{"pageNumber":"13","pageRowStart":"300","pageSize":"25","recordCount":46593,"records":[{"id":70272078,"text":"70272078 - 2025 - Relationship of basin structure and bedrock lithology to faulting in the 2019 Ridgecrest earthquake region, California, from gravity and aeromagnetic data","interactions":[],"lastModifiedDate":"2025-11-14T14:34:06.927888","indexId":"70272078","displayToPublicDate":"2025-10-24T08:30:50","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Relationship of basin structure and bedrock lithology to faulting in the 2019 Ridgecrest earthquake region, California, from gravity and aeromagnetic data","docAbstract":"<p>We investigate patterns of cumulative offsets on the faults that ruptured in 2019 and along the Garlock Fault in the Ridgecrest region, California using recently published gravity and aeromagnetic data. We also examine the relationship of basin structure and bedrock structure to the 2019 M7.1 Ridgecrest earthquake ruptures (Fig. 1A), which were primarily along a dextral northwest-striking fault system, and along a sinistral northeast-striking fault, which ruptured hours earlier with a M6.4 event.&nbsp;</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Friends of the Pleistocene Pacific Cell annual meeting fieldtrip guidebook","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2025 Pacific Cell Friends of the Pleistocene Field Conference","conferenceDate":"October 24-26, 2025","conferenceLocation":"Ridgecrest, CA","language":"English","publisher":"Friends of the Pleistocene","usgsCitation":"Langenheim, V., and Haddon, E., 2025, Relationship of basin structure and bedrock lithology to faulting in the 2019 Ridgecrest earthquake region, California, from gravity and aeromagnetic data, <i>in</i> Friends of the Pleistocene Pacific Cell annual meeting fieldtrip guidebook, Ridgecrest, CA, October 24-26, 2025, p. 166-169.","productDescription":"4 p.","startPage":"166","endPage":"169","ipdsId":"IP-183325","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":496472,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496456,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fop.cascadiageo.org/field-trips/pacific-cell-field-trips/2025-pacific-cell-ridgecrest-ca/"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.333,\n              36.333\n            ],\n            [\n              -118.333,\n              35\n            ],\n            [\n              -117,\n              35\n            ],\n            [\n              -117,\n              36.333\n            ],\n            [\n              -118.333,\n              36.333\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Langenheim, Victoria 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":217151,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haddon, Elizabeth 0000-0001-7601-7755 ehaddon@usgs.gov","orcid":"https://orcid.org/0000-0001-7601-7755","contributorId":196407,"corporation":false,"usgs":true,"family":"Haddon","given":"Elizabeth","email":"ehaddon@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":950004,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70274544,"text":"70274544 - 2025 - Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats","interactions":[],"lastModifiedDate":"2026-03-31T15:35:20.916707","indexId":"70274544","displayToPublicDate":"2025-10-23T10:30:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Characterizing the diversity of migration behaviors from the individual to the population level is essential for understanding how organisms respond to environmental variation and how these responses affect survival and habitat use. Lake sturgeon (<i>Acipenser fulvescens</i>) is a species of special concern in the Laurentian Great Lakes that are long-lived and generally classified as intermittent, adfluvial spawners. Observations of lake sturgeon movements at ecologically relevant spatiotemporal scales have shown that migration behavior often varies among individuals within the same population. However, studies on individual populations, particularly when focused only on a part of the life cycle (e.g., often spawning), provide just a partial understanding of the species’ full migratory scope and processes underlying expression of different migratory behaviors. To better understand lake sturgeon migratory diversity, we characterized and compared migratory behaviors of six lake sturgeon populations occupying environments that varied in habitat availability and connectivity in different Laurentian Great Lakes.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>Sequence analysis combined with agglomerative hierarchical clustering and visual inspection of daily location data were used to identify distinct lake sturgeon migratory behaviors present in each population.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Seven distinct migratory behaviors were identified based on differential patterns of lake and river use that encompass spawning and other seasonal periods. Behaviors were categorized as annual spring river, intermittent spring river, intermittent two-step, annual summer river, annual winter river, and annual interlake migrants along with river residents. The presence and frequency of migratory behaviors varied substantially among populations.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Our study demonstrated that migratory diversity is a general feature of lake sturgeon life history that may be partially shaped by habitat availability and connectivity. Given these results, we propose a conceptual model that links habitat availability and connectivity to migratory diversity and predict a positive association between them. This updated framework provides a cohesive basis for understanding lake sturgeon migratory behavior across variable ecological contexts in the Laurentian Great Lakes and will help promote future research to refute or refine the model.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-025-00585-y","usgsCitation":"Fissette, S.D., Krueger, C.C., O'Connor, L.M., Pratt, T.C., Isermann, D.A., Wilfond, D., Sweka, J.A., and Hondorp, D.W., 2025, Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats: Movement Ecology, v. 13, 75, 23 p., https://doi.org/10.1186/s40462-025-00585-y.","productDescription":"75, 23 p.","ipdsId":"IP-175394","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":502075,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-025-00585-y","text":"Publisher Index 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State University","active":true,"usgs":false}],"preferred":false,"id":958216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Connor, Lisa M. 0000-0003-2390-7150","orcid":"https://orcid.org/0000-0003-2390-7150","contributorId":368988,"corporation":false,"usgs":false,"family":"O'Connor","given":"Lisa","middleInitial":"M.","affiliations":[{"id":13015,"text":"Department of Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Thomas C. 0009-0003-3648-2144","orcid":"https://orcid.org/0009-0003-3648-2144","contributorId":368989,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas","middleInitial":"C.","affiliations":[{"id":13015,"text":"Department of Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":958218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":958219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilfond, Dan","contributorId":359121,"corporation":false,"usgs":false,"family":"Wilfond","given":"Dan","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":958220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sweka, John A. 0009-0005-4787-6741","orcid":"https://orcid.org/0009-0005-4787-6741","contributorId":368990,"corporation":false,"usgs":false,"family":"Sweka","given":"John","middleInitial":"A.","affiliations":[{"id":40296,"text":"United States Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":958221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":958222,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70272108,"text":"70272108 - 2025 - Linking bathythermal habitat selection to management of a migratory freshwater fish","interactions":[],"lastModifiedDate":"2025-11-17T15:44:10.712292","indexId":"70272108","displayToPublicDate":"2025-10-23T09:38:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linking bathythermal habitat selection to management of a migratory freshwater fish","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>For migratory fishes, habitat selection in dimensions of temperature and depth may be jointly used to define the bathythermal niche. Seasonal and long-term changes in the availability of bathythermal habitat can cause behavioral responses that have consequences for managing interjurisdictional fisheries that target migratory fishes. Management of such fisheries typically relies on standardized surveys to provide knowledge of stock status, yet changes in fish behavior may complicate interpretation of survey results. For example, changes in bathythermal habitat selection could uncouple fish availability from surveys designed to intercept migrating fish in predefined bathythermal habitats.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We applied electronic tagging methods to Lake Erie walleye (<i>Sander vitreus</i>) to address spatial management and stock assessment questions regarding bathythermal habitat. Specifically, we sought to determine if bathythermal habitat use varied in relation to body size, season, and time of day, with a particular focus on how these may influence availability to fisheries-independent surveys conducted during September-November.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>As predicted, bathythermal habitat distribution fluctuated substantially throughout the year, was most limited during spawning months, and most expansive during fall migration. During the summer stratified months, walleye primarily selected epilimnetic habitats, despite the prevailing notion that colder hypolimnetic waters would be preferred during this time.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>While our results did not support a previous hypothesis that smaller fish were more available to assessment survey gears, our results did support previous assertions that walleye were more active and available to suspended gill nets during late crepuscular periods in fall. Considering uncertainties in water quality and long-term warming trends, our case study could improve decisions regarding spatial management of this species in the context of independent water quality management objectives.</p>","language":"English","publisher":"BMC","doi":"10.1186/s40462-025-00570-5","usgsCitation":"Kraus, R., Faust, M., Colborne, S.F., and Vandergoot, C., 2025, Linking bathythermal habitat selection to management of a migratory freshwater fish: Movement Ecology, v. 13, 76, 16 p., https://doi.org/10.1186/s40462-025-00570-5.","productDescription":"76, 16 p.","ipdsId":"IP-169243","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":496723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-025-00570-5","text":"Publisher Index Page"},{"id":496546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Detroit River, Lake Erie, Lake St. Clair","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.60511028915917,\n              43.124830511606035\n            ],\n            [\n              -83.65975266356337,\n              43.124830511606035\n            ],\n            [\n              -83.65975266356337,\n              40.97016521622899\n            ],\n            [\n              -78.60511028915917,\n              40.97016521622899\n            ],\n            [\n              -78.60511028915917,\n              43.124830511606035\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-10-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":950096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faust, Matthew","contributorId":268770,"corporation":false,"usgs":false,"family":"Faust","given":"Matthew","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":950097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colborne, Scott F.","contributorId":174737,"corporation":false,"usgs":false,"family":"Colborne","given":"Scott","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":950098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher","contributorId":340837,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":950099,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70273250,"text":"70273250 - 2025 - Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes","interactions":[],"lastModifiedDate":"2025-12-23T14:59:24.331062","indexId":"70273250","displayToPublicDate":"2025-10-21T07:44:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes","docAbstract":"<p><span>The use of winter cover crops and conservation tillage are agricultural practices promoted to reduce nutrient and sediment loss from cropland, improve soil health, increase infiltration, and support farm nutrient cycling and ecosystem services. However, environmental performance of these practices is variable in the working farm landscape. The Lower Chesapeake Bay research project within the USDA Long-Term Agroecosystem Research (LTAR) network has collaboratively developed satellite remote sensing algorithms to measure the performance and phenology of winter cover crops (aboveground biomass, nitrogen content, fractional cover, and emergence and termination dates) using no-cost Harmonized Landsat and Sentinel-2 multispectral satellite imagery. This research supports annual operational assessment of&nbsp;&gt;28,000 fields per year in four states. Results document the impacts of agronomic management on conservation outcomes, support adaptive management of incentive payment structures, and can reduce the workload for conservation district staff by remotely verifying cover crop management. Additionally, super-spectral satellite applications have been developed to accurately map crop residue cover by measuring lignocellulose absorption in shortwave infrared wavelengths, producing a 7-year time series of tillage intensity maps for the Delmarva Peninsula. These remote sensing products can be used in decision support and modeling to estimate changes in nutrient, sediment, and carbon cycling resulting from conservation practice implementation in the working farm landscape. This manuscript provides an overview of remote sensing research findings and applications associated with the USDA LTAR and Conservation Effects Assessment Projects (CEAP), documenting a variety of previously published outcomes with update and expansion of techniques using additional unpublished data and analyses as appropriate.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.70082","usgsCitation":"Hively, W.D., Gao, F., McCarty, G.W., Daughtry, C.S., Zhang, X., Jennewein, J., Thieme, A., Lamb, B.T., Keppler, J., Hapeman, C.J., Cosh, M., and Mirsky, S.B., 2025, Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes: Journal of Environmental Quality, v. 54, no. 6, p. 1548-1571, https://doi.org/10.1002/jeq2.70082.","productDescription":"24 p.","startPage":"1548","endPage":"1571","ipdsId":"IP-174155","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":498052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.70082","text":"Publisher Index Page"},{"id":497934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Chesapeake Bay, Delmarva Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.968001494542,\n              38.9830420903468\n            ],\n            [\n              -76.13945750419632,\n              38.41949313855301\n            ],\n            [\n              -75.79643857812154,\n              38.461896436666535\n            ],\n            [\n              -75.63401655681334,\n              39.0636830303699\n            ],\n            [\n              -75.968001494542,\n              38.9830420903468\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"54","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":952861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":952862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCarty, Gregory W.","contributorId":78861,"corporation":false,"usgs":true,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":952863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daughtry, Craig S.T.","contributorId":75863,"corporation":false,"usgs":true,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S.T.","affiliations":[],"preferred":false,"id":952864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Xuesong 0000-0003-4711-7751","orcid":"https://orcid.org/0000-0003-4711-7751","contributorId":364557,"corporation":false,"usgs":false,"family":"Zhang","given":"Xuesong","affiliations":[{"id":65190,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":952865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jennewein, Jyoti 0000-0002-9650-6537","orcid":"https://orcid.org/0000-0002-9650-6537","contributorId":364558,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":86849,"text":"USDA-ARS Sustainable Agricutural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":952866,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thieme, Alison 0000-0001-5458-7554","orcid":"https://orcid.org/0000-0001-5458-7554","contributorId":364559,"corporation":false,"usgs":false,"family":"Thieme","given":"Alison","affiliations":[{"id":86849,"text":"USDA-ARS Sustainable Agricutural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":952867,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952868,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Keppler, Jason","contributorId":364560,"corporation":false,"usgs":false,"family":"Keppler","given":"Jason","affiliations":[{"id":65189,"text":"Maryland Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":952869,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hapeman, Cathleen J. 0000-0003-3439-2826","orcid":"https://orcid.org/0000-0003-3439-2826","contributorId":364550,"corporation":false,"usgs":false,"family":"Hapeman","given":"Cathleen","middleInitial":"J.","affiliations":[{"id":86844,"text":"U.S. Department of Agriculture, Agricultural Research Service (USDA-ARS), Hydrology and Remote Sensing Laboratory, Beltsville Agricultural Research Center, Beltsville, Maryland, USA","active":true,"usgs":false}],"preferred":false,"id":952870,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cosh, Michael 0000-0003-4776-1918","orcid":"https://orcid.org/0000-0003-4776-1918","contributorId":364561,"corporation":false,"usgs":false,"family":"Cosh","given":"Michael","affiliations":[{"id":65190,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":952871,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mirsky, Steven B. 0000-0003-3016-5773","orcid":"https://orcid.org/0000-0003-3016-5773","contributorId":364562,"corporation":false,"usgs":false,"family":"Mirsky","given":"Steven","middleInitial":"B.","affiliations":[{"id":86849,"text":"USDA-ARS Sustainable Agricutural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":952872,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70274022,"text":"70274022 - 2025 - Red spruce forest stand structure and Virginia northern flying squirrel habitat suitability","interactions":[],"lastModifiedDate":"2026-02-20T15:26:36.787455","indexId":"70274022","displayToPublicDate":"2025-10-20T09:24:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2043,"text":"International Journal of Forestry Research","active":true,"publicationSubtype":{"id":10}},"title":"Red spruce forest stand structure and Virginia northern flying squirrel habitat suitability","docAbstract":"<p><span>The Virginia northern flying squirrel (</span><i>Glaucomys sabrinus fuscus</i><span>; VNFS) is a rare, Pleistocene-relict, disjunct subspecies of the northern flying squirrel. The squirrel occurs only in high-elevation red spruce (</span><i>Picea rubens</i><span>) forests of the central Appalachian Mountains of Virginia and West Virginia—a forest type that was substantially reduced by exploitative logging and wildfire in the 1890s–1930. Owing to its cryptic nature and difficulty of capture, managers have relied on an evolving series of predicted habitat suitability models that primarily have used topographic measures and red spruce cover class to assess potential occupancy on the landscape. Currently, VNFS is considered the sentinel species in the region whereby its predicted presence indicates red spruce forests with higher relative habitat integrity, and unsuitable habitat highlights where red spruce restoration or enhancement should occur. However, extant VNFS models only use red spruce percent composition and do not provide insights into forest structure, such as forest canopy height or basal area, that are needed by managers to implement restoration or assess effectiveness. We examined recent historical VNFS observations from nest-box surveys and radiotelemetry data (natural dens and foraging points) relative to random pseudoabsence points across red spruce cover classes from the most current VNFS predicted probability habitat model. Using generalized linear models in an information-theoretic approach, we found that within each red spruce composition class, suitable VNFS habitat was related to increased forest canopy height (m), basal area (m</span><sup>2</sup><span>·ha</span><sup>−1</sup><span>), quadratic mean diameter (cm), and stem density (number of trees ha</span><sup>−1</sup><span>), indicating that, within red spruce and mixed red spruce–northern hardwood forests, VNFS is associated most with mature forest conditions. Accordingly, our results could be recombined with habitat suitability models to prioritize where, for example, red spruce forest structural enhancement would facilitate shifting a given stand to a higher probability condition for VNFS use.</span></p>","language":"English","publisher":"Wiley","doi":"10.1155/ijfr/4526136","usgsCitation":"Humbert, T.R., McKellips, A.W., Carter, D.R., Green, P.C., De La Cruz, J.L., Diggins, C.A., Ford, W., 2025, Red spruce forest stand structure and Virginia northern flying squirrel habitat suitability: International Journal of Forestry Research, v. 2025, 4526136, 9 p., https://doi.org/10.1155/ijfr/4526136.","productDescription":"4526136, 9 p.","ipdsId":"IP-180938","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/ijfr/4526136","text":"Publisher Index Page"},{"id":500341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia, West Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78,\n              39.5833\n            ],\n            [\n              -80.833,\n              39.5833\n            ],\n            [\n              -80.833,\n              37.9167\n            ],\n            [\n              -78,\n              37.9167\n            ],\n            [\n              -78,\n              39.5833\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"2025","noUsgsAuthors":false,"publicationDate":"2025-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Humbert, Tanner R.","contributorId":366758,"corporation":false,"usgs":false,"family":"Humbert","given":"Tanner","middleInitial":"R.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":956186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKellips, Abigail W.","contributorId":366759,"corporation":false,"usgs":false,"family":"McKellips","given":"Abigail","middleInitial":"W.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":956187,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, David R.","contributorId":366863,"corporation":false,"usgs":false,"family":"Carter","given":"David","middleInitial":"R.","affiliations":[],"preferred":false,"id":956333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, P. Corey","contributorId":366760,"corporation":false,"usgs":false,"family":"Green","given":"P.","middleInitial":"Corey","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":956188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De La Cruz, Jesse L.","contributorId":366761,"corporation":false,"usgs":false,"family":"De La Cruz","given":"Jesse","middleInitial":"L.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":956189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diggins, Corinne A.","contributorId":366762,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":956190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":956191,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273934,"text":"70273934 - 2025 - Correspondence between satellite-derived and long-term field observations of vegetation cover at Great Basin experimental treatments.","interactions":[],"lastModifiedDate":"2026-02-18T15:21:19.569373","indexId":"70273934","displayToPublicDate":"2025-10-16T08:14:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Correspondence between satellite-derived and long-term field observations of vegetation cover at Great Basin experimental treatments.","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Vegetation treatments are frequently utilized in Western US rangelands to reduce woody plant cover in sagebrush stands threatened by increased wildfire risk and in pinyon-juniper woodlands expanding into formerly high-value sagebrush habitats. Despite widespread use of these treatments, monitoring data to evaluate long-term vegetation responses are often insufficient or absent. Long-term field experiments and remote-sensing based vegetation data may be complementary for assessing treatment effectiveness across temporal and spatial scales. The SageSTEP project experimentally implemented treatments at numerous sites across the Intermountain West and monitored the subsequent response of vegetation cover components with 15+ yr of field observations. However, while pretreatment data were collected in the year of implementation, long-term observations of pretreatment vegetation conditions are lacking in the SageSTEP database. Remote-sensing based time-series maps (1985–2023) of vegetation cover from Rangeland Condition Monitoring Assessment and Projection (RCMAP) could fill temporal gaps in monitoring data and scale findings across broader extents. We evaluate the relationship between pretreatment vegetation cover in the RCMAP data and the post-treatment response in both the RCMAP and field observations. Additionally, we explore the correspondence between SageSTEP field observations and RCMAP at various scales, and examine key factors related to the strength of relationships. Overall, SageSTEP and RCMAP data show a similar direction of treatment effect for each component, and to a lesser extent the magnitude of effect. SageSTEP and RCMAP data tended to agree most strongly where treatment effects were strong; when averaged across broader spatial scales; and for components such as tree and bare ground that are more easily distinguished spectrally. Remote sensing tools such as RCMAP, in combination with field-based climate and vegetation observations, can help assess postdisturbance recovery trajectories and facilitate regional decision-making around treatment alternatives, fire risk reduction, and protection of critical habitats.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2025.09.007","usgsCitation":"Rigge, M.B., Case, M.F., Shaff, S.E., Ellsworth, L., Bunde, B., and Postma, K., 2025, Correspondence between satellite-derived and long-term field observations of vegetation cover at Great Basin experimental treatments.: Rangeland Ecology & Management, v. 103, p. 341-355, https://doi.org/10.1016/j.rama.2025.09.007.","productDescription":"15 p.","startPage":"341","endPage":"355","ipdsId":"IP-167032","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":500252,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2025.09.007","text":"Publisher Index Page"},{"id":500139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.92270708025353,\n              48.478358686610875\n            ],\n            [\n              -117.92270708025353,\n              36.755797428874644\n            ],\n            [\n              -107.75776722181647,\n              36.755797428874644\n            ],\n            [\n              -107.75776722181647,\n              48.478358686610875\n            ],\n            [\n              -117.92270708025353,\n              48.478358686610875\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"103","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":955806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Case, Madelon Florence 0000-0003-4830-5324","orcid":"https://orcid.org/0000-0003-4830-5324","contributorId":329634,"corporation":false,"usgs":true,"family":"Case","given":"Madelon","email":"","middleInitial":"Florence","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaff, Scott E. 0000-0001-8978-9260","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":219813,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":955808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellsworth, Lisa M.","contributorId":328375,"corporation":false,"usgs":false,"family":"Ellsworth","given":"Lisa M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":955809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bunde, Brett 0000-0003-0228-779X","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":288364,"corporation":false,"usgs":false,"family":"Bunde","given":"Brett","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":955810,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Postma, Kory 0000-0001-8058-498X","orcid":"https://orcid.org/0000-0001-8058-498X","contributorId":293879,"corporation":false,"usgs":false,"family":"Postma","given":"Kory","affiliations":[{"id":63548,"text":"KBRwyle, under contract to USGS","active":true,"usgs":false}],"preferred":false,"id":955811,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273077,"text":"70273077 - 2025 - Museum records provide unique information about the distribution of the Yellow Lampmussel <i>Lampsilis cariosa</i> (Unionidae)","interactions":[],"lastModifiedDate":"2025-12-12T19:14:40.520059","indexId":"70273077","displayToPublicDate":"2025-10-15T12:07:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Museum records provide unique information about the distribution of the Yellow Lampmussel <i>Lampsilis cariosa</i> (Unionidae)","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Natural history museum records may provide unique information on the distribution of species that can supplement survey data collected by resource managers. However, there can be challenges to using museum data for analyses, such as spurious geographic information, misidentifications, and incorrect labeling. Museum records have been centralized by open-source repositories with flags for coordinate precision and out-of-range specimens, providing some information about record uncertainty in general. Verification of uncertain museum records could increase confidence in distribution data and improve understanding of biodiversity patterns and range dynamics through time. The goal of this study was to determine if museum records provide unique information about the distribution of the Yellow Lampmussel&nbsp;</span><i>Lampsilis cariosa</i><span>&nbsp;(Say, 1817), an at-risk freshwater mussel species. We created a dichotomous key based on a hierarchy of conchological characteristics to verify the taxonomic identity of flagged&nbsp;</span><i>L. cariosa</i><span>&nbsp;specimens and assessed records occurring outside of the species’ expected range as compiled from primary literature. Fifty percent of flagged specimens were confirmed as&nbsp;</span><i>L. cariosa</i><span>. Of the invalid records, 56% were misidentifications, mainly of other&nbsp;</span><i>Lampsilis</i><span>&nbsp;species. Overall, museum collections (1800s–present) contributed 32 unique watersheds not represented by modern survey records (1980s–present, comprising 92 watersheds) including 13 unexpected watersheds in regions of New York and Vermont (USA) and Québec and Ontario (Canada). Our study provides a reproducible method for the reverification of freshwater mussel museum records and highlights how these records can provide unique contributions to our understanding of the geographic range of a rare, at-risk mussel species.</span></span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/738615","usgsCitation":"Fedarick, J., Murphy, C.A., Record, S., and Roy, A.H., 2025, Museum records provide unique information about the distribution of the Yellow Lampmussel <i>Lampsilis cariosa</i> (Unionidae): Freshwater Science, v. 44, no. 4, p. 434-442, https://doi.org/10.1086/738615.","productDescription":"9 p.","startPage":"434","endPage":"442","ipdsId":"IP-174004","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"New York, Vermont","otherGeospatial":"Ontario, Quebec","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.15950260000896,\n              56.462837792190584\n            ],\n            [\n              -95.77691469485542,\n              49.71284520828655\n            ],\n            [\n              -85.11013420152203,\n              46.85470065182994\n            ],\n            [\n              -81.95949958747218,\n              44.63027898467527\n            ],\n            [\n              -79.51850001152886,\n              42.05772807401594\n            ],\n            [\n              -73.39821683387511,\n              41.96978452451617\n            ],\n            [\n              -72.36699219294661,\n              42.840968406530905\n            ],\n            [\n              -71.94060238105281,\n              45.20492109068548\n            ],\n            [\n              -64.41091936819154,\n              50.95131087236287\n            ],\n            [\n              -72.30757566485309,\n              56.462837792190584\n            ],\n            [\n              -90.15950260000896,\n              56.462837792190584\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"44","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fedarick, Jillian","contributorId":363950,"corporation":false,"usgs":false,"family":"Fedarick","given":"Jillian","affiliations":[],"preferred":false,"id":952246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Record, Sydne 0000-0001-7293-2155","orcid":"https://orcid.org/0000-0001-7293-2155","contributorId":353707,"corporation":false,"usgs":false,"family":"Record","given":"Sydne","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":952248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952249,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272172,"text":"70272172 - 2025 - Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years","interactions":[],"lastModifiedDate":"2025-12-15T16:40:30.851106","indexId":"70272172","displayToPublicDate":"2025-10-15T09:08:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years","docAbstract":"<p><span>Ecological systems can undergo large changes and regime shifts that are either catastrophic, neutral, or desirable. Rivers worldwide have recently undergone desirable regime shifts related to re-oligotrophy, which is a notable and ongoing reduction in concentrations of total suspended solids (TSS), total N, total P, or phytoplankton. For example, the Upper Mississippi River, USA, has experienced major water-quality changes in multiple river reaches in recent decades. In this study, we sought to understand the timing and magnitude of re-oligotrophy in the Mississippi River over a 20-y period. We used 2 topological data analysis algorithms to address hypotheses related to the following questions: What were the order and timing of water-quality changes? What was the time period over which the major changes occurred? What was the magnitude of water-quality change before and after change points (i.e., specific years when water-quality conditions transitioned abruptly to new states)? We examined 6 water-quality state variables that defined the ecological regime for the Upper Mississippi River. In one river reach, we found that strong reductions in phytoplankton/chlorophyll&nbsp;</span><i>a</i><span>&nbsp;had occurred first (2008), followed by total P (2013), and last in TSS (2014). In a downriver reach, we found notable reductions for chlorophyll&nbsp;</span><i>a</i><span>&nbsp;(2007) but substantial increases in TSS (2013). In both reaches, the water-quality changes trended over ≥15 y, but the largest changes and a likely regime shift occurred in just 6 y. The timing (2007–2014) and range (~6 y) of water-quality changes were similar between the 2 river reaches, but the directionality of the regime shift indicated re-oligotrophy for the upstream reach and water-quality degradation for the downstream reach. Topological methods applied to long-term datasets can aid our understanding of re-oligotrophication and degradation processes and may help resource managers restore desirable regimes.</span></p>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/738457","usgsCitation":"Davis, K., Bungula, W., and Larson, D.M., 2025, Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years: Freshwater Science, v. 44, no. 4, p. 409-421, https://doi.org/10.1086/738457.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-158399","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496580,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-10-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Killian","contributorId":315371,"corporation":false,"usgs":false,"family":"Davis","given":"Killian","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":950301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bungula, Wako","contributorId":315367,"corporation":false,"usgs":false,"family":"Bungula","given":"Wako","email":"","affiliations":[{"id":68293,"text":"University of Wisconsin La Crosse","active":true,"usgs":false}],"preferred":false,"id":950302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950303,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70273317,"text":"70273317 - 2025 - Summer roost site suitability analyses for 4 special status bat species in the Eastern United States","interactions":[],"lastModifiedDate":"2026-01-06T14:41:32.178329","indexId":"70273317","displayToPublicDate":"2025-10-14T08:37:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Summer roost site suitability analyses for 4 special status bat species in the Eastern United States","docAbstract":"<p><span>Data describing habitat suitability are crucial for implementing effective conservation planning but are often lacking at regional and continental scales. We address this gap for 4 bat species that are listed, proposed for listing, or under Endangered Species Act listing review by highlighting a framework for estimating summer roost suitability with a presence-background approach to aid development of conservation policy and management plans. The 4 species of concern are the Little Brown Bat (</span><i>Myotis lucifugus</i><span>), the Northern Long-eared Bat (</span><i>M. septentrionalis</i><span>), the Indiana Bat (</span><i>M. sodalis</i><span>), and the Tricolored Bat (</span><i>Perimyotis subflavus</i><span>). Our estimates of summer roost suitability were developed for the eastern United States at a fine spatial resolution (250 m pixels) suitable for conservation planning across multiple scales. Summer roost habitat suitability was higher in areas with higher tree canopy cover for each of these species, though subtle differences were observed between the species that often use buildings (e.g., Little Brown Bat), tree crevices, cavities, and elements of dead or dying trees (e.g., Northern Long-eared Bat and Indiana Bat), and foliage (e.g., Tricolored Bat). To this end, roost suitability was not identical among species, and each showed subtly different relationships to the environmental covariates considered here. We also use a novel approach, gradient surface metrics, to quantify differences in the spatial pattern of summer roost suitability among the 4 species and found that tricolored bats and northern long-eared bats showed the most homogeneous and spatially smooth habitat suitability surfaces. Estimates of summer roost suitability developed here were also used to identify areas of good summer habitat where our models showed the least uncertainty that may be beneficial for targeted conservation, such as limiting disturbance to potential roost habitat. We also identified areas where additional data would benefit future summer roost modeling efforts. This work provides a first step toward developing multistate inventories of summer roost habitat suitable for implementing effective conservation planning at multiple scales.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyaf057","usgsCitation":"Inman, R.D., Schuhmann, A.N., Sawyer, S., Gaulke, S.M., Tousley, F.C., Davis, H.T., Udell, B.J., Straw, B., Reichard, J.D., and Reichert, B., 2025, Summer roost site suitability analyses for 4 special status bat species in the Eastern United States: Journal of Mammalogy, v. 106, no. 6, p. 1399-1411, https://doi.org/10.1093/jmammal/gyaf057.","productDescription":"13 p.","startPage":"1399","endPage":"1411","ipdsId":"IP-165519","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":498339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":953313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuhmann, Andrea Nichole 0009-0005-8244-4303","orcid":"https://orcid.org/0009-0005-8244-4303","contributorId":329059,"corporation":false,"usgs":true,"family":"Schuhmann","given":"Andrea","email":"","middleInitial":"Nichole","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sawyer, Sarah","contributorId":210922,"corporation":false,"usgs":false,"family":"Sawyer","given":"Sarah","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":953315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaulke, Sarah Mccrimmon 0000-0002-2657-5844","orcid":"https://orcid.org/0000-0002-2657-5844","contributorId":225564,"corporation":false,"usgs":true,"family":"Gaulke","given":"Sarah","email":"","middleInitial":"Mccrimmon","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":953316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tousley, Frank Charles 0000-0002-6859-7558","orcid":"https://orcid.org/0000-0002-6859-7558","contributorId":304216,"corporation":false,"usgs":true,"family":"Tousley","given":"Frank","middleInitial":"Charles","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Helen Trice 0000-0001-5449-4331","orcid":"https://orcid.org/0000-0001-5449-4331","contributorId":336752,"corporation":false,"usgs":true,"family":"Davis","given":"Helen","middleInitial":"Trice","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953318,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Udell, Bradley James 0000-0001-5225-4959","orcid":"https://orcid.org/0000-0001-5225-4959","contributorId":271174,"corporation":false,"usgs":true,"family":"Udell","given":"Bradley","email":"","middleInitial":"James","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953319,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Straw, Bethany R. 0000-0001-9086-4600","orcid":"https://orcid.org/0000-0001-9086-4600","contributorId":271020,"corporation":false,"usgs":true,"family":"Straw","given":"Bethany","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953320,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reichard, Jonathan D. 0000-0002-4792-2868","orcid":"https://orcid.org/0000-0002-4792-2868","contributorId":337073,"corporation":false,"usgs":false,"family":"Reichard","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":953321,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":953322,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70273772,"text":"70273772 - 2025 - VIPER site analysis","interactions":[],"lastModifiedDate":"2026-01-28T15:34:44.161644","indexId":"70273772","displayToPublicDate":"2025-10-14T08:12:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8607,"text":"The Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"VIPER site analysis","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>We needed to evaluate available orbital data of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) mission area in order to derive a variety of maps to help the science team identify scientifically interesting places for the rover to visit and to provide scientific context for our mission. Some of these maps also fulfilled engineering and mission design needs to enable safe and efficient landing and roving. We incorporated data from the Lunar Reconnaissance Orbiter Camera, the Lunar Orbital Laser Altimeter, the Mini-RF instrument, the Chandrayaan-2 Orbital High Resolution Camera, the Korean Pathfinder Lunar Orbiter’s Shadowcam, the Kaguya Spectral Profiler and Multiband Imager, and the Chandrayaan-1 Moon Mineralogy Mapper. We used a variety of techniques to build these maps, including stereogrammetry, shape-from-shading, ice stability depth and surface temperature calculations, and the horizon method for solar illumination and direct-to-Earth communications maps. Altogether, these maps allowed us to survey for boulders, evaluate features in permanently shadowed regions that VIPER might explore, provide mineralogic context for what VIPER’s instruments may learn, estimate the ages and radar properties of craters in the VIPER mission area, and evaluate the potential for gravity traverses with the rover. These data and techniques provided a rich set of information from which both the VIPER science team and engineering teams were able to draw in order to plan a safe landing and to plan a VIPER surface mission that will be both scientifically valuable and robust from an operational perspective.</span></span></p>","language":"English","publisher":"American Astronomical Society","doi":"10.3847/PSJ/ae061a","usgsCitation":"Beyer, R.A., Shirley, M., Colaprete, A., Fassett, C.I., Fernando, B., Himani, T.P., Lemelin, M., Martinez-Comacho, J., Siegler, M., Annex, A., Balaban, E., Bickel, V.T., Coyan, J.A., Deutsch, A.N., Heldmann, J.L., Hirabayashi, M., Keszthelyi, L.P., Lewis, K.W., Lim, D.S., and Dobrea, E., 2025, VIPER site analysis: The Planetary Science Journal, v. 6, 236, 18 p., https://doi.org/10.3847/PSJ/ae061a.","productDescription":"236, 18 p.","ipdsId":"IP-180642","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":499324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/ae061a","text":"Publisher Index Page"},{"id":499169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moon","volume":"6","noUsgsAuthors":false,"publicationDate":"2025-10-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Beyer, Ross A. 0000-0002-8450-7364","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":365744,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","middleInitial":"A.","affiliations":[{"id":87205,"text":"Sagan Center at SETI Institute","active":true,"usgs":false}],"preferred":false,"id":954716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shirley, Mark 0000-0001-8767-1760","orcid":"https://orcid.org/0000-0001-8767-1760","contributorId":354405,"corporation":false,"usgs":false,"family":"Shirley","given":"Mark","affiliations":[{"id":84625,"text":"SETI Institute/NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":954717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colaprete, Anthony 0000-0002-5847-2241","orcid":"https://orcid.org/0000-0002-5847-2241","contributorId":365745,"corporation":false,"usgs":false,"family":"Colaprete","given":"Anthony","affiliations":[{"id":87206,"text":"NASA Ames Research Center,","active":true,"usgs":false}],"preferred":false,"id":954718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fassett, Caleb I. 0000-0001-9155-3804","orcid":"https://orcid.org/0000-0001-9155-3804","contributorId":365746,"corporation":false,"usgs":false,"family":"Fassett","given":"Caleb","middleInitial":"I.","affiliations":[{"id":87207,"text":"3Applied Physics Lab, Johns Hopkins University,","active":true,"usgs":false}],"preferred":false,"id":954719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fernando, Benjamin 0000-0002-7321-8401","orcid":"https://orcid.org/0000-0002-7321-8401","contributorId":365747,"corporation":false,"usgs":false,"family":"Fernando","given":"Benjamin","affiliations":[{"id":87208,"text":"Dept. of Earth and Planetary Science, Johns Hopkins University,","active":true,"usgs":false}],"preferred":false,"id":954720,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Himani, Tanish P. 0000-0003-3029-5631","orcid":"https://orcid.org/0000-0003-3029-5631","contributorId":365748,"corporation":false,"usgs":false,"family":"Himani","given":"Tanish","middleInitial":"P.","affiliations":[{"id":87208,"text":"Dept. of Earth and Planetary Science, Johns Hopkins University,","active":true,"usgs":false}],"preferred":false,"id":954721,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lemelin, Myriam 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jcoyan@usgs.gov","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":197481,"corporation":false,"usgs":true,"family":"Coyan","given":"Joshua","email":"jcoyan@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":954728,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Deutsch, Ariel N. 0000-0001-9831-3619","orcid":"https://orcid.org/0000-0001-9831-3619","contributorId":365753,"corporation":false,"usgs":false,"family":"Deutsch","given":"Ariel","middleInitial":"N.","affiliations":[{"id":87212,"text":"Bay Area Environmental Research Institute, NASA Ames Research Center,","active":true,"usgs":false}],"preferred":false,"id":954729,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Heldmann, Jennifer L. 0000-0003-3397-1682","orcid":"https://orcid.org/0000-0003-3397-1682","contributorId":365754,"corporation":false,"usgs":false,"family":"Heldmann","given":"Jennifer","middleInitial":"L.","affiliations":[{"id":87206,"text":"NASA Ames Research Center,","active":true,"usgs":false}],"preferred":false,"id":954730,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hirabayashi, Masatoshi 0000-0002-1821-5689","orcid":"https://orcid.org/0000-0002-1821-5689","contributorId":365755,"corporation":false,"usgs":false,"family":"Hirabayashi","given":"Masatoshi","affiliations":[{"id":87213,"text":"Georgia Institute of Technology,","active":true,"usgs":false}],"preferred":false,"id":954731,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":227,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"laz@usgs.gov","middleInitial":"P.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":954732,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lewis, Kevin W. 0000-0003-3412-803X","orcid":"https://orcid.org/0000-0003-3412-803X","contributorId":365756,"corporation":false,"usgs":false,"family":"Lewis","given":"Kevin","middleInitial":"W.","affiliations":[{"id":87208,"text":"Dept. of Earth and Planetary Science, Johns Hopkins University,","active":true,"usgs":false}],"preferred":false,"id":954733,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Lim, Darlene S.S.","contributorId":365757,"corporation":false,"usgs":false,"family":"Lim","given":"Darlene","middleInitial":"S.S.","affiliations":[{"id":87206,"text":"NASA Ames Research Center,","active":true,"usgs":false}],"preferred":false,"id":954734,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Dobrea, Eldar Noe","contributorId":365758,"corporation":false,"usgs":false,"family":"Dobrea","given":"Eldar Noe","affiliations":[{"id":87214,"text":"6 Sagan Center at the SETI Institute, NASA Ames Research Center,","active":true,"usgs":false}],"preferred":false,"id":954735,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}}
,{"id":70272763,"text":"70272763 - 2025 - Genetic and environmental factors associated with survival of a rare songbird in a fragmented urban landscape","interactions":[],"lastModifiedDate":"2026-01-07T17:38:24.690661","indexId":"70272763","displayToPublicDate":"2025-10-08T08:07:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Genetic and environmental factors associated with survival of a rare songbird in a fragmented urban landscape","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>The coastal Cactus Wren (</span><i>Campylorhynchus brunneicapillus</i><span>) persists in small and fragmented populations throughout southern California that are subject to genetic drift and inbreeding. We combined individual banding and resighting data and genotyped individuals at 22 microsatellite loci to assess whether heterozygosity was associated with survival across three regional Cactus Wren populations on conserved lands in Orange and San Diego Counties between 2009 and 2020. Using Cormack-Jolly-Seber models (CJS) to analyze the 5-year capture histories of 528 individual wrens, we found that age class (hatch year or after hatch year) was the strongest predictor of survival. Individual heterozygosity and precipitation also had positive effects on survival, with survival up to 2 times higher in the most heterozygous individuals compared to the least and up to 1.5 times higher in high precipitation years versus drought years. Multi-locus heterozygosity was significantly correlated across loci, suggesting that inbreeding depression is likely driving the association between survival and heterozygosity. Study results support that genetic rescue efforts that reduce inbreeding have the potential to improve fitness and mitigate further loss of genetic variation in managed populations.</span></span></p>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.70155","usgsCitation":"Vandergast, A.G., Mitelberg, A., Kus, B.E., Preston, K.L., Lynn, S., Houston, A., and Klinger, R.C., 2025, Genetic and environmental factors associated with survival of a rare songbird in a fragmented urban landscape: Conservation Science and Practice, v. 7, no. 12, e70155, 14 p., https://doi.org/10.1111/csp2.70155.","productDescription":"e70155, 14 p.","ipdsId":"IP-180356","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497185,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":497395,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.70155","text":"Publisher Index Page"}],"country":"United States","state":"California","county":"Orange County, San Diego County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.45098240465302,\n              33.788832546013026\n            ],\n            [\n              -118.45098240465302,\n              32.58385755405139\n            ],\n            [\n              -116.21159447208314,\n              32.58385755405139\n            ],\n            [\n              -116.21159447208314,\n              33.788832546013026\n            ],\n            [\n              -118.45098240465302,\n              33.788832546013026\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"7","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitelberg, Anna 0000-0002-3309-9946 amitelberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3309-9946","contributorId":218945,"corporation":false,"usgs":true,"family":"Mitelberg","given":"Anna","email":"amitelberg@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":203745,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara","email":"barbara_kus@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Preston, Kristine L. 0000-0002-6958-1128 kpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-6958-1128","contributorId":207765,"corporation":false,"usgs":true,"family":"Preston","given":"Kristine","email":"kpreston@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynn, Suellen 0000-0003-1543-0209 suellen_lynn@usgs.gov","orcid":"https://orcid.org/0000-0003-1543-0209","contributorId":3843,"corporation":false,"usgs":true,"family":"Lynn","given":"Suellen","email":"suellen_lynn@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houston, Alexandra 0000-0002-8599-8265 ahouston@usgs.gov","orcid":"https://orcid.org/0000-0002-8599-8265","contributorId":139460,"corporation":false,"usgs":true,"family":"Houston","given":"Alexandra","email":"ahouston@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Klinger, Robert C.","contributorId":363410,"corporation":false,"usgs":false,"family":"Klinger","given":"Robert","middleInitial":"C.","affiliations":[{"id":17847,"text":"USGS-WERC","active":true,"usgs":false}],"preferred":false,"id":951641,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70272273,"text":"70272273 - 2025 - Estimating recruitment of Largemouth Bass to exceptional weights using angler-reported catches","interactions":[],"lastModifiedDate":"2026-01-22T16:30:03.333116","indexId":"70272273","displayToPublicDate":"2025-10-07T10:13:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating recruitment of Largemouth Bass to exceptional weights using angler-reported catches","docAbstract":"<h2 id=\"538412594\" class=\"abstract-title js-splitscreen-abstract-title\">ABSTRACT</h2><div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">Although most facets of Largemouth Bass<span>&nbsp;</span><i>Micropterus nigricans</i><span>&nbsp;</span>ecology have been researched, the upper tiers of weight distributions (i.e., ≥3.6 kg; herein, “lunkers”) have received little attention due to the challenges of collecting sufficient sample sizes. Our aim was to estimate Largemouth Bass recruitment to higher weights after reaching 3.6 kg and to identify factors correlated with such recruitment.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">We used an online database of angler-reported catches to investigate recruitment of Largemouth Bass after reaching lunker size and to identify associated factors. Recruitment was indexed by the slopes of the reversed cumulative counts relative to increasing weights, with gentler negative slopes indicating higher recruitment. The influence of environmental variables on these slopes identified the factors associated with recruitment.</p></div><div class=\" sec\"><div class=\"title\">Results</div><p class=\"chapter-para\">An average of 20% (minimum = 4%; maximum = 45%) of lunker bass were estimated to recruit after reaching 3.6 kg. When expanded, these estimates revealed that recruitment from 3.6 to 4.5 kg averaged 23.5% and recruitment from 3.6 to 5.9 kg averaged 2.5%. The observed recruitment was positively correlated with the frequency of Florida Bass<span>&nbsp;</span><i>M. salmoides</i><span>&nbsp;</span>alleles in the population and was inversely correlated with human population densities in the vicinity of the reservoir and with chlorophyll-<i>a</i><span>&nbsp;</span>concentrations in the environment.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">Recruitment of Largemouth Bass after reaching 3.6 kg appears to require a nuanced equilibrium enabled by a higher frequency of Florida Bass alleles, a remote location of the fishery, and a reservoir trophic state that balances adequate environmental conditions and food supply.</p></div>","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqaf082","usgsCitation":"Miranda, L.E., Griffin, F., Goldstrohm, N., Neal, J.W., and Lang, T.J., 2025, Estimating recruitment of Largemouth Bass to exceptional weights using angler-reported catches: North American Journal of Fisheries Management, v. 45, no. 6, p. 1001-1011, https://doi.org/10.1093/najfmt/vqaf082.","productDescription":"11 p.","startPage":"1001","endPage":"1011","ipdsId":"IP-173874","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496695,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffin, Frank","contributorId":360287,"corporation":false,"usgs":false,"family":"Griffin","given":"Frank","affiliations":[{"id":85992,"text":"University of Arkansas for Medical Sciences","active":true,"usgs":false}],"preferred":false,"id":950636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldstrohm, Natalie","contributorId":217292,"corporation":false,"usgs":false,"family":"Goldstrohm","given":"Natalie","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":950637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neal, J. Wesley","contributorId":360289,"corporation":false,"usgs":false,"family":"Neal","given":"J.","middleInitial":"Wesley","affiliations":[{"id":85993,"text":"Mississippi State","active":true,"usgs":false}],"preferred":false,"id":950638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lang, Thomas J.","contributorId":360290,"corporation":false,"usgs":false,"family":"Lang","given":"Thomas","middleInitial":"J.","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":950639,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273503,"text":"70273503 - 2025 - Near real-time indicators of burn severity in the western U.S. from active fire tracking","interactions":[],"lastModifiedDate":"2026-01-20T15:25:21.631459","indexId":"70273503","displayToPublicDate":"2025-10-07T08:18:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Near real-time indicators of burn severity in the western U.S. from active fire tracking","docAbstract":"<p>Background</p><p><span>Timely information on wildfire burn severity is critical to assess and mitigate potential post-fire impacts on soils, vegetation, and hillslope stability. Tracking individual fire spread and intensity using satellite active fire data provides a pathway to near real-time (NRT) information. Here, we generated a large database (</span><i>n</i><span> = 2177) of wildfire events in the western United States (U.S.) between 2012 and 2021 using active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Fire Events Data Suite (FEDS) algorithm to track large fire growth every 12&nbsp;h. We integrated fire tracking data with final fire perimeters and burn severity data from the Monitoring Trends in Burn Severity (MTBS) program to evaluate the relationship between burn severity and fire behavior metrics derived from the fire tracking approach, including the rate of fire spread and average fire radiative power (FRP) of fire detections for each 12-h growth increment.</span></p><p><span>Results</span></p><p><span>When stratified by vegetation type, FRP and rate of spread metrics were positively correlated with classified burn severity for each 12-h growth increment, highlighting the potential to rapidly identify areas of high and low severity burning. In forests, integrated measures of FRP over the fire lifetime captured persistent flaming and smoldering that compensated for initial differences between AM (01:30) and PM (13:30) fire detections. Predictive modeling of these relationships based on multiple fire behavior indicators and vegetation type from the LANDFIRE program yielded an accuracy of 78% for the separation of unburned/low and moderate/high burn severity classes.</span></p><p><span>Conclusions</span></p><p><span>These results demonstrate the ability to capture within-fire differences in burn severity using NRT indicators from fire tracking to assist with emergency management and disaster preparedness for post-fire hazards, such as landslides, debris flows, or changes in stream flow and water quality. As VIIRS data are available within minutes of each satellite overpass in the U.S., rapid estimates of burn severity based on fire tracking can be made days or weeks before a large wildfire is fully contained.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s42408-025-00407-x","usgsCitation":"Orland, E., McCabe, T., Chen, Y., Scholten, R.C., Becker, Z., Loehman, R.A., Randerson, J.T., Coffield, S.R., Liu, T., Shiklomanov, A.N., Nelson, K., Peterson, B., Follette-Cook, M.B., and Morton, D.C., 2025, Near real-time indicators of burn severity in the western U.S. from active fire tracking: Fire Ecology, v. 21, 55, 18 p., https://doi.org/10.1186/s42408-025-00407-x.","productDescription":"55, 18 p.","ipdsId":"IP-170216","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":498919,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-025-00407-x","text":"Publisher Index Page"},{"id":498774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.28023348660705,\n              49.14849222332691\n            ],\n            [\n              -124.28023348660705,\n              31.366087454025504\n            ],\n            [\n              -101.57330654663889,\n              31.366087454025504\n            ],\n            [\n              -101.57330654663889,\n              49.14849222332691\n            ],\n            [\n              -124.28023348660705,\n              49.14849222332691\n            ]\n          ]\n        ],\n 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0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":954036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Randerson, James T. 0000-0001-6559-7387","orcid":"https://orcid.org/0000-0001-6559-7387","contributorId":365278,"corporation":false,"usgs":false,"family":"Randerson","given":"James","middleInitial":"T.","affiliations":[{"id":87119,"text":"Univ California Irvine","active":true,"usgs":false}],"preferred":false,"id":954037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coffield, Shane R. 0000-0002-0550-5126","orcid":"https://orcid.org/0000-0002-0550-5126","contributorId":365279,"corporation":false,"usgs":false,"family":"Coffield","given":"Shane","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954038,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Tianjia 0000-0003-3129-0154","orcid":"https://orcid.org/0000-0003-3129-0154","contributorId":365280,"corporation":false,"usgs":false,"family":"Liu","given":"Tianjia","affiliations":[{"id":52230,"text":"University of British Columbia, Vancouver, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":954039,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shiklomanov, Alexey N. 0000-0003-4022-5979","orcid":"https://orcid.org/0000-0003-4022-5979","contributorId":245541,"corporation":false,"usgs":false,"family":"Shiklomanov","given":"Alexey","email":"","middleInitial":"N.","affiliations":[{"id":49218,"text":"Boston University Department of Earth and Environment","active":true,"usgs":false}],"preferred":false,"id":954040,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":954041,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":954042,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Follette-Cook, Melanie B. 0000-0002-5648-584X","orcid":"https://orcid.org/0000-0002-5648-584X","contributorId":365282,"corporation":false,"usgs":false,"family":"Follette-Cook","given":"Melanie","middleInitial":"B.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954043,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Morton, Douglas C.","contributorId":225139,"corporation":false,"usgs":false,"family":"Morton","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":954044,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70274600,"text":"70274600 - 2025 - Ambient field seismology in critical zone hydrological sciences","interactions":[],"lastModifiedDate":"2026-04-01T15:12:52.682494","indexId":"70274600","displayToPublicDate":"2025-10-06T10:07:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23777,"text":"Comptes Rendus. Géoscience","active":true,"publicationSubtype":{"id":10}},"title":"Ambient field seismology in critical zone hydrological sciences","docAbstract":"<p><span>Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.</span></p>","language":"English","publisher":"Academie des Sciences, Institut de France","doi":"10.5802/crgeos.310","usgsCitation":"Denolle, M.A., Shi, Q., Clements, T., Viens, L., Rodriguez-Tribaldos, V., and Cotton, F., 2025, Ambient field seismology in critical zone hydrological sciences: Comptes Rendus. Géoscience, v. 357, p. 425-451, https://doi.org/10.5802/crgeos.310.","productDescription":"27 p.","startPage":"425","endPage":"451","ipdsId":"IP-181097","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":502104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5802/crgeos.310","text":"Publisher Index Page"},{"id":501930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"357","noUsgsAuthors":false,"publicationDate":"2025-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Denolle, Marine A.","contributorId":345689,"corporation":false,"usgs":false,"family":"Denolle","given":"Marine","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":958469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Qibin","contributorId":369115,"corporation":false,"usgs":false,"family":"Shi","given":"Qibin","affiliations":[{"id":49969,"text":"Department of Earth and Space Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":958470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clements, Timothy Hugh 0000-0001-6632-1796","orcid":"https://orcid.org/0000-0001-6632-1796","contributorId":350753,"corporation":false,"usgs":true,"family":"Clements","given":"Timothy Hugh","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":958471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viens, Loic","contributorId":362345,"corporation":false,"usgs":false,"family":"Viens","given":"Loic","affiliations":[{"id":48588,"text":"Los Alamos National Lab","active":true,"usgs":false}],"preferred":false,"id":958472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez-Tribaldos, Veronica","contributorId":369117,"corporation":false,"usgs":false,"family":"Rodriguez-Tribaldos","given":"Veronica","affiliations":[{"id":87725,"text":"GFZ Helmholtz Centre for Geosciences, Telegrafenberg 14473 Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":958473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cotton, Fabrice","contributorId":264167,"corporation":false,"usgs":false,"family":"Cotton","given":"Fabrice","email":"","affiliations":[],"preferred":false,"id":958474,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70273139,"text":"70273139 - 2025 - Assessing flood water infiltration and storage in a restored floodplain","interactions":[],"lastModifiedDate":"2025-12-16T15:30:48.761523","indexId":"70273139","displayToPublicDate":"2025-10-05T09:20:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23098,"text":"Hydological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Assessing flood water infiltration and storage in a restored floodplain","docAbstract":"<p><span>In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70281","usgsCitation":"Corson-Dosch, N., Fitzpatrick, F., Juckem, P., Blount, J.D., and Ha, W.S., 2025, Assessing flood water infiltration and storage in a restored floodplain: Hydological Processes, v. 39, no. 10, e70281, 18 p., https://doi.org/10.1002/hyp.70281.","productDescription":"e70281, 18 p.","ipdsId":"IP-141807","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70281","text":"Publisher Index Page"},{"id":497570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Underwood Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.047778,\n              43.047222\n            ],\n            [\n              -88.047778,\n              43.0375\n            ],\n            [\n              -88.043333,\n              43.0375\n            ],\n            [\n              -88.043333,\n              43.047222\n            ],\n            [\n              -88.047778,\n              43.047222\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"39","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Corson-Dosch, Nicholas 0000-0002-6776-6241","orcid":"https://orcid.org/0000-0002-6776-6241","contributorId":202630,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Nicholas","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209588,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juckem, Paul 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":214445,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ha, Wonsook S. 0000-0002-7252-698X","orcid":"https://orcid.org/0000-0002-7252-698X","contributorId":266139,"corporation":false,"usgs":true,"family":"Ha","given":"Wonsook","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952432,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273513,"text":"70273513 - 2025 - Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks","interactions":[],"lastModifiedDate":"2026-01-22T14:31:14.015253","indexId":"70273513","displayToPublicDate":"2025-10-05T07:43:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks","docAbstract":"<p>Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly<sup>TM</sup> program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes &lt;24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in &lt;15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.</p>","language":"English","publisher":"OJS/PKP","doi":"10.30909/vol/gsfc1696","usgsCitation":"Halverson, B.A., Loewen, M.W., Dietterich, H., and Whittington, A., 2025, Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks: Volcanica, v. 8, no. 2, p. 427-443, https://doi.org/10.30909/vol/gsfc1696.","productDescription":"17 p.","startPage":"427","endPage":"443","ipdsId":"IP-168707","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":498931,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol/gsfc1696","text":"Publisher Index Page"},{"id":498793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -169.2081935551017,\n              55.01025512098417\n            ],\n            [\n              -169.2081935551017,\n              53.07434331835552\n            ],\n            [\n              -165.56066240589334,\n              53.07434331835552\n            ],\n            [\n              -165.56066240589334,\n              55.01025512098417\n            ],\n            [\n              -169.2081935551017,\n              55.01025512098417\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Halverson, Brenna A. 0009-0009-7766-7384","orcid":"https://orcid.org/0009-0009-7766-7384","contributorId":365304,"corporation":false,"usgs":false,"family":"Halverson","given":"Brenna","middleInitial":"A.","affiliations":[{"id":87127,"text":"University of Texas San Antonio","active":true,"usgs":false}],"preferred":false,"id":954099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":954101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whittington, Alan 0000-0003-2477-3043","orcid":"https://orcid.org/0000-0003-2477-3043","contributorId":365305,"corporation":false,"usgs":false,"family":"Whittington","given":"Alan","affiliations":[{"id":87127,"text":"University of Texas San Antonio","active":true,"usgs":false}],"preferred":false,"id":954102,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272077,"text":"70272077 - 2025 - Magma fragmentation and tephra deposition from a small-volume phreatomagmatic eruption: Blue Lake crater, Oregon, USA","interactions":[],"lastModifiedDate":"2025-11-14T16:06:29.946987","indexId":"70272077","displayToPublicDate":"2025-10-03T08:46:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Magma fragmentation and tephra deposition from a small-volume phreatomagmatic eruption: Blue Lake crater, Oregon, USA","docAbstract":"<p><span>Maars pose considerable hazards due to their more explosive nature (compared with more common scoria cones) and likelihood that eruptions produce pyroclastic surges. Blue Lake crater is a maar in the Oregon High Cascades that erupted within the last 3000&nbsp;years, making it one of the youngest eruptions in the Oregon Cascades. Its young, unaltered deposits make it an excellent site to examine the relationship between fragmentation processes and ash characteristics. This paper presents an extensive data set of grain size, componentry, texture, particle morphology, and surface features for 23 samples from 17 layers from Blue Lake crater to better understand fragmentation style and eruptive dynamics over the course of the eruption. We present detailed stratigraphy from 22 tephra pits and analyze tephra samples following a standardized method. An improved isopach map and a new isopleth map show the extensive, ENE-trending fallout and surge deposits. Based on the tephra sheet, the eruption can be divided into three phases, starting with a phreatomagmatic phase that produced laterally extensive, lithic-rich fallout deposits and excavated the initial crater. The middle phase of the eruption produced phreatomagmatically fragmented intercalated fallout and surge deposits. The eruption closed with coarse grained fallout deposits with a declining lithic content, indicating a shift towards a hybrid or phreato-Strombolian style. This detailed examination of the deposits leads to a more nuanced explanation of the eruption and fragmentation dynamics, which contribute to a better understanding of maar eruption processes and hazards.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01857-6","usgsCitation":"Leiter, S., Ross, P., and Johnson, E.R., 2025, Magma fragmentation and tephra deposition from a small-volume phreatomagmatic eruption: Blue Lake crater, Oregon, USA: Bulletin of Volcanology, no. 87, 92, 27 p., https://doi.org/10.1007/s00445-025-01857-6.","productDescription":"92, 27 p.","ipdsId":"IP-175655","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Blue Lake crater","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.87499438259134,\n              44.522898198963645\n            ],\n            [\n              -121.87499438259134,\n              44.51967210758181\n            ],\n            [\n              -121.87067741535604,\n              44.51967210758181\n            ],\n            [\n              -121.87067741535604,\n              44.522898198963645\n            ],\n            [\n              -121.87499438259134,\n              44.522898198963645\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","issue":"87","noUsgsAuthors":false,"publicationDate":"2025-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Leiter, Sophia","contributorId":362099,"corporation":false,"usgs":false,"family":"Leiter","given":"Sophia","affiliations":[{"id":86462,"text":"Eau Terre Environnement Research Centre","active":true,"usgs":false}],"preferred":false,"id":950000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Pierre-Simon","contributorId":362100,"corporation":false,"usgs":false,"family":"Ross","given":"Pierre-Simon","affiliations":[{"id":86462,"text":"Eau Terre Environnement Research Centre","active":true,"usgs":false}],"preferred":false,"id":950001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Emily Renee 0000-0002-7967-6913","orcid":"https://orcid.org/0000-0002-7967-6913","contributorId":269628,"corporation":false,"usgs":true,"family":"Johnson","given":"Emily","email":"","middleInitial":"Renee","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950002,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272967,"text":"70272967 - 2025 - UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape","interactions":[],"lastModifiedDate":"2025-12-11T14:57:10.87794","indexId":"70272967","displayToPublicDate":"2025-10-03T07:48:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape","docAbstract":"<p>Context</p><p><span>Cheatgrass (</span><i>Bromus tectorum</i><span>&nbsp;L.) is a problem across the western United States, where it outcompetes and replaces native grass species, alters habitats, and increases the risk of wildfires. Cheatgrass greens up earlier in the growing season compared to native grasses, making it classifiable with multi-temporal and multi-spectral remote sensing.</span></p><p><span>Objectives</span></p><p><span>We mapped cheatgrass at different scales in the Greater Yellowstone Ecosystem using 10-m Sentinel-2 imagery, 3-m PlanetScope, and 10-cm Uncrewed Aerial Systems (UAS) imagery. We compared these maps to field-collected data to address 1) variation in seasonal phenological signals of native and cheatgrass patches, 2) the influence of scale on detectability and map accuracy across our study area.</span></p><p><span>Results</span></p><p><span>Model accuracy to predict cheatgrass presence increased with imagery resolution and ranged from 83% using 10-m Sentinel-2 to 94% with the integration of PlanetScope and UAS imagery. While there was spatial agreement across models, the fusion of UAS data with satellite sources allowed the detection of small cheatgrass with more precision. Our novel use of NExR and dNExR (a redness and differenced redness index) data in the classification of cheatgrass capitalizes on the senescence of cheatgrass during peak summer periods where cloud free imagery is more prevalent.</span></p><p><span>Conclusions</span></p><p><span>Our satellite and UAS-based models of cheatgrass prediction compare the fusion of very high resolution imagery and phenological time differencing to identify infested areas. Tradeoffs between accuracy and expense lead to important questions for management applications.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s10980-025-02200-2","usgsCitation":"Kreitler, J.R., Von Nonn, J.W., Munson, S.M., Zaideman, A.C., Bekedam, S.T., Rodman, A., and Villarreal, M., 2025, UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape: Landscape Ecology, v. 40, 189, 17 p., https://doi.org/10.1007/s10980-025-02200-2.","productDescription":"189, 17 p.","ipdsId":"IP-171263","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":497380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02200-2","text":"Publisher Index Page"},{"id":497321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","city":"Gardiner","otherGeospatial":"northern gate to Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.74822627648368,\n              45.036818856935014\n            ],\n            [\n              -110.74822627648368,\n              44.9980588003821\n            ],\n            [\n              -110.6517700780241,\n              44.9980588003821\n            ],\n            [\n              -110.6517700780241,\n              45.036818856935014\n            ],\n            [\n              -110.74822627648368,\n              45.036818856935014\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2025-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Kreitler, Jason R. 0000-0002-0243-5281 jkreitler@usgs.gov","orcid":"https://orcid.org/0000-0002-0243-5281","contributorId":4050,"corporation":false,"usgs":true,"family":"Kreitler","given":"Jason","email":"jkreitler@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Von Nonn, Joshua W. 0009-0003-7251-7308","orcid":"https://orcid.org/0009-0003-7251-7308","contributorId":332293,"corporation":false,"usgs":true,"family":"Von Nonn","given":"Joshua","email":"","middleInitial":"W.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":951918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zaideman, Alex C.","contributorId":363745,"corporation":false,"usgs":false,"family":"Zaideman","given":"Alex","middleInitial":"C.","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":951919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bekedam, Steven T.","contributorId":363746,"corporation":false,"usgs":false,"family":"Bekedam","given":"Steven","middleInitial":"T.","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":951920,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodman, Ann","contributorId":150932,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":951921,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":214980,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951922,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70272669,"text":"70272669 - 2025 - Monitoring Pacific walrus coastal haulouts by satellite to estimate herd abundance and distribution","interactions":[],"lastModifiedDate":"2026-01-07T17:33:27.413096","indexId":"70272669","displayToPublicDate":"2025-10-02T10:23:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring Pacific walrus coastal haulouts by satellite to estimate herd abundance and distribution","docAbstract":"<p><span>The Pacific walrus (</span><i>Odobenus rosmarus divergens</i><span>) has a single, panmictic stock that ranges across the Bering and Chukchi Seas. However, its seasonal distribution is incompletely described, particularly in autumn when herds gather on shore, and abundance is of interest to management entities. We monitored walrus herds using satellite imagery on shore across their summer and autumn range in the Chukchi Sea to provide insights on seasonal distribution and abundance. During each study year (2017–2024), we documented walrus herd abundance at 8 Chukchi Sea haulouts based on the herd area detected in satellite imagery multiplied by herd density estimates derived from aerial survey data. In contrast to historical seasonal use, we found large herds on shore at only 3 sites, 1 in Alaska and 2 in northern Chukotka (Russia). In 2022, we observed a very large herd with an abundance (and 90% prediction interval) of 184,000 (min–max = 153,000–214,000) northwest of the Bering Strait, which enabled us to estimate a minimum population size (N</span><sub>min</sub><span>) by correcting the abundance estimate by the proportion of walruses that may be hauled out and available for detection. Our estimate of 250,000 was commensurate with the N</span><sub>min</sub><span>&nbsp;estimate (214,000) from a 2013–2017 Pacific walrus genetic mark-recapture study.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1614","usgsCitation":"Fischbach, A., Taylor, R.L., and Douglas, D., 2025, Monitoring Pacific walrus coastal haulouts by satellite to estimate herd abundance and distribution: Wildlife Society Bulletin, v. 49, no. 4, e1614, 15 p., https://doi.org/10.1002/wsb.1614.","productDescription":"e1614, 15 p.","ipdsId":"IP-177020","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":497118,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1614","text":"Publisher Index Page"},{"id":497014,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Chukchi Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.93329442452998,\n              71.88906251809732\n            ],\n            [\n              -179.83432013170355,\n              67.84896545701015\n            ],\n            [\n              -173.47189614919742,\n              65.81108912941576\n            ],\n            [\n              -169.36873613536477,\n              65.64307141045649\n            ],\n            [\n              -162.35050637387656,\n              66.07780618690225\n            ],\n            [\n              -159.94513066611069,\n              70.71050879067744\n            ],\n            [\n              -179.93329442452998,\n              71.88906251809732\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              177.62607489674906,\n              72.2560194763146\n            ],\n            [\n              177.62607489674906,\n              68.47301701440111\n            ],\n            [\n              179.9,\n              68.47301701440111\n            ],\n            [\n              179.9,\n              72.2560194763146\n            ],\n            [\n              177.62607489674906,\n              72.2560194763146\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":951274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":951275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":951276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70274044,"text":"70274044 - 2025 - Fitness consequences of catastrophic wildfire are mitigated by behavioral responses of an iconic bird","interactions":[],"lastModifiedDate":"2026-02-24T15:02:57.568821","indexId":"70274044","displayToPublicDate":"2025-10-01T10:07:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fitness consequences of catastrophic wildfire are mitigated by behavioral responses of an iconic bird","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Drought, human disturbance, and invasive species are reshaping disturbance regimes and increasing the scale, severity, and frequency of wildfire in many ecosystems around the globe, including the sagebrush steppe of western North America. Recent studies suggested greater sage-grouse (<i>Centrocercus urophasianus</i>) adhere to strong site fidelity in the aftermath of wildfire, remaining inside fire perimeters for nesting and brood rearing despite negative consequences for survival and reproduction. Sage-grouse in Idaho exhibited context-dependent changes to space use after a large, high-severity fire that burned &gt; 40,000&nbsp;ha, yet the specific behavioral responses to fire and their fitness consequences remain unclear. We used data collected from 269 hens over a 6-year period under a multi-level before-after-control-impact design to test the hypothesis that sage-grouse mitigated fitness consequences of high-severity wildfire through adaptive behavioral responses and spatial redistribution.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>We tested predictions deduced from our hypothesis at the population and individual levels using behavioral, demographic, and life history data, including nesting metrics, brood-rearing metrics, hen survival, and body mass at capture. Fifteen of 16 predictions were supported, demonstrating that post-fire space use and avoidance of the burn was adaptive and helped mitigate fitness effects of the fire. Short-term consequences included elimination of nesting and brood rearing habitat and subsequent shifts to the distribution of usable space. Yet fitness consequences were minimal because of behavioral flexibility employed by hens during nesting and brood rearing.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Behavioral responses to wildfire by sage-grouse are more flexible than has been described, and sage-grouse demonstrated resilience by rapidly adapting space use to avoid short-term consequences of catastrophic fire when high-quality habitat remained adjacent to the burn and within their seasonal range. Our results imply behavioral and fitness consequences of fire are context-dependent and likely impacted by attributes of the fire and surrounding landscape after disturbance. Furthermore, among-study differences in behavioral and fitness outcomes of sage-grouse after fire supported underappreciated predictions from both fire ecology and site fidelity theory, and suggest conditions where behavioral flexibility should be expressed, and fidelity relaxed, based on severity of disturbance, landscape context, and species mobility.</p>","language":"English","publisher":"Springer","doi":"10.1186/s42408-025-00391-2","usgsCitation":"Stevens, B.S., Conway, C.J., Roberts, S.B., Englestead, D.K., 2025, Fitness consequences of catastrophic wildfire are mitigated by behavioral responses of an iconic bird: Fire Ecology, v. 21, 54, 26 p., https://doi.org/10.1186/s42408-025-00391-2.","productDescription":"54, 26 p.","ipdsId":"IP-169334","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500603,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-025-00391-2","text":"Publisher Index Page"},{"id":500413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","volume":"21","noUsgsAuthors":false,"publicationDate":"2025-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":171809,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":956282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane B.","contributorId":338986,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","email":"","middleInitial":"B.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":956284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Englestead, Devin K.","contributorId":366830,"corporation":false,"usgs":false,"family":"Englestead","given":"Devin","middleInitial":"K.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":956285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272182,"text":"70272182 - 2025 - One hundred ninety-nine dead birds: Review of the scientific basis of ecological incident reporting requirements for pesticide registrants under Fifra § 6(A)(2)","interactions":[],"lastModifiedDate":"2025-11-18T15:41:36.861691","indexId":"70272182","displayToPublicDate":"2025-10-01T09:37:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1088,"text":"Buffalo Environmental Law Journal","active":true,"publicationSubtype":{"id":10}},"title":"One hundred ninety-nine dead birds: Review of the scientific basis of ecological incident reporting requirements for pesticide registrants under Fifra § 6(A)(2)","docAbstract":"<p>The U.S. Environmental Protection Agency (EPA) regulates pesticide use in the United States. The EPA is charged by the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) with ensuring that a pesticide will not cause unreasonable adverse effects on the environment. Incident reports (documentation of exposure and injury from pesticide applications) can serve as a reality check on the pesticide registration decisions made by the EPA scientists and risk managers. The EPA collects incident reports on human, domestic animal, and ecological injury. The FIFRA section 6(a)(2) rule requires the pesticide registrant (generally, the company or other entity that wishes to market the pesticide, hereafter registrant) to submit such data to the EPA. </p><p>The EPA’s ecological incident category includes injuries to aquatic (fish), terrestrial (wildlife), other non-target organisms (ONT, e.g., invertebrates) and plants. Our document focuses on the fish and wildlife ecological incidents that are submitted by registrants. We critique the application of the FIFRA section 6(a)(2) rule that controls the quality and quantity of ecological incident data that the EPA receives from registrants. We conclude that the section 6(a)(2) provisions can impede the transfer of ecological incident data from registrant to the EPA. Consequently, detailed data for many fish and wildlife incidents may never reach the EPA, and policies and decisions may be formulated in the absence of these data.</p>","language":"English","publisher":"University at Buffalo School of Law","usgsCitation":"Vyas, N.B., and Palmer, C., 2025, One hundred ninety-nine dead birds: Review of the scientific basis of ecological incident reporting requirements for pesticide registrants under Fifra § 6(A)(2): Buffalo Environmental Law Journal, v. 31, 63 p.","productDescription":"63 p.","ipdsId":"IP-154414","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496572,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.law.buffalo.edu/belj/vol31/iss1/","linkFileType":{"id":5,"text":"html"}}],"volume":"31","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vyas, Nimish B. 0000-0003-0191-1319 nvyas@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-1319","contributorId":4494,"corporation":false,"usgs":true,"family":"Vyas","given":"Nimish","email":"nvyas@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Cynthia","contributorId":362357,"corporation":false,"usgs":false,"family":"Palmer","given":"Cynthia","affiliations":[{"id":86509,"text":"Moms Clean Air Force, c/o Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":950359,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70272235,"text":"70272235 - 2025 - A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters","interactions":[],"lastModifiedDate":"2025-11-19T15:10:27.951072","indexId":"70272235","displayToPublicDate":"2025-10-01T09:02:45","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters","docAbstract":"<p><span>Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.</span></p>","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.09.29.679270","usgsCitation":"Murphy, J.C., Gorney, R.M., Lucas, L., Zwart, J.A., and Graham, J.L., 2025, A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters: BioRxiv, https://doi.org/10.1101/2025.09.29.679270.","productDescription":"52 p.","ipdsId":"IP-179513","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":496741,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.09.29.679270","text":"External Repository"},{"id":496628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca Michelle 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","email":"","middleInitial":"Michelle","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Lisa 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","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":950536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":950537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":202923,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":950538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70273159,"text":"70273159 - 2025 - Texas coastal wetland surface elevation static survey campaign report","interactions":[],"lastModifiedDate":"2025-12-17T14:50:42.729443","indexId":"70273159","displayToPublicDate":"2025-10-01T08:44:18","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Texas coastal wetland surface elevation static survey campaign report","docAbstract":"<p>Surface elevation data along the Texas Coast is limited, despite having some of the highest rates of relative sea-level rise in the country (Sweet et al., 2022). To narrow these knowledge and data gaps, the U.S. Fish and Wildlife Service (USFWS) established the first landscape-scale rod surface elevation table (RSET) monitoring project aimed at examining surface elevation dynamics of coastal marshes in Texas (Moon et al., 2022). The project, conducted cooperatively between the USFWS and the U.S. Geological Survey (USGS), has focused on 14 coastal marsh sites located within five National Wildlife Refuges (Figure 1). The main objective of this project’s RSET data collection is to quantify the impacts of sea-level rise on coastal properties owned by the USFWS and similar surrounding areas. Data from RSETs will be used to determine areas that are at the greatest risk for potential habitat loss and degradation by examining subsidence and accretion rates. However, for the RSET data to be tied into the national vertical datum of 1988 (NAVD88) and, therefore, linked to the relative sea-level change calculations, it is necessary to establish primary vertical control at each study site through highly accurate and precise global navigation satellite systems (GNSS) surveys. Having a clear methodology for standardization is important for quality data. This report focuses on the methods, with particular emphasis on post-processing, used to survey benchmarks for the RSET data collection along the Texas Coast for the USFWS. &nbsp;Furthermore, this report serves as a general reference guide on the technical aspects of performing and processing GNSS surveys within the Texas coastal refuges to maintain quality and consistency.&nbsp;</p>","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Patton, B., Sanspree, C.R., Moon, J.A., and Moran, S.R., 2025, Texas coastal wetland surface elevation static survey campaign report, 17 p.","productDescription":"17 p.","ipdsId":"IP-180807","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":497625,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iris.fws.gov/APPS/ServCat/Reference/Profile/187715"}],"country":"United States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97,\n              30\n            ],\n            [\n              -97,\n              28\n            ],\n            [\n              -94,\n              28\n            ],\n            [\n              -94,\n              30\n            ],\n            [\n              -97,\n              30\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Patton, Brett 0000-0002-7396-3452 pattonb@usgs.gov","orcid":"https://orcid.org/0000-0002-7396-3452","contributorId":5458,"corporation":false,"usgs":true,"family":"Patton","given":"Brett","email":"pattonb@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":952534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanspree, Colt R. 0000-0001-9794-5008","orcid":"https://orcid.org/0000-0001-9794-5008","contributorId":360902,"corporation":false,"usgs":false,"family":"Sanspree","given":"Colt","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":952535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moon, Jena A. 0000-0001-5141-2281","orcid":"https://orcid.org/0000-0001-5141-2281","contributorId":360893,"corporation":false,"usgs":false,"family":"Moon","given":"Jena","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":952536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moran, Sierra R. 0009-0001-4354-4345","orcid":"https://orcid.org/0009-0001-4354-4345","contributorId":360688,"corporation":false,"usgs":false,"family":"Moran","given":"Sierra","middleInitial":"R.","affiliations":[{"id":78526,"text":"Student Services Contractor","active":true,"usgs":false}],"preferred":false,"id":952537,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70272015,"text":"sir20255080 - 2025 - Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018","interactions":[],"lastModifiedDate":"2026-02-03T16:24:50.121719","indexId":"sir20255080","displayToPublicDate":"2025-09-30T16:45:00","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":"2025-5080","displayTitle":"Potentiometric Surface Maps and Groundwater-Level Hydrographs for Confined Aquifers of the New Jersey Coastal Plain, 2018","title":"Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection (NJDEP), prepared potentiometric surface maps for 10 confined aquifers of the New Jersey Coastal Plain physiographic province based on water-level measurements collected during late 2018 and early 2019 from 951 wells in New Jersey and parts of Pennsylvania and Delaware. Maps were prepared for the confined Cohansey aquifer, Rio Grande water-bearing zone, Atlantic City 800-foot sand, Piney Point aquifer, Vincentown aquifer, Wenonah-Mount Laurel aquifer, Englishtown aquifer system, and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy aquifer system.</p><p>Potentiometric surface maps indicate regional cones of depression in the following aquifers and the counties in which they are centered: Atlantic City 800-foot sand in Atlantic County, the Piney Point aquifer in Cumberland County, the Wenonah-Mount Laurel aquifer and Englishtown aquifer system in Monmouth and Ocean Counties, the Wenonah-Mount Laurel aquifer in Camden and Gloucester County, the upper aquifer of the Potomac-Raritan-Magothy aquifer system in Ocean County, and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy aquifer system in Camden County. Cones of depression with smaller areal extents were in the confined Cohansey aquifer, the Rio Grande water-bearing zone, the Atlantic City 800-foot sand centered in Cape May County, the Piney Point aquifer centered in Ocean County, the Wenonah-Mount Laurel aquifer in Salem and Burlington Counties, the Englishtown aquifer system in Camden County, the upper aquifer of the Potomac-Raritan-Magothy aquifer system in Monmouth County, and the middle aquifer of the Potomac-Raritan-Magothy aquifer system in Monmouth, Ocean, and Salem Counties. No cone of depression was interpreted in the Vincentown aquifer.</p><p>Long-term hydrographs are presented for 75 wells spanning each of the 10 confined aquifers, and contain a mix of discrete water-level measurements and daily mean water levels based on continuously recorded 15-minute data. Changes of water levels during 2014–19, as indicated by the hydrographs, were compared with those of previous periods to assess any departures from historical data. During 2014–19, water levels were stable and fluctuated within similar ranges as previous periods in the following aquifers and locations: all wells in the confined Cohansey aquifer, the Rio Grande water-bearing zone, the Vincentown aquifer, the Englishtown aquifer system, the Piney Point aquifer wells in Burlington and Ocean Counties, six of eight wells in the Wenonah-Mount Laurel aquifer, all wells in the upper and lower aquifers of the Potomac-Raritan-Magothy aquifer system outside NJDEP Critical Areas, and all wells in the middle aquifer of the Potomac-Raritan-Magothy aquifer system except those within NJDEP Critical Area II. Increasing water levels in 2014–19, ongoing since historical periods, were indicated in the following aquifers and locations: Atlantic County wells in the Piney Point aquifer, all wells in the upper and lower aquifers of the Potomac-Raritan-Magothy aquifer system outside NJDEP Critical Areas, and all wells in the middle aquifer of the Potomac-Raritan-Magothy aquifer system within NJDEP Critical Area II. Water levels in the Atlantic City 800-foot sand also increased during 2014–19 in wells in Atlantic County and northern Cape May County closer to the center of the cone of depression in that aquifer, which is a response unique to this period and absent from previous periods. During 2013–19, continued decreasing water levels, ongoing since previous periods, were indicated by hydrographs of Atlantic City 800-foot sand wells in southern Cape May County, Piney Point aquifer wells in Cumberland County where the regional cone of depression is located, and two wells in the Wenonah-Mount Laurel aquifer—070478, which in 2014–19 departed from previous periods, and 330020, which continued a gradual decrease throughout its period of record.</p>","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255080","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Fiore, A.R., Cauller, S.J., and Brown, E.J., 2025, Potentiometric surface maps and groundwater-level hydrographs for confined aquifers of the New Jersey Coastal Plain, 2018: U.S. Geological Survey Scientific Investigations Report 2025–5080, 37 p., 9 pls., https://doi.org/10.3133/sir20255080.","productDescription":"Report: viii, 37 p.; 9 Plates: 19.50 x 26.50 inches; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158226","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":496280,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AT8Z9B","text":"USGS data release","linkHelpText":"Geospatial data representing wells open to, and 2018 potentiometric surface contours of, the confined aquifers of the New Jersey Coastal Plain"},{"id":496298,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080_plates.pdf","text":"Plates 1–9","size":"69.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":496277,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5080 HTML"},{"id":496276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080.pdf","text":"Report","size":"5.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5080 PDF"},{"id":496279,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5080/images/"},{"id":496275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5080/coverthb.jpg"},{"id":496278,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5080/sir20255080.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5080 XML"},{"id":497788,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118951.htm"}],"country":"United States","state":"New Jersey","otherGeospatial":"Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.86248123191035,\n              40.48417444667285\n            ],\n            [\n              -74.37454480427728,\n              40.52176772292319\n            ],\n            [\n              -74.76300682469329,\n              40.185368171011504\n            ],\n            [\n              -75.09849675141594,\n              39.98542938463885\n            ],\n            [\n              -75.2574130324954,\n              39.85000334106027\n            ],\n            [\n              -75.46223846144186,\n              39.77133356243843\n            ],\n            [\n              -75.58230854047962,\n              39.61100346658509\n            ],\n            [\n              -75.5363993926121,\n              39.43666527993781\n            ],\n            [\n              -74.85835659334042,\n              38.83679593629347\n            ],\n            [\n           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Aquifer of the Potomac-Raritan-Magothy Aquifer System</li><li>Middle and Undifferentiated Aquifers of the Potomac-Raritan-Magothy Aquifer System</li><li>Lower Aquifer of the Potomac-Raritan-Magothy Aquifer System</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2025-09-30","noUsgsAuthors":false,"publicationDate":"2025-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Fiore, Alex R. 0000-0002-0986-5225 afiore@usgs.gov","orcid":"https://orcid.org/0000-0002-0986-5225","contributorId":4977,"corporation":false,"usgs":true,"family":"Fiore","given":"Alex","email":"afiore@usgs.gov","middleInitial":"R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cauller, Stephen J. 0000-0002-1823-8813 sjcaulle@usgs.gov","orcid":"https://orcid.org/0000-0002-1823-8813","contributorId":199484,"corporation":false,"usgs":true,"family":"Cauller","given":"Stephen","email":"sjcaulle@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":949731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Eileen J. 0000-0003-3417-0203 ejbrown@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-0203","contributorId":361968,"corporation":false,"usgs":true,"family":"Brown","given":"Eileen","email":"ejbrown@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949732,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70272016,"text":"tm2A22 - 2025 - Long Term Resource Monitoring procedures—Aquatic vegetation monitoring","interactions":[],"lastModifiedDate":"2026-02-03T16:24:07.215237","indexId":"tm2A22","displayToPublicDate":"2025-09-30T14:48:28","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-A22","displayTitle":"Long Term Resource Monitoring Procedures—Aquatic Vegetation Monitoring","title":"Long Term Resource Monitoring procedures—Aquatic vegetation monitoring","docAbstract":"<p>This standard operating procedure (SOP) manual describes the collection of standardized, long-term data for aquatic vegetation communities in selected study pools of the Upper Mississippi River System in the United States. The primary intent of the data collection is to assess the status and trends that aid in understanding the unique river ecosystem and to guide large-scale ecological restoration of the river and its biological communities, like aquatic plants and their dependent wildlife. This SOP is an update to the version published in 2000 and reflects modifications to sample sizes and additions of new data collection procedures. All long-term monitoring programs and their SOPs must be adapted to changing conditions and be improved through learning, and this SOP clarifies procedures and adds new elements since the initial SOP was written more than 25 years ago. The SOP is intended for multiple audiences, including vegetation specialists through the Upper Mississippi River Restoration Program, data analysts using the publicly available data generated through this SOP, and natural resource managers and restoration practitioners who need data and science to guide some decisions. This SOP may be transferable and adaptable to other ecosystems when the aquatic plant community is the focus.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2A22","collaboration":"Prepared in cooperation with the Long Term Resource Monitoring element of the Upper Mississippi River Restoration Program, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, Iowa Department of Natural Resources, Minnesota Department of Natural Resources, and Wisconsin Department of Natural Resources","usgsCitation":"Larson, D.M., Lund, E., Carhart, A.M., Fopma, S., and Szura, S., 2025, Long Term Resource Monitoring procedures—Aquatic vegetation monitoring: U.S. Geological Survey Techniques and Methods, book 2, chap. A22, 40 p., https://doi.org/10.3133/tm2A22.","productDescription":"Report: vi, 40 p.; 2 Linked Figures","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-167317","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496282,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/a22/tm2A22.pdf","text":"Report","size":"4.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 2-A22"},{"id":496281,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/a22/coverthb2.jpg"},{"id":496283,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/02/a22/tm2A22.XML"},{"id":496284,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/02/a22/images/"},{"id":496286,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm2A22/full"},{"id":496285,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/tm/02/a22/downloads/","text":"Printable versions of figures 2.1 and 7.1"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois River, Upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.82084396790316,\n              44.04246451932946\n            ],\n            [\n              -91.50791848601513,\n              38.40902936668505\n            ],\n            [\n              -89.8837153943196,\n              38.45968306709577\n            ],\n            [\n              -89.16595397141731,\n              41.89729975230259\n            ],\n            [\n              -90.33908638801539,\n              43.40513483806296\n            ],\n            [\n              -91.27142102824394,\n              43.92243866259706\n            ],\n            [\n              -91.82084396790316,\n              44.04246451932946\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/umesc\" data-mce-href=\"https://www.usgs.gov/centers/umesc\">Upper Midwest Environmental Sciences Center</a><br>U.S. Geological Survey<br>2630 Fanta Reed Road<br>La Crosse, Wisconsin 54603</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgments</li><li>Abstract</li><li>Plain Language Summary</li><li>Monitoring Aquatic Vegetation</li><li>Taxonomy and Species Codes</li><li>Voucher and Herbarium Specimens</li><li>Quality Assurance and Quality Control</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Species List</li><li>Appendix 2. Data Sheet</li><li>Appendix 3. Explanations of Field Options</li><li>Appendix 4. Population Size, Sample Size, and Selection Probabilities</li><li>Appendix 5. Commonly Used Computations</li><li>Appendix 6. Standard Operating Procedure Manual Updates</li><li>Appendix 7. Herbarium Label</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-09-30","noUsgsAuthors":false,"plainLanguageSummary":"<p>The Upper Mississippi River Restoration Program’s Long Term Resource Monitoring element made updates to the standardized operating procedure manual for collecting standardized data for aquatic vegetation in the Upper Mississippi River System. This updated manual helps users collect data more effectively. The information from the monitoring surveys is used to assess the status and trends of aquatic plants, and helps restoration managers to engineer habitat conditions for this unique river ecosystem.</p>","publicationDate":"2025-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lund, Eric","contributorId":221777,"corporation":false,"usgs":false,"family":"Lund","given":"Eric","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carhart, Alicia M.","contributorId":361967,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","middleInitial":"M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fopma, Seth","contributorId":360281,"corporation":false,"usgs":false,"family":"Fopma","given":"Seth","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szura, Stephanie","contributorId":360278,"corporation":false,"usgs":false,"family":"Szura","given":"Stephanie","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":949729,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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