{"pageNumber":"223","pageRowStart":"5550","pageSize":"25","recordCount":184617,"records":[{"id":70250639,"text":"70250639 - 2023 - Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","interactions":[],"lastModifiedDate":"2024-10-15T17:20:38.127462","indexId":"70250639","displayToPublicDate":"2023-12-01T07:22:20","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":18745,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":19}},"title":"Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","docAbstract":"Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. The Nevada Machine Learning Project (NVML) tested the use of a digital elevation map (DEM) of topography as an input feature to predict geothermal system favorability. A recent study re-examines the NVML data, identifying the DEM as the most important feature, showing a broad uniform pattern of high-favorability in the lower-elevation west and low-favorability in the higher elevation east of their study area in north-central Nevada. This regional elevation trend conflicts with the geologic notion that local relative topography should be used to identify geologic structures associated with favorable structural settings for hydrothermal upflow. Specifically, local relative topography gives information about position in the mountains, in the valleys, or at the transitions between, aiding in identification of faults and fault intersections. As part of U.S. Geological Survey efforts to engineer features that are useful for predicting geothermal resources, we construct a detrended elevation map that emphasizes local relative topography and highlights features that geologists use for identifying geothermal systems (i.e., providing machine learning algorithms with features that may improve predictive skill by emphasizing the information used by geologists). Herein, we describe the removal of the regional trend in elevation to emphasize the basin-and-range scale structural features, creating detrended elevation maps.\nRegional elevation trends were estimated using a local linear regression and subtracted from the actual elevation using a 30-m DEM. In an effort to optimize the detrended surface, alternate versions were produced with different rates of smoothness resulting in three detrended elevation maps. The resulting elevation trend surfaces (a proxy for crustal thickness) are compared with conductive heat flow maps, and a general pattern was observed of a negative correlation between heat flow and regional elevation in many areas, indicating that thinner crust may be causing elevated heat flow in some areas and thicker crust may cause the observed heat flow lows. Because these detrended elevation maps emphasize geologic structure and relative displacement, these products may also be useful for other geologic research including mineral exploration, hydrologic research, and defining geologic provinces.","language":"English","publisher":"Geothermal Rising","usgsCitation":"DeAngelo, J., Burns, E.R., Mordensky, S.P., and Lindsey, C.R., 2023, Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability, v. 47, p. 1694-1702.","productDescription":"9 p.","startPage":"1694","endPage":"1702","ipdsId":"IP-155138","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423843,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034786","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251485,"text":"70251485 - 2023 - Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations","interactions":[],"lastModifiedDate":"2024-02-13T13:12:40.92934","indexId":"70251485","displayToPublicDate":"2023-12-01T07:05:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations","docAbstract":"<div class=\"html-p\">Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (&lt;5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R<sup>2</sup><span>&nbsp;</span>= 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.</div>","language":"English","publisher":"MDPI","doi":"10.3390/w15234167","usgsCitation":"Grossman, E.E., Tehranirad, B., Nederhoff, K., Crosby, S., Stevens, A.W., VanArendonk, N.R., Nowacki, D.J., Erikson, L.H., and Barnard, P.L., 2023, Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations: Water, v. 15, no. 23, 4167, 24 p., https://doi.org/10.3390/w15234167.","productDescription":"4167, 24 p.","ipdsId":"IP-146065","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441512,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w15234167","text":"Publisher Index Page"},{"id":425601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -130.71708563654397,\n              52.25092388193306\n            ],\n            [\n              -130.71708563654397,\n              44.0989255001023\n            ],\n            [\n              -118.67607001154398,\n              44.0989255001023\n            ],\n            [\n              -118.67607001154398,\n              52.25092388193306\n            ],\n            [\n              -130.71708563654397,\n              52.25092388193306\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"23","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@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":894698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tehranirad, Babak 0000-0002-1634-9165","orcid":"https://orcid.org/0000-0002-1634-9165","contributorId":299107,"corporation":false,"usgs":false,"family":"Tehranirad","given":"Babak","affiliations":[{"id":64774,"text":"contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":894699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":894700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crosby, Sean","contributorId":334092,"corporation":false,"usgs":false,"family":"Crosby","given":"Sean","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":894701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":894702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VanArendonk, Nathan R.","contributorId":334097,"corporation":false,"usgs":false,"family":"VanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":894703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":894704,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":894705,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":894706,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250655,"text":"70250655 - 2023 - A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data","interactions":[],"lastModifiedDate":"2023-12-22T12:57:30.745882","indexId":"70250655","displayToPublicDate":"2023-12-01T06:52:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10389,"text":"San Francisco Estuary and Watershed Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data","docAbstract":"<div id=\"main\"><div data-reactroot=\"\"><div class=\"body\"><div><div class=\"c-columns--sticky-sidebar\"><div class=\"c-tabs\"><div class=\"c-tabs__content\"><div class=\"c-tabcontent\"><div class=\"c-clientmarkup\"><p>The diffuse attenuation coefficient of photosynthetically active radiation (KdPAR) is commonly used to predict light attenuation in aquatic productivity models, but obtaining measurements of PAR to compute KdPAR is difficult. In situ calculations of KdPAR require multiple measurements of PAR through the water column, and these measurements are infeasible for real-time recording. Instead, predictive models using surface-water measurements may be used. Traditional KdPAR models are based on open-ocean habitats and rely on chlorophyll—as a proxy measurement for phytoplankton abundance—as the main predictive parameter. However, elevated suspended sediments and dissolved organic materials may also affect KdPAR values of inland water bodies and estuaries. In this study, we leverage KdPAR calculations derived from in situ light measurements collected along with surface-water-quality parameters across the Sacramento-San Joaquin River Delta in California, USA (the Delta). Sampling occurred between January of 2013 and May of 2014. We also explored regional and seasonal effects, but these did not clearly affect the model. Ultimately, the best-performing model included surface-level turbidity only (R2 = 0.91). The simplicity of the model facilitates use of KdPAR estimates for a variety of purposes throughout the Delta, including euphotic depth calculations, and as inputs to primary-productivity and habitat-suitability models. We demonstrate the model’s usability with two open-sources data sets (one spatially dense, and one temporally dense), and estimate KdPAR, euphotic depth, and primary productivity within the Delta. We provide calculations for each estimation, allowing users to easily adopt these models and apply them to their own data or with open-sourced data, which are abundant.</p></div></div></div></div></div></div></div></div></div>","language":"English","publisher":"University of California","doi":"10.15447/sfews.2023v21iss4art5","usgsCitation":"Richardson, E.T., Bouma-Gregson, K., O’Donnell, K., and Bergamaschi, B.A., 2023, A simple approach to modeling light attenuation in the Sacramento-San Joaquin Delta using commonly available data: San Francisco Estuary and Watershed Sciences, v. 21, no. 4, 5, 15 p., https://doi.org/10.15447/sfews.2023v21iss4art5.","productDescription":"5, 15 p.","ipdsId":"IP-149629","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":441515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2023v21iss4art5","text":"Publisher Index Page"},{"id":423859,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.26086948103463,\n              38.478699734733226\n            ],\n            [\n              -122.26086948103463,\n              37.77218409560264\n            ],\n            [\n              -121.28033969587833,\n              37.77218409560264\n            ],\n            [\n              -121.28033969587833,\n              38.478699734733226\n            ],\n            [\n              -122.26086948103463,\n              38.478699734733226\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Katy 0000-0003-2323-8970 kodonnell@usgs.gov","orcid":"https://orcid.org/0000-0003-2323-8970","contributorId":5640,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katy","email":"kodonnell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":890902,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250601,"text":"70250601 - 2023 - Divergent responses of western Alaska salmon to a changing climate","interactions":[],"lastModifiedDate":"2024-02-07T17:14:56.026768","indexId":"70250601","displayToPublicDate":"2023-12-01T06:49:07","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Divergent responses of western Alaska salmon to a changing climate","docAbstract":"<h3 class=\"wp-block-heading\">Headlines</h3><ul><li>Western Alaska salmon abundance reached historic extremes during 2021-22, with record lows for Chinook and chum salmon (81% and 92% below the 30-year mean, respectively) and record highs for sockeye salmon (98% above the 30-year mean).</li><li>Salmon are maturing at smaller sizes. Since the 1970s, for example, Yukon River Chinook salmon have decreased an estimated 6% in mean adult body length and 15% in fecundity, likely exacerbating population declines.</li><li>Salmon population declines have led to fishery closures, worsened user conflicts, and had profound cultural and food security impacts in Indigenous communities that have been tied to salmon for millennia.</li><li>Changes in abundance and size are associated with climatic changes in freshwater and marine ecosystems and competition in the ocean. Changes in predators, food supply, and disease are also likely important drivers.</li></ul>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2023 Arctic Report Card","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"NOAA","doi":"10.25923/f2hv-5581","usgsCitation":"Schoen, E., Howard, K.G., Murphy, J., Schindler, D., Westley, P., and von Biela, V.R., 2023, Divergent responses of western Alaska salmon to a changing climate, HTML Document, https://doi.org/10.25923/f2hv-5581.","productDescription":"HTML Document","ipdsId":"IP-158550","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":423744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -139.6101604988394,\n              61.2015830860681\n            ],\n            [\n              -139.43437924883952,\n              66.17389289158615\n            ],\n            [\n              -140.1375042488394,\n              67.95408453891542\n            ],\n            [\n              -144.7078167488394,\n              68.92291840612816\n            ],\n            [\n              -153.8484417488394,\n              67.42020730537521\n            ],\n            [\n              -160.87969174883918,\n              65.52668632036398\n            ],\n            [\n              -162.9890667488394,\n              64.10587463586813\n            ],\n            [\n              -167.20781674883932,\n              62.364181084501865\n            ],\n            [\n              -166.50469174883943,\n              59.81851305865456\n            ],\n            [\n              -161.40703549883915,\n              58.556875579514866\n            ],\n            [\n              -159.1218792488393,\n              57.53360560212221\n            ],\n            [\n              -165.09844174883935,\n              54.59125546767737\n            ],\n            [\n              -162.28594174883924,\n              54.794443813412215\n            ],\n            [\n              -157.18828549883924,\n              57.344396153787955\n            ],\n            [\n              -154.7273479988392,\n              58.185754905844135\n            ],\n            [\n              -152.96953549883932,\n              60.85620691034802\n            ],\n            [\n              -150.5085979988393,\n              62.850205674657445\n            ],\n            [\n              -145.76250424883938,\n              63.32755335378286\n            ],\n            [\n              -139.6101604988394,\n              61.2015830860681\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoen, Erik","contributorId":280216,"corporation":false,"usgs":false,"family":"Schoen","given":"Erik","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":890521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Kathrine G.","contributorId":302903,"corporation":false,"usgs":false,"family":"Howard","given":"Kathrine","email":"","middleInitial":"G.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":890522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, James","contributorId":210957,"corporation":false,"usgs":false,"family":"Murphy","given":"James","affiliations":[],"preferred":false,"id":890523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schindler, Daniel","contributorId":331940,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":890524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Westley, Peter A. H.","contributorId":287084,"corporation":false,"usgs":false,"family":"Westley","given":"Peter A. H.","affiliations":[{"id":61459,"text":"afg","active":true,"usgs":false}],"preferred":false,"id":890525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":890526,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70250597,"text":"70250597 - 2023 - Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling","interactions":[],"lastModifiedDate":"2023-12-19T12:40:36.280538","indexId":"70250597","displayToPublicDate":"2023-12-01T06:38:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3824,"text":"Letters in Biomathematics","active":true,"publicationSubtype":{"id":10}},"title":"Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling","docAbstract":"Mathematical biology is a wide field of study with many venues that undergraduate students can access through research. However, the topics of study for these students can be overwhelming, and many topics of study yield either only trivial results or abstract outcomes that are nonintuitive and diffcult to understand. We have used natural resource modeling, and more specifically, a partnership between academic researchers and federal scientists, as a bridge between undergraduate research and mathematical biology. Our collaboration is an interdisciplinary team that combines biology, mathematics, and statistics professors with government research scientists. As a team, we have mentored students through opportunities such as a Research Experiences for Undergraduates and other projects. In this article, we provide an overview of how we develop questions for undergraduates and outline two case studies, both of which resulted in peer reviewed journal articles. Last, we describe how we also transfer the results from these undergraduate projects to resource managers so the results may be applied to real world problems.","language":"English","publisher":"Intercollegiate Biomathematics Alliance","usgsCitation":"Erickson, R.A., Baumann, D., Bennie, B., Bungula, W., Cupp, A.R., Diffendorfer, J., Eager, E., Haro, R.J., Jankowski, K.J., Larson, D.M., Sandland, G., Van Appledorn, M., and Peirce, J.P., 2023, Bridging the gap between mathematical biology and undergraduate education using applicable natural resource modeling: Letters in Biomathematics, v. 10, no. 1, p. 185-191.","productDescription":"7 p.","startPage":"185","endPage":"191","ipdsId":"IP-147034","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":423742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423737,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://lettersinbiomath.journals.publicknowledgeproject.org/index.php/lib/article/view/635/367"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baumann, Douglas","contributorId":328549,"corporation":false,"usgs":false,"family":"Baumann","given":"Douglas","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barbara","contributorId":328550,"corporation":false,"usgs":false,"family":"Bennie","given":"Barbara","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bungula, Wako","contributorId":315367,"corporation":false,"usgs":false,"family":"Bungula","given":"Wako","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":890505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":890507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eager, Eric A.","contributorId":140447,"corporation":false,"usgs":false,"family":"Eager","given":"Eric A.","affiliations":[{"id":13504,"text":"Department of Mathematics, University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890508,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":890509,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890510,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890511,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sandland, Greg J.","contributorId":190137,"corporation":false,"usgs":false,"family":"Sandland","given":"Greg J.","affiliations":[],"preferred":false,"id":890512,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":890513,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":890514,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70256529,"text":"70256529 - 2023 - Aging, climate, and invasions threaten reservoirs in the Mississippi basin","interactions":[],"lastModifiedDate":"2024-08-16T16:37:24.141886","indexId":"70256529","displayToPublicDate":"2023-12-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Aging, climate, and invasions threaten reservoirs in the Mississippi basin","docAbstract":"<p><span>Reservoirs in the Mississippi River basin are facing three momentous threats. The first two, aging and climate change, are relatively slow moving and their signal can be hard to discern given their stretched temporal scales. The third, species invasions, is faster paced and discernable within shorter temporal scales and restricted spatial scales. Aging and climate directly affect reservoir environments and indirectly affect their biotic communities. Climate change is expected to interact with aging to speed up and, in some instances, slow down aging. Conversely, invasions primarily imperil biotic communities but can also impact environmental elements. This triple jeopardy is expected to transform reservoir environs and their biotic assemblages in various, often uncertain, ways. I take a broad view of these threats within the Mississippi River basin. A basin-scale perspective, in contrast to a single reservoir or regional scale, may enhance awareness of reservoirs at a larger level and produce understanding less evident at local levels, hence possibly offering a wider range of choices for confronting threats. My aim is to (1) provide a synopsis of the assemblage of reservoirs and their attributes over the Mississippi River basin, (2) describe the issues related to aging, climate change, and invasions, and (3) consider a conservation framework for confronting these pressures. Given the overlapping temporal, spatial, and ecological effects of these threats, it is essential to address their effects simultaneously.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10990","usgsCitation":"Miranda, L.E., 2023, Aging, climate, and invasions threaten reservoirs in the Mississippi basin: Fisheries Magazine, v. 48, no. 12, p. 499-514, https://doi.org/10.1002/fsh.10990.","productDescription":"16 p.","startPage":"499","endPage":"514","ipdsId":"IP-151790","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fsh.10990","text":"Publisher Index Page"},{"id":432866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.70500995271088,\n              29.01665894418747\n            ],\n            [\n              -87.84690317711288,\n              33.54915630164602\n            ],\n            [\n              -81.00873115774787,\n              37.45591553762907\n            ],\n            [\n              -78.93790401814765,\n              41.96679217920834\n            ],\n            [\n              -83.62542898487561,\n              41.81918715620617\n            ],\n            [\n              -87.73555865475336,\n              41.70064246159154\n            ],\n            [\n              -88.67261557203858,\n              44.96630422012075\n            ],\n            [\n              -93.08599492063011,\n              47.38065175487887\n            ],\n            [\n              -98.48423664388794,\n              48.43354009429689\n            ],\n            [\n              -112.80019584593275,\n              48.34084011217669\n            ],\n            [\n              -109.13885539240077,\n              44.853455766288505\n            ],\n            [\n              -105.17484654049274,\n              41.33941938263584\n            ],\n            [\n              -103.17753122235543,\n              38.76054766960715\n            ],\n            [\n              -101.04477212147036,\n              36.16726262455268\n            ],\n            [\n              -98.00084294825474,\n              32.268870505741845\n            ],\n            [\n              -92.62187823928058,\n              29.79492566370429\n            ],\n            [\n              -88.70500995271088,\n              29.01665894418747\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907834,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70257366,"text":"70257366 - 2023 - A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes","interactions":[],"lastModifiedDate":"2024-08-23T16:23:27.893177","indexId":"70257366","displayToPublicDate":"2023-12-01T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes","docAbstract":"<p><span>A variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad-scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophyll&nbsp;</span><i>a</i><span>&nbsp;(Chl&nbsp;</span><i>a</i><span>), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chl&nbsp;</span><i>a</i><span>) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/lno.12457","usgsCitation":"Lapierre, J., Webster, K.E., Hanks, E., Wagner, T., Soranno, P.A., McCullough, I., Reinl, K.L., Domka, M., and Lotting, N.R., 2023, A continuous classification of the 476,697 lakes of the conterminous US based on geographic archetypes: Limnology and Oceanography, v. 69, no. 12, p. 2759-2773, https://doi.org/10.1002/lno.12457.","productDescription":"15 p.","startPage":"2759","endPage":"2773","ipdsId":"IP-145952","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.12457","text":"Publisher Index Page"},{"id":433110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n        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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Status of 3DEP in Minnesota</li><li>Water Supply and Quality</li><li>Forest Resources Management</li><li>Infrastructure and Construction Management</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-30","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Bergeson, Mitch 0000-0002-4675-8082 mbergeson@usgs.gov","orcid":"https://orcid.org/0000-0002-4675-8082","contributorId":331686,"corporation":false,"usgs":true,"family":"Bergeson","given":"Mitch","email":"mbergeson@usgs.gov","affiliations":[],"preferred":true,"id":888470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nail, David 0000-0003-0793-2305 dnail@usgs.gov","orcid":"https://orcid.org/0000-0003-0793-2305","contributorId":331534,"corporation":false,"usgs":true,"family":"Nail","given":"David","email":"dnail@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":888471,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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Because of its location along the Continental Divide, the rivers in Montana drain into either the Pacific Ocean or the Gulf of Mexico. Montana is often called the Treasure State due to its mineral wealth, which includes oil, gas, and coal, but the State’s primary economic activity is agriculture. Other economic activities include natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, and geologic resource assessment and hazard mitigation. 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, Mail Stop 511<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Status of 3DEP in Montana</li><li>Agriculture and Precision Farming</li><li>Flood Risk Management</li><li>Geologic Resource Assessment and Hazard Mitigation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-30","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Tom 0000-0002-5682-8988","orcid":"https://orcid.org/0000-0002-5682-8988","contributorId":304658,"corporation":false,"usgs":true,"family":"Carlson","given":"Tom","email":"","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":888663,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250421,"text":"70250421 - 2023 - Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands","interactions":[],"lastModifiedDate":"2023-12-08T13:09:02.418401","indexId":"70250421","displayToPublicDate":"2023-11-30T07:06:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands","docAbstract":"<p><span>Studying how species interact with their environment and other co-occurring species are 2 main aspects of ecology. For marine turtles, ocean currents drive migratory routes and may determine the location of surrounding foraging grounds. As a result, circumglobal species like the hawksbill turtle&nbsp;</span><i>Eretmochelys imbricata</i><span>&nbsp;and green turtle&nbsp;</span><i>Chelonia mydas</i><span>&nbsp;adapt to diverse foraging habitats and employ varied feeding strategies. Dietary specializations may reduce competition for available food and space resources between co-occurring hawksbill and green turtles in US Virgin Island shallow reef habitats. This study analyzed isotopic data from immature hawksbill (n = 49; range: 18.7-49.8 cm straight carapace length [SCL]) and green turtles (n = 225; range: 24.1-69.4 cm SCL) to examine foraging niche. We used nitrogen stable isotope (δ</span><sup>15</sup><span>N) values as an indicator of trophic positioning and carbon stable isotope (δ</span><sup>13</sup><span>C) values as a habitat variable. Turtles were hand-captured across an 8 yr period (2012-2019), which facilitated the distinction of isotopic patterns in both the environment and among individual turtles. Understanding variations in habitat, community dynamics, and dietary consumption allowed us to utilize a 5 point framework to translate isotopic space to foraging niche. We found that the site’s relatively stable environmental conditions allow for isotopic overlap between hawksbill and green turtles despite the specialized feeding strategies each species employs. We also underscore the need to evaluate species-specific tissue turnover estimates as evidenced by the influence of tropical storms on recaptured turtle isotopic signatures. These findings inform our understanding of resource use for these imperiled species at our study site and are useful for future global isotopic comparisons.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01276","usgsCitation":"Moorehouse, M.A., Baldwin, J.D., and Hart, K., 2023, Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands: Endangered Species Research, v. 52, p. 265-283, https://doi.org/10.3354/esr01276.","productDescription":"19 p.","startPage":"265","endPage":"283","ipdsId":"IP-142711","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441523,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01276","text":"Publisher Index Page"},{"id":435114,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ED29DJ","text":"USGS data release","linkHelpText":"Stable isotope signatures from green turtles and hawksbills at Buck Island Reef National Monument, U.S. Virgin Islands from 2012-2019"},{"id":423325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"U.S. Virgin Islands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -65.06621906831514,\n              18.4297449274477\n            ],\n            [\n              -65.06621906831514,\n              17.60831911760907\n            ],\n            [\n              -64.46197361578831,\n              17.60831911760907\n            ],\n            [\n              -64.46197361578831,\n              18.4297449274477\n            ],\n            [\n              -65.06621906831514,\n              18.4297449274477\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moorehouse, Melissa A. 0000-0001-5891-4110","orcid":"https://orcid.org/0000-0001-5891-4110","contributorId":332281,"corporation":false,"usgs":false,"family":"Moorehouse","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":79441,"text":"United States Military Academy","active":true,"usgs":false}],"preferred":false,"id":889869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, John D.","contributorId":210505,"corporation":false,"usgs":false,"family":"Baldwin","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":889870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250366,"text":"70250366 - 2023 - Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","interactions":[],"lastModifiedDate":"2023-12-05T13:13:51.187375","indexId":"70250366","displayToPublicDate":"2023-11-30T07:05:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","docAbstract":"<p class=\"abstract_block\">Haleakalā National Park and montane areas on east Maui, Hawaiian Archipelago, support critical nesting habitat for endangered ‘ua‘u Hawaiian petrel<span>&nbsp;</span><i>Pterodroma sandwichensis</i>. Habitat loss, non-native predators, and damage by feral ungulates are limiting factors for ground-nesting petrels at Haleakalā and throughout Hawai‘i. Because nesting habitats differ among the Hawaiian Islands, habitat distribution modeling for Hawaiian petrel has been island specific. Based on 2453 known nest site locations, we provide the first landscape-scale predictive model describing relative abundance and habitat available for nesting petrels throughout upper Haleakalā (1830 to 3055 m). We evaluated (principal components analyses and Pearson’s correlation) 13 spatial landscape and climate predictor variables associated with nest sites and the background landscape followed by random forest modeling to predict nest site density. Six variables (elevation, slope, topographic position index at 2 scales, heat load index, presence-absence ash/cinder, and presence-absence vegetation) indicated nest sites occurred non-randomly throughout the central part of the summit and crater; greatest concentrations were predicted along the crater rim and a ridgeline extending southwest from the summit. Moderately high predicted density occurred in the northeastern and northern crater. Lower elevations to the north, west, and south flanks of Haleakalā had relatively fewer predicted nest sites. Although we focused on higher elevations on Haleakalā, there is no reason to suspect that conservation efforts would not be successful at lower elevations, provided nesting petrels were protected from invasive predators, grazing ungulates, and significant land alteration.</p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01280","usgsCitation":"Adams, J., Felis, J., Klinger, R.C., Kelsey, E.C., Tamayose, J., Kaholoa’a, R., Bailey, C.N., Penniman, J.F., Learned, J., Ganter, C., Medeiros, J., and Chen, H., 2023, Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui: Endangered Species Research, v. 52, p. 231-246, https://doi.org/10.3354/esr01280.","productDescription":"16 p.","startPage":"231","endPage":"246","ipdsId":"IP-148421","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01280","text":"Publisher Index Page"},{"id":423239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Haleakalā, Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":332148,"corporation":false,"usgs":false,"family":"Felis","given":"Jonathan J.","affiliations":[{"id":17847,"text":"USGS-WERC","active":true,"usgs":false}],"preferred":false,"id":889571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tamayose, Joy","contributorId":332150,"corporation":false,"usgs":false,"family":"Tamayose","given":"Joy","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaholoa’a, Raina","contributorId":332151,"corporation":false,"usgs":false,"family":"Kaholoa’a","given":"Raina","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, Cathleen Natividad","contributorId":220473,"corporation":false,"usgs":false,"family":"Bailey","given":"Cathleen","email":"","middleInitial":"Natividad","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":889576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Penniman, Jay F.","contributorId":332154,"corporation":false,"usgs":false,"family":"Penniman","given":"Jay","email":"","middleInitial":"F.","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Learned, Jennifer","contributorId":332155,"corporation":false,"usgs":false,"family":"Learned","given":"Jennifer","email":"","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ganter, Ciara","contributorId":332156,"corporation":false,"usgs":false,"family":"Ganter","given":"Ciara","email":"","affiliations":[{"id":79397,"text":"Hawai'i State of Dep. of Land and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":889579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Medeiros, John","contributorId":167591,"corporation":false,"usgs":false,"family":"Medeiros","given":"John","email":"","affiliations":[{"id":24766,"text":"4. State of Hawaii, Division of Forestry and Wildlife-Maui, 54 South High Street # 101, Wailuku, HI 96793.","active":true,"usgs":false}],"preferred":false,"id":889580,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chen, Huisheng","contributorId":332157,"corporation":false,"usgs":false,"family":"Chen","given":"Huisheng","email":"","affiliations":[{"id":79398,"text":"NPS; University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":889581,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70251909,"text":"70251909 - 2023 - Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA","interactions":[],"lastModifiedDate":"2025-01-27T16:22:06.901739","indexId":"70251909","displayToPublicDate":"2023-11-30T06:57:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA","docAbstract":"<div id=\"141891235\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>The middle Eocene lower Coaledo Formation was interpreted as ten shoaling upward delta-margin cycles based on sediments and macrofauna. The strata, however, contains deep-water foraminifers. Explanations to resolve this anomaly included reworking, bathymetric range extension, or upward migration of water masses. Paleoecology analysis of foraminifers indicates that the few shelf species are poorly preserved whereas the well-preserved lower bathyal species dominate, and planktic organisms are present. Evidence for reworking, bathymetric range extension, or upward migration of water masses was not found in any of the cycles. The paleoecologic utility of hummocky cross-bedded sandstones is questioned as these features are controversial. In addition, there is no evidence of sea-level changes or tectonic activity to accommodate the bathymetric changes needed. Deposition of the lower Coaledo Formation on a submarine fan at lower bathyal depths eliminates the need to explain bathymetric anomalies or lack of tectonic movement.</p></div>","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.2113/gsjfr.53.4.311","usgsCitation":"McDougall-Reid, K., 2023, Micropaleontological evidence of a submarine fan in the lower Coaledo Formation, Southwestern Oregon, USA: Journal of Foraminiferal Research, v. 53, no. 4, p. 311-337, https://doi.org/10.2113/gsjfr.53.4.311.","productDescription":"27 p.","startPage":"311","endPage":"337","ipdsId":"IP-142682","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501082,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2113/gsjfr.53.4.311","text":"Publisher Index Page"},{"id":426363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126.02697115657307,\n              45.34305686940033\n            ],\n            [\n              -126.02697115657307,\n              41.77805423530663\n            ],\n            [\n              -121.58849459407304,\n              41.77805423530663\n            ],\n            [\n              -121.58849459407304,\n              45.34305686940033\n            ],\n            [\n              -126.02697115657307,\n              45.34305686940033\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"53","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"McDougall-Reid, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":216211,"corporation":false,"usgs":true,"family":"McDougall-Reid","given":"Kristin","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":896042,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250696,"text":"70250696 - 2023 - FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","interactions":[],"lastModifiedDate":"2023-12-27T12:54:08.529","indexId":"70250696","displayToPublicDate":"2023-11-30T06:50:51","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","docAbstract":"This report on baseline assessment of fish community assemblage and migratory patterns of fishes in the lower Boardman River (LBR; Traverse City, MI (USA)) is one of four assessment projects conceived circa 2017 after the Boardman (Ottaway) River was selected by the Great Lakes Fishery Commission (GLFC) and collaborating agencies as the future site of the Selective Bi-directional Fish Passage (FishPass) project. This report describes the results from\nfisheries community sampling from 2017-2021 and the concurrent bio-telemetry project aimed at understanding phenological changes in the fish community and movement and space-use of a variety of large-bodied fishes in the LBR against which selective fish passage treatments will be developed and evaluated.\nFish migration in riverine environments is a growing area of concern as mounting anthropogenic influences, particularly fragmentation from dams and barriers, constitute a major threat to global river species diversity. Specifically, In the Laurentian Great Lakes basin, more than 250,000 dams, weirs, culverts, and other significant obstructions prevent the movement of species both between the Great Lakes and rivers, and within rivers. Barriers\nimpede the movement of fishes between areas critical to the completion of their lifecycle, affecting both population and ecosystem viability. However, a conundrum arises in that the same barriers can also prevent the upstream invasion of non-native or undesirable species (most notably the sea lamprey Petromyzon marinus in the Great Lakes),prevent the transfer of contaminants and diseases, halt deleterious genes, provide recreational opportunities, or\ngenerate power. As a result, fish passage solutions with the capability of selectively passing desirable taxa while restricting the dispersal of undesirable taxa (selective connectivity) are sought to solve this connectivity conundrum. FishPass is a multi-agency initiative planned to replace the Union Street Dam on the Boardman River in Traverse City,MI (USA), aimed at developing and implementing automatic or semiautomatic selective bi-directional fish guidance,\nsorting, and passage techniques and technologies. Pivotal to both the successful development of selective connectivity and assessment of its effects is a more complete understanding of the Boardman River’s fishery. Specifically, understanding the species and size composition of the fish community, fish movement phenology and the associated abiotic conditions.\n\nFish community sampling confirmed the presence of 28 unique species in the LBR (Boardman River reach below Union Street Dam). Passive Integrated Transponder (PIT) tag telemetry increased the resolution of phenological shifts in the fish community that could not have been captured from periodic fish sampling. This data demonstrates large variation within species and overlap between species presence. However, discrete periods of presence were identified across most species when considering the central tendencies in the distribution of their presence. Rainbow trout Oncorhynchus mykiss were found to be omni-present in the river while brown trout Salmo trutta and smallmouth bass Micropterus dolomieu also persisted throughout a majority of the year; all of which will require continually sorting at FishPass. PIT tag telemetry also provided the important understanding that individuals (3-64%) of all species return to\nthe LBR across multiple years.\n\nRadio telemetry (RT) proved useful in refining the entry and exit timing and in evaluating the proportion of individuals that encountered the current Union Street Dam and Kid’s Creek (the only tributary confluence below the Union Street Dam) across six species (common white sucker Catostomus commersonii, rainbow trout, smallmouth bass, walleye Sander vitreus, brown trout, and common carp Cyprinus carpio). The RT results show that these species are present in FishPass Research Publication: baseline assessment\nof fish community assemblage and migratory pattern in the Boardman River, Traverse City, Michigan, USA November 2023 7 between April and August. Our analysis also demonstrated that not all fish that entered the river proceeded to the Union Street Dam, but those that did, did so prior to being detected encountering Kid’s Creek. Common white sucker and rainbow trout were the only species to be detected encountering Kid’s Creek.\n\nCollectively, the results of this study provide a baseline understanding of the seasonal fish diversity and relative abundance of fishes in the LBR, and a basic description of observed movement patterns of a subset of species in the context of seasonal phenology, entry and exit behavior within the LBR, and the propensity at which telemetered individuals encounter the Union Street dam and/or Kid’s Creek.","language":"English","publisher":"Great Lakes Fishery Commission","collaboration":"Great Lakes Fisheries Commission","usgsCitation":"Swanson, R.G., Zielinski, D.P., Castro-Santos, T., and Muir, A., 2023, FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA, 49 p.","productDescription":"49 p.","ipdsId":"IP-155321","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":423903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423897,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.glfc.org/pubs/pdfs/research/FishPassResearchPublication2023-CommunityAssemblage.pdf"}],"country":"United States","state":"Michigan","city":"Traverse City","otherGeospatial":"Boardman River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swanson, Reid G.","contributorId":332833,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid","email":"","middleInitial":"G.","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":891020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zielinski, Daniel P.","contributorId":211034,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":34820,"text":"Great Lakes Fisheries Commission, Ann Arbor, MI","active":true,"usgs":false}],"preferred":false,"id":891021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":891022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muir, Andrew M.","contributorId":103933,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew M.","affiliations":[],"preferred":false,"id":891023,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70250826,"text":"70250826 - 2023 - Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.","interactions":[],"lastModifiedDate":"2024-01-08T16:55:00.87656","indexId":"70250826","displayToPublicDate":"2023-11-29T10:49:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.","docAbstract":"<p><span>Eruptions from Mauna Loa’s Southwest Rift Zone (SWRZ) pose a significant threat to nearby communities due to high eruption rates and steep slopes resulting in little time for evacuation. Despite the large body of research done on Mauna Loa, knowledge of the timing and duration of magma residence and transfer through its internal plumbing system is still poorly constrained. This study presents a first quantitative look at thermochemical conditions and timescales of potentially deep storage and disaggregation of magmatic mush during the run-up to the voluminous 1950 AD SWRZ eruption. Details of heterogeneous compositions and textures of the macrocryst and glomerocryst cargo in 1950 AD lavas suggest magma mixing and crystal recycling along the entire plumbing system. Furthermore, the crystal cargo contains evidence for the direct interaction between primitive, deeply stored magma and pockets of more evolved magma stored at shallow to intermediate depths. An enigmatic attribute of 1950 near-vent lava is the near-ubiquitous presence of subhedral, unreacted Mg-rich orthopyroxene phenocrysts (Mg#&gt;80). Phase relations of Mauna Loa olivine-tholeiite indicate that orthopyroxene joins olivine as a primary phase at pressures higher than 0.6 GPa. Coexisting Mg-rich olivine and orthopyroxene and the occurrence of harzburgitic (olivine-orthopyroxene) glomerocrysts provide evidence for cognate crystallisation at near-Moho (~ 18 km) depths (Thornber and Trusdell&nbsp;</span>2008<span>). Petrogenetically diverse populations of glomerocrysts and macrocrysts alongside evidence of multilevel magma storage indicate a network of ephemeral and possibly interconnected magma pockets from near-Moho depths to the upper/mid-crust. Fe-Mg diffusion chronometry applied to 1950 AD olivine populations implies rapid mobilisation and transport of large volumes of magma (376×10</span><sup>6</sup><span>&nbsp;m</span><sup>3</sup><span>) from near-Moho storage to the surface within less than 8 months, with little residence time (~ 2 weeks) in the shallow (3–5 km) plumbing system.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-023-01680-x","usgsCitation":"Kahl, M., Morgan, D.J., Thornber, C., Walshaw, R., Lynn, K.J., and Trusdell, F., 2023, Dynamics of magma mixing and magma mobilization beneath Mauna Loa – Insights from the 1950 AD Southwest Rift Zone eruption.: Bulletin of Volcanology, v. 85, 75, 21 p., https://doi.org/10.1007/s00445-023-01680-x.","productDescription":"75, 21 p.","ipdsId":"IP-152183","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science 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Daniel J.","contributorId":333025,"corporation":false,"usgs":false,"family":"Morgan","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":891689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thornber, Carl","contributorId":333026,"corporation":false,"usgs":false,"family":"Thornber","given":"Carl","affiliations":[{"id":79711,"text":"Cascades Volcano Observatory, Emeritus","active":true,"usgs":false}],"preferred":false,"id":891690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walshaw, Richard","contributorId":333027,"corporation":false,"usgs":false,"family":"Walshaw","given":"Richard","email":"","affiliations":[{"id":79713,"text":"The University of Leeds","active":true,"usgs":false}],"preferred":false,"id":891691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":891692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":891693,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251252,"text":"70251252 - 2023 - Browsing the literature","interactions":[],"lastModifiedDate":"2024-01-31T15:55:31.519107","indexId":"70251252","displayToPublicDate":"2023-11-29T09:55:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Browsing the literature","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Society for Range Management","doi":"10.1016/j.rala.2023.11.003","usgsCitation":"Germino, M., 2023, Browsing the literature: Rangelands, v. 45, no. 6, p. 135-137, https://doi.org/10.1016/j.rala.2023.11.003.","productDescription":"3 p.","startPage":"135","endPage":"137","ipdsId":"IP-159368","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":425149,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":893657,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70251314,"text":"70251314 - 2023 - Long-term biocrust responses to wildfires in Washington, USA","interactions":[],"lastModifiedDate":"2024-02-03T14:28:21.061054","indexId":"70251314","displayToPublicDate":"2023-11-29T08:24:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":724,"text":"American Journal of Botany","active":true,"publicationSubtype":{"id":10}},"title":"Long-term biocrust responses to wildfires in Washington, USA","docAbstract":"<h3 id=\"ajb216261-sec-0010-title\" class=\"article-section__sub-title section1\">Premise</h3><p>Dryland ecosystems in the western United States are affected by invasive species, wildfires, livestock grazing, and climate change in ways that are difficult to distinguish. Biocrusts perform important ecological roles in these systems and are sensitive to all of these pressures.</p><h3 id=\"ajb216261-sec-0020-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We revisited a Washington, USA, site sampled for biocrusts in 1999 to focus on effects of exotic annual grass invasion and wildfires in the absence of livestock grazing. We examined changes between 1999 and 2020 using a Bayesian directed acyclic graph (DAG) to interpret direct and indirect causal impacts of wildfire on perennial bunchgrasses, exotic annual grasses, and biocrusts.</p><h3 id=\"ajb216261-sec-0030-title\" class=\"article-section__sub-title section1\">Results</h3><p>Between 1999 and 2020, exotic annual grass cover increased in all plots and in unburned plots by 16% and 18%, respectively, bunchgrass cover decreased by 21% and 25%, and biocrust cover decreased by 8.9% and 9.8%. Our DAG suggested that decreases in bunchgrass increased exotic annual grass, which reduced biocrust cover. Wildfires did not directly influence changes in bunchgrass, exotic annual grass, or biocrust cover. Areas dominated by exotic annual grass had less abundant and diverse biocrusts than areas with less exotic annual grass.</p><h3 id=\"ajb216261-sec-0040-title\" class=\"article-section__sub-title section1\">Conclusions</h3><p>Biocrust community changes were more strongly related to increasing exotic annual grasses than to wildfires. Changes may relate to other soil disturbances or broad-scale changes in climate or air quality. The minimal influence of wildfire on exotic annual grass and biocrusts suggests that apparent negative impacts of wildfire at other sites may be due to exacerbation by livestock grazing or other surface disturbance.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ajb2.16261","usgsCitation":"Root, H.T., Chan, J., Ponzetti, J.M., Pyke, D.A., and McCune, B., 2023, Long-term biocrust responses to wildfires in Washington, USA: American Journal of Botany, v. 110, no. 12, e16261, https://doi.org/10.1002/ajb2.16261.","productDescription":"e16261","ipdsId":"IP-153752","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":499287,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ajb2.16261","text":"Publisher Index Page"},{"id":425360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"110","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Root, Heather T.","contributorId":333826,"corporation":false,"usgs":false,"family":"Root","given":"Heather","email":"","middleInitial":"T.","affiliations":[{"id":78358,"text":"Weber State University","active":true,"usgs":false}],"preferred":false,"id":894001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chan, Julian","contributorId":333827,"corporation":false,"usgs":false,"family":"Chan","given":"Julian","email":"","affiliations":[{"id":78358,"text":"Weber State University","active":true,"usgs":false}],"preferred":false,"id":894002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ponzetti, Jeanne M","contributorId":328413,"corporation":false,"usgs":false,"family":"Ponzetti","given":"Jeanne","email":"","middleInitial":"M","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":894003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":894004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCune, Bruce","contributorId":149054,"corporation":false,"usgs":false,"family":"McCune","given":"Bruce","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":894005,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250284,"text":"70250284 - 2023 - Climate change impacts on bird migration and highly pathogenic avian influenza","interactions":[],"lastModifiedDate":"2023-12-01T13:25:17.798376","indexId":"70250284","displayToPublicDate":"2023-11-29T07:24:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5843,"text":"Nature Microbiology","onlineIssn":"2058-5276","active":true,"publicationSubtype":{"id":10}},"title":"Climate change impacts on bird migration and highly pathogenic avian influenza","docAbstract":"<div class=\"c-article-section__content c-article-section__content--standfirst u-text-bold\" lang=\"en\"><p>The unprecedented extent of highly pathogenic avian influenza coincides with intensifying global climate changes that alter host ecology and physiology, and could impact virus evolution and dynamics.</p></div>","language":"English","publisher":"Nature","doi":"10.1038/s41564-023-01538-0","usgsCitation":"Prosser, D., Teitelbaum, C., Yin, S., Hill, N.J., and Xiao, X., 2023, Climate change impacts on bird migration and highly pathogenic avian influenza: Nature Microbiology, v. 8, p. 2223-2225, https://doi.org/10.1038/s41564-023-01538-0.","productDescription":"3 p.","startPage":"2223","endPage":"2225","ipdsId":"IP-156469","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":423146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2023-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":889283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teitelbaum, Claire S.","contributorId":174360,"corporation":false,"usgs":false,"family":"Teitelbaum","given":"Claire S.","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":889284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yin, Shenglai","contributorId":223544,"corporation":false,"usgs":false,"family":"Yin","given":"Shenglai","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":889285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hill, Nichola J.","contributorId":189563,"corporation":false,"usgs":false,"family":"Hill","given":"Nichola","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":889286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiao, Xiangming","contributorId":181792,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","email":"","affiliations":[],"preferred":false,"id":889287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250411,"text":"70250411 - 2023 - U.S. Geological Survey Core Research Center: A gateway to subsurface discovery for geoscience research","interactions":[],"lastModifiedDate":"2023-12-08T13:16:47.447012","indexId":"70250411","displayToPublicDate":"2023-11-29T07:15:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"U.S. Geological Survey Core Research Center: A gateway to subsurface discovery for geoscience research","docAbstract":"<p>The U.S. Geological Survey (USGS) operates the Core Research Center (CRC) in Denver, Colorado, USA, a public access repository of rock cores from over 9800 wells and drill cuttings from over 53 000 wells, primarily from states in or adjacent to the Rocky Mountain Region. 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,{"id":70256464,"text":"70256464 - 2023 - The smaller, the better? First evaluation of growth and mortality in crayfish internally tagged with p-Chips","interactions":[],"lastModifiedDate":"2024-08-05T21:59:19.66848","indexId":"70256464","displayToPublicDate":"2023-11-28T16:57:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2235,"text":"Journal of Crustacean Biology","active":true,"publicationSubtype":{"id":10}},"title":"The smaller, the better? First evaluation of growth and mortality in crayfish internally tagged with p-Chips","docAbstract":"<p><span>Small-bodied aquatic animals present a challenge to researchers seeking to uniquely mark individuals for scientific study. Microtransponder tags, such as p-Chips, represent the smallest electronic animal tags available to meet this need. The use of p-Chips to tag freshwater crayfishes, however, has not been explored. The goal of this study, therefore, was to determine the effects of p-Chip tagging on growth and survival of crayfishes in a controlled laboratory environment. We also investigated potential influences from variables such as sex, reproductive form, number of molt events, and crayfish size on mortality. We internally tagged individuals of the woodland crayfish&nbsp;</span><i>Faxonius hylas</i><span>&nbsp;(Faxon, 1890) (12.2–26.6 mm carapace length; CL) with either one p-Chip (single-tag) or one p-Chip and one visual implant elastomer tag (double-tagged) and observed the effects over a period of 90 days. Survival probability over time was not statistically different (</span><i>P</i><span>&nbsp;&gt; 0.05) among tagging groups, sex, and reproductive form. Survival rates were similar across all tagging groups, with 75% in the control group, 77% in the double-tagged group, and 78% in the single-tag group. A strong correlation, however, was observed between survival and the number of molt events. Additionally, there was a negative correlation between survival and crayfish size (CL), indicating a higher risk of mortality for larger individuals. There were no statistically significant differences in growth in CL (</span><i>P</i><span>&nbsp;= 0.30) or mass (</span><i>P</i><span>&nbsp;= 0.19) among the tagging groups. We conclude that p-Chips are a viable tagging option for the study of crayfishes given their size, readability, and retention through molting cycles. We recommend that future studies repeat this experiment using smaller individuals to determine the minimum crayfish size compatible with p-Chip tagging. It is also important to test p-Chips with other crayfish species and compare the growth and mortality of crayfish tagged with p-Chips in natural habitats.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jcbiol/ruad071","usgsCitation":"Huber, A.F., Fitzsimmons, W.A., and Westhoff, J.T., 2023, The smaller, the better? First evaluation of growth and mortality in crayfish internally tagged with p-Chips: Journal of Crustacean Biology, v. 43, no. 4, ruad071, 10 p., https://doi.org/10.1093/jcbiol/ruad071.","productDescription":"ruad071, 10 p.","ipdsId":"IP-155252","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1093/jcbiol/ruad071","text":"Publisher Index Page"},{"id":432244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Huber, Augusto F.","contributorId":340734,"corporation":false,"usgs":false,"family":"Huber","given":"Augusto","email":"","middleInitial":"F.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzsimmons, Wesley A.","contributorId":340735,"corporation":false,"usgs":false,"family":"Fitzsimmons","given":"Wesley","email":"","middleInitial":"A.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":907493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westhoff, Jacob Thomas 0000-0002-2347-5098","orcid":"https://orcid.org/0000-0002-2347-5098","contributorId":288958,"corporation":false,"usgs":true,"family":"Westhoff","given":"Jacob","email":"","middleInitial":"Thomas","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907494,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250098,"text":"tm9A6.8 - 2023 - Use of multiparameter instruments for routine field measurements","interactions":[{"subject":{"id":70203116,"text":"twri09A6.8 - 2012 - Chapter A6. Section 6.8.  Use of multiparameter instruments for routine field measurements","indexId":"twri09A6.8","publicationYear":"2012","noYear":false,"displayTitle":"Chapter A6. Section 6.8. Use of Multiparameter Instruments for Routine Field Measurements","title":"Chapter A6. Section 6.8.  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This chapter, NFM A6.8, provides guidance and protocols for the use of multiparameter instruments for routine field measurements, which includes storage and maintenance of equipment, calibration, troubleshooting, and procedures for measurement and reporting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.8, version 1.1, by Jacob Gibs, Franceska D. Wilde, and Heather A. Heckathorn. The use of multiparameter instruments for conducting field measurements has become routine. The methods described here are specific to the use of multiparameter instruments. The field methods described in this chapter are applicable to most natural waters.</p><p>Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at <a href=\"https://doi.org/10.3133/tm9A0\" data-mce-href=\"https://doi.org/10.3133/tm9A0\">https://doi.org/10.3133/tm9A0</a>. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at <a href=\"https://pubs.er.usgs.gov/\" data-mce-href=\"https://pubs.er.usgs.gov/\">https://pubs.er.usgs.gov/</a>. Comments, questions, and suggestions related to the NFM can be addressed to <a href=\"mailto:nfm@usgs.gov\" data-mce-href=\"mailto:nfm@usgs.gov\">nfm@usgs.gov</a>.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A6.8","usgsCitation":"U.S. Geological Survey, 2023, Use of multiparameter instruments for routine field measurements (ver. 1.1, June 2025): U.S. Geological Survey Techniques and Methods, book 9, chap. A6.8, 13 p., https://doi.org/10.3133/tm9A6.8. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A6.8, version 1.1; and USGS Techniques and Methods, book 9, chap. A6.8, version 1.0.]","productDescription":"v, 13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118565","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":489432,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/09/a6.8/tm9a6.8.XML","linkFileType":{"id":8,"text":"xml"},"description":"T&M 9-A6.8 XML"},{"id":489431,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm9A6.8/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"T&M 9-A6.8 HTML"},{"id":422959,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General introduction for the “National Field Manual for the Collection of Water-Quality Data”"},{"id":422687,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/mission-areas/water-resources/science/national-field-manual-collection-water-quality-data-nfm","text":"National Field Manual for the Collection of Water-Quality Data (NFM)"},{"id":489433,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/09/a6.8/images/"},{"id":422685,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/09/a6.8/versionHist.txt","size":"3.97 KB","linkFileType":{"id":2,"text":"txt"},"description":"T&M 9-A6.8 version history"},{"id":422684,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a6.8/tm9a6.8.pdf","text":"Report","size":"687 KB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 9-A6.8"},{"id":422683,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a6.8/coverthb2.jpg"}],"edition":"Version 1.0: November 28, 2023; Version 1.1: June 12, 2025","contact":"<p><a href=\"https://www.usgs.gov/mission-areas/water-resources\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources\">Water Mission Area</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:nfm@usgs.gov\" data-mce-href=\"mailto:nfm@usgs.gov\">nfm@usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract</li><li>1.0 Introduction</li><li>2.0 Equipment and Supplies</li><li>3.0 Calibration</li><li>4.0 Measurement</li><li>5.0 Troubleshooting</li><li>6.0 Reporting</li><li>Selected References</li><li>Acknowledgments</li><li>Appendix 6.8–1</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-28","revisedDate":"2025-06-12","noUsgsAuthors":false,"publicationDate":"2023-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":152492,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":888329,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250153,"text":"gip227 - 2023 - New England Water Science Center—Bringing quality and reliable water science to New England","interactions":[],"lastModifiedDate":"2023-11-29T01:01:41.271554","indexId":"gip227","displayToPublicDate":"2023-11-28T13:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"227","displayTitle":"New England Water Science Center—Bringing Quality and Reliable Water Science to New England","title":"New England Water Science Center—Bringing quality and reliable water science to New England","docAbstract":"The U.S. Geological Survey (USGS) New England Water Science Center provides timely and reliable information to Federal, State, Tribal, and local stakeholders on the water resources of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. This information product broadly describes the center’s research priorities and monitoring network and how its work benefits the public and environment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip227","usgsCitation":"Rossos, K., 2023, New England Water Science Center—Bringing quality and reliable water science to New England: U.S. Geological Survey General Information Product 227, 1 p., https://doi.org/10.3133/gip227.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-157069","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":422977,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/gip/227/gip227_print.pdf","text":"PDF optimized for printing","size":"1.49 MB"},{"id":422848,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/gip/227/images/"},{"id":422847,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/gip/227/gip227.XML"},{"id":422846,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/gip227/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"GIP 227"},{"id":422845,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/227/gip227.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 227"},{"id":422844,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/227/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Vermont","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.9766341462254,\n              45.282328956258226\n            ],\n            [\n              -74.19636070872549,\n              40.15337389935635\n            ],\n            [\n              -71.33991539622544,\n              40.88829126584898\n            ],\n            [\n              -69.5381575837254,\n              41.87743657809517\n            ],\n            [\n              -66.68171227122534,\n              44.5040492508908\n            ],\n            [\n              -67.0772200837256,\n              45.375014720313544\n            ],\n            [\n              -67.42878258372544,\n              46.6265251987532\n            ],\n            [\n              -67.56061852122568,\n              47.25658613739171\n            ],\n            [\n              -68.39557945872559,\n              47.67250995928134\n            ],\n            [\n              -69.66999352122565,\n              47.52434349852143\n            ],\n            [\n              -70.6367903962253,\n              46.29353264069857\n            ],\n            [\n              -71.33991539622544,\n              45.46754882214901\n            ],\n            [\n              -72.21882164622578,\n              45.22045418725463\n            ],\n            [\n              -73.9766341462254,\n              45.282328956258226\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water-science-center\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-11-28","noUsgsAuthors":false,"publicationDate":"2023-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Rossos, Katrina 0000-0002-3819-4344","orcid":"https://orcid.org/0000-0002-3819-4344","contributorId":331723,"corporation":false,"usgs":true,"family":"Rossos","given":"Katrina","email":"","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250805,"text":"70250805 - 2023 - Practical guide to measuring wetland carbon pools and fluxes","interactions":[],"lastModifiedDate":"2024-01-08T17:36:42.174027","indexId":"70250805","displayToPublicDate":"2023-11-28T07:39:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Practical guide to measuring wetland carbon pools and fluxes","docAbstract":"<p><span>Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first&nbsp;</span><i>define</i><span>&nbsp;each of the major C pools and fluxes and provide&nbsp;</span><i>rationale</i><span>&nbsp;for their importance to wetland C dynamics. For each approach, we clarify&nbsp;</span><i>what</i><span>&nbsp;component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as&nbsp;</span><i>where</i><span>&nbsp;and&nbsp;</span><i>when</i><span>&nbsp;an approach is typically used,&nbsp;</span><i>who</i><span>&nbsp;can conduct the measurements (expertise, training requirements), and&nbsp;</span><i>how</i><span>&nbsp;approaches are conducted, including considerations on equipment complexity and costs. Finally, we review&nbsp;</span><i>key covariates</i><span>&nbsp;and&nbsp;</span><i>ancillary measurements</i><span>&nbsp;that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s13157-023-01722-2","usgsCitation":"Bansal, S., Creed, I., Tangen, B., Bridgham, S.D., Desai, A.R., Krauss, K., Neubauer, S.C., Noe, G.E., Rosenberry, D.O., Trettin, C.C., Wickland, K., Allen, S.T., Arias-Ortiz, A., Armitage, A.R., Baldocchi, D., Banerjee, K., Bastviken, D., Berg, P., Bogard, M.J., Chow, A.T., Conner, W.H., Craft, C., Creamer, C., Delsontro, T., Duberstein, J., Eagle, M.J., Fennessey, M.S., Finkelstein, S.A., Goeckede, M., Grunwald, S., Halibisky, M., Herbert, E.R., Jahangir, M., Johnson, O., Jones, M.C., Kelleway, J., Knox, S., Kroeger, K.D., Kuehn, K., Lobb, D., Loder, A., Ma, S., Maher, D., McNicol, G., Meier, J., Middleton, B.A., Mills, C.T., Mistry, P., Mitra, A., Mobilian, C., Nahlik, A.M., Newman, S., O’Connell, J., Oikawa, P., Post van der Burg, M., Schutte, C.A., Song, C., Stagg, C.L., Turner, J., Vargas, R., Waldrop, M., Wallin, M., Wang, Z.A., Ward, E., Willard, D., Yarwood, S.A., and Zhu, X., 2023, Practical guide to measuring wetland carbon pools and fluxes: Wetlands, v. 43, 105, 169 p., https://doi.org/10.1007/s13157-023-01722-2.","productDescription":"105, 169 p.","ipdsId":"IP-138829","costCenters":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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,{"id":70250223,"text":"70250223 - 2023 - Editorial: Remote sensing of volcanic gas emissions from the ground, air, and space","interactions":[],"lastModifiedDate":"2023-11-29T12:57:49.920719","indexId":"70250223","displayToPublicDate":"2023-11-28T06:56:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Remote sensing of volcanic gas emissions from the ground, air, and space","docAbstract":"When magma rises in volcanic systems, volatile species exsolve from the melt and are outgassed to the atmosphere. The melt composition and temperature, depth at which degassing occurs, extent of gas-water-rock interactions, and volume of ascending magma are all factors that determine the composition and rate of gas emissions at the surface. Interpreted in a petrological framework, gas measurements thus provide information on these fundamental parameters of volcanic systems. Volcanic gases have traditionally been sampled in the field and later analyzed with standard laboratory methods, but remote sensing measurements are playing an increasingly central role in characterizing emissions and the volcanoes from which they originate. The 17 contributions in this Research Topic summarize the state-of-the-art in volcanic gas remote sensing and identify key areas in which the field could further improve our understanding of global volcanism and its impact on Earth’s environment in the next decade.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2023.1340395","usgsCitation":"Kern, C., Arellano, S., Campion, R., Hidalgo, S., and Kazahaya, R., 2023, Editorial: Remote sensing of volcanic gas emissions from the ground, air, and space: Frontiers in Earth Science, v. 11, 1340395, 4 p., https://doi.org/10.3389/feart.2023.1340395.","productDescription":"1340395, 4 p.","ipdsId":"IP-158987","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":441541,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1340395","text":"Publisher Index Page"},{"id":423040,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":888980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arellano, Santiago","contributorId":205719,"corporation":false,"usgs":false,"family":"Arellano","given":"Santiago","affiliations":[{"id":37153,"text":"Department of Earth and Space Sciences – Chalmers University of Technology, Göteborg, Sweden","active":true,"usgs":false}],"preferred":false,"id":888981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campion, Robin","contributorId":148070,"corporation":false,"usgs":false,"family":"Campion","given":"Robin","email":"","affiliations":[{"id":16993,"text":"Instituto de Geofisica, Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":888982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hidalgo, Silvana","contributorId":178530,"corporation":false,"usgs":false,"family":"Hidalgo","given":"Silvana","affiliations":[],"preferred":false,"id":888983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kazahaya, Ryunosuke","contributorId":331867,"corporation":false,"usgs":false,"family":"Kazahaya","given":"Ryunosuke","email":"","affiliations":[{"id":27746,"text":"Geological Survey of Japan","active":true,"usgs":false}],"preferred":false,"id":888984,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250206,"text":"70250206 - 2023 - At what scales does a river meander? Scale-specific sinuosity (S3) metric for quantifying stream meander size distribution","interactions":[],"lastModifiedDate":"2023-11-28T12:55:24.267682","indexId":"70250206","displayToPublicDate":"2023-11-28T06:52:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"At what scales does a river meander? Scale-specific sinuosity (S3) metric for quantifying stream meander size distribution","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif text-s\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0065\">Stream bend geometry is linked to terrain features, hydrologic and ecologic conditions, and anthropogenic forces. Knowledge of the distributions of geometric properties of streams advances understanding of changing landscape conditions and associated processes that operate over a range of spatial scales. Statistical decomposition of sinuosity in natural linear features has proven a longstanding challenge and a particular impediment to automated analysis. This paper demonstrates that sinuosity can vary with the magnitude of units at which it is measured (measurement scales). The paper derives a scale-specific sinuosity (S3) metric intended to measure stream bend geometry across a range of measurement scales. The metric is warranted for analysis and modeling at measurement scales equal or similar to the spatial process and landscape conditions under investigation. Derived from the Richardson (1961) plot, the S3 metric quantifies a frequency signature of<span>&nbsp;</span>planform<span>&nbsp;bend sizes spanning a range&nbsp;of measurement units, enabling visual and quantitative analysis of bend geometry in linear stream features. Derivation of the metric makes evident a systematic relationship between stream bend size, sinuosity, and measurement scale, formalizing a relationship between sinuosity and fractal dimension. The paper shows the utility of the S3 metric in examining bend patterns for synthetic and real-world linear stream data.</span></p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.108734","usgsCitation":"Stanislawski, L., Kronenfeld, B.J., Buttenfield, B.P., and Shavers, E.J., 2023, At what scales does a river meander? Scale-specific sinuosity (S3) metric for quantifying stream meander size distribution: Geomorphology, v. 436, 108734, 11 p., https://doi.org/10.1016/j.geomorph.2023.108734.","productDescription":"108734, 11 p.","ipdsId":"IP-147902","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":441543,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2023.108734","text":"Publisher Index Page"},{"id":499546,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VXT4Z","text":"USGS data release","linkHelpText":"Scale_Specific_Sinuosity"},{"id":423008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"436","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":888907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":888908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888909,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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