disturbances shape the dimensional stability of stream invertebrates","interactions":[],"lastModifiedDate":"2023-05-25T15:35:44.832482","indexId":"70239770","displayToPublicDate":"2023-01-12T06:35:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Taxonomic identity, biodiversity, and antecedent disturbances shape the dimensional stability of stream invertebrates","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>The “dimensional stability” approach measures different components of ecological stability to investigate how they are related. Yet, most empirical work has used small-scale and short-term experimental manipulations. Here, we apply this framework to a long-term observational dataset of stream macroinvertebrates sampled between the winter flooding and summer monsoon seasons. We test hypotheses that relate variation among stability metrics across different taxa, the magnitude of antecedent (monsoon) and immediate (winter) floods to stability metrics, and the relative importance of disturbance magnitude and taxonomic richness on community dimensional stability. Cluster analysis revealed four distinct stability types, and we found that the magnitude of floods during the prior monsoon was more important in influencing stability than the winter flood itself. For dimensional stability at the community level, taxonomic richness was more important than disturbance magnitude. This work demonstrates that abiotic and biotic factors determine dimensional stability in a natural ecosystem.</p></div></div>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10303","usgsCitation":"Allen, D.C., Gill, B.A., Metcalfe, A., Bonjour, S.M., Starr, S., Wang, J., Valentin, D., and Grimm, N.B., 2023, Taxonomic identity, biodiversity, and antecedent disturbances shape the dimensional stability of stream invertebrates: Limnology and Oceanography Letters, v. 8, no. 3, p. 464-472, https://doi.org/10.1002/lol2.10303.","productDescription":"9 p.","startPage":"464","endPage":"472","ipdsId":"IP-137395","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444851,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10303","text":"Publisher Index Page"},{"id":412065,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Daniel C","contributorId":301055,"corporation":false,"usgs":false,"family":"Allen","given":"Daniel","email":"","middleInitial":"C","affiliations":[{"id":65293,"text":"Department of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA","active":true,"usgs":false}],"preferred":false,"id":861843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, Brian A","contributorId":301056,"corporation":false,"usgs":false,"family":"Gill","given":"Brian","email":"","middleInitial":"A","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":861844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Metcalfe, Anya 0000-0002-6286-4889","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":221738,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":861845,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonjour, Sophia M","contributorId":244905,"corporation":false,"usgs":false,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"M","affiliations":[{"id":49015,"text":"School of Life Sciences, Arizona State University, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":861846,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Starr, Scott","contributorId":301057,"corporation":false,"usgs":false,"family":"Starr","given":"Scott","email":"","affiliations":[{"id":65294,"text":"Biology Department, Hampden-Sydney College, Hampden-Sydney, VA","active":true,"usgs":false}],"preferred":false,"id":861847,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Junna","contributorId":301058,"corporation":false,"usgs":false,"family":"Wang","given":"Junna","email":"","affiliations":[{"id":65295,"text":"Department of Environmental Science and Policy, University of California, Davis, CA","active":true,"usgs":false}],"preferred":false,"id":861848,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valentin, Diana","contributorId":301059,"corporation":false,"usgs":false,"family":"Valentin","given":"Diana","email":"","affiliations":[{"id":65296,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":861849,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grimm, Nancy B.","contributorId":44058,"corporation":false,"usgs":false,"family":"Grimm","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":861850,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70261552,"text":"70261552 - 2023 - Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands","interactions":[],"lastModifiedDate":"2024-12-16T15:26:09.876503","indexId":"70261552","displayToPublicDate":"2023-01-11T09:10:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2142,"text":"Journal for Nature Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands","docAbstract":"<p><span>Wetlands are among the most threatened ecosystems worldwide due to&nbsp;</span>climate change<span>&nbsp;and land-use conversion. Regional biodiversity of temporary wetlands is dependent on the existence of habitat complexes with variable&nbsp;hydroperiods. Because temperature and rainfall regimes are predicted to shift globally, together with land-use patterns, different scenarios of wetland loss are expected in the future. To understand how wetland biodiversity might change in the future, it is important to evaluate how the loss of particular&nbsp;hydroperiods&nbsp;will affect overall diversity in a region. Using invertebrate datasets from five wetland complexes distributed across South and North America, we calculated&nbsp;beta diversity&nbsp;metrics for each region. Then we contrasted those metrics to simulations of sequential deletions of subsets (30%) of the long-, moderate- and short-hydroperiod wetlands to assess which wetland class would most affect invertebrate&nbsp;beta diversity&nbsp;in each region. Deletions of the short-hydroperiod wetlands led to the most significant decline in beta diversity. However, deletion effects of different wetland classes varied across study regions, with a negative correlation existing between deletions of the long- and short-hydroperiod wetlands on invertebrate beta diversity. Our simulations indicate that loss of short-hydroperiod wetlands will have the most significant effects on invertebrate beta diversity, but loss of long-hydroperiod wetlands will also be important. Thus, wetlands from both hydroperiod extremes should be considered when assessing potential biodiversity declines associated with habitat loss.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jnc.2023.126332","usgsCitation":"Pires, M.M., Garcia, P.E., Maltchik, L., Stenert, C., Epele, L.B., McLean, K., Kneitel, J., Racey, S., and Batzer, D., 2023, Searching for the Achilles heel(s) for maintaining invertebrate biodiversity across complexes of depressional wetlands: Journal for Nature Conservation, v. 72, 126332, 8 p., https://doi.org/10.1016/j.jnc.2023.126332.","productDescription":"126332, 8 p.","ipdsId":"IP-144845","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467126,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jnc.2023.126332","text":"Publisher Index Page"},{"id":465145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pires, Mateus M.","contributorId":347168,"corporation":false,"usgs":false,"family":"Pires","given":"Mateus","email":"","middleInitial":"M.","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Patricia E.","contributorId":347170,"corporation":false,"usgs":false,"family":"Garcia","given":"Patricia","email":"","middleInitial":"E.","affiliations":[{"id":83093,"text":"Grupo de Ecología de Sistemas Acuáticos a Escala de Paisaje (GESAP), INIBIOMA-CONICET Universidad Nacional del Comahue, Bariloche, Argentina","active":true,"usgs":false}],"preferred":false,"id":921005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maltchik, Leonardo","contributorId":347171,"corporation":false,"usgs":false,"family":"Maltchik","given":"Leonardo","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stenert, Cristina","contributorId":347172,"corporation":false,"usgs":false,"family":"Stenert","given":"Cristina","email":"","affiliations":[{"id":83092,"text":"Programa de Pós-Graduação em Biologia de Ambientes Aquáticos Continentais, Universidade Federal do Rio Grande (FURG), Rio Grande, RS, Brazil","active":true,"usgs":false}],"preferred":false,"id":921007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Epele, Luis B.","contributorId":347173,"corporation":false,"usgs":false,"family":"Epele","given":"Luis","email":"","middleInitial":"B.","affiliations":[{"id":57276,"text":"Centro de Investigación Esquel de Montaña y Estepa Patagónica (CONICET-UNPSJB), Roca 12 780, Esquel, Chubut, Argentina","active":true,"usgs":false}],"preferred":false,"id":921008,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McLean, Kyle 0000-0003-3803-0136 kmclean@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-0136","contributorId":168533,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle","email":"kmclean@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":921009,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kneitel, Jamie M.","contributorId":347174,"corporation":false,"usgs":false,"family":"Kneitel","given":"Jamie M.","affiliations":[{"id":83096,"text":"Department of Biological Sciences, California State University, 6000 J St, Sacramento, CA 95819, USA","active":true,"usgs":false}],"preferred":false,"id":921010,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Racey, Sophie","contributorId":347169,"corporation":false,"usgs":false,"family":"Racey","given":"Sophie","email":"","affiliations":[{"id":57293,"text":"Department of Entomology, University of Georgia, Athens, GA, USA","active":true,"usgs":false}],"preferred":false,"id":921004,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Batzer, Darold P.","contributorId":347175,"corporation":false,"usgs":false,"family":"Batzer","given":"Darold P.","affiliations":[{"id":83097,"text":"Department of Entomology, 120 Cedar St, University of Georgia, Athens, GA 30605, USA","active":true,"usgs":false}],"preferred":false,"id":921011,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70239374,"text":"70239374 - 2023 - “Aftershock Faults” and what they could mean for seismic hazard assessment","interactions":[],"lastModifiedDate":"2023-01-11T12:59:10.683661","indexId":"70239374","displayToPublicDate":"2023-01-11T06:57:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"“Aftershock Faults” and what they could mean for seismic hazard assessment","docAbstract":"<div id=\"135440517\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>We study stress‐loading mechanisms for the California faults used in rupture forecasts. Stress accumulation drives earthquakes, and that accumulation mechanism governs recurrence. Most moment release in California occurs because of relative motion between the Pacific plate and the Sierra Nevada block; we calculate relative motion directions at fault centers and compare with fault displacement directions. Dot products between these vectors reveal that some displacement directions are poorly aligned with plate motions. We displace a 3D finite‐element model according to relative motions and resolve stress tensors onto defined fault surfaces, which reveal that poorly aligned faults receive no tectonic loading. Because these faults are known to be active, we search for other loading mechanisms. We find that nearly all faults with no tectonic loading show increase in stress caused by slip on the San Andreas fault, according to an elastic dislocation model. Globally, faults that receive a sudden stress change respond with triggered earthquakes that obey an Omori law rate decay with time. We therefore term this class of faults as “aftershock faults.” These faults release ∼4% of the moment release in California, have ∼0.1%–5% probability of<span>&nbsp;</span><i>M</i>&nbsp;6.7 earthquakes in 30&nbsp;yr, and have a 0.001%–1% 30 yr<span>&nbsp;</span><i>M</i>&nbsp;7.7 probability range.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320220036","usgsCitation":"Parsons, T.E., Geist, E.L., and Parsons, S.E., 2023, “Aftershock Faults” and what they could mean for seismic hazard assessment: The Seismic Record, v. 3, no. 1, p. 1-11, https://doi.org/10.1785/0320220036.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-144223","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444863,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320220036","text":"Publisher Index 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 \"}}]}","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parsons, Sophie E.","contributorId":300733,"corporation":false,"usgs":false,"family":"Parsons","given":"Sophie","email":"","middleInitial":"E.","affiliations":[{"id":27208,"text":"UC San Diego","active":true,"usgs":false}],"preferred":false,"id":861323,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70254813,"text":"70254813 - 2023 - Density effects on native and non-native trout survival in streams","interactions":[],"lastModifiedDate":"2024-06-11T11:59:31.236011","indexId":"70254813","displayToPublicDate":"2023-01-11T06:55:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Density effects on native and non-native trout survival in streams","docAbstract":"<div class=\"abstract-group \"><div class=\"article-section__content en main\"><p>Environmental stressors associated with a changing climate and non-native fish, individually, represent significant threats to native fish conservation. These threats can exacerbate risks to native fishes when conditions interact at the trailing edge of a population's distribution. We collected capture–mark–recapture data for Rio Grande cutthroat trout (RGCT,<span>&nbsp;</span><i>Oncorhynchus clarkii virginalis</i>) at the trailing edge of all cutthroat trout distributions from eight northern New Mexico populations. We used a factorial sampling design from streams characterised as “cool” or “warm” and whether RGCT were sympatric with non-native brown trout (<i>Salmo trutta</i>). We tested competing hypotheses that warm temperatures, reduced flows, high densities and sympatry with brown trout would negatively impact RGCT apparent survival rates. We found the strongest evidence for a non-native trout interaction with total trout density affecting RGCT apparent survival rates. Our results are consistent with patterns observed in northern cutthroat trout populations where non-native salmonids negatively impacted apparent survival rates. We also found that a negative density effect was observed on allopatric RGCT and sympatric brown trout apparent survival, but a positive density effect was observed for sympatric RGCT. These results suggest higher density populations of RGCT may be more resilient to displacement by non-native trout than low-density populations.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12699","usgsCitation":"Huntsman, B., Flynn, L., Caldwell, C.A., Lynch, A., and Abadi, F., 2023, Density effects on native and non-native trout survival in streams: Ecology of Freshwater Fish, v. 32, no. 2, p. 464-476, https://doi.org/10.1111/eff.12699.","productDescription":"13 p.","startPage":"464","endPage":"476","ipdsId":"IP-131431","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1111/eff.12699","text":"Publisher Index Page"},{"id":429856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock M.","contributorId":337709,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock M.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Lauren","contributorId":337710,"corporation":false,"usgs":false,"family":"Flynn","given":"Lauren","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Colleen A. 0000-0002-4730-4867 ccaldwel@usgs.gov","orcid":"https://orcid.org/0000-0002-4730-4867","contributorId":3050,"corporation":false,"usgs":true,"family":"Caldwell","given":"Colleen","email":"ccaldwel@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":216203,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":902631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Abadi, Fitsum","contributorId":337711,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":902632,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241145,"text":"70241145 - 2023 - The detection and attribution of extreme reductions in vegetation growth across the global land surface","interactions":[],"lastModifiedDate":"2023-03-15T15:27:33.034592","indexId":"70241145","displayToPublicDate":"2023-01-11T06:46:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"The detection and attribution of extreme reductions in vegetation growth across the global land surface","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Negative extreme anomalies in vegetation growth (NEGs) usually indicate severely impaired ecosystem services. These NEGs can result from diverse natural and anthropogenic causes, especially climate extremes (CEs). However, the relationship between NEGs and many types of CEs remains largely unknown at regional and global scales. Here, with satellite-derived vegetation index data and supporting tree-ring chronologies, we identify periods of NEGs from 1981 to 2015 across the global land surface. We find 70% of these NEGs are attributable to five types of CEs and their combinations, with compound CEs generally more detrimental than individual ones. More importantly, we find that dominant CEs for NEGs vary by biome and region. Specifically, cold and/or wet extremes dominate NEGs in temperate mountains and high latitudes, whereas soil drought and related compound extremes are primarily responsible for NEGs in wet tropical, arid and semi-arid regions. Key characteristics (e.g., the frequency, intensity and duration of CEs, and the vulnerability of vegetation) that determine the dominance of CEs are also region- and biome-dependent. For example, in the wet tropics, dominant individual CEs have both higher intensity and longer duration than non-dominant ones. However, in the dry tropics and some temperate regions, a longer CE duration is more important than higher intensity. Our work provides the first global accounting of the attribution of NEGs to diverse climatic extremes. Our analysis has important implications for developing climate-specific disaster prevention and mitigation plans among different regions of the globe in a changing climate.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16595","usgsCitation":"Yang, H., Munson, S.M., Huntingford, C., Carvalhais, N., Knapp, A., Li, X., Penuelas, J., Zscheichler, J., and Chen, A., 2023, The detection and attribution of extreme reductions in vegetation growth across the global land surface: Global Change Biology, v. 29, no. 8, p. 2351-2362, https://doi.org/10.1111/gcb.16595.","productDescription":"12 p.","startPage":"2351","endPage":"2362","ipdsId":"IP-140874","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444867,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16595","text":"Publisher Index Page"},{"id":414006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Yang, Huiping","contributorId":219482,"corporation":false,"usgs":false,"family":"Yang","given":"Huiping","email":"","affiliations":[],"preferred":false,"id":866264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":866265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntingford, Chris","contributorId":303012,"corporation":false,"usgs":false,"family":"Huntingford","given":"Chris","email":"","affiliations":[{"id":65604,"text":"UK Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB, UK","active":true,"usgs":false}],"preferred":false,"id":866266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carvalhais, Nuno","contributorId":167796,"corporation":false,"usgs":false,"family":"Carvalhais","given":"Nuno","email":"","affiliations":[],"preferred":false,"id":866267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knapp, Alan K.","contributorId":139807,"corporation":false,"usgs":false,"family":"Knapp","given":"Alan K.","affiliations":[{"id":13277,"text":"Graduate Degree Program in Ecology and Department of Biology, Colorado State University, Ft. Collins, CO","active":true,"usgs":false}],"preferred":false,"id":866268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Xiangyi","contributorId":303013,"corporation":false,"usgs":false,"family":"Li","given":"Xiangyi","email":"","affiliations":[{"id":65605,"text":"Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China","active":true,"usgs":false}],"preferred":false,"id":866269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Penuelas, Josep","contributorId":204946,"corporation":false,"usgs":false,"family":"Penuelas","given":"Josep","email":"","affiliations":[{"id":37012,"text":"Global Ecology Unit CREAF-CSIC-UAB, CSIC, Bellaterra (Catalonia) E-08193, Spain","active":true,"usgs":false}],"preferred":false,"id":866270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zscheichler, Jakob","contributorId":303014,"corporation":false,"usgs":false,"family":"Zscheichler","given":"Jakob","email":"","affiliations":[{"id":65606,"text":"Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":866271,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chen, Anping","contributorId":303015,"corporation":false,"usgs":false,"family":"Chen","given":"Anping","email":"","affiliations":[{"id":37774,"text":"Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":866272,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70241048,"text":"70241048 - 2023 - National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images","interactions":[],"lastModifiedDate":"2023-11-08T16:49:21.339686","indexId":"70241048","displayToPublicDate":"2023-01-11T06:41:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>National Land Cover Database (NLCD) 2019 is a new epoch of national land cover products for the conterminous United States. Image quality is fundamental to the quality of any land cover product. Image preprocessing has often taken a considerable proportion of overall time and effort for this kind of national project. An approach to prepare image inputs for NLCD 2019 production was developed to ensure efficiency and quality of operational production. Here, we introduce a new and comprehensive strategy to produce clear Landsat composite images for NLCD 2019 production. First, we developed a new median-value compositing method. Second, we designed parameter settings for selecting images and pixels to generate 4 composite images (leaf-on, leaf-off, primary reference, and complementary reference) for a target year based on the US Landsat Analysis Ready Data surface reflectance dataset. Third, we developed a method, referred to as Detection and Filling with Simulated Image, to detect and replace clouds and cloud shadow pixels to produce the final clean leaf-on and leaf-off image composites. This image compositing and processing strategy was implemented for the entire conterminous United States to produce images for NLCD 2019. Our image results and NLCD 2019 change detection and land cover products, which were released in July 2021, showed this new strategy to be effective and efficient.</div></div></div>","language":"English","publisher":"AAAS","doi":"10.34133/remotesensing.0022","usgsCitation":"Jin, S., Dewitz, J., Danielson, P., Granneman, B., Costello, C., and Zhu, Z., 2023, National Land Cover Database 2019: A new strategy for creating clean leaf-on and leaf-off Landsat composite images: ISPRS Journal of Photogrammetry and Remote Sensing, v. 3, 0022, 13 p., https://doi.org/10.34133/remotesensing.0022.","productDescription":"0022, 13 p.","ipdsId":"IP-130136","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":444871,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.34133/remotesensing.0022","text":"Publisher Index Page"},{"id":413845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2023-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":865853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewitz, Jon 0000-0002-0458-212X","orcid":"https://orcid.org/0000-0002-0458-212X","contributorId":215192,"corporation":false,"usgs":true,"family":"Dewitz","given":"Jon","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":865854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danielson, Patrick 0000-0002-2990-2783","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":302925,"corporation":false,"usgs":false,"family":"Danielson","given":"Patrick","affiliations":[{"id":65584,"text":"KBR, contractor to the USGS EROS","active":true,"usgs":false}],"preferred":false,"id":865855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Granneman, Brian 0000-0002-1910-0955","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":302926,"corporation":false,"usgs":false,"family":"Granneman","given":"Brian","affiliations":[{"id":65584,"text":"KBR, contractor to the USGS EROS","active":true,"usgs":false}],"preferred":false,"id":865856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Costello, Catherine 0000-0001-7158-2675","orcid":"https://orcid.org/0000-0001-7158-2675","contributorId":223238,"corporation":false,"usgs":true,"family":"Costello","given":"Catherine","email":"","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":865857,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhu, Zhe 0000-0001-8283-6407","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":190828,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhe","affiliations":[],"preferred":false,"id":865858,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239951,"text":"70239951 - 2023 - Drivers and facilitators of the illegal killing of elephants across 64 African sites","interactions":[],"lastModifiedDate":"2023-01-26T12:46:13.942324","indexId":"70239951","displayToPublicDate":"2023-01-11T06:40:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and facilitators of the illegal killing of elephants across 64 African sites","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Ivory poaching continues to threaten African elephants. We (1) used criminology theory and literature evidence to generate hypotheses about factors that may drive, facilitate or motivate poaching, (2) identified datasets representing these factors, and (3) tested those factors with strong hypotheses and sufficient data quality for empirical associations with poaching. We advance on previous analyses of correlates of elephant poaching by using additional poaching data and leveraging new datasets for previously untested explanatory variables. Using data on 10 286 illegally killed elephants detected at 64 sites in 30 African countries (2002–2020), we found strong evidence to support the hypotheses that the illegal killing of elephants is associated with poor national governance, low law enforcement capacity, low household wealth and health, and global elephant ivory prices. Forest elephant populations suffered higher rates of illegal killing than savannah elephants. We found only weak evidence that armed conflicts may increase the illegal killing of elephants, and no evidence for effects of site accessibility, vegetation density, elephant population density, precipitation or site area. Results suggest that addressing wider systemic challenges of human development, corruption and consumer demand would help reduce poaching, corroborating broader work highlighting these more ultimate drivers of the global illegal wildlife trade.</p></div></div>","language":"English","publisher":"The Royal Society of Publishing","doi":"10.1098/rspb.2022.2270","usgsCitation":"Kuiper, T., Altwegg, R., Beale, C., Carroll, T., Dublin, H., Hauenstein, S., Kshatriya, M., Schwarz, C., Thouless, C., Royle, A., and Milner-Gulland, E., 2023, Drivers and facilitators of the illegal killing of elephants across 64 African sites: Proceedings of the Royal Society B: Biological Sciences, v. 290, 20222270, 11 p., https://doi.org/10.1098/rspb.2022.2270.","productDescription":"20222270, 11 p.","ipdsId":"IP-140428","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2022.2270","text":"Publisher Index Page"},{"id":412352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -18.71132543209356,\n              16.524150185381018\n            ],\n            [\n              -18.71132543209356,\n              -27.708482935366042\n            ],\n            [\n              51.47900643913226,\n              -27.708482935366042\n            ],\n            [\n              51.47900643913226,\n              16.524150185381018\n            ],\n            [\n              -18.71132543209356,\n              16.524150185381018\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"290","noUsgsAuthors":false,"publicationDate":"2023-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Kuiper, Timothy","contributorId":301237,"corporation":false,"usgs":false,"family":"Kuiper","given":"Timothy","email":"","affiliations":[{"id":65336,"text":"Univ. Cape Town","active":true,"usgs":false}],"preferred":false,"id":862486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Altwegg, Res","contributorId":171528,"corporation":false,"usgs":false,"family":"Altwegg","given":"Res","email":"","affiliations":[],"preferred":false,"id":862548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beale, Colin","contributorId":301238,"corporation":false,"usgs":false,"family":"Beale","given":"Colin","email":"","affiliations":[{"id":65337,"text":"Univ. of York","active":true,"usgs":false}],"preferred":false,"id":862487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, Thea","contributorId":301261,"corporation":false,"usgs":false,"family":"Carroll","given":"Thea","email":"","affiliations":[],"preferred":false,"id":862549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dublin, Holy","contributorId":301239,"corporation":false,"usgs":false,"family":"Dublin","given":"Holy","affiliations":[{"id":65338,"text":"International Inst. for Environment and Development","active":true,"usgs":false}],"preferred":false,"id":862488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hauenstein, Severin","contributorId":301240,"corporation":false,"usgs":false,"family":"Hauenstein","given":"Severin","email":"","affiliations":[{"id":33350,"text":"University of Freiburg","active":true,"usgs":false}],"preferred":false,"id":862489,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kshatriya, Mrigesh","contributorId":301241,"corporation":false,"usgs":false,"family":"Kshatriya","given":"Mrigesh","email":"","affiliations":[{"id":65340,"text":"United Nations MIKE program","active":true,"usgs":false}],"preferred":false,"id":862490,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schwarz, Carl","contributorId":301242,"corporation":false,"usgs":false,"family":"Schwarz","given":"Carl","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":862491,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thouless, Chris","contributorId":301243,"corporation":false,"usgs":false,"family":"Thouless","given":"Chris","email":"","affiliations":[{"id":65341,"text":"Save the Elephants","active":true,"usgs":false}],"preferred":false,"id":862492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862493,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Milner-Gulland, E.J.","contributorId":301244,"corporation":false,"usgs":false,"family":"Milner-Gulland","given":"E.J.","email":"","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":862494,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70239830,"text":"70239830 - 2023 - Comparison of ventifact orientations and recent wind direction indicators on the floor of Jezero crater, Mars","interactions":[],"lastModifiedDate":"2023-03-31T15:08:31.574902","indexId":"70239830","displayToPublicDate":"2023-01-11T06:36:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9967,"text":"JGR Planets","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of ventifact orientations and recent wind direction indicators on the floor of Jezero crater, Mars","docAbstract":"<div class=\"article-section__content en main\"><p>Wind-abraded rocks and aeolian bedforms have been observed at the Mars 2020<span>&nbsp;</span><i>Perseverance</i><span>&nbsp;</span>landing site, providing evidence for recent and older wind directions. This study reports orientations of aeolian features measured in<span>&nbsp;</span><i>Perseverance</i><span>&nbsp;</span>images to infer formative wind directions. It compares these measurements with orbital observations, climate model predictions, and wind data acquired by the Mars Environmental Dynamics Analyzer. Three-dimensional orientations of flute textures on rocks, regolith wind tails extending from behind obstacles, and other aeolian features were measured using Digital Terrain Models (DTMs) derived from Mastcam-Z and navigation camera (Navcam) stereo images. Orientations of rock flutes measured in images acquired through Sol (martian day) 400 yielded a mean azimuth of 94° ± 7° (wind from the west). However, similar measurements of regolith wind tails indicate that recent sand-driving winds have been blowing from the east-southeast, nearly the opposite direction (mean azimuth = 285° ± 15°). Atmospheric modeling generally predicts net annual sand transport from the east-southeast at present, consistent with<span>&nbsp;</span><i>Perseverance</i><span>&nbsp;</span>regolith wind tail and orbital observations. The orientation of ventifact flutes thus suggests that they were formed under a different climate regime. Differences in orientations of recent and paleo-wind indicators have been noted at other Mars landing sites and may result from major orbital/axial changes that can cause significant changes in atmospheric circulation. Orientation differences between modern and older wind direction indicators at Jezero are useful clues to the climate history of the region.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JE007599","usgsCitation":"Herkenhoff, K., Sullivan, R., Newman, C.E., Paar, G., Baker, M., Viudez-Moreiras, D., Ashley, J.W., Bechtold, A., and Nunez, J.I., 2023, Comparison of ventifact orientations and recent wind direction indicators on the floor of Jezero crater, Mars: JGR Planets, v. 128, no. 3, e2022JE007599, 16 p., https://doi.org/10.1029/2022JE007599.","productDescription":"e2022JE007599, 16 p.","ipdsId":"IP-144757","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":444876,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022je007599","text":"Publisher Index Page"},{"id":435514,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAGUG1","text":"USGS data release","linkHelpText":"Comparison of Ventifact Orientations and Recent Wind Direction Indicators on the Floor of Jezero Crater, Mars"},{"id":412208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Jezero Crater, Mars","volume":"128","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":862072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Rob","contributorId":218474,"corporation":false,"usgs":false,"family":"Sullivan","given":"Rob","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":862073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Newman, Claire E","contributorId":301113,"corporation":false,"usgs":false,"family":"Newman","given":"Claire","email":"","middleInitial":"E","affiliations":[{"id":37347,"text":"Aeolis Research","active":true,"usgs":false}],"preferred":false,"id":862074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paar, Gerhard","contributorId":300669,"corporation":false,"usgs":false,"family":"Paar","given":"Gerhard","email":"","affiliations":[{"id":65226,"text":"Institute for Information and Communication Technology","active":true,"usgs":false}],"preferred":false,"id":862075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baker, Mariah","contributorId":301114,"corporation":false,"usgs":false,"family":"Baker","given":"Mariah","email":"","affiliations":[{"id":65314,"text":"Smithsonian National Air and Space Museum","active":true,"usgs":false}],"preferred":false,"id":862076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viudez-Moreiras, Daniel","contributorId":301115,"corporation":false,"usgs":false,"family":"Viudez-Moreiras","given":"Daniel","email":"","affiliations":[{"id":47594,"text":"Centro de Astrobiologia","active":true,"usgs":false}],"preferred":false,"id":862077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ashley, James W.","contributorId":102523,"corporation":false,"usgs":false,"family":"Ashley","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":862078,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bechtold, Andreas","contributorId":301116,"corporation":false,"usgs":false,"family":"Bechtold","given":"Andreas","email":"","affiliations":[{"id":12677,"text":"University of Vienna","active":true,"usgs":false}],"preferred":false,"id":862079,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nunez, Jorge I","contributorId":301117,"corporation":false,"usgs":false,"family":"Nunez","given":"Jorge","email":"","middleInitial":"I","affiliations":[{"id":48418,"text":"JHU Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":862080,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70241135,"text":"70241135 - 2023 - Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions","interactions":[],"lastModifiedDate":"2023-03-15T15:26:40.68993","indexId":"70241135","displayToPublicDate":"2023-01-11T06:19:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Wetlands are the largest natural source of methane (CH<sub>4</sub>) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH<sub>4</sub>, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH<sub>4</sub><span>&nbsp;</span>production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH<sub>4</sub><span>&nbsp;</span>emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH<sub>4</sub><span>&nbsp;</span>production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH<sub>4</sub><span>&nbsp;</span>emissions. Based on a sensitivity analysis, CH<sub>4</sub><span>&nbsp;</span>emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH<sub>4</sub><span>&nbsp;</span>transport. Contributions from ebullition and diffusion were relatively high during low LAI (&lt;20%) periods. The lag time between CH<sub>4</sub><span>&nbsp;</span>production and CH<sub>4</sub><span>&nbsp;</span>emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH<sub>4</sub><span>&nbsp;</span>production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH<sub>4</sub><span>&nbsp;</span>emissions across biomes. These processes and associated parameters for CH<sub>4</sub><span>&nbsp;</span>emissions among and within the wetlands provide useful insights for interpreting observed net CH<sub>4</sub><span>&nbsp;</span>fluxes, estimating sensitivities to biophysical variables, and modeling global CH<sub>4</sub><span>&nbsp;</span>fluxes.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16594","usgsCitation":"Ueyama, M., Knox, S., Delwiche, K.B., Bansal, S., Riley, W.J., Baldocchi, D., Hirano, T., McNicol, G., Schafer, K., Windham-Myers, L., Poulter, B., Jackson, R.B., Chang, K., Chen, J., Chu, H., Desai, A.R., Gogo, S., Iwata, H., Kang, M., Mammarella, I., Peichl, M., Sonnentag, O., Tuittila, E., Ryu, Y., Euskirchen, E.S., Goeckede, M., Jacotot, A., Nilsson, M.B., and Sachs, T., 2023, Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions: Global Change Biology, v. 29, no. 8, p. 2313-2334, https://doi.org/10.1111/gcb.16594.","productDescription":"22 p.","startPage":"2313","endPage":"2334","ipdsId":"IP-143872","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":444880,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.16594","text":"Publisher Index Page"},{"id":414000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-01-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Ueyama, Masahito 0000-0002-4000-4888","orcid":"https://orcid.org/0000-0002-4000-4888","contributorId":217432,"corporation":false,"usgs":false,"family":"Ueyama","given":"Masahito","email":"","affiliations":[{"id":39629,"text":"Osaka Prefecture University","active":true,"usgs":false}],"preferred":false,"id":866198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knox, Sarah 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":167493,"corporation":false,"usgs":false,"family":"Knox","given":"Sarah","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":866199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delwiche, Kyle B.","contributorId":139866,"corporation":false,"usgs":false,"family":"Delwiche","given":"Kyle","email":"","middleInitial":"B.","affiliations":[{"id":13299,"text":"Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":866200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bansal, Sheel 0000-0003-1233-1707 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