Gulf ribbed mussels (Geukensia granosissima) act as ecosystem engineers and reside within the marsh platform of saltmarshes across the northern Gulf of Mexico. With climate models projecting increasing temperatures, and more frequent and extreme heat events, these mussels face increasing temperature-related risks. Marsh surface and subsurface (5-cm depth) temperature was measured continuously in the summer of 2022 in south Louisiana Gulf ribbed mussel habitat at nine stations. Marsh surface maximum temperatures were 5°C higher and more variable than recorded water temperatures, exceeding 38°C for periods of up to 3 h which generally coincided with low tides and peak solar radiation. Marsh subsurface temperatures were cooler with a lower mean and maximum temperature compared with the marsh surface, but higher than adjacent water. In two laboratory experiments the acclimated and acute thermal tolerance of wild mussels collected from the saltmarsh where temperatures were recorded, were explored. G. granosissima survived more than 40 days of continuous exposure in the laboratory to mean daily temperature values recorded for the marsh and subsurface microhabitats (28°C–34°C) but their calculated median lethal time (LT50) ranged from 35 to 56 days (36°C), to less than 3 days (40°C). Mussels acclimated to temperatures similar to long-term average water temperatures (28°C–32°C) and then exposed to maximum daily temperatures acutely experienced LT50 of less than 6 days (38°C), <1 day (40°C), and of less than 5 h (42°C). For G. granosissima both their thermal tolerance and behavioral response likely contribute to their survival in the face of extreme heat events, and their resulting distribution across the marsh surface and subsurface. Overall, results indicate that ribbed mussels in coastal Louisiana may rely on their ability to migrate vertically and bury in the marsh to avoid extreme heat exposure (temperature, duration) that may be lethal. The ability of Gulf ribbed mussels to endure short-term thermal extremes may ultimately determine the mussels' use as a tool in marsh stabilization and coastal restoration.
","language":"English","publisher":"BioOne","doi":"10.2983/035.044.0105","usgsCitation":"Liner, S.R., Roberts, B.J., Coxe, N., Lavaud, R., La Peyre, J.F., and La Peyre, M., 2025, Vulnerability of gulf ribbed mussels to marsh surface maximum temperatures: Journal of Shellfish Research, v. 44, no. 1, p. 45-53, https://doi.org/10.2983/035.044.0105.","productDescription":"9 p.","startPage":"45","endPage":"53","ipdsId":"IP-164252","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Cocodrie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.81142673123271,\n 29.357597141906496\n ],\n [\n -90.81142673123271,\n 29.191048554283725\n ],\n [\n -90.47329864138207,\n 29.191048554283725\n ],\n [\n -90.47329864138207,\n 29.357597141906496\n ],\n [\n -90.81142673123271,\n 29.357597141906496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liner, Skylar R.","contributorId":360165,"corporation":false,"usgs":false,"family":"Liner","given":"Skylar","middleInitial":"R.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":946868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Brian J.","contributorId":360168,"corporation":false,"usgs":false,"family":"Roberts","given":"Brian","middleInitial":"J.","affiliations":[{"id":16627,"text":"Louisiana Universities Marine Consortium (LUMCON)","active":true,"usgs":false}],"preferred":false,"id":946869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coxe, Nicholas","contributorId":341331,"corporation":false,"usgs":false,"family":"Coxe","given":"Nicholas","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":946870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lavaud, Romain","contributorId":341281,"corporation":false,"usgs":false,"family":"Lavaud","given":"Romain","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":946871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Jerome F.","contributorId":360171,"corporation":false,"usgs":false,"family":"La Peyre","given":"Jerome","middleInitial":"F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":946872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946873,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267879,"text":"70267879 - 2025 - Stressor-driven changes in freshwater biological indicators inform spatial management strategies using expert knowledge, observational data, and hierarchical models","interactions":[],"lastModifiedDate":"2025-06-09T14:25:22.071785","indexId":"70267879","displayToPublicDate":"2025-04-17T07:56:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Stressor-driven changes in freshwater biological indicators inform spatial management strategies using expert knowledge, observational data, and hierarchical models","docAbstract":"Stream ecosystems face continuous pressures from multiple anthropogenic stressors that reshape biological communities and impact ecosystem health and services. Managers can encounter challenges in stewarding ecosystems threatened by multiple stressors, in part because most multiple stressor studies are experimental and, while valuable, offer limited management relevance in targeting these stressors on the landscape. Recent advances in causal inference coupled with large biomonitoring data sets could further understanding of observational stressor-response relationships, aiding management. In this study, we use bioassessment data in the Chesapeake Bay watershed in the mid-Atlantic region of the United States to identify how water quality and physical habitat stressors influence key benthic macroinvertebrate response metrics, considering hierarchical relationships using Bayesian networks. Results suggest water temperature and specific conductivity were prevalent stressors in a mountainous region (northern Appalachians), whereas in an agriculturally dominated region (southern Appalachians) physical habitat alterations were the predominant stressor. In mixed-land use regions (Piedmont & Coastal Plains), specific conductivity was a key stressor, but habitat heterogeneity was important for macroinvertebrate metrics. To illustrate how these stressor-response relationships can be used to guide management decisions, we applied the resist-accept-direct (RAD) framework to develop a portfolio of management options based on predicted changes in macroinvertebrate metrics in response to physical habitat and water quality stressors. For example, accepting changes in areas with co-occurring stressors may be the most feasible option, whereas directing changes through stream restoration or water quality improvements may be effective in areas with single stressor groups. By leveraging observational bioassessment data and causal inference to identify key stressor-response relationships, this research supports decision making by building a simple, strategic management portfolio.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113501","usgsCitation":"Emmons, S.C., Cashman, M.J., Fanelli, R.M., Pond, G., Noe, G.E., Woods, T., and Maloney, K.O., 2025, Stressor-driven changes in freshwater biological indicators inform spatial management strategies using expert knowledge, observational data, and hierarchical models: Ecological Indicators, v. 174, 113501, 14 p., https://doi.org/10.1016/j.ecolind.2025.113501.","productDescription":"113501, 14 p.","ipdsId":"IP-174046","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":490670,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113501","text":"Publisher Index Page"},{"id":490199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1904296875,\n 38.41916639395372\n ],\n [\n -75.223388671875,\n 38.64261790634527\n ],\n [\n -75.35522460937499,\n 38.79690830348427\n ],\n [\n -75.498046875,\n 38.87392853923629\n ],\n [\n -75.5419921875,\n 39.0533181067413\n ],\n [\n -75.662841796875,\n 39.30029918615029\n ],\n [\n -75.750732421875,\n 39.70718665682654\n ],\n [\n -75.6298828125,\n 40.052847601823984\n ],\n [\n -75.69580078125,\n 40.07807142745009\n ],\n [\n -75.95947265625,\n 40.052847601823984\n ],\n [\n -76.0693359375,\n 40.069664523297774\n ],\n [\n -76.058349609375,\n 40.18726672309203\n ],\n [\n -75.9375,\n 40.29628651711716\n ],\n [\n -75.91552734375,\n 40.3549167507906\n ],\n [\n -75.89355468749999,\n 40.47202439692057\n ],\n [\n -76.09130859375,\n 40.56389453066509\n ],\n [\n -76.190185546875,\n 40.64730356252251\n ],\n [\n -76.0693359375,\n 40.75557964275589\n ],\n [\n -75.83862304687499,\n 40.871987756697415\n ],\n [\n -75.76171875,\n 40.91351257612758\n ],\n [\n -75.706787109375,\n 40.95501133048621\n ],\n [\n -75.7177734375,\n 41.071069130806414\n ],\n [\n -75.662841796875,\n 41.1455697310095\n ],\n [\n -75.5419921875,\n 41.13729606112276\n ],\n [\n -75.322265625,\n 41.104190944576466\n ],\n [\n -75.377197265625,\n 41.22824901518529\n ],\n [\n -75.377197265625,\n 41.28606238749825\n ],\n [\n -75.377197265625,\n 41.43449030894922\n ],\n [\n -75.399169921875,\n 41.6154423246811\n ],\n [\n -75.34423828125,\n 41.68111756290652\n ],\n [\n -75.2783203125,\n 41.91045347666418\n ],\n [\n -75.38818359375,\n 42.00848901572399\n ],\n [\n -75.377197265625,\n 42.09007006868398\n ],\n [\n -75.223388671875,\n 42.17968819665961\n ],\n [\n -74.970703125,\n 42.26917949243506\n ],\n [\n -74.8388671875,\n 42.32606244456202\n ],\n [\n -74.520263671875,\n 42.415346114253616\n ],\n [\n -74.278564453125,\n 42.54498667313236\n ],\n [\n -74.322509765625,\n 42.64204079304426\n ],\n [\n -74.410400390625,\n 42.80346172417078\n ],\n [\n -74.68505859374999,\n 42.924251753870685\n ],\n [\n -75.069580078125,\n 42.98053954751642\n ],\n [\n -75.38818359375,\n 42.96446257387128\n ],\n [\n -75.684814453125,\n 42.93229601903058\n ],\n [\n -75.9375,\n 42.87596410238256\n ],\n [\n -76.201171875,\n 42.827638636242284\n ],\n [\n -76.26708984375,\n 42.72280375732727\n ],\n [\n -76.2890625,\n 42.601619944327965\n ],\n [\n -76.2890625,\n 42.52069952914966\n ],\n [\n -76.343994140625,\n 42.415346114253616\n ],\n [\n -76.46484375,\n 42.382894009614034\n ],\n [\n -76.640625,\n 42.431565872579185\n ],\n [\n -76.7724609375,\n 42.39912215986002\n ],\n [\n -76.80541992187499,\n 42.24478535602799\n ],\n [\n -76.88232421875,\n 42.285437007491545\n ],\n [\n -76.9482421875,\n 42.415346114253616\n ],\n [\n -77.04711914062499,\n 42.44778143462245\n ],\n [\n -77.14599609375,\n 42.415346114253616\n ],\n [\n -77.2998046875,\n 42.382894009614034\n ],\n [\n -77.222900390625,\n 42.54498667313236\n ],\n [\n -77.442626953125,\n 42.69858589169842\n ],\n [\n -77.574462890625,\n 42.60970621339408\n ],\n [\n -77.640380859375,\n 42.48830197960227\n ],\n [\n -77.728271484375,\n 42.439674178149424\n ],\n [\n -77.6513671875,\n 42.31793945446847\n ],\n [\n -77.596435546875,\n 42.22851735620852\n ],\n [\n -77.5634765625,\n 42.09007006868398\n ],\n [\n -77.6953125,\n 41.92680320648791\n ],\n [\n -77.9150390625,\n 41.83682786072714\n ],\n [\n -78.0908203125,\n 41.795888098191426\n ],\n [\n -78.453369140625,\n 41.599013054830216\n ],\n [\n -78.453369140625,\n 41.50857729743935\n ],\n [\n -78.42041015625,\n 41.376808565702355\n ],\n [\n -78.3984375,\n 41.21172151054787\n ],\n [\n -78.519287109375,\n 41.054501963290505\n ],\n [\n -78.541259765625,\n 40.9218144123785\n ],\n [\n -78.409423828125,\n 40.713955826286046\n ],\n [\n -78.299560546875,\n 40.55554790286311\n ],\n [\n -78.343505859375,\n 40.48873742102282\n ],\n [\n -78.475341796875,\n 40.30466538259176\n ],\n [\n -78.64013671875,\n 40.06125658140474\n ],\n [\n -78.826904296875,\n 39.9434364619742\n ],\n [\n -78.848876953125,\n 39.80853604144591\n ],\n [\n -78.85986328125,\n 39.715638134796336\n ],\n [\n -78.99169921875,\n 39.69873414348139\n ],\n [\n -79.046630859375,\n 39.64799732373418\n ],\n [\n -79.266357421875,\n 39.436192999314095\n ],\n [\n -79.420166015625,\n 39.2832938689385\n ],\n [\n -79.354248046875,\n 39.26628442213066\n ],\n [\n -79.266357421875,\n 39.232253141714885\n ],\n [\n -79.2333984375,\n 39.155622393423215\n ],\n [\n -79.244384765625,\n 39.01918369029134\n ],\n [\n -79.27734374999999,\n 38.89103282648846\n ],\n [\n -79.398193359375,\n 38.74551518488265\n ],\n [\n -79.661865234375,\n 38.54816542304656\n ],\n [\n -79.683837890625,\n 38.47079371120379\n ],\n [\n -79.727783203125,\n 38.34165619279595\n ],\n [\n -79.815673828125,\n 38.20365531807149\n ],\n [\n -80.04638671875,\n 38.013476231041935\n ],\n [\n -80.17822265625,\n 37.779398571318765\n ],\n [\n -80.2880859375,\n 37.59682400108367\n ],\n [\n -80.4638671875,\n 37.47485808497102\n ],\n [\n -80.694580078125,\n 37.38761749978395\n ],\n [\n -80.771484375,\n 37.23032838760387\n ],\n [\n -80.57373046875,\n 37.26530995561875\n ],\n [\n -80.44189453125,\n 37.309014074275915\n ],\n [\n -80.255126953125,\n 37.31775185163688\n ],\n [\n -80.013427734375,\n 37.3002752813443\n ],\n [\n -79.8486328125,\n 37.23907530202184\n ],\n [\n -79.771728515625,\n 37.18657859524883\n ],\n [\n -79.6728515625,\n 37.07271048132943\n ],\n [\n -79.541015625,\n 37.09900294387622\n ],\n [\n -79.354248046875,\n 37.142803443716836\n ],\n [\n -79.1455078125,\n 37.10776507118514\n ],\n [\n -79.112548828125,\n 37.055177106660814\n ],\n [\n -78.936767578125,\n 36.932330061503144\n ],\n [\n -78.837890625,\n 36.94111143010769\n ],\n [\n -78.662109375,\n 37.055177106660814\n ],\n [\n -78.486328125,\n 37.03763967977139\n ],\n [\n -78.42041015625,\n 36.94111143010769\n ],\n [\n -78.20068359374999,\n 36.96744946416934\n ],\n [\n -77.904052734375,\n 37.03763967977139\n ],\n [\n -77.750244140625,\n 37.081475648860525\n ],\n [\n -77.53051757812499,\n 37.081475648860525\n ],\n [\n -77.354736328125,\n 37.07271048132943\n ],\n [\n -77.069091796875,\n 37.081475648860525\n ],\n [\n -76.959228515625,\n 37.01132594307015\n ],\n [\n -76.893310546875,\n 36.932330061503144\n ],\n [\n -76.871337890625,\n 36.83566824724438\n ],\n [\n -76.849365234375,\n 36.677230602346214\n ],\n [\n -76.7724609375,\n 36.527294814546245\n ],\n [\n -76.629638671875,\n 36.55377524336089\n ],\n [\n -76.46484375,\n 36.589068371399115\n ],\n [\n -76.35498046875,\n 36.48314061639213\n ],\n [\n -76.256103515625,\n 36.57142382346277\n ],\n [\n -76.190185546875,\n 36.66841891894786\n ],\n [\n -76.0693359375,\n 36.65079252503471\n ],\n [\n -75.9375,\n 36.66841891894786\n ],\n [\n -75.948486328125,\n 36.76529191711624\n ],\n [\n -75.904541015625,\n 37.01132594307015\n ],\n [\n -75.926513671875,\n 37.17782559332976\n ],\n [\n -75.882568359375,\n 37.42252593456307\n ],\n [\n -75.618896484375,\n 37.640334898059486\n ],\n [\n -75.509033203125,\n 37.82280243352756\n ],\n [\n -75.38818359375,\n 38.013476231041935\n ],\n [\n -75.16845703124999,\n 38.272688535980976\n ],\n [\n -75.1904296875,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"174","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Emmons, Sean Cassian 0000-0003-3548-1927","orcid":"https://orcid.org/0000-0003-3548-1927","contributorId":337235,"corporation":false,"usgs":true,"family":"Emmons","given":"Sean","email":"","middleInitial":"Cassian","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":939257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":939258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925 rfanelli@usgs.gov","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":199822,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary","email":"rfanelli@usgs.gov","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":939259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pond, Greg","contributorId":238186,"corporation":false,"usgs":false,"family":"Pond","given":"Greg","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":939260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":939261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woods, Taylor 0000-0002-6277-1260","orcid":"https://orcid.org/0000-0002-6277-1260","contributorId":304097,"corporation":false,"usgs":true,"family":"Woods","given":"Taylor","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":939262,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":939263,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70265913,"text":"70265913 - 2025 - Gaps in water quality modeling of hydrologic systems","interactions":[],"lastModifiedDate":"2025-04-21T13:16:19.082806","indexId":"70265913","displayToPublicDate":"2025-04-16T09:41:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Gaps in water quality modeling of hydrologic systems","docAbstract":"This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.
","language":"English","publisher":"MDPI","doi":"10.3390/w17081200","usgsCitation":"Lucas, L., Brown, C., Robertson, D., Baker, N.T., Johnson, Z., Green, C., Cho, J., Erickson, M., Gellis, A.C., Jasmann, J.R., Knowles, N., Prein, A., and Stackelberg, P.E., 2025, Gaps in water quality modeling of hydrologic systems: Water, v. 17, no. 8, 1200, 98 p., https://doi.org/10.3390/w17081200.","productDescription":"1200, 98 p.","ipdsId":"IP-157684","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488460,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17081200","text":"Publisher Index Page"},{"id":484764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Lisa V. 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","middleInitial":"V.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":933941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Craig J. 0000-0002-3858-3964","orcid":"https://orcid.org/0000-0002-3858-3964","contributorId":210450,"corporation":false,"usgs":true,"family":"Brown","given":"Craig J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Nancy T. 0000-0002-7979-5744","orcid":"https://orcid.org/0000-0002-7979-5744","contributorId":222870,"corporation":false,"usgs":true,"family":"Baker","given":"Nancy","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":933945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":933946,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cho, Jong 0000-0001-5514-6056","orcid":"https://orcid.org/0000-0001-5514-6056","contributorId":291384,"corporation":false,"usgs":true,"family":"Cho","given":"Jong","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":933947,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933948,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933949,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jasmann, Jeramy Roland 0000-0002-5251-6987","orcid":"https://orcid.org/0000-0002-5251-6987","contributorId":238713,"corporation":false,"usgs":true,"family":"Jasmann","given":"Jeramy","email":"","middleInitial":"Roland","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":933950,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Knowles, Noah 0000-0001-5652-1049","orcid":"https://orcid.org/0000-0001-5652-1049","contributorId":206338,"corporation":false,"usgs":true,"family":"Knowles","given":"Noah","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":933951,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Prein, Andreas","contributorId":352146,"corporation":false,"usgs":false,"family":"Prein","given":"Andreas","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":933952,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":933953,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70266843,"text":"70266843 - 2025 - Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?","interactions":[],"lastModifiedDate":"2025-05-13T16:35:06.894023","indexId":"70266843","displayToPublicDate":"2025-04-16T09:29:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?","docAbstract":"The basaltic Lost Jim lava flow, the youngest member of the Imuruk Lake volcanic field, Alaska, is reported to have interacted with underlying permafrost by thawing it and forming cavities into which the lava flow collapsed, forming pits and other depressions on the lava flow's surface. Our field observations contradict this hypothesis. The Lost Jim lava flow exhibits surface features typical of an inflated pāhoehoe flow, and we propose instead that most of the pits are unambiguously the result of flow inflation (i.e., lava-rise pits). These pits are found on elevated, relatively level surfaces, and their inner walls preserve features like rotated surface slabs and fine-scale flow banding on exposed crack surfaces, both of which are hallmarks of lava flow inflation. While collapse pits do exist on the Lost Jim lava flow, they are morphologically distinct and formed by crustal failure into drained lava tubes.
Satellite images of the Lost Jim lava flow show similarities in the size and distribution of pits within other young pāhoehoe lava flows scattered across the globe. The small diameter of many of the pits (<10 m), compared to flow thickness (≥10 m), also argues against collapse—numerical modeling shows that the relatively high tensile strength of a coherent lava flow would have prevented its collapse into cavities similar in diameter to the lava flow's thickness. Finally, the pits are found scattered across the Lost Jim lava flow, including in locations where the lava flow rests directly on bedrock, which consists of older lava flows. Segregated ice lenses and soil expansion—necessary components for thermokarst formation when thawed—do not exist in such locations. Altogether, these factors show that the Lost Jim lava flow is an inflated lava flow, and permafrost played no significant role during or after its emplacement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108347","usgsCitation":"Orr, T., Coombs, W., Rader, E., and Larsen, J., 2025, Does the Lost Jim lava flow (Alaska) really preserve evidence of interaction with permafrost?: Journal of Volcanology and Geothermal Research, v. 464, 108347, 12 p., https://doi.org/10.1016/j.jvolgeores.2025.108347.","productDescription":"108347, 12 p.","ipdsId":"IP-156249","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488269,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108347","text":"Publisher Index Page"},{"id":485838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Lost Jim lava flow","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.99392503271278,\n 65.97766449153795\n ],\n [\n -163.99392503271278,\n 65.7063086880865\n ],\n [\n -162.3815948765932,\n 65.7063086880865\n ],\n [\n -162.3815948765932,\n 65.97766449153795\n ],\n [\n -163.99392503271278,\n 65.97766449153795\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"464","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":26365,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":936886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, William M. 0000-0003-2099-1676","orcid":"https://orcid.org/0000-0003-2099-1676","contributorId":355121,"corporation":false,"usgs":false,"family":"Coombs","given":"William M.","affiliations":[{"id":35079,"text":"Durham University, Durham, UK","active":true,"usgs":false}],"preferred":false,"id":936887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rader, Erika 0000-0001-8205-3461","orcid":"https://orcid.org/0000-0001-8205-3461","contributorId":331813,"corporation":false,"usgs":false,"family":"Rader","given":"Erika","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":936888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936889,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270107,"text":"70270107 - 2025 - What is the lowest latitude of discrete aurorae during superstorms?","interactions":[],"lastModifiedDate":"2025-08-11T15:47:09.174324","indexId":"70270107","displayToPublicDate":"2025-04-16T08:41:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"What is the lowest latitude of discrete aurorae during superstorms?","docAbstract":"From a survey of published accounts of visual sightings of aurorae, a compilation is presented of the lowest identified geomagnetic latitude at which discrete aurorae were seen at local zenith during magnetic storms having intensities with maximum −Dst > 200 nT. The compilation includes data for the superstorms of 2 September 1859, 4 February 1872, and 15 May 1921. A statistical model is developed representing the equatorward boundary of discrete aurorae versus storm intensity. The model indicates that a once-per-century storm would likely induce discrete aurorae at zenith down to a geomagnetic latitude of 34°. Insofar as aurorae can be taken as a proxy for electrojet currents, such a storm would expose many nighttime electric-power systems, in the contiguous United States or Europe, to high levels of geomagnetic disturbance. A Carrington-class storm would induce discrete aurorae down to 24°. These exposures are much greater than those indicated in recent numerical simulations of extreme magnetic storms. Using the model to infer storm intensity from reports of low-latitude aurorae, a storm on 28 August 1859, likely had maximum −Dst = 673 nT. That this storm occurred just a few days before the Carrington storm of 2 September (maximum −Dst = 964 nT) deserves attention. A storm that occurred on 17 September 1770 is estimated to have had maximum −Dst = 928 nT. The vision of Ezekiel could have been inspired by aurorae from a storm with maximum −Dst = 550 nT.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024SW004286","usgsCitation":"Love, J.J., Mann, I., Qvick, T., and Mursula, K., 2025, What is the lowest latitude of discrete aurorae during superstorms?: Space Weather, v. 23, no. 4, e2024SW004286, 22 p., https://doi.org/10.1029/2024SW004286.","productDescription":"e2024SW004286, 22 p.","ipdsId":"IP-173082","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":494191,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024sw004286","text":"Publisher Index Page"},{"id":493936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":945473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mann, Ian R.","contributorId":359451,"corporation":false,"usgs":false,"family":"Mann","given":"Ian R.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":945474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qvick, Timo","contributorId":359452,"corporation":false,"usgs":false,"family":"Qvick","given":"Timo","affiliations":[{"id":82926,"text":"University of Oulu","active":true,"usgs":false}],"preferred":false,"id":945475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mursula, Kalevi","contributorId":344048,"corporation":false,"usgs":false,"family":"Mursula","given":"Kalevi","affiliations":[{"id":82280,"text":"Space Climate Group, Space Physics and Astronomy Research Unit, University of Oulu, PO Box 3000, 90014 Oulu, Finland","active":true,"usgs":false}],"preferred":false,"id":945476,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267815,"text":"70267815 - 2025 - Lithium from magma to mine in an early Yellowstone hotspot caldera","interactions":[],"lastModifiedDate":"2025-07-10T14:50:14.042773","indexId":"70267815","displayToPublicDate":"2025-04-16T08:37:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Lithium from magma to mine in an early Yellowstone hotspot caldera","docAbstract":"Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G53140.1","usgsCitation":"Watts, K., 2025, Lithium from magma to mine in an early Yellowstone hotspot caldera: Geology, v. 53, no. 7, p. 592-596, https://doi.org/10.1130/G53140.1.","productDescription":"5 p.","startPage":"592","endPage":"596","ipdsId":"IP-167363","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":489475,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490666,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/g53140.1","text":"Publisher Index Page"}],"country":"United States","state":"Idaho, Nevada, Oregon, Wyoming","otherGeospatial":"Yellowstone hotspot caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.21830246150877,\n 45.126578896874065\n ],\n [\n -119.21693278725452,\n 45.126578896874065\n ],\n [\n -119.21693278725452,\n 41.23242701033587\n ],\n [\n -114.17059390138817,\n 40.859473447854995\n ],\n [\n -114.02540645163282,\n 42.00890055289802\n ],\n [\n -110.44161856797778,\n 41.981517173869975\n ],\n [\n -110.21830246150877,\n 45.126578896874065\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":939006,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70266349,"text":"70266349 - 2025 - The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset","interactions":[],"lastModifiedDate":"2025-05-07T13:11:44.831779","indexId":"70266349","displayToPublicDate":"2025-04-16T08:13:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset","docAbstract":"Frequent multispectral observations of sufficient spatial detail from well-calibrated spaceborne sensors are needed for large-scale terrestrial monitoring. To meet this demand, the NASA Harmonized Landsat and Sentinel-2 (HLS) project was initiated in early 2010s to produce comparable 30-m surface reflectance from the US Landsat 8 Operational Land Imager (OLI) and the European Copernicus Sentinel-2A MultiSpectral Instrument (MSI), and currently from two OLI and two MSI sensors, by applying atmospheric correction to top-of-atmosphere (TOA) reflectance, masking out clouds and cloud shadows, normalizing bi-directional reflectance view angle effects, adjusting for sensor bandpass differences with the OLI as the reference, and providing the harmonized data in a common grid. Several versions of HLS dataset have been produced in the last few years. The recent improvements on almost all the harmonization algorithms had prompted a production of a new HLS dataset, tagged Version 2.0, which was completed in the summer of 2023 and for the first time takes on a global coverage (except for Antarctica). The HLS V2.0 data record starts in April 2013, two months after Landsat 8 launch. For 2022, the first whole year two Landsat and two Sentinel-2 satellites were available, HLS provides a global median of 66 cloud-free observations over land, substantially more than from a single sensor. This paper describes the HLS algorithm improvements and assesses the harmonization efficacy by examining how the reflectance difference between contemporaneous Landsat and Sentinel-2 observations was successively reduced by each harmonization step. The assessment was conducted on 545 pairs of globally distributed same-day Landsat/Sentinel-2 images from 2021 to 2022. Compared to the TOA data, the HLS atmospheric correction slightly increased the reflectance relative difference between Landsat and Sentinel-2 for most of the spectral bands, especially for the two blue bands and the green bands. The subsequent bi-directional reflectance view angle effect normalization effectively reduced the between-sensor reflectance difference present in the atmospherically corrected data for all the spectral bands, and notably to a level below the TOA differences for the red, near-infrared (NIR), and the two shortwave infrared (SWIR) bands. The bandpass adjustment only had a modest effect on reducing the between-sensor reflectance difference. In the final HLS products, the same-day reflectance difference between Landsat and Sentinel-2 was below 4.2% for the red, NIR, and the two SWIR bands, all smaller than the difference in the TOA data. However, the between-sensor differences for the two blue and the green bands remain slightly higher than in TOA data, and this reflects the difficulty in accurately correcting for atmospheric effects in the shorter wavelength visible bands. The data consistency evaluation on a suite of commonly used vegetation indices (VI) calculated from the HLS V2.0 reflectance data showed that the between-sensor VI difference is below 4.5% for most of the indices. These results suggest that the harmonization is robust and the HLS V2.0 data are adequate for quantitative terrestrial applications.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2025.114723","usgsCitation":"Ju, J., Zhou, Q., Freitag, B., Roy, D., Zhang, H., Sridhar, M., Mandel, J., Arab, S., Schmidt, G.L., Crawford, C., Gascon, F., Strobl, P., Masek, J.G., and Neigh, C., 2025, The Harmonized Landsat and Sentinel-2 version 2.0 surface reflectance dataset: Remote Sensing of Environment, v. 324, 114723, 17 p., https://doi.org/10.1016/j.rse.2025.114723.","productDescription":"114723, 17 p.","ipdsId":"IP-178601","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488127,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2025.114723","text":"Publisher Index Page"},{"id":485453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ju, Junchang","contributorId":354466,"corporation":false,"usgs":false,"family":"Ju","given":"Junchang","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":935736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Qiang","contributorId":354468,"corporation":false,"usgs":false,"family":"Zhou","given":"Qiang","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":935737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freitag, Brian","contributorId":354470,"corporation":false,"usgs":false,"family":"Freitag","given":"Brian","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935738,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, David P.","contributorId":294404,"corporation":false,"usgs":false,"family":"Roy","given":"David P.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":935739,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Hankui","contributorId":354472,"corporation":false,"usgs":false,"family":"Zhang","given":"Hankui","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":935740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sridhar, Madhu","contributorId":350383,"corporation":false,"usgs":false,"family":"Sridhar","given":"Madhu","affiliations":[{"id":83729,"text":"University of Alabama Huntsville","active":true,"usgs":false}],"preferred":false,"id":935741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mandel, John","contributorId":354474,"corporation":false,"usgs":false,"family":"Mandel","given":"John","affiliations":[{"id":16239,"text":"NASA Marshall Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935742,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":354476,"corporation":false,"usgs":true,"family":"Arab","given":"Saeed","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":935743,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":935744,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":935745,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gascon, Ferran","contributorId":173965,"corporation":false,"usgs":false,"family":"Gascon","given":"Ferran","email":"","affiliations":[{"id":27013,"text":"European Space Agency, Belgium","active":true,"usgs":false}],"preferred":false,"id":935746,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Strobl, Peter A.","contributorId":354478,"corporation":false,"usgs":false,"family":"Strobl","given":"Peter A.","affiliations":[{"id":54481,"text":"European Commission","active":true,"usgs":false}],"preferred":false,"id":935747,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Masek, Jeffrey G.","contributorId":197725,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":935748,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Neigh, Christopher S.R.","contributorId":354481,"corporation":false,"usgs":false,"family":"Neigh","given":"Christopher S.R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":935749,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70265700,"text":"sir20255003 - 2025 - Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","interactions":[],"lastModifiedDate":"2025-08-07T20:57:16.247704","indexId":"sir20255003","displayToPublicDate":"2025-04-16T07:09:29","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5003","displayTitle":"Estimation of Baseflow and Flooding Characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","title":"Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah","docAbstract":"An improved understanding of hydrologic responses to changing climatic conditions is needed to better inform water management practices. East Canyon Creek, a perennial, snowmelt-dominated stream in the Wasatch Mountains of northern Utah, is subjected to increasing development and demands on water in the Snyderville Basin and adjacent areas. In this study, streamflow and specific conductance measured at three U.S. Geological Survey streamgages on East Canyon Creek were used to estimate daily baseflow for water years 2011–22. Trends in these estimates and correlations with climate data from two Natural Resource Conservation Service snow telemetry (SNOTEL) stations within the Snyderville Basin above East Canyon Reservoir, were quantified and reported. Peak annual streamflow also was assessed for flood potential on the study reach of East Canyon Creek. The hydrograph separations showed consistent baseflow indices among all sites, with a larger baseflow component during the fall–spring period (September–April; baseflow indices approximately equal to [≈] 0.751–0.835) and smaller component during the summer period (May–August; baseflow indices ≈ 0.428–0.532). In-stream specific conductance during spring (February–April) was influenced by road salt application, limiting the utility of the hydrograph separation approach. Annual streamflow and climate data were evaluated for trends using the nonparametric Mann–Kendall test, with inconclusive results. Related tests for trends, the Seasonal and Regional Kendall tests, were used to evaluate data at monthly timesteps and indicated a decreasing trend in total streamflow and baseflow at all streamgages. The rank-based Kendall’s tau test for correlation was used to measure the ordinal association with climatic data at co-located SNOTEL stations. Total streamflow and baseflow were strongly correlated with precipitation and snow-water equivalent. By incorporating a predictive regression model, the nonparametric Theil–Sen line, these correlations could support the development of streamflow forecast models using climate data from SNOTEL stations. Such models would provide water managers with tools to help make proactive decisions, such as reservoir or water reclamation releases and curtailment of withdrawals, in response to regional drought or varying snowpack and spring runoff in a given year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255003","collaboration":"Prepared in cooperation with Snyderville Basin Water Reclamation District","usgsCitation":"Root, J.C., and Rumsey, C.A., 2025, Estimation of baseflow and flooding characteristics for East Canyon Creek, Summit and Morgan Counties, Utah: U.S. Geological Survey Scientific Investigations Report 2025–5003, 29 p., https://doi.org/10.3133/sir20255003.","productDescription":"Report: viii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-162488","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":493759,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118539.htm","linkFileType":{"id":5,"text":"html"}},{"id":484540,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14SJDMX","text":"USGS data release","description":"Root, J.C., 2025, Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022: U.S. Geological Survey data release, https://doi.org/10.5066/P14SJDMX.","linkHelpText":"Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah, 2010–2022"},{"id":484539,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5003/images"},{"id":484538,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.XML","description":"SIR 2025-5003 XML"},{"id":484537,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255003/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5003 HTML"},{"id":484536,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5003/sir20255003.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5003 PDF"},{"id":484535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5003/coverthb.jpg"}],"country":"United States","state":"Utah","county":"Morgan County, Summit County","otherGeospatial":"East Canyon Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.85739630382633,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 40.5798335667547\n ],\n [\n -110.91729451616551,\n 41.2514958778022\n ],\n [\n -111.85739630382633,\n 41.2514958778022\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
Many open-vent arc volcanoes display two modes in their continuous gas emissions, one with a characteristic CO2/ ST ratio typical of periods of quiescent degassing and another punctuated by high CO2/ ST gas emitted in the weeks before eruption, a recently recognized eruption precursor. In this study we explore the origin of the two modes of degassing revealed by time-series gas data at Turrialba volcano (Costa Rica) in the context of new melt inclusion (MI) data. To reconstruct the c[CO2] of undegassed magma, we developed a rapid-quench piston-cylinder assembly to rehomogenize the vapor bubble commonly contained in MIs. We focus on olivine-hosted MIs from a mafic scoria sample erupted from Turrialba in 1864–1866. The reconstructed CO2 contents in MIs decrease from ∼4000 to <1000 ppmw as S contents decrease from 3500 to <1000 ppmw. The highest reconstructed S and CO2 in the MIs resulted in an initial magmatic CO2/ ST ratio (molar) of 0.83. Informed by the MI data, we modeled the decompression degassing of Turrialba magma and vapor composition using the Sulfur_X and EVo models. Instead of being controlled by initial magmatic CO2/ST ratio as suggested by previous studies, we find that the quiescent gas emitted from Turrialba during 2014–2018 (CO2/ ST = 2.3 ± 0.8, molar) appears to reflectequilibrium with magmas stored at 4–8 km (Sulfur_X) or 2 km (EVo) depth, when H2O is degassing extensively from the magma. A magma storage region at 4–8 km is also supported by seismic tomography. The second gas mode is noted by spikes in CO2/ ST ∼ 7.9 ± 2 in the weeks prior to eruption. This gas reflects equilibrium with a magma at 12–18 km (Sulfur_X) or 4–8 km (EVo), where the ascending magma is saturated with a CO2-rich vapor. Thus, there are two important trans crustal depths beneath the volcano: one where the rate of H2O loss from the magma and thus magma viscosity increases, and one at greater depths where high CO2/ST vapor forms and may facilitate dike propagation. We interpret the shallower, H2O-loss region as the main site of magma stalling and storage, where quiescent gas is generated continuously. We interpret the greater depth (12–18 km) as the source of the precursory gas that precedes eruption, and where the mafic melt lastly equilibrated with a mush zone before ascending and triggering eruption weeks later. This hypothesis is ripe for testing at other volcanoes that exhibit two modes in gas geochemistry.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2025.119349","usgsCitation":"Ding, S., Plank, T., de Moor, J., Moussallam, Y., Brounce, M., and Kelly, P.J., 2025, Volcanic gases reflect magma stalling and launching depths: Earth and Planetary Science Letters, v. 660, 119349, 13 p., https://doi.org/10.1016/j.epsl.2025.119349.","productDescription":"119349, 13 p.","ipdsId":"IP-160372","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":484641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"Turrialba volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.92,\n 10.0833\n ],\n [\n -83.92,\n 9.9167\n ],\n [\n -83.667,\n 9.9167\n ],\n [\n -83.667,\n 10.0833\n ],\n [\n -83.92,\n 10.0833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"660","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ding, Shuo","contributorId":353454,"corporation":false,"usgs":false,"family":"Ding","given":"Shuo","affiliations":[{"id":84404,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, USA","active":true,"usgs":false}],"preferred":false,"id":933573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plank, Terry","contributorId":353455,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":84404,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, USA","active":true,"usgs":false}],"preferred":false,"id":933574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Moor, J. Maarten","contributorId":353456,"corporation":false,"usgs":false,"family":"de Moor","given":"J. Maarten","affiliations":[{"id":38348,"text":"Observatorio Vulcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":933575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moussallam, Yves","contributorId":353457,"corporation":false,"usgs":false,"family":"Moussallam","given":"Yves","affiliations":[{"id":84404,"text":"Lamont Doherty Earth Observatory, Columbia University, Palisades, NY, USA","active":true,"usgs":false}],"preferred":false,"id":933576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brounce, Maryjo","contributorId":353458,"corporation":false,"usgs":false,"family":"Brounce","given":"Maryjo","affiliations":[{"id":84406,"text":"Earth & Planetary Sciences Department, University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":933577,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":933578,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272696,"text":"70272696 - 2025 - Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York","interactions":[],"lastModifiedDate":"2025-12-04T15:01:52.627998","indexId":"70272696","displayToPublicDate":"2025-04-15T08:56:58","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York","docAbstract":"Nitrogen transported along groundwater flow paths in coastal aquifers can contribute substantially to nitrogen loading into surface water receptors, particularly in hydrologic systems dominated by groundwater discharge. Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.
","language":"English","publisher":"EarthArXiv","doi":"10.31223/X56Q8J","usgsCitation":"Jahn, K., and Walter, D.A., 2025, Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York: EarthArXiv, https://doi.org/10.31223/X56Q8J.","productDescription":"38 p.","ipdsId":"IP-170367","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":497047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jahn, Kalle 0000-0002-4976-0137","orcid":"https://orcid.org/0000-0002-4976-0137","contributorId":333053,"corporation":false,"usgs":true,"family":"Jahn","given":"Kalle","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951353,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270315,"text":"70270315 - 2025 - Multi-species telemetry quantifies current and future efficacy of a remote marine protected area","interactions":[],"lastModifiedDate":"2025-08-14T14:54:17.613606","indexId":"70270315","displayToPublicDate":"2025-04-15T07:47:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-species telemetry quantifies current and future efficacy of a remote marine protected area","docAbstract":"Large-scale marine protected areas (LSMPAs; > 1000 km2) provide important refuge for large mobile species, but most do not encompass species' ranges. To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5–350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1–2.6, “Sustainability”; SSP 3–7.0, “Rocky Road”), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040–2050, followed by an equilibrium response and regained habitat by 2090–2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.70138","usgsCitation":"Gilmour, M.E., Pollock, K., Adams, J., Block, B.A., Caselle, J.E., Filous, A., Friedlander, A.M., Game, E.T., Hazen, E.L., Hill, M., Holmes, N.D., Lafferty, K.D., Maxwell, S.M., McCauley, D.J., Schallert, R., Shaffer, S.A., Wolff, N.H., and Wegmann, A., 2025, Multi-species telemetry quantifies current and future efficacy of a remote marine protected area: Global Change Biology, v. 31, no. 4, e70138, 17 p., https://doi.org/10.1111/gcb.70138.","productDescription":"e70138, 17 p.","ipdsId":"IP-169295","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":494201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.70138","text":"Publisher Index Page"},{"id":494095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Kingman Reef, Palmyra Atoll, U.S. Pacific Islands Heritage Marine National Monument.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -162.47031093286282,\n 6.4554137414790915\n ],\n [\n -162.47031093286282,\n 5.8142234034186515\n ],\n [\n -161.9746083876704,\n 5.8142234034186515\n ],\n [\n -161.9746083876704,\n 6.4554137414790915\n ],\n [\n -162.47031093286282,\n 6.4554137414790915\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Gilmour, Morgan Elizabeth 0000-0002-2618-1095","orcid":"https://orcid.org/0000-0002-2618-1095","contributorId":289509,"corporation":false,"usgs":true,"family":"Gilmour","given":"Morgan","email":"","middleInitial":"Elizabeth","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":945997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Kydd","contributorId":359650,"corporation":false,"usgs":false,"family":"Pollock","given":"Kydd","affiliations":[{"id":34601,"text":"Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":945998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":945999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Block, Barbara A.","contributorId":359653,"corporation":false,"usgs":false,"family":"Block","given":"Barbara","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":946000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caselle, Jennifer E.","contributorId":359655,"corporation":false,"usgs":false,"family":"Caselle","given":"Jennifer","middleInitial":"E.","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":946001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Filous, Alexander","contributorId":272557,"corporation":false,"usgs":false,"family":"Filous","given":"Alexander","email":"","affiliations":[],"preferred":false,"id":946002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Friedlander, Alan M.","contributorId":359658,"corporation":false,"usgs":false,"family":"Friedlander","given":"Alan","middleInitial":"M.","affiliations":[{"id":85893,"text":"National Geographic Society; Hawaiʻi Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":946003,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Game, Edward T.","contributorId":359659,"corporation":false,"usgs":false,"family":"Game","given":"Edward","middleInitial":"T.","affiliations":[{"id":34601,"text":"Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":946004,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hazen, Elliott L.","contributorId":359660,"corporation":false,"usgs":false,"family":"Hazen","given":"Elliott","middleInitial":"L.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":946005,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hill, Marie","contributorId":359661,"corporation":false,"usgs":false,"family":"Hill","given":"Marie","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":946006,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holmes, Nick D.","contributorId":359662,"corporation":false,"usgs":false,"family":"Holmes","given":"Nick","middleInitial":"D.","affiliations":[{"id":34601,"text":"Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":946007,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":946008,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Maxwell, Sara M.","contributorId":359663,"corporation":false,"usgs":false,"family":"Maxwell","given":"Sara","middleInitial":"M.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":946009,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McCauley, Douglas J.","contributorId":359664,"corporation":false,"usgs":false,"family":"McCauley","given":"Douglas","middleInitial":"J.","affiliations":[{"id":37180,"text":"UC Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":946010,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schallert, Robert","contributorId":359665,"corporation":false,"usgs":false,"family":"Schallert","given":"Robert","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":946011,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shaffer, Scott A.","contributorId":359666,"corporation":false,"usgs":false,"family":"Shaffer","given":"Scott","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":946012,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Wolff, Nicholas H.","contributorId":359667,"corporation":false,"usgs":false,"family":"Wolff","given":"Nicholas","middleInitial":"H.","affiliations":[{"id":34601,"text":"Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":946013,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wegmann, Alex","contributorId":189488,"corporation":false,"usgs":false,"family":"Wegmann","given":"Alex","email":"","affiliations":[],"preferred":false,"id":946014,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70266481,"text":"70266481 - 2025 - Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study","interactions":[],"lastModifiedDate":"2025-05-28T14:57:24.741473","indexId":"70266481","displayToPublicDate":"2025-04-15T07:40:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study","docAbstract":"We illustrate the systematic difference between moment magnitude and local magnitude caused by underlying earthquake source physics, using seismic moments submitted to the Statewide California Earthquake Center/United States Geological Survey Community Stress Drop Validation Study 2019 Ridgecrest data set. While the relationship between seismic moment and moment magnitude (M or Mw) of log10(M0) ~ 1.5* M is uniformly valid for all earthquake sizes by definition (Hanks and Kanamori, 1979), the relationship between local magnitude ML and moment is itself magnitude dependent. For moderate events, ~3< M < ~6, M and ML are coincident; for earthquakes smaller than ~3, ML ~ 1.0 log10 M0 (Hanks and Boore, 1984). This is a physical consequence of the corner frequency fc becoming larger than the upper frequency of observation and implies that ML and M differ systematically by a factor of 1.5 for these small events. While this idea is not new, we propose a new, continuous relationship between local magnitude and moment, for magnitudes 2 to 6 which extrapolates to smaller and larger magnitudes, applicable to southern California specific to the Ridgecrest region. We make use of the plethora of seismic moments as submitted by many participants of the Community Stress Drop study, compared to the Southern California Seismic Network (SCSN) catalog magnitudes. Overall, the seismic moments in the Community Study recover moment magnitude well, so we use our new ML-M0 to convert ML to M, refining the SCSN operational MLr scale. This systematic difference of 50% in slope between local and moment magnitude at small magnitudes has implications for spectral stress drop estimates, earthquake ground motion modeling, as well as other magnitude scales and earthquake occurrence statistics.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240162","usgsCitation":"Baltay Sundstrom, A.S., and Abercrombie, R., 2025, Seismic moment and local magnitude scales in Ridgecrest, CA from the SCEC/USGS Community Stress Drop Validation Study: Bulletin of the Seismological Society of America, v. 115, no. 3, p. 1279-1293, https://doi.org/10.1785/0120240162.","productDescription":"15 p.","startPage":"1279","endPage":"1293","ipdsId":"IP-167974","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":485557,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.78392771143658,\n 35.70994070706057\n ],\n [\n -117.78392771143658,\n 35.55296259649002\n ],\n [\n -117.5741750312894,\n 35.55296259649002\n ],\n [\n -117.5741750312894,\n 35.70994070706057\n ],\n [\n -117.78392771143658,\n 35.70994070706057\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":936193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abercrombie, Rachel E.","contributorId":293131,"corporation":false,"usgs":false,"family":"Abercrombie","given":"Rachel E.","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":936194,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70265508,"text":"sir20255005 - 2025 - Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22","interactions":[],"lastModifiedDate":"2025-08-07T20:54:11.145385","indexId":"sir20255005","displayToPublicDate":"2025-04-14T12:55:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5005","displayTitle":"Potential Water-Quality and Hydrology Stressors on Freshwater Mussels With Development of Environmental DNA Assays for Selected Mussels and Macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22","title":"Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22","docAbstract":"The richness and abundance of freshwater mussels in the Big Darby Creek Basin has declined in recent decades, according to survey results published by the Ohio Biological Survey. In October 2016, a major mussel die-off of undetermined cause reportedly affected over 50 miles of Big Darby Creek; however, fishes and other wildlife were not noticeably impacted. Pollution, habitat destruction, climate change, and hydrologic modification have all been theorized as potential reasons for the widespread declines in freshwater mussel populations in North America. To better understand potential stressors to mussels and other aquatic organisms in the Big Darby Creek Basin, the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority, evaluated water quality and temporal changes in hydrology at selected locations. In addition, environmental deoxyribonucleic acid (eDNA) quantitative polymerase chain reaction (qPCR) assays were developed to detect the presence of selected mussels and macroinvertebrates using stream water.
Time-weighted average concentrations of pesticides, organic wastewater compounds (OWCs), and polycyclic aromatic hydrocarbons (PAHs) were determined for selected locations within the Big Darby Creek Basin. Passive samplers designed to mimic the respiratory exposure of aquatic organisms and the bioconcentration of organic contaminants into their fatty tissues were deployed three times annually at three sites within the Big Darby Creek Basin in 2020 and 2021. Analyses were done for 204 pesticide compounds, 38 OWCs, and 33 PAHs. Of the 204 pesticide compounds, 70 were detected in at least one sample; 30 were detected in all samples. Herbicides and herbicide degradates were the pesticides most frequently detected and also had some of the highest concentrations of the pesticides detected in this study. Three herbicides (atrazine, ametryn, and metribuzin) were detected in at least 88 percent of samples and two fungicides (azoxystrobin and propiconazole) were detected in all samples. Of the 38 OWCs, 24 were detected in at least one sample; however, only one (N,N-diethyltoluamide [DEET]) was detected in all samples. Of the 33 PAHs, 29 were detected in at least one sample; 12 were detected in all samples.
A continuous water-quality monitor was operated seasonally on Big Darby Creek above Georgesville, Ohio, from 2020 to 2022. Dissolved oxygen concentrations generally followed a daily cycle, peaking in early evening and troughing around sunrise. There were occasional 24-hour swings in dissolved oxygen concentration that had a range exceeding 10 milligrams per liter. However, dissolved oxygen concentrations never fell below Ohio’s aquatic life criteria for warmwater habitats (outside of mixing zones) of 4.0 milligrams per liter as an instantaneous minimum and 5.0 milligrams per liter as a minimum 24-hour average. The Ohio water-quality criteria for temperatures are 29.4 degrees Celsius as an instantaneous maximum and 27.8 degrees Celsius as a 24-hour average maximum. In 2020, there were 10 days when the maximum instantaneous value for temperature was exceeded and 3 consecutive days when the maximum 24-hour average temperature was exceeded.
Streamflow time-series data from three gaging stations within the Big Darby Creek Basin were evaluated for trends in annual flow statistics and daily nonexceedance probabilities over time. In general, the evaluation of streamflow conditions at the Big Darby Creek gage (with 97 years of record) indicated that streamflow changed between water years 1922 and 2021. During that time span, flows in general increased, the number of high-flow pulses became more frequent, and low-flow pulses and extreme low-flow periods became less frequent. The only strong indication of trends over time in annual flow statistics for the relatively short records for the other two gages (on Little Darby Creek, with 25 years of record, and Hellbranch Run, with 29 years of record) was that as time went on, reversals between rising and falling periods became more frequent.
The U.S. Geological Survey Ohio Water Microbiology Laboratory developed eDNA qPCR assays to detect Epioblasma rangiana (northern riffleshell mussels), Chimarra obscura (a species of caddisfly), Maccaffertium pulchellum (a species of mayfly), and optimized a preexisting eDNA qPCR assay to detect for Ptychobranchus fasciolaris (kidneyshell mussels). The assays were validated by using environmental sampling methods. Assay sensitivity was established by determining the limits of detection and quantification. Water samples were collected at 12 sites in the Big Darby Creek Basin between 2020 and 2022 and analyzed for eDNA with the qPCR assays developed for this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255005","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Huitger, C.A., Koltun, G.F., Stelzer, E.A., and Lynch, L.D., 2025, Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22: U.S. Geological Survey Scientific Investigations Report 2025–5005, 59 p., https://doi.org/10.3133/sir20255005.","productDescription":"Report: ix, 59 p.; 2 Appendices; 2 Data Releases","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-161896","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":484334,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13GN45M","text":"USGS data release","linkHelpText":"Pesticide, organic wastewater compound (OWC) and polycyclic aromatic hydrocarbon (PAH) data determined from samples collected with instream passive samplers in the Big Darby Creek Basin, Ohio, 2020–21"},{"id":484333,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WELW7W","text":"USGS data release","linkHelpText":"Annual streamflow statistics for selected streamgages on Big and Little Darby Creeks and Hellbranch Run, Ohio (through water year 2021)"},{"id":484331,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005_app1_csv.zip","text":"Tables 1.1–1.17 (CSV)","size":"34.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"Appendix 1. Quality Control and Summary Information for Analyses of Pesticides, Organic Wastewater Compounds, and Polycyclic Aromatic Hydrocarbons"},{"id":484330,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005_app1_tables.xlsx","text":"Tables 1.1–1.17","size":"131 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Appendix 1. Quality Control and Summary Information for Analyses of Pesticides, Organic Wastewater Compounds, and Polycyclic Aromatic Hydrocarbons"},{"id":484329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5005/images/"},{"id":484328,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5005 XML"},{"id":493757,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118527.htm","linkFileType":{"id":5,"text":"html"}},{"id":484327,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255005/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5005 HTML"},{"id":484326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5005/sir20255005.pdf","size":"4.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5005 PDF"},{"id":484324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5005/coverthb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Big Darby Creek basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.8333,\n 40.333\n ],\n [\n -83.8333,\n 39.5\n ],\n [\n -83,\n 39.5\n ],\n [\n -83,\n 40.333\n ],\n [\n -83.8333,\n 40.333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
The geologic history and anthropogenic modifications of Minnesota’s Wild Rice River have caused major morphological adjustments, which induce erosion and excess fluvial sediment transport. The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251008","collaboration":"Prepared in cooperation with the Wild Rice Watershed District","usgsCitation":"Groten, J.T., Levin, S.B., Storey, G.G., Coenen, E.N., Blount, J.D., Lund, J.W., and Brannon, D.J., 2025, Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023: U.S. Geological Survey Open-File Report 2025–1008, 38 p., https://doi.org/10.3133/ofr20251008.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154644","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":493754,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118525.htm","linkFileType":{"id":5,"text":"html"}},{"id":483763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1008/coverthb.jpg"},{"id":483764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1008"},{"id":483765,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.XML"},{"id":483766,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1008/images/"},{"id":483767,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483768,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251008/full"}],"country":"United States","state":"Minnesota","otherGeospatial":"Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97,\n 47.5833\n ],\n [\n -97,\n 47\n ],\n [\n -95.25,\n 47\n ],\n [\n -95.25,\n 47.5833\n ],\n [\n -97,\n 47.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e., fine scales, ≤ 1 km) enables precise interventions to maintain water quality and protect aquatic habitats. Although spatiotemporal models have made substantial progress in spatially coarse time series modeling, challenges persist in predicting at fine spatial scales due to the lack of data at that scale. To address the problem of insufficient fine-scale data, we propose a Multi-Scale Graph Learning (MSGL) method. This method employs a multi-task learning framework where coarse-scale graph learning, bolstered by larger datasets, simultaneously enhances fine-scale graph learning. Although existing multi-scale or multi-resolution methods integrate data from different spatial scales, they often overlook the spatial correspondences across graph structures at various scales. To address this, our MSGL introduces an additional learning task, cross-scale interpolation learning, which leverages the hydrological connectedness of stream locations across coarse- and fine-scale graphs to establish cross-scale connections, thereby enhancing overall model performance. Furthermore, we have broken free from the mindset that multi-scale learning is limited to synchronous training by proposing an Asynchronous Multi-Scale Graph Learning method (ASYNC-MSGL). Extensive experiments demonstrate the state-of-the-art performance of our method for anti-sparse downscaling of daily stream temperatures in the Delaware River Basin, USA, highlighting its potential utility for water resources monitoring and management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the AAAI conference on artificial intelligence","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Association for the Advancement of Artificial Intelligence","doi":"10.1609/aaai.v39i27.35014","usgsCitation":"Fan, Y., Yu, R., Barclay, J.R., Appling, A.P., Sun, Y., Xie, Y., and Jia, X., 2025, Multi-Scale Graph Learning for anti-sparse downscaling, in Proceedings of the AAAI conference on artificial intelligence, v. 39, no. 27, p. 27969-27977, https://doi.org/10.1609/aaai.v39i27.35014.","productDescription":"9 p.","startPage":"27969","endPage":"27977","ipdsId":"IP-167502","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":497731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1609/aaai.v39i27.35014","text":"Publisher Index Page"},{"id":497583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"27","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Yingda","contributorId":352470,"corporation":false,"usgs":false,"family":"Fan","given":"Yingda","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Runlong 0000-0003-4080-2377","orcid":"https://orcid.org/0000-0003-4080-2377","contributorId":352471,"corporation":false,"usgs":false,"family":"Yu","given":"Runlong","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":952394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Yiming","contributorId":352472,"corporation":false,"usgs":false,"family":"Sun","given":"Yiming","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":952396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":952397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70265521,"text":"ofr20251010 - 2025 - Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data","interactions":[],"lastModifiedDate":"2025-08-07T20:42:30.599263","indexId":"ofr20251010","displayToPublicDate":"2025-04-10T14:01:28","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1010","displayTitle":"Benthic Habitat Map of Olowalu Reef, Maui, Hawaii—Geomorphological Structure, Biological Cover, and Geologic Zonation Determined with Spectral, Lidar, and Acoustic Data","title":"Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data","docAbstract":"The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km2) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m2) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points (n=870) during active mapping and accuracy assessment points (n=216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones.
The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251010","usgsCitation":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Stone, K., Silva, I., Martinez, T., Peralto, C., Levine, A.S., Stow, D., and Maloney, J., 2025, Benthic Habitat Map of Olowalu Reef, Maui, Hawaii—Geomorphological Structure, Biological Cover, and Geologic Zonation Determined with Spectral, Lidar, and Acoustic Data: U.S. Geological Survey Open-File Report 2025–1010, 32 p., https://doi.org/10.3133/ofr20251010.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-152179","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":493749,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118524.htm","linkFileType":{"id":5,"text":"html"}},{"id":484394,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ICJ7CF","text":"USGS Data Release","description":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Silva, I., Stone, K., Martinez, T., and Peralto, C., 2025, Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui: U.S. Geological Survey data release, https://doi.org/10.5066/P9ICJ7CF.","linkHelpText":"Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui"},{"id":484407,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1010/covrthb.jpg"},{"id":484408,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1010/ofr20251010.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui, Olowalu Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.66330945257621,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.84439182546096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Invasive carps continue to spread across the Mississippi River basin, posing significant ecological risk. Identifying technologies to slow their dispersal is critical. The use of sound has been proposed as a method to modify the behavior of Silver Carp Hypophthalmichthys molitrix, offering a nonstructural deterrent strategy.
Silver Carp implanted with acoustic transmitters were released into earthen ponds equipped with telemetry arrays. The fish were exposed to a 30-min playback of three underwater sounds (chirp saw, chirp square, and 100-hp boat motor). Movement trajectories were analyzed using a two-state hidden Markov model to estimate the effects of environmental and experimental variables on fish behavior.
The results of the hidden Markov model supported two behavioral states. State 1 was characterized by longer step lengths (distance between positions) and greater directional persistence in turning angle (change in direction between two intervals), indicative of heighted activity. State 2 was defined by shorter step lengths and less directional persistence, suggesting reduced activity. Silver Carp that were exposed to the chirp square sound had an increased likelihood of entering state 1, whereas the 100-hp boat motor sound promoted transitions to state 2.
Underwater sounds distinctly influenced the movement of Silver Carp in earthen ponds. The chirp square sound elicited heightened activity levels, demonstrating potential for use in acoustic deterrent applications. However, the response of Silver Carp to these sounds may be influenced by the size of the study environment or the absence of natural drivers of fish behavior, such as food or reproduction. This study contributes to the development of nonstructural, species-specific deterrent systems by identifying sounds that influence the behavior of invasive carps. The application of sound-based methods may play a critical role in integrated pest management strategies for invasive carps, potentially limiting their spread while minimizing effects on native species.
Infrastructure along the U.S.-Mexico Border may not be equally permeable to all types of insect pollinators with potential implications for pollen and gene flow between plant populations. Pollinators were observed on their approach to two types of border barriers (slatted and cemented) along the U.S.-Mexico Border from March 2023 to January 2024. Near the barrier, four insect behaviors were observed including 1) flying over the barrier, 2) crossing through the slats of the barrier, 3) not crossing the barrier, or 4) flying parallel to the barrier without crossing. Overall, 90.2% of the pollinators crossed the barrier. Butterflies were most often observed flying over the barrier (86.8%) or sometimes moving through the slats in the barrier (6.8%). It was more common for moths to crawl through the slats than to fly over the barrier based on the occurrence model. On windy days, both butterflies and moths sometimes flew parallel to the barrier without crossing (1.2% and 27.3%, respectively), although moth crossing behavior was not related to the abundance model. Butterfly abundance increased in higher temperatures and decreased in higher wind speeds. Other insect pollinators were also observed (bee, skipper, wasp) but their crossing behavior was not significantly related to the model. Because pollinators support endangered plant species, strategies to facilitate their barrier crossing could support plant conservation in South Texas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113421","usgsCitation":"Middleton, B., 2025, Insect pollinator crossing of international border barriers along the U.S.-Mexico border: Ecological Indicators, v. 174, 113421, 6 p., https://doi.org/10.1016/j.ecolind.2025.113421.","productDescription":"113421, 6 p.","ipdsId":"IP-168032","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113421","text":"Publisher Index Page"},{"id":484840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Rio Grande Valley National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.55875994836624,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.271404139036903\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.13781819292579,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.51105231424154\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"174","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934236,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70265711,"text":"70265711 - 2025 - Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","interactions":[],"lastModifiedDate":"2025-04-15T15:03:17.346697","indexId":"70265711","displayToPublicDate":"2025-04-10T07:58:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","docAbstract":"The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNdi = ‐2.2 ± 0.8) and zircon Lu-Hf (εHfi = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHfi in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2025.108060","usgsCitation":"Benson, E.K., Watts, K., and Hillenbrand, I.W., 2025, Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California: LITHOS, v. 508-509, 108060, 18 p., https://doi.org/10.1016/j.lithos.2025.108060.","productDescription":"108060, 18 p.","ipdsId":"IP-173126","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.lithos.2025.108060","text":"Publisher Index Page"},{"id":484582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.29333455287775,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 36.19312110709426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"508-509","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265548,"text":"70265548 - 2025 - The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data","interactions":[],"lastModifiedDate":"2025-04-14T15:58:28.046525","indexId":"70265548","displayToPublicDate":"2025-04-09T10:55:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16703,"text":"PLOS Climate","active":true,"publicationSubtype":{"id":10}},"title":"The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data","docAbstract":"We investigated how visitors to federal, state, and local parks and protected areas (PPAs) respond to weather and air quality conditions in the Pacific Northwest (PNW), United States. Specifically, we modeled the relationship between weekly visitation and mean weekly minimum and maximum temperature, precipitation, Air Quality Index (AQI), and particulate matter 2.5 concentration (PM2.5, often used as an indicator of wildfire smoke) during an extended peak visitation season from 2017 to 2021 in 91 PNW PPAs. We used mobile device data from StreetLight Data Inc. to estimate weekly vehicular visitation. Our findings indicate that increasing precipitation corresponded with decreased weekly visitation to all three types of PPAs and rising minimum temperatures corresponded with increased visitation. We found that rising maximum temperatures corresponded with increased visitation in federal and local PPAs, but corresponded with decreased visitation in local PPAs once temperatures reach a maximum threshold. We did not observe a maximum threshold effect in federal or state settings. Further, we found that the effect of air quality and smoke on visitation varies based on the metric used: increased PM2.5 concentrations (possibly indicating the presence of wildfire smoke) in federal and local PPAs corresponded with decreased visitation, while increased AQI in federal PPAs corresponded with increased visitation. These findings indicate that visitors may respond differently to different types of air pollution. Our results have implications for adapting peak- and shoulder- season visitor use management to current and future climate change within and beyond PPAs of the PNW.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pclm.0000537","usgsCitation":"Minehart, K., D'Antonio, A., and Wilkins, E.J., 2025, The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data: PLOS Climate, v. 4, no. 4, e0000537, 22 p., https://doi.org/10.1371/journal.pclm.0000537.","productDescription":"e0000537, 22 p.","ipdsId":"IP-167823","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pclm.0000537","text":"Publisher Index Page"},{"id":484508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-111.044156,43.020052],[-111.046689,42.001567],[-113.893261,41.988057],[-114.831077,42.002207],[-121.035195,41.993323],[-123.145959,42.009247],[-123.656998,41.995137],[-124.211605,41.99846],[-124.270464,42.045553],[-124.299649,42.051736],[-124.356229,42.114952],[-124.361009,42.180752],[-124.383633,42.22716],[-124.410982,42.250547],[-124.410556,42.307431],[-124.429288,42.331746],[-124.424863,42.395426],[-124.434882,42.434916],[-124.390664,42.566593],[-124.401177,42.627192],[-124.413119,42.657934],[-124.45074,42.675798],[-124.473864,42.732671],[-124.491679,42.741789],[-124.510017,42.734746],[-124.552441,42.840568],[-124.456918,43.000315],[-124.434451,43.115986],[-124.401726,43.184896],[-124.38246,43.270167],[-124.402814,43.305872],[-124.373037,43.338953],[-124.341587,43.351337],[-124.315012,43.388389],[-124.233534,43.55713],[-124.168392,43.808903],[-124.142704,43.958182],[-124.111054,44.235071],[-124.1152,44.286486],[-124.084401,44.415611],[-124.071706,44.423662],[-124.084429,44.486927],[-124.067251,44.60804],[-124.082326,44.608861],[-124.065202,44.622445],[-124.058281,44.658866],[-124.070394,44.683514],[-124.059077,44.737656],[-124.075473,44.771403],[-124.074066,44.798107],[-124.025136,44.928175],[-124.004598,45.044959],[-124.017991,45.049808],[-124.015851,45.064759],[-123.989529,45.094045],[-123.975425,45.145476],[-123.964169,45.317026],[-123.972899,45.33689],[-124.007756,45.336813],[-123.973398,45.354791],[-123.965728,45.386242],[-123.960557,45.430778],[-123.976544,45.489733],[-123.957568,45.510399],[-123.939005,45.661923],[-123.943121,45.727031],[-123.982578,45.761815],[-123.969459,45.782371],[-123.962736,45.869974],[-123.96763,45.907807],[-123.993703,45.946431],[-123.969991,45.969139],[-123.941831,45.97566],[-123.927891,46.009564],[-123.933366,46.071672],[-123.974124,46.168798],[-124.024305,46.229256],[-124.001998,46.237316],[-123.987196,46.211521],[-123.950148,46.204097],[-123.9042,46.169293],[-123.854801,46.157342],[-123.841521,46.169824],[-123.863347,46.18235],[-123.838801,46.192211],[-123.636474,46.214359],[-123.625219,46.233868],[-123.605487,46.2393],[-123.586205,46.228654],[-123.548194,46.248245],[-123.547659,46.259109],[-123.669501,46.266832],[-123.680574,46.296025],[-123.700764,46.305278],[-123.75956,46.275073],[-123.806139,46.283588],[-123.875525,46.239787],[-123.909306,46.245491],[-123.985204,46.309039],[-124.020551,46.315737],[-124.044018,46.275925],[-124.080671,46.267239],[-124.057425,46.409315],[-124.069583,46.630651],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.023566,46.582559],[-124.026032,46.462978],[-123.990615,46.463019],[-123.988386,46.497008],[-123.97083,46.47537],[-123.943667,46.477197],[-123.894254,46.537028],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.893054,46.750204],[-123.929073,46.725278],[-123.968564,46.736106],[-123.979655,46.724658],[-123.966886,46.705184],[-124.003458,46.702337],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.117712,46.91238],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.049279,46.891253],[-123.985082,46.921916],[-123.86018,46.948556],[-123.898245,46.971927],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.026345,47.030187],[-124.122057,47.04165],[-124.151288,47.021112],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.355955,47.545698],[-124.425195,47.738434],[-124.453927,47.765334],[-124.471687,47.766907],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.696542,48.069274],[-124.688602,48.092466],[-124.731746,48.169997],[-124.696111,48.198599],[-124.6909,48.212617],[-124.705031,48.238774],[-124.684677,48.255228],[-124.65894,48.331057],[-124.731828,48.381157],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.858821,48.154273],[-123.672445,48.162715],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.239129,48.118217],[-123.133445,48.177276],[-123.143229,48.156633],[-123.06621,48.120469],[-123.038727,48.081138],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.877641,48.047025],[-122.849273,48.053808],[-122.878255,48.076072],[-122.882013,48.100779],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.68724,48.101662],[-122.69222,48.087081],[-122.669868,48.017217],[-122.723374,48.008095],[-122.718082,47.987739],[-122.683223,47.972226],[-122.681924,47.936415],[-122.651063,47.920985],[-122.646494,47.894771],[-122.610341,47.887343],[-122.63636,47.866186],[-122.69376,47.868002],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.856611,47.649615],[-122.754186,47.671612],[-122.740159,47.736228],[-122.714801,47.768176],[-122.690562,47.778372],[-122.684085,47.798574],[-122.608105,47.856728],[-122.573672,47.857582],[-122.588235,47.912923],[-122.616701,47.925139],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.495458,47.786692],[-122.470333,47.757109],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.49824,47.598242],[-122.483805,47.586721],[-122.543118,47.556326],[-122.547207,47.528257],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.573739,47.318419],[-122.550134,47.290496],[-122.589454,47.227618],[-122.611464,47.2181],[-122.692426,47.280026],[-122.671256,47.343774],[-122.634823,47.370583],[-122.639126,47.377822],[-122.725738,47.33047],[-122.749621,47.276408],[-122.641802,47.205013],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.799025,47.289306],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.863732,47.270221],[-122.838298,47.208353],[-122.858735,47.167955],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.527586,47.291531],[-122.547747,47.316403],[-122.4442,47.266723],[-122.409199,47.288556],[-122.444635,47.300421],[-122.423535,47.319121],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.365236,47.48842],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.358238,47.58482],[-122.339513,47.599113],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.37314,47.729219],[-122.397043,47.779719],[-122.394944,47.803318],[-122.339944,47.846718],[-122.307048,47.949117],[-122.230046,47.970917],[-122.224979,48.016626],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.395499,48.228551],[-122.449605,48.232598],[-122.441731,48.211776],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.363107,48.054546],[-122.4675,48.130353],[-122.486736,48.12095],[-122.512031,48.133931],[-122.53722,48.183745],[-122.530996,48.249821],[-122.480925,48.251706],[-122.466803,48.269604],[-122.406516,48.25183],[-122.371693,48.287839],[-122.408718,48.326413],[-122.533452,48.383409],[-122.554536,48.40604],[-122.557298,48.444438],[-122.649839,48.408526],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.689121,48.476849],[-122.700603,48.457632],[-122.710362,48.461584],[-122.712981,48.47879],[-122.684521,48.509123],[-122.606961,48.522152],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.498463,48.556206],[-122.534719,48.574246],[-122.495904,48.575927],[-122.482406,48.559653],[-122.44456,48.570115],[-122.425271,48.599522],[-122.500308,48.656163],[-122.519172,48.713095],[-122.490401,48.751128],[-122.535803,48.776128],[-122.596844,48.771492],[-122.637146,48.735708],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.673472,48.733082],[-122.645743,48.781538],[-122.680246,48.80275],[-122.693683,48.804475],[-122.703106,48.786321],[-122.7112,48.79146],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.818232,48.939062],[-122.817226,48.95597],[-122.796887,48.975026],[-122.756318,48.996881],[-116.049193,49.000912],[-116.04885,47.977186],[-116.030751,47.973349],[-115.906409,47.846261],[-115.881522,47.849672],[-115.852291,47.827991],[-115.835365,47.760957],[-115.824597,47.752154],[-115.803917,47.75848],[-115.780441,47.743447],[-115.776219,47.719818],[-115.72377,47.696671],[-115.73627,47.654762],[-115.694284,47.62346],[-115.689404,47.595402],[-115.734674,47.567401],[-115.747263,47.543197],[-115.717024,47.532693],[-115.686704,47.485596],[-115.655272,47.477944],[-115.654318,47.468077],[-115.671188,47.45439],[-115.718247,47.45316],[-115.731348,47.433381],[-115.657681,47.400651],[-115.644341,47.381826],[-115.609492,47.380799],[-115.556318,47.353076],[-115.51186,47.295219],[-115.428359,47.278722],[-115.410685,47.264228],[-115.326903,47.255912],[-115.29211,47.209861],[-115.300805,47.19393],[-115.261885,47.181742],[-115.243707,47.150347],[-115.200547,47.139154],[-115.140375,47.093013],[-115.107132,47.049041],[-115.087806,47.045519],[-115.049538,46.970774],[-115.001274,46.971901],[-114.963978,46.932889],[-114.929997,46.919625],[-114.931058,46.882108],[-114.947413,46.859324],[-114.928615,46.854815],[-114.920459,46.827697],[-114.888146,46.808573],[-114.864342,46.813858],[-114.829117,46.782503],[-114.79004,46.778729],[-114.765106,46.758153],[-114.788656,46.714033],[-114.76689,46.696901],[-114.713516,46.715138],[-114.699008,46.740223],[-114.649388,46.73289],[-114.620859,46.707415],[-114.623198,46.691511],[-114.641745,46.679286],[-114.635713,46.659375],[-114.595213,46.633456],[-114.547321,46.644485],[-114.466902,46.631695],[-114.424424,46.660648],[-114.360709,46.669059],[-114.320665,46.646963],[-114.348733,46.533792],[-114.342072,46.519679],[-114.35874,46.505306],[-114.403019,46.498675],[-114.376413,46.442983],[-114.384756,46.411784],[-114.422458,46.387097],[-114.411592,46.366688],[-114.413758,46.335945],[-114.431708,46.310744],[-114.425587,46.287899],[-114.470479,46.26732],[-114.445497,46.220227],[-114.445928,46.173933],[-114.472643,46.162202],[-114.514706,46.167726],[-114.527096,46.146218],[-114.5213,46.125287],[-114.474415,46.112515],[-114.460049,46.097104],[-114.468529,46.062484],[-114.493418,46.03717],[-114.470965,45.995742],[-114.425843,45.984984],[-114.403712,45.967049],[-114.431328,45.938023],[-114.387166,45.889164],[-114.409477,45.85164],[-114.44868,45.858891],[-114.509303,45.845531],[-114.512973,45.828825],[-114.562509,45.779927],[-114.495421,45.703321],[-114.507645,45.658949],[-114.561046,45.639906],[-114.538132,45.606834],[-114.559038,45.565706],[-114.460542,45.561283],[-114.456764,45.543983],[-114.415804,45.509753],[-114.36852,45.492716],[-114.360719,45.474116],[-114.333218,45.459316],[-114.270717,45.486116],[-114.247824,45.524283],[-114.248121,45.545877],[-114.192802,45.536596],[-114.180043,45.551432],[-114.135249,45.557465],[-114.122322,45.58426],[-114.086584,45.59118],[-114.067619,45.627706],[-114.018731,45.648616],[-114.019315,45.692937],[-113.986656,45.704564],[-113.93422,45.682232],[-113.898883,45.644167],[-113.904691,45.622007],[-113.861404,45.62366],[-113.806729,45.602146],[-113.803261,45.584193],[-113.834555,45.520729],[-113.766022,45.520621],[-113.759986,45.480735],[-113.78416,45.454946],[-113.764591,45.431403],[-113.765203,45.410601],[-113.734402,45.392353],[-113.738729,45.329741],[-113.689359,45.28355],[-113.684946,45.253706],[-113.599506,45.191114],[-113.57467,45.128411],[-113.554744,45.112901],[-113.513342,45.115225],[-113.506638,45.107288],[-113.520134,45.093033],[-113.485278,45.063519],[-113.45197,45.059247],[-113.437726,45.006967],[-113.446884,44.998545],[-113.443782,44.95989],[-113.498745,44.942314],[-113.455071,44.865424],[-113.356062,44.819798],[-113.3461,44.800611],[-113.354763,44.795468],[-113.341704,44.784853],[-113.247166,44.82295],[-113.131453,44.772837],[-113.134824,44.752763],[-113.102138,44.729027],[-113.098064,44.697477],[-113.06776,44.679474],[-113.068306,44.656374],[-113.049349,44.62938],[-113.083819,44.60222],[-113.019777,44.528505],[-113.020917,44.493827],[-113.003544,44.450814],[-112.951146,44.416699],[-112.886041,44.395874],[-112.855395,44.359975],[-112.814156,44.377198],[-112.812608,44.392275],[-112.836034,44.422653],[-112.781294,44.484888],[-112.71911,44.504344],[-112.664485,44.48645],[-112.541989,44.483971],[-112.50031,44.463051],[-112.473207,44.480027],[-112.387389,44.448058],[-112.358926,44.48628],[-112.35421,44.535638],[-112.319198,44.53911],[-112.286187,44.568472],[-112.242785,44.568091],[-112.221698,44.543519],[-112.183937,44.533067],[-112.136454,44.539911],[-112.106755,44.520829],[-112.069011,44.537104],[-112.036943,44.530323],[-112.032707,44.546642],[-111.980833,44.536682],[-111.947941,44.556776],[-111.870504,44.564033],[-111.821488,44.509286],[-111.715474,44.543543],[-111.704218,44.560205],[-111.617348,44.549467],[-111.591768,44.561502],[-111.471682,44.540824],[-111.469185,44.552044],[-111.519126,44.582916],[-111.525764,44.604883],[-111.473178,44.665479],[-111.468833,44.679335],[-111.484898,44.687578],[-111.486019,44.707654],[-111.438793,44.720546],[-111.414271,44.710741],[-111.385005,44.755128],[-111.355768,44.727602],[-111.323669,44.724474],[-111.26875,44.668279],[-111.276956,44.655626],[-111.25268,44.651092],[-111.224161,44.623402],[-111.225208,44.581006],[-111.189617,44.571062],[-111.143557,44.535732],[-111.122654,44.493659],[-111.048974,44.474072],[-111.044156,43.020052]]],[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.623779,48.269431],[-122.652639,48.265081],[-122.668385,48.223967],[-122.63126,48.220686],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571615,48.105113],[-122.54512,48.05255],[-122.516314,48.057181],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.380497,47.904023],[-122.431035,47.914732],[-122.445519,47.930226],[-122.446682,47.963155],[-122.47266,47.988449],[-122.546824,47.967215],[-122.542924,47.996404],[-122.607342,48.030992],[-122.593621,48.0472],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.679556,48.155113],[-122.693084,48.181509],[-122.770045,48.224395],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664659,48.401508],[-122.634991,48.404244],[-122.637892,48.395681],[-122.60198,48.409907],[-122.585038,48.395166],[-122.585162,48.353304],[-122.506568,48.310041],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460442,47.493764],[-122.433385,47.46643],[-122.437656,47.407424],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.618225,48.670721],[-122.609576,48.645018],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.801096,48.585425],[-122.771206,48.562426],[-122.788503,48.530393],[-122.779124,48.508911],[-122.816332,48.487841],[-122.81973,48.458843],[-122.802509,48.433098],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.119451,48.492576],[-123.163234,48.529544],[-123.173061,48.579086],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.102074,48.604035],[-123.048403,48.569216],[-122.987296,48.561895],[-122.995026,48.578162],[-123.034101,48.591767],[-123.024902,48.594484],[-123.048652,48.621002],[-122.941316,48.702904],[-122.894599,48.71503],[-122.743049,48.661991],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.14799,48.668001],[-123.106165,48.633473],[-123.237148,48.683466],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.009787,48.722291],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.035672,48.68535],[-123.047058,48.695772],[-123.070427,48.699971],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.583985,48.551534],[-122.572967,48.529028],[-122.599948,48.536904],[-122.649256,48.528769],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.670638,48.568812],[-122.68944,48.543903],[-122.717278,48.539739],[-122.73944,48.573893],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.699266,48.621115]]]]},\"properties\":{\"name\":\"Idaho\",\"nation\":\"USA \"}}]}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Minehart, Kira 0009-0006-6007-0782","orcid":"https://orcid.org/0009-0006-6007-0782","contributorId":353124,"corporation":false,"usgs":false,"family":"Minehart","given":"Kira","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Antonio, Ashley","contributorId":353127,"corporation":false,"usgs":false,"family":"D'Antonio","given":"Ashley","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkins, Emily J. 0000-0003-3055-4808","orcid":"https://orcid.org/0000-0003-3055-4808","contributorId":328409,"corporation":false,"usgs":true,"family":"Wilkins","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":933008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271313,"text":"70271313 - 2025 - Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","interactions":[],"lastModifiedDate":"2025-09-04T15:13:46.061817","indexId":"70271313","displayToPublicDate":"2025-04-09T08:06:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","docAbstract":"The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.
","language":"English","publisher":"MDPI","doi":"10.3390/w17081120","usgsCitation":"Nelson, K., Quinn, N., and Traum, J.A., 2025, Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management: Water, v. 17, no. 8, 1120, 26 p., https://doi.org/10.3390/w17081120.","productDescription":"1120, 26 p.","ipdsId":"IP-175116","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":495188,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17081120","text":"Publisher Index Page"},{"id":495166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.73121499117096,\n 38.53799288965703\n ],\n [\n -120.87600359152006,\n 36.83520659574968\n ],\n [\n -119.56082081779095,\n 35.04449080764874\n ],\n [\n -118.38309238355373,\n 35.35382368503207\n ],\n [\n -120.95162530913443,\n 38.878303068488464\n ],\n [\n -121.73121499117096,\n 38.53799288965703\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Nelson, Kirk","contributorId":360939,"corporation":false,"usgs":false,"family":"Nelson","given":"Kirk","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":947952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Nigel","contributorId":360940,"corporation":false,"usgs":false,"family":"Quinn","given":"Nigel","affiliations":[{"id":86123,"text":"Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":947953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947954,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265476,"text":"fs20253018 - 2025 - The 3D Elevation Program—Supporting Rhode Island’s economy","interactions":[],"lastModifiedDate":"2025-05-15T00:36:15.96651","indexId":"fs20253018","displayToPublicDate":"2025-04-08T14:25:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3018","displayTitle":"The 3D Elevation Program—Supporting Rhode Island’s Economy","title":"The 3D Elevation Program—Supporting Rhode Island’s economy","docAbstract":"High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20253018","usgsCitation":"Walters, D., 2025, The 3D Elevation Program—Supporting Rhode Island’s economy: U.S. Geological Survey Fact Sheet 2025–3018, 2 p., https://doi.org/10.3133/fs20253018.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146497","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":484263,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253018/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3018 HTML"},{"id":484262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3018/fs20253018.pdf","text":"Report","size":"628 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3018 PDF"},{"id":484261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3018/coverthb.jpg"},{"id":484264,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3018/fs20253018.XML","linkFileType":{"id":8,"text":"xml"},"description":"FS 2025-3018 XML"},{"id":484265,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3018/images/"}],"country":"United States","state":"Rhode Island","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-71.383586,41.464782],[-71.389284,41.460605],[-71.390275,41.455043],[-71.399568,41.448596],[-71.40056,41.46094],[-71.395927,41.492215],[-71.386511,41.493071],[-71.378914,41.504948],[-71.391005,41.514578],[-71.392137,41.524468],[-71.384478,41.556736],[-71.379021,41.567772],[-71.373618,41.573214],[-71.370194,41.573963],[-71.36356,41.57086],[-71.359868,41.556308],[-71.363292,41.501952],[-71.360403,41.483121],[-71.380947,41.474561],[-71.383586,41.464782]]],[[[-71.326769,41.491286],[-71.325365,41.487601],[-71.327822,41.482985],[-71.343013,41.495615],[-71.341122,41.498598],[-71.326769,41.491286]]],[[[-71.140588,41.605102],[-71.138599,41.60347],[-71.137492,41.602561],[-71.131618,41.593918],[-71.131312,41.592308],[-71.1224,41.522156],[-71.12057,41.497448],[-71.136867,41.493942],[-71.141093,41.489937],[-71.140224,41.485855],[-71.167345,41.471405],[-71.170131,41.463974],[-71.19302,41.457931],[-71.194967,41.459037],[-71.196857,41.461116],[-71.196607,41.464756],[-71.190016,41.478275],[-71.190167,41.484285],[-71.19939,41.491769],[-71.199692,41.495511],[-71.206382,41.499215],[-71.200788,41.514371],[-71.213563,41.545818],[-71.20865,41.571028],[-71.20778,41.60066],[-71.212656,41.610072],[-71.212417,41.61829],[-71.212004,41.62299],[-71.21616,41.62549],[-71.240709,41.619225],[-71.2436,41.587508],[-71.23613,41.574767],[-71.236642,41.535852],[-71.234775,41.532538],[-71.227989,41.528297],[-71.229444,41.521544],[-71.240614,41.500557],[-71.238586,41.486845],[-71.237175,41.486546],[-71.236751,41.483369],[-71.24071,41.474872],[-71.246703,41.47196],[-71.245992,41.481302],[-71.252692,41.485902],[-71.264793,41.488902],[-71.285639,41.487805],[-71.295111,41.48435],[-71.304394,41.454502],[-71.311394,41.450802],[-71.312694,41.451402],[-71.312718,41.454597],[-71.32141,41.4556],[-71.337695,41.448902],[-71.351096,41.450802],[-71.362743,41.460379],[-71.36152,41.464831],[-71.34707,41.47123],[-71.335992,41.469647],[-71.316519,41.47756],[-71.317414,41.488776],[-71.323125,41.503088],[-71.327804,41.504258],[-71.330694,41.507699],[-71.330831,41.518364],[-71.313079,41.534672],[-71.310533,41.54692],[-71.303652,41.559925],[-71.294363,41.571416],[-71.288376,41.573274],[-71.285142,41.577127],[-71.273445,41.60699],[-71.272412,41.615041],[-71.275234,41.619444],[-71.271862,41.623986],[-71.251082,41.63878],[-71.212136,41.641945],[-71.19564,41.67509],[-71.194384,41.674803],[-71.191178,41.674216],[-71.191175,41.674292],[-71.18129,41.672502],[-71.17599,41.671402],[-71.17609,41.668502],[-71.17609,41.668102],[-71.153989,41.664102],[-71.14587,41.662795],[-71.135188,41.660502],[-71.134688,41.660502],[-71.132888,41.660102],[-71.13267,41.658744],[-71.134478,41.641262],[-71.134484,41.641198],[-71.135688,41.628402],[-71.140468,41.623893],[-71.141509,41.616076],[-71.14091,41.607405],[-71.140588,41.605102]]],[[[-71.3312,41.580318],[-71.335949,41.585898],[-71.337048,41.594688],[-71.333751,41.605859],[-71.329559,41.609097],[-71.326609,41.616114],[-71.325877,41.623988],[-71.333305,41.629536],[-71.34657,41.632229],[-71.362869,41.651457],[-71.366165,41.66098],[-71.348402,41.663727],[-71.338696,41.658782],[-71.336182,41.647961],[-71.337048,41.646146],[-71.342514,41.644791],[-71.343666,41.6399],[-71.330711,41.632992],[-71.314889,41.630398],[-71.30555,41.622523],[-71.303352,41.606591],[-71.307381,41.597984],[-71.317474,41.583187],[-71.326103,41.578583],[-71.3312,41.580318]]],[[[-71.281571,41.648207],[-71.278171,41.647309],[-71.274315,41.638125],[-71.283791,41.637797],[-71.286755,41.642725],[-71.283005,41.644434],[-71.281571,41.648207]]],[[[-71.58955,41.196557],[-71.580228,41.204837],[-71.577301,41.21471],[-71.576661,41.224434],[-71.573785,41.228436],[-71.561093,41.224207],[-71.555006,41.216822],[-71.554067,41.212957],[-71.557459,41.204542],[-71.564119,41.195372],[-71.565752,41.184373],[-71.560969,41.176186],[-71.550226,41.166787],[-71.544446,41.164912],[-71.543872,41.161321],[-71.547051,41.153684],[-71.551953,41.151718],[-71.5937,41.146339],[-71.599993,41.146932],[-71.611706,41.153239],[-71.613133,41.160281],[-71.605565,41.182139],[-71.594994,41.188392],[-71.58955,41.196557]]],[[[-71.797649,41.928556],[-71.797922,41.935395],[-71.799242,42.008065],[-71.76601,42.009745],[-71.576908,42.014098],[-71.559439,42.014342],[-71.527606,42.014998],[-71.527306,42.015098],[-71.500905,42.017098],[-71.499905,42.017198],[-71.498258,42.01722],[-71.458104,42.017762],[-71.381401,42.018798],[-71.381466,41.984998],[-71.381501,41.966699],[-71.381401,41.964799],[-71.3816,41.922899],[-71.3817,41.922699],[-71.3817,41.893199],[-71.3766,41.893999],[-71.373799,41.894399],[-71.370999,41.894599],[-71.365399,41.895299],[-71.364699,41.895399],[-71.362499,41.895599],[-71.354699,41.896499],[-71.352699,41.896699],[-71.338698,41.898399],[-71.339298,41.893599],[-71.339298,41.893399],[-71.340798,41.8816],[-71.333997,41.8623],[-71.342198,41.8448],[-71.341797,41.8437],[-71.335197,41.8355],[-71.337597,41.8337],[-71.339597,41.832],[-71.344897,41.828],[-71.347197,41.8231],[-71.339197,41.809],[-71.338897,41.8083],[-71.339297,41.8065],[-71.339297,41.8044],[-71.340797,41.8002],[-71.340697,41.7983],[-71.339297,41.7963],[-71.335797,41.7948],[-71.333896,41.7945],[-71.332196,41.7923],[-71.329296,41.7868],[-71.329396,41.7826],[-71.327896,41.780501],[-71.317795,41.776101],[-71.31779,41.776099],[-71.261392,41.752301],[-71.225709,41.711603],[-71.224798,41.710498],[-71.227875,41.705498],[-71.240991,41.697744],[-71.237635,41.681635],[-71.24155,41.667205],[-71.25956,41.642595],[-71.267055,41.644945],[-71.270075,41.652439],[-71.26918,41.6549],[-71.280366,41.672575],[-71.287637,41.672463],[-71.290546,41.662395],[-71.299159,41.649531],[-71.301396,41.649978],[-71.303746,41.654788],[-71.306095,41.672575],[-71.302627,41.681747],[-71.298935,41.681524],[-71.293119,41.688347],[-71.291217,41.702666],[-71.305759,41.718662],[-71.31482,41.723808],[-71.342786,41.728506],[-71.350057,41.727835],[-71.353172,41.725191],[-71.353748,41.724702],[-71.365717,41.711615],[-71.365717,41.694947],[-71.372988,41.672575],[-71.37791,41.666646],[-71.382049,41.667317],[-71.38988,41.671903],[-71.390775,41.680629],[-71.389432,41.683425],[-71.390551,41.684096],[-71.418069,41.684208],[-71.441336,41.686446],[-71.443082,41.688303],[-71.441896,41.690025],[-71.445923,41.691144],[-71.449318,41.687401],[-71.444468,41.664409],[-71.430038,41.667541],[-71.425452,41.670785],[-71.409302,41.662643],[-71.408636,41.653819],[-71.40377,41.589321],[-71.447712,41.5804],[-71.442567,41.565075],[-71.421649,41.537892],[-71.417398,41.534536],[-71.414825,41.523126],[-71.414937,41.516303],[-71.421425,41.498629],[-71.419971,41.484758],[-71.417957,41.482073],[-71.417621,41.477934],[-71.418404,41.472652],[-71.421157,41.469888],[-71.422991,41.472682],[-71.430744,41.470636],[-71.430926,41.465655],[-71.427935,41.459529],[-71.428652,41.454158],[-71.433612,41.444995],[-71.43767,41.441302],[-71.441199,41.441602],[-71.448948,41.438479],[-71.455845,41.432986],[-71.455371,41.407962],[-71.474918,41.386104],[-71.483295,41.371722],[-71.513401,41.374702],[-71.526724,41.376636],[-71.555381,41.373316],[-71.624505,41.36087],[-71.68807,41.342823],[-71.701631,41.336968],[-71.72074,41.331567],[-71.773702,41.327977],[-71.785957,41.325739],[-71.833755,41.315631],[-71.857432,41.306318],[-71.862772,41.309791],[-71.862109,41.316612],[-71.860513,41.320248],[-71.839013,41.334042],[-71.829595,41.344544],[-71.835951,41.353935],[-71.837738,41.363529],[-71.831613,41.370899],[-71.833443,41.384524],[-71.842131,41.395359],[-71.843472,41.40583],[-71.842563,41.409855],[-71.839649,41.412119],[-71.81839,41.419599],[-71.797683,41.416709],[-71.789359,41.596852],[-71.789356,41.59691],[-71.787637,41.639917],[-71.786994,41.655992],[-71.789672,41.724569],[-71.789678,41.724734],[-71.791062,41.770273],[-71.792767,41.807001],[-71.792786,41.80867],[-71.794161,41.840141],[-71.794161,41.841101],[-71.797649,41.928556]]]]},\"properties\":{\"name\":\"Rhode Island\",\"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819