{"pageNumber":"143","pageRowStart":"3550","pageSize":"25","recordCount":185169,"records":[{"id":70256539,"text":"70256539 - 2024 - Warmwater fish in small standing waters","interactions":[],"lastModifiedDate":"2025-01-31T16:00:12.982825","indexId":"70256539","displayToPublicDate":"2024-11-01T09:58:10","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Warmwater fish in small standing waters","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes, second edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","usgsCitation":"Flammang, M., Shoup, D., Michaletz, P., and Pope, K.L., 2024, Warmwater fish in small standing waters, chap. 2 <i>of</i> Standard methods for sampling North American freshwater fishes, second edition, p. 23-44.","productDescription":"22 p.","startPage":"23","endPage":"44","ipdsId":"IP-131100","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flammang, M.K.","contributorId":341065,"corporation":false,"usgs":false,"family":"Flammang","given":"M.K.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoup, D.E.","contributorId":280137,"corporation":false,"usgs":false,"family":"Shoup","given":"D.E.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michaletz, P.H.","contributorId":341066,"corporation":false,"usgs":false,"family":"Michaletz","given":"P.H.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":907878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":907879,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70256693,"text":"70256693 - 2024 - Warmwater fish in large standing waters","interactions":[],"lastModifiedDate":"2025-01-31T15:57:46.420073","indexId":"70256693","displayToPublicDate":"2024-11-01T09:55:05","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Warmwater fish in large standing waters","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"American Fisheries Society","usgsCitation":"Miranda, L.E., Bonvechio, K., Koch, J., and Moncayo-Estrada, R., 2024, Warmwater fish in large standing waters, p. 45-64.","productDescription":"20 p.","startPage":"45","endPage":"64","ipdsId":"IP-122991","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481551,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"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":908674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonvechio, K.I.","contributorId":341598,"corporation":false,"usgs":false,"family":"Bonvechio","given":"K.I.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":908675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, J.","contributorId":7065,"corporation":false,"usgs":false,"family":"Koch","given":"J.","affiliations":[],"preferred":false,"id":908676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moncayo-Estrada, R.","contributorId":243535,"corporation":false,"usgs":false,"family":"Moncayo-Estrada","given":"R.","email":"","affiliations":[{"id":48720,"text":"Instituto Politécnico Nacional-CICIMAR and COFAA","active":true,"usgs":false}],"preferred":false,"id":908677,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70274727,"text":"70274727 - 2024 - Indices for common North American fishes","interactions":[],"lastModifiedDate":"2026-04-08T15:01:12.860751","indexId":"70274727","displayToPublicDate":"2024-11-01T09:54:44","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"20","title":"Indices for common North American fishes","docAbstract":"<p><span>One of the greatest advantages to the standardization of fisheries sampling methods is the comparable data they produce (Bonar et al. 2017). Following American Fisheries Society (AFS) standardized sampling methods, fisheries professionals can more easily compare their data with standardized data collected across North America to address both small- and large-scale fisheries questions. For example, access to standardized data can allow fisheries managers to evaluate if a fish species is within an expected range for weight or length in a particular water body, providing them with valuable information about the baseline health of their fish population. Additionally, given that fish can take years to respond to certain management actions (Meals et al. 2010), access to standardized data over time can be used to assess the effectiveness of these actions. Finally, standardized fisheries data can be analyzed over large geographic regions and provide increased sample sizes to evaluate management actions that cross local or state borders, such as habitat improvements or regulations, as well as the effects of large-scale transformations such as climate change on fish growth or body condition. Ultimately, the use of standardized data enhances the ability of fisheries professionals to address both small- and large-scale threats currently facing freshwater ecosystems and the fishes they support.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch20","usgsCitation":"Tracy, E.E., Brouder, M.J., Iles, A.C., Teal, C.N., and Bonar, S.A., 2024, Indices for common North American fishes, chap. 20 <i>of</i> Standard methods for sampling North American freshwater fishes, p. 441-786, https://doi.org/10.47886/9781934874769.ch20.","productDescription":"346 p.","startPage":"441","endPage":"786","ipdsId":"IP-157649","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tracy, Erin E.","contributorId":369324,"corporation":false,"usgs":false,"family":"Tracy","given":"Erin","middleInitial":"E.","affiliations":[],"preferred":false,"id":958868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brouder, Mark J.","contributorId":369325,"corporation":false,"usgs":false,"family":"Brouder","given":"Mark","middleInitial":"J.","affiliations":[],"preferred":false,"id":958869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iles, Alison C.","contributorId":369326,"corporation":false,"usgs":false,"family":"Iles","given":"Alison","middleInitial":"C.","affiliations":[],"preferred":false,"id":958870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Teal, Chad N.","contributorId":337952,"corporation":false,"usgs":false,"family":"Teal","given":"Chad","email":"","middleInitial":"N.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":958962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958871,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70257344,"text":"70257344 - 2024 - Warmwater fish in wadeable streams","interactions":[],"lastModifiedDate":"2025-01-31T15:54:43.066269","indexId":"70257344","displayToPublicDate":"2024-11-01T09:52:00","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Warmwater fish in wadeable streams","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes, second edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","usgsCitation":"Mercado-Silva, N., Lyons, J., Magnelia, S.J., Peterson, J.T., and Roy, A.H., 2024, Warmwater fish in wadeable streams, chap. 4 <i>of</i> Standard methods for sampling North American freshwater fishes, second edition, p. 65-84.","productDescription":"20 p.","startPage":"65","endPage":"84","ipdsId":"IP-147694","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mercado-Silva, Norman","contributorId":295289,"corporation":false,"usgs":false,"family":"Mercado-Silva","given":"Norman","affiliations":[{"id":63827,"text":"Centro de Investigación en Biodiversidad y Conservación","active":true,"usgs":false}],"preferred":false,"id":925866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, John","contributorId":176499,"corporation":false,"usgs":false,"family":"Lyons","given":"John","email":"","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":925867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnelia, Stephan J.","contributorId":172959,"corporation":false,"usgs":false,"family":"Magnelia","given":"Stephan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":925868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, James T. 0000-0002-7709-8590","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":204948,"corporation":false,"usgs":false,"family":"Peterson","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":925869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":910026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70261991,"text":"70261991 - 2024 - Warmwater fish in rivers","interactions":[],"lastModifiedDate":"2025-01-31T14:27:01.025151","indexId":"70261991","displayToPublicDate":"2024-11-01T09:45:48","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"5","title":"Warmwater fish in rivers","docAbstract":"<div class=\"page-content\"><div class=\"page-content\"><div class=\"page-content\"><p>In addition to the gears described in the previous version, this edition includes an updated water body definition that is inclusive of Mexico and Canada as well as standard methods for the use of cast nets in warmwater rivers. There were organizational changes in the trawling and hoop-net sections to make them consistent with the format for this edition, but the methods themselves have not been changed and no standardized gears (e.g., small-mesh and large-mesh trawls are still both present) have been removed.</p><p>The diversity of warmwater rivers of North America owes to the mosaic of precipitation and geology spanning the continent from the arid systems of the Sonoran Desert to the humid forests of the Appalachian Mountains. The types of rivers discussed in this chapter are highly variable in size from headwaters to mouth but will include parts of rivers that are nonwadeable and larger. Here, we use this flexible definition because we found that regardless of how we classified a river as a whole, whether through basin area, discharge, or stream order, there is sufficient diversity across North America such that major rivers of some regions would be left out. We, therefore, chose to use site-level characterization because characteristics like target fish species and communities and habitat characteristics like water depth, velocity, and channel geomorphology drive or constrain our decisions in the field about what sampling gear to use rather than overall river or river basin characteristics.</p></div></div></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standard methods for sampling North American freshwater fishes, second edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874769.ch5","usgsCitation":"Pracheil, B., Braaten, P., Macias, E., Guy, C.S., Herzog, D., Hamel, M.J., Justice, J., Loeppky, A., Mollish, J., Simmons, J., and Tripp, S.J., 2024, Warmwater fish in rivers, chap. 5 <i>of</i> Standard methods for sampling North American freshwater fishes, second edition, p. 85-110, https://doi.org/10.47886/9781934874769.ch5.","productDescription":"26 p.","startPage":"85","endPage":"110","ipdsId":"IP-136997","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":481514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pracheil, Brenda M.","contributorId":280027,"corporation":false,"usgs":false,"family":"Pracheil","given":"Brenda M.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":922576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Braaten, Patrick 0000-0003-3362-420X pbraaten@usgs.gov","orcid":"https://orcid.org/0000-0003-3362-420X","contributorId":152682,"corporation":false,"usgs":true,"family":"Braaten","given":"Patrick","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":922575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macias, Everardo Barba","contributorId":347841,"corporation":false,"usgs":false,"family":"Macias","given":"Everardo Barba","affiliations":[{"id":83259,"text":"ECOSUR-Tabasco","active":true,"usgs":false}],"preferred":false,"id":922577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":922578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, David P","contributorId":347842,"corporation":false,"usgs":false,"family":"Herzog","given":"David P","affiliations":[{"id":83260,"text":"Missouri Dept. Of Conservation","active":true,"usgs":false}],"preferred":false,"id":922579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamel, Martin J.","contributorId":171901,"corporation":false,"usgs":false,"family":"Hamel","given":"Martin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":922580,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Justice, John C","contributorId":347843,"corporation":false,"usgs":false,"family":"Justice","given":"John C","affiliations":[{"id":13217,"text":"Tennessee Valley Authority","active":true,"usgs":false}],"preferred":false,"id":922581,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loeppky, Alison R","contributorId":347844,"corporation":false,"usgs":false,"family":"Loeppky","given":"Alison R","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":922582,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mollish, Jon M","contributorId":347845,"corporation":false,"usgs":false,"family":"Mollish","given":"Jon M","affiliations":[{"id":13217,"text":"Tennessee Valley Authority","active":true,"usgs":false}],"preferred":false,"id":922583,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Simmons, Jeffrey W","contributorId":347846,"corporation":false,"usgs":false,"family":"Simmons","given":"Jeffrey W","affiliations":[{"id":13217,"text":"Tennessee Valley Authority","active":true,"usgs":false}],"preferred":false,"id":922584,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tripp, Sara J.","contributorId":253122,"corporation":false,"usgs":false,"family":"Tripp","given":"Sara","email":"","middleInitial":"J.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":922585,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70266578,"text":"70266578 - 2024 - Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers","interactions":[],"lastModifiedDate":"2025-05-09T14:36:58.886325","indexId":"70266578","displayToPublicDate":"2024-11-01T09:34:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13429,"text":"Transactions of American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers","docAbstract":"<div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">Sea Lamprey Petromyzon marinus remain problematic for Lake Trout Salvelinus namaycush restoration in the Laurentian Great Lakes. Fisheries assessments would benefit from knowledge of spatial–temporal patterns of Sea Lamprey parasitism on Lake Trout; however, such patterns are challenging to estimate from wounding rates on caught Lake Trout. Electronic tags have been used to identify distinct fish behaviors (e.g., foraging or spawning) using measurements of acceleration or heart rate. We hypothesized that Sea Lamprey attachment would elicit changes in the heart rate and swimming behavior of Lake Trout. Here, we determined whether tagging devices could record these changes and whether we could accurately predict lamprey attachment on Lake Trout using these recordings.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">Adult Lake Trout (n = 34) were implanted with acceleration and heart rate tags and then were subjected to Sea Lamprey parasitism within a laboratory setting. Approximately 70 different acceleration and heart rate metrics were collected and tried as predictors of lamprey attachment. The top variables were used to train random forest models and then tried on test data sets. The accuracy of these models was then validated using a jackknife approach.</p></div><div class=\" sec\"><div class=\"title\">Result</div><p class=\"chapter-para\">Metrics related to body orientation and heart rate were identified as the best predictors of Sea Lamprey attachment. The best models predicted lamprey attachments with high accuracy; however, individual‐level jackknife tests resulted in less accurate cross‐individual prediction and regularly predicted false negatives. These findings may be related to individual variance in the Lake Trout response to attachment, but there was evidence that the shifting of tags after implantation impacted predictive performance, which could be remedied with adjustments during implantation.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">Our study highlights the potential to use tagging devices for quantifying Sea Lamprey attachments on Lake Trout in the wild. Further development appears necessary; however, once improved, these predictive models have the potential to generate field‐based estimates of Sea Lamprey attack rates on Lake Trout.</p></div>","language":"English","publisher":"Oxford Academic","doi":"10.1002/tafs.10491","usgsCitation":"Reeve, C., Adams, J., Miehls, S.M., Lowe, M.R., Cooke, S.J., Moser, M.L., and Brownscombe, J., 2024, Developing a predictive model to identify Sea Lamprey parasitism on Lake Trout using biologgers: Transactions of American Fisheries Society, v. 153, no. 6, p. 781-801, https://doi.org/10.1002/tafs.10491.","productDescription":"21 p.","startPage":"781","endPage":"801","ipdsId":"IP-153709","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488292,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10491","text":"Publisher Index Page"},{"id":485642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"153","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Reeve, Connor","contributorId":354867,"corporation":false,"usgs":false,"family":"Reeve","given":"Connor","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V.","contributorId":354868,"corporation":false,"usgs":false,"family":"Adams","given":"Jean V.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":936594,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":936596,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooke, Steven J.","contributorId":224158,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936597,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moser, Mary L.","contributorId":195100,"corporation":false,"usgs":false,"family":"Moser","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":936598,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brownscombe, Jake W.","contributorId":354870,"corporation":false,"usgs":false,"family":"Brownscombe","given":"Jake W.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":936599,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70261022,"text":"70261022 - 2024 - Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species","interactions":[],"lastModifiedDate":"2024-11-20T16:28:34.438486","indexId":"70261022","displayToPublicDate":"2024-11-01T09:19:22","publicationYear":"2024","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":"Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species","docAbstract":"<p>Sagebrush ecosystems support a suite of unique species such as the emblematic greater sage-grouse (<i>Centrocercus urophasianus</i>; sage-grouse) but are under increasing pressure from anthropogenic stressors such as annual grass invasion, conifer encroachment, altered wildfire regimes, and land use change. We examined the ability of an ecosystem-based framework for sagebrush conservation, the sagebrush conservation design (SCD) strategy, and the associated model of sagebrush ecological integrity (SEI), to identify and rank priority habitats for sage-grouse, a sagebrush indicator species. We compared sage-grouse population trends from 1996–2021 across the three ranked SEI categories. We then modeled those trends directly as a function of the same landcover predictors underlying SEI, used the median trend estimates to recategorize the sage-grouse’s range, and used spatial correlation methods to compare our sage-grouse performance categories with those of SEI. Finally, we compared the sage-grouse condition categories, predicted by our landcover-based model, to empirical trends derived from population count data. We found that the SCD and SEI were effective tools for identifying and ranking priority habitats for sage-grouse. Population trends were stable in the core areas identified by SEI but declining in the lower (i.e., growth and other) condition categories. As a result, core areas encompassed an increasingly larger share of the total sage-grouse population in a disproportionately smaller area. Our model supports the general functional relationships between landcover and sage-grouse performance suggested by SEI. We found strong spatial congruence between our categories of predicted sage-grouse population performance, the condition categories of SEI, and empirical trends derived from population count data. Our analysis demonstrates that proactive ecosystem-based approaches to the conservation of the sagebrush biome can help optimize the return on limited conservation resources and benefits for sagebrush obligate species and help reduce some of the real and perceived conflicts inherent in single-species management.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.021","usgsCitation":"Prochazka, B.G., Lundblad, C.G., Doherty, K., O’Neil, S.T., Tull, J.C., Abele, S., Aldridge, C.L., and Coates, P.S., 2024, Evaluating the sagebrush conservation design through the lens of a sagebrush indicator species: Rangeland Ecology & Management, v. 97, p. 146-159, https://doi.org/10.1016/j.rama.2024.08.021.","productDescription":"14 p.","startPage":"146","endPage":"159","ipdsId":"IP-162640","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.08.021","text":"Publisher Index Page"},{"id":464350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, New Mexico, Nevada, Montana, Oregon, Utah, Washington, Wyoming","otherGeospatial":"Great Plains, Intermountain West, Southern Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.46461214797594,\n              47.34790601551299\n            ],\n            [\n              -120.46461214797594,\n              35.22486431641359\n            ],\n            [\n              -104.39395814136043,\n              35.22486431641359\n            ],\n            [\n              -104.39395814136043,\n              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0000-0001-7925-9055","orcid":"https://orcid.org/0000-0001-7925-9055","contributorId":346421,"corporation":false,"usgs":true,"family":"Lundblad","given":"Carl","email":"","middleInitial":"Gregory","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":918952,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research 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aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":918956,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918957,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70260930,"text":"70260930 - 2024 - Spread and frequency of explosive silicic volcanism of the Carpathian-Pannonian Region during Early Miocene: Clues from the SW Pannonian Basin and the Dinaridesion during Early Miocene: clues from the SW Pannonian Basin and the Dinarides","interactions":[],"lastModifiedDate":"2024-11-15T14:52:30.682183","indexId":"70260930","displayToPublicDate":"2024-11-01T08:34:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Spread and frequency of explosive silicic volcanism of the Carpathian-Pannonian Region during Early Miocene: Clues from the SW Pannonian Basin and the Dinaridesion during Early Miocene: clues from the SW Pannonian Basin and the Dinarides","docAbstract":"<p><span>Explosive silicic volcanism of the Carpathian-Pannonian Region (CPR) is increasingly recognized as the primary source of tephra across the Alpine-Mediterranean region during the Early and Middle Miocene. However, the tephrostratigraphic framework for this period of volcanic activity is still incomplete. We present new multi-proxy data from Lower Miocene ignimbrites and tephra fallout deposits from the southwestern CPR and the Dinaride Lake System and integrate them into existing datasets to better resolve the regional extent and scale of these eruptions of the CPR. Volcanic glass geochemistry indicates distal fallout tuffs deposited in the Sinj Basin are correlative with the proximal Ostoros ignimbrites from the Bükkalja Volcanic Field, indicative of regionally extensive volcanism at 17.295&nbsp;±&nbsp;0.028&nbsp;Ma, based on CA-ID-TIMS U</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Pb zircon geochronology. Based on integrated tephrostratigraphic data, newly identified 17.064&nbsp;±&nbsp;0.010&nbsp;Ma massive rhyolitic ignimbrite deposits from the Kalnik Volcaniclastic Complex located in the southwestern CPR are correlative with the 17.062&nbsp;±&nbsp;0.010&nbsp;Ma Mangó massive ignimbrite found in the Bükkalja Volcanic Field located in the northern CPR. Based on these new observations of its potential areal distribution and estimated thicknesses, these two widespread ∼17.1&nbsp;Ma ignimbrites represent intermediate to large caldera-forming ignimbrites, larger than previously suggested. Finally, volcanic glass geochemistry of fallout deposits from the Dinaridic Sinj and Livno-Tomislavgrad Basins have similar volcanic glass geochemistry as the rhyolitic pumices from the lowermost part of the Bogács ignimbrite unit of the Bükkalja Volcanic Field. However, high-precision geochronology indicates that these distal ashfalls were deposited at 16.9567&nbsp;±&nbsp;0.0074&nbsp;Ma, significantly predating the 16.824&nbsp;±&nbsp;0.028&nbsp;Ma emplacement of the fiamme-bearing part of the Bogács ignimbrite. These distinct ages suggest that the Bogács unit represents multiple eruptive events and indicating that further work is required to deconvolve this portion of the CPR volcanic record. Together, these data suggest that large volume CPR ignimbrite volcanism was more frequent and widespread than previously understood, enhancing the existing volcanic framework and history of the source region for this time period.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2024.108215","usgsCitation":"Brlek, M., Trinajstic, N., Gaynor, S.P., Kutterolf, S., Hauff, F., Schindlbeck-Belo, J., Suica, S., Wang, K., Lee, H., Watts, E., Georgiev, S.V., Brcic, V., Spelic, M., Misur, I., Kukoc, D., Schoene, B., and Lukacs, R., 2024, Spread and frequency of explosive silicic volcanism of the Carpathian-Pannonian Region during Early Miocene: Clues from the SW Pannonian Basin and the Dinaridesion during Early Miocene: clues from the SW Pannonian Basin and the Dinarides: Journal of Volcanology and Geothermal Research, v. 445, 108215, 22 p., https://doi.org/10.1016/j.jvolgeores.2024.108215.","productDescription":"108215, 22 p.","ipdsId":"IP-167234","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":464120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bosnia and Herzegovina, Croatia, Hungary, Romania, Serbia, Slovakia, Slovenia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              13,\n              48.5\n            ],\n            [\n              13,\n              43.75\n            ],\n            [\n              27,\n              43.75\n            ],\n            [\n              27,\n              48.5\n            ],\n            [\n              13,\n              48.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":918548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kutterolf, Steffen","contributorId":346265,"corporation":false,"usgs":false,"family":"Kutterolf","given":"Steffen","affiliations":[{"id":82808,"text":"GEOMAR Helmholtz Cetner for Ocean Research","active":true,"usgs":false}],"preferred":false,"id":918549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hauff, Folkmar","contributorId":346266,"corporation":false,"usgs":false,"family":"Hauff","given":"Folkmar","affiliations":[{"id":82808,"text":"GEOMAR Helmholtz Cetner for Ocean Research","active":true,"usgs":false}],"preferred":false,"id":918550,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schindlbeck-Belo, Julie","contributorId":346267,"corporation":false,"usgs":false,"family":"Schindlbeck-Belo","given":"Julie","email":"","affiliations":[{"id":82808,"text":"GEOMAR Helmholtz Cetner for Ocean 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Duje","contributorId":346275,"corporation":false,"usgs":false,"family":"Kukoc","given":"Duje","email":"","affiliations":[{"id":82807,"text":"Croatian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":918559,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schoene, Blair","contributorId":270797,"corporation":false,"usgs":false,"family":"Schoene","given":"Blair","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":918637,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Lukacs, Reka","contributorId":346276,"corporation":false,"usgs":false,"family":"Lukacs","given":"Reka","email":"","affiliations":[{"id":82810,"text":"MTA-ELTE Volcanology Research Group, Budapest","active":true,"usgs":false}],"preferred":false,"id":918560,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70261136,"text":"70261136 - 2024 - Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping","interactions":[],"lastModifiedDate":"2024-11-26T15:30:10.726606","indexId":"70261136","displayToPublicDate":"2024-11-01T08:31:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping","docAbstract":"<p><span>Hyperspectral sensors provide near-continuous spectral data that can facilitate advancements in agricultural crop classification and characterization, which are important for addressing global food and water security issues. We investigated two new-generation hyperspectral sensors, Germany’s Deutsches Zentrum für Luft‐ und Raumfahrt Earth Sensing Imaging Spectrometer (DESIS) and Italy’s PRecursore IperSpettrale della Missione Applicativa (PRISMA), within California's Central Valley in August 2021 focusing on five irrigated agricultural crops (alfalfa, almonds, corn, grapes, and pistachios). With reference data from the U.S. Department of Agriculture Cropland Data Layer, we developed a spectral library of the crops and classified them using three machine learning algorithms (support vector machines [SVM], random forest [RF], and spectral angle mapper [SAM]) and two philosophies: 1. Full spectral analysis (FSA) and 2. Optimal hyperspectral narrowband (OHNB) analysis. For FSA, we used 59 DESIS four-bin product bands and 207 of 238 PRISMA bands. For OHNB analysis, 9 DESIS and 16 PRISMA nonredundant OHNBs for studying crops were selected. FSA achieved only 1% to 3% higher accuracies relative to OHNB analysis in most cases. SVM provided the best results, closely followed by RF. Using both DESIS and PRISMA image OHNBs in SVM for classification led to higher accuracy than using either image alone, with an overall accuracy of 99%, producer’s accuracies of 94% to 100%, and user's accuracies of 95% to 100%.</span></p>","language":"English","publisher":"Ingenta","doi":"10.14358/PERS.24-00026R2","usgsCitation":"Aneece, I.P., Thenkabail, P., McCormick, R.L., Haireti, A., Foley, D., Oliphant, A., and Teluguntla, P., 2024, Machine learning and new-generation spaceborne hyperspectral data advance crop type mapping: Photogrammetric Engineering and Remote Sensing, v. 90, no. 11, p. 687-698, https://doi.org/10.14358/PERS.24-00026R2.","productDescription":"12 p.","startPage":"687","endPage":"698","ipdsId":"IP-163096","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":498261,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.24-00026r2","text":"Publisher Index Page"},{"id":464465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.00224368510789,\n              37.29219185284313\n            ],\n            [\n              -120.00224368510789,\n              36.59828829039613\n            ],\n            [\n              -118.67344220549262,\n              36.59828829039613\n            ],\n            [\n              -118.67344220549262,\n              37.29219185284313\n            ],\n            [\n              -120.00224368510789,\n              37.29219185284313\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"90","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aneece, Itiya P. 0000-0002-1201-5459","orcid":"https://orcid.org/0000-0002-1201-5459","contributorId":208265,"corporation":false,"usgs":true,"family":"Aneece","given":"Itiya","middleInitial":"P.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Richard L. 0009-0002-8208-2136","orcid":"https://orcid.org/0009-0002-8208-2136","contributorId":346504,"corporation":false,"usgs":true,"family":"McCormick","given":"Richard","email":"","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haireti, Alifu","contributorId":346506,"corporation":false,"usgs":false,"family":"Haireti","given":"Alifu","email":"","affiliations":[],"preferred":false,"id":919401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foley, Daniel 0000-0002-2051-6325","orcid":"https://orcid.org/0000-0002-2051-6325","contributorId":208266,"corporation":false,"usgs":true,"family":"Foley","given":"Daniel","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliphant, Adam 0000-0001-8622-7932 aoliphant@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-7932","contributorId":192325,"corporation":false,"usgs":true,"family":"Oliphant","given":"Adam","email":"aoliphant@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919398,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Teluguntla, Pardhasaradhi 0000-0001-8060-9841","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":211780,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":919397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70261260,"text":"70261260 - 2024 - Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California","interactions":[],"lastModifiedDate":"2024-12-04T15:32:09.263599","indexId":"70261260","displayToPublicDate":"2024-11-01T08:24:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California","docAbstract":"The largest rare earth element (REE) deposit in the United States is a carbonatite intrusion at Mountain Pass in the Mojave Desert, California. Despite a clear spatiotemporal association of alkaline silicate and carbonatite intrusions at Mountain Pass, a genetic model of their mutual formation has not been resolved. The Mountain Pass carbonatite has long been upheld as an example of a primary magmatic body, but recent work has suggested it could be fluid-derived. This study investigates the geochemistry of apatite and monazite grains from the alkaline silicate and carbonatite stocks and dikes of the Mountain Pass district, to elucidate the magmatic history of the intrusive suite and identify the role of fluids in rare earth element mineralization. Three apatite populations are identified in the alkaline silicate rocks. A primary magmatic apatite group supports intrusion of the stocks as separate pulses of magma derived from a spatially extensive metasomatized mantle source region. The second group implicates the role of a regional fluid that mobilized light rare earth elements from apatite grains. A minor group of inherited apatite cores, identified by low Sr and negative Eu anomalies, supports assimilation of crustal material in the formation of the intrusive suite. Analyses of monazite and apatite grains from the carbonatite orebody also reveal a mix of primary magmatic and metasomatic (fluid-related) minerals. Compositional similarities between primary phosphates in the carbonatite and alkaline silicate rocks support a genetic link between the intrusive suites. The presence of fluids regionally and within the carbonatite orebody indicates the Mountain Pass carbonatite should not be classified as a purely magmatic REE deposit.","language":"English","publisher":"GeoScienceWorld","doi":"10.5382/econgeo.5108","usgsCitation":"Benson, E.K., and Watts, K., 2024, Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California: Economic Geology, v. 119, no. 7, p. 1611-1642, https://doi.org/10.5382/econgeo.5108.","productDescription":"32 p.","startPage":"1611","endPage":"1642","ipdsId":"IP-159227","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":466789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.5108","text":"Publisher Index Page"},{"id":464750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert, Mountain Pass","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.06188935809527,\n              36.65925978640696\n            ],\n            [\n              -115.95168822883412,\n              36.65925978640696\n            ],\n            [\n              -115.95168822883412,\n              34.494804652285\n            ],\n            [\n              -114.06188935809527,\n              34.494804652285\n            ],\n            [\n              -114.06188935809527,\n              36.65925978640696\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"119","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":920138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261416,"text":"70261416 - 2024 - Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand","interactions":[],"lastModifiedDate":"2024-12-09T15:09:14.311686","indexId":"70261416","displayToPublicDate":"2024-11-01T08:02:51","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand","docAbstract":"<p>On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast.</p><p>The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2024.104878","usgsCitation":"Wein, A., McBride, S., Becker, J., Christophersen, A., Hudson Doyle, E., Gerstenberger, M., and Potter, S., 2024, Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand: International Journal of Disaster Risk Reduction, v. 114, 104878, 23 p., https://doi.org/10.1016/j.ijdrr.2024.104878.","productDescription":"104878, 23 p.","ipdsId":"IP-164388","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":466790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2024.104878","text":"Publisher Index Page"},{"id":464918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","city":"Christchurch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              172.16906048121103,\n              -43.39513530218538\n            ],\n            [\n              172.16906048121103,\n              -43.911124672963645\n            ],\n            [\n              173.1531190191008,\n              -43.911124672963645\n            ],\n            [\n              173.1531190191008,\n              -43.39513530218538\n            ],\n            [\n              172.16906048121103,\n              -43.39513530218538\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"114","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":920536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":920537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becker, Julia S.","contributorId":217541,"corporation":false,"usgs":false,"family":"Becker","given":"Julia S.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":920538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christophersen, Annemarie","contributorId":175090,"corporation":false,"usgs":false,"family":"Christophersen","given":"Annemarie","email":"","affiliations":[],"preferred":false,"id":920539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson Doyle, Emma","contributorId":347020,"corporation":false,"usgs":false,"family":"Hudson Doyle","given":"Emma","email":"","affiliations":[{"id":83040,"text":"Massey  University, Aotearoa New Zealand","active":true,"usgs":false}],"preferred":false,"id":920540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gerstenberger, Matthew","contributorId":217542,"corporation":false,"usgs":false,"family":"Gerstenberger","given":"Matthew","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":920541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Potter, Sally H.","contributorId":217521,"corporation":false,"usgs":false,"family":"Potter","given":"Sally H.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":920542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70261263,"text":"70261263 - 2024 - In vitro impacts of glyphosate on manatee lymphocytes","interactions":[],"lastModifiedDate":"2024-12-04T14:57:29.641711","indexId":"70261263","displayToPublicDate":"2024-11-01T07:50:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"In vitro impacts of glyphosate on manatee lymphocytes","docAbstract":"<p>Exposure to contaminants, such as the herbicide glyphosate, can suppress protective immune functions. Glyphosate is the herbicide most used worldwide and has been found in the plasma of more than 50 % of the Florida manatees (<i>Trichechus manatus latirostris</i>) and all-year-round in their aquatic environment. Our objectives were to analyze the consequences of glyphosate exposure on their immune responses via T-lymphocyte proliferation assays and transcriptomics. We isolated peripheral blood mononuclear cells (mainly lymphocytes) of free-ranging manatees and performed T-cell proliferation assays. We used transcriptomics to understand the consequences of glyphosate <i>in vitro</i> exposure. The three doses chosen ranged from environmentally relevant concentrations at 10 to 10,000 µg.L<sup>−1</sup> that is considered an environmental contamination scenario. Glyphosate caused a dose-dependent reduction in T-lymphocyte proliferation, with a significant mean reduction of 27.3 % at 10,000 µg.L<sup>−1</sup> and up to 51.5 % in some individuals. Additionally, T-lymphocyte proliferation was significantly reduced in mid-winter compared to early winter. Transcriptomic analysis of peripheral blood mononuclear cells indicated that all doses of glyphosate (10, 1,000, and 10,000 µg.L<sup>−1</sup>) resulted in up-regulation of genes related to acute phase inflammation and inhibition of the T-lymphocyte proliferation pathway. Exposure to this contaminant along with other environmental stressors, such as extreme winters and red tide, might further affect the adaptive immune response of this threatened species.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2024.109054","usgsCitation":"De Maria, M., Garcia-Reyero, N., Stacy, N.I., Abbott, J., Yu, F., Pu, R., Kroll, K., Barboza, F.R., Walsh, M.T., Perez-Jimenez, J.G., Moraga Amador, D.A., Hunter, M., and Denslow, N., 2024, In vitro impacts of glyphosate on manatee lymphocytes: Environment International, v. 193, 109054, 14 p., https://doi.org/10.1016/j.envint.2024.109054.","productDescription":"109054, 14 p.","ipdsId":"IP-164391","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envint.2024.109054","text":"Publisher Index 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Florida","active":true,"usgs":false}],"preferred":false,"id":920146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abbott, Jeffrey R.","contributorId":346887,"corporation":false,"usgs":false,"family":"Abbott","given":"Jeffrey R.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":920147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yu, Fahong","contributorId":240782,"corporation":false,"usgs":false,"family":"Yu","given":"Fahong","affiliations":[],"preferred":false,"id":920148,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pu, Ruyiu","contributorId":346888,"corporation":false,"usgs":false,"family":"Pu","given":"Ruyiu","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":920149,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kroll, Kevin J.","contributorId":289365,"corporation":false,"usgs":false,"family":"Kroll","given":"Kevin J.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":920150,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barboza, Francisco R.","contributorId":346890,"corporation":false,"usgs":false,"family":"Barboza","given":"Francisco","email":"","middleInitial":"R.","affiliations":[{"id":83007,"text":"Estonian Marine Institute, University of Tartu, Estonia","active":true,"usgs":false}],"preferred":false,"id":920151,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walsh, Michael T.","contributorId":177177,"corporation":false,"usgs":false,"family":"Walsh","given":"Michael","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":920152,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Perez-Jimenez, Juan G.","contributorId":346892,"corporation":false,"usgs":false,"family":"Perez-Jimenez","given":"Juan","email":"","middleInitial":"G.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":920153,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Moraga Amador, David A.","contributorId":339594,"corporation":false,"usgs":false,"family":"Moraga Amador","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":81350,"text":"Interdisciplinary Center for Biotechnology Research, University of Florida","active":true,"usgs":false}],"preferred":false,"id":920154,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207589,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920155,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Denslow, Nancy D.","contributorId":200649,"corporation":false,"usgs":false,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":920156,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70266277,"text":"70266277 - 2024 - Droughts reshape apex predator space use and intraguild overlap","interactions":[],"lastModifiedDate":"2025-05-02T17:35:19.0661","indexId":"70266277","displayToPublicDate":"2024-11-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Droughts reshape apex predator space use and intraguild overlap","docAbstract":"<p>1. Droughts are increasing in frequency and severity globally due to climate change, leading to changes in resource availability that may have cascading effects on animal ecology. Resource availability is a key driver of animal space use, which in turn influences interspecific interactions like intraguild competition. Understanding how climate-induced changes in resource availability influence animal space use, and how species-specific responses scale up to affect intraguild dynamics, is necessary for predicting broader community-level responses to climatic changes.</p><p>2. Although several studies have demonstrated the ecological impacts of drought, the behavioral responses of individuals that scale up to these broader-scale effects are not well known, particularly among animals in top trophic levels, such as large carnivores. Furthermore, we currently lack understanding of how the impacts of climate variability on individual carnivore behavior are linked to intraguild dynamics, in part because multi-species datasets collected at timescales relevant to climatic changes are rare.</p><p>3. Using 11 years of GPS data from four sympatric large carnivore species in southern Africa – lions (<i>Panthera leo</i>), leopards (<i>Panthera pardus</i>), African wild dogs (<i>Lycaon pictus)</i>, and cheetahs (<i>Acinonyx</i> <i>jubatus</i>) – spanning 4 severe drought events, we test whether drought conditions impact 1) large carnivore space use, 2) broad-scale intraguild spatial overlap, and 3) fine-scale intraguild interactions.</p><p>4. Drought conditions expanded space use across species, with carnivores increasing their monthly home range sizes by 35% (wild dogs) to 66% (leopards). Drought conditions increased the amount of spatial overlap between lions and subordinate felids (cheetahs and leopards) by up to 119%, but only lion-cheetah encounter rates were affected by these changes, declining in response to drought. </p><p>5. Our findings reveal that drought has a clear signature on the space use of multiple sympatric large carnivore species, which can alter spatiotemporal partitioning between competing species. Our study thereby illuminates the links between environmental change, animal behavior, and intraguild dynamics. While fine-scale avoidance strategies may facilitate intraguild coexistence during periodic droughts, large carnivore conservation may require considerable expansion of protected areas or revised human-carnivore coexistence strategies to accommodate the likely long-term increased space demands of large carnivores under projected increases in drought intensity.</p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.14192","usgsCitation":"West, L., Rafiq, K., Converse, S.J., Wilson, A., Jordan, N., Golabek, K., McNutt, J., and Abrahms, B., 2024, Droughts reshape apex predator space use and intraguild overlap: Journal of Animal Ecology, v. 93, no. 11, p. 1785-1798, https://doi.org/10.1111/1365-2656.14192.","productDescription":"14 p.","startPage":"1785","endPage":"1798","ipdsId":"IP-166498","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502514,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":485354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Botswana","otherGeospatial":"Okavango Delta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              21.06855004382743,\n              -18.33344673603129\n            ],\n            [\n              21.06855004382743,\n              -19.979158912722966\n            ],\n            [\n              23.959554595120153,\n              -19.979158912722966\n            ],\n            [\n              23.959554595120153,\n              -18.33344673603129\n            ],\n            [\n              21.06855004382743,\n              -18.33344673603129\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"93","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"West, Leigh","contributorId":338294,"corporation":false,"usgs":false,"family":"West","given":"Leigh","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":935354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rafiq, Kasim","contributorId":338293,"corporation":false,"usgs":false,"family":"Rafiq","given":"Kasim","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":935355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Alan M.","contributorId":354290,"corporation":false,"usgs":false,"family":"Wilson","given":"Alan M.","affiliations":[{"id":84607,"text":"Royal Veterinary College","active":true,"usgs":false}],"preferred":false,"id":935357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jordan, Neil R.","contributorId":354291,"corporation":false,"usgs":false,"family":"Jordan","given":"Neil R.","affiliations":[{"id":84609,"text":"Wild Entrust","active":true,"usgs":false}],"preferred":false,"id":935358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golabek, Krystyna A.","contributorId":354292,"corporation":false,"usgs":false,"family":"Golabek","given":"Krystyna A.","affiliations":[{"id":84609,"text":"Wild Entrust","active":true,"usgs":false}],"preferred":false,"id":935359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McNutt, J. 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,{"id":70266842,"text":"70266842 - 2024 - Juvenile coho salmon growth differences track biennial pink salmon spawning patterns","interactions":[],"lastModifiedDate":"2025-05-13T15:33:11.662904","indexId":"70266842","displayToPublicDate":"2024-11-01T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile coho salmon growth differences track biennial pink salmon spawning patterns","docAbstract":"<p>1. Spawning Pacific salmon (<i>Oncorhynchus</i>&nbsp;spp.) provide marine-derived resources (MDR) to freshwater food webs in the form of eggs, flesh and maggots that consume salmon carcasses, all of which positively impact stream-dwelling fish growth. Pink salmon (<i>O. gorbuscha</i>) are widely distributed throughout coastal catchments along the North Pacific Ocean and display increased spawning abundances in odd years, owing to a fixed 2-year life history. While many studies have found that foraging and growth of stream-dwelling salmonids are improved by increased adult salmon spawning abundance, few studies have investigated the importance of alternating pink salmon spawning abundance between years.</p><p>2. Here, we examined how patterns of pink salmon spawning abundance impact the foraging and growth of juvenile coho salmon (<i>O. kisutch</i>). First, we used bioenergetic simulations to generate a hypothesis that coho salmon growth would increase during odd relative to even years. We then collected empirical juvenile coho salmon diet and growth data from a Southeast Alaska catchment in 2021 (pink salmon spawning) and 2022 (no pink salmon spawning). Field data were compared against simulation predictions to understand impacts of biennial pink salmon spawning patterns on juvenile coho salmon growth.</p><p>3. Empirical growth data revealed similar patterns to bioenergetic simulations. Age-1 coho salmon grew 16.6 mm longer and 5.5 g heavier on average in 2021 compared to 2022. Age-0 coho salmon displayed minor growth differences between years.</p><p>4. These results support bioenergetic model predictions and suggest that patterns of pink salmon spawning abundance can impart interannual growth disparities to juvenile coho salmon. Moreover, we show that distinct spawning characteristics of Pacific salmon species are important when understanding patterns of MDR transfer and growth responses in stream fishes.</p>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.14328","usgsCitation":"Fitzgerald, K., Bellmore, J., Fellman, J., Cheng, M., Boyles-Muehleck, N., Delbecq, C., and Falke, J.A., 2024, Juvenile coho salmon growth differences track biennial pink salmon spawning patterns: Freshwater Biology, v. 69, no. 11, p. 1583-1595, https://doi.org/10.1111/fwb.14328.","productDescription":"13 p.","startPage":"1583","endPage":"1595","ipdsId":"IP-155328","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Juneau","otherGeospatial":"Tongass National Forest, upper Montana Creek","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -134.02770952221633,\n              58.39172878863832\n            ],\n            [\n              -134.02770952221633,\n              57.6331041033996\n            ],\n            [\n              -133.0242790552512,\n              57.6331041033996\n            ],\n            [\n              -133.0242790552512,\n              58.39172878863832\n            ],\n            [\n              -134.02770952221633,\n              58.39172878863832\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"69","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzgerald, Kevin A.","contributorId":355111,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Kevin A.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bellmore, J. Ryan","contributorId":355112,"corporation":false,"usgs":false,"family":"Bellmore","given":"J. Ryan","affiliations":[{"id":40821,"text":"U. S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":936880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fellman, Jason B.","contributorId":355113,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason B.","affiliations":[{"id":84706,"text":"University of Alaska Southeast,  Forest Service","active":true,"usgs":false}],"preferred":false,"id":936881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheng, Matthew L.H.","contributorId":355115,"corporation":false,"usgs":false,"family":"Cheng","given":"Matthew L.H.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936882,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyles-Muehleck, Naomi","contributorId":355118,"corporation":false,"usgs":false,"family":"Boyles-Muehleck","given":"Naomi","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":936883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delbecq, Claire E.","contributorId":355120,"corporation":false,"usgs":false,"family":"Delbecq","given":"Claire E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":936884,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":936885,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70264070,"text":"70264070 - 2024 - Assessing mosquito populations to limit the spread of avian disease and inform the conservation of Hawaiian forest birds","interactions":[],"lastModifiedDate":"2025-03-05T16:43:47.910501","indexId":"70264070","displayToPublicDate":"2024-10-31T10:39:31","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":20198,"text":"Final Project Report","active":true,"publicationSubtype":{"id":1}},"title":"Assessing mosquito populations to limit the spread of avian disease and inform the conservation of Hawaiian forest birds","docAbstract":"<p>The introduced mosquito-borne avian malaria, <i>Plasmodium relictum</i>, along with its mosquito vector, <i>Culex quinquefasciatus</i>, are key limiting factors for endemic Hawaiian forest birds and are, in part, responsible for past extinctions and continued population declines of extant species. In the last 10 years steep declines in forest bird populations have been documented on Kaua`i and Maui. Presently two endemic species on Kaua`i, `Akikiki (<i>Oreomystis bairdi</i>) and `Akeke`e (<i>Loxops caeruleirostris</i>) and two endemic species on Maui, Kiwikiu (<i>Pseudonestor xanthophrys</i>) and `Ākohekohe, (<i>Palmeria dolei</i>) are facing extinction. These declines have been attributed to avian malaria transmission exacerbated by climate change. While little can be done to reduce the effects of climate change on vector abundance and transmission, recent innovations in landscape-level mosquito suppression and eradication may provide new tools to control or eliminate vectors from forest bird habitat. The current management focus is on the development and implementation of a <i>Wolbachia</i>-based Incompatible Insect Technique (IIT) to reduce vector abundance. IIT involves using naturally occurring strains of <i>Wolbachia</i>, an endosymbiotic bacterium of <i>C. quinquefasciatus</i> and other arthropods, to facilitate reproductive incompatibility and infertility through cross matings. Through sustained releases of male mosquitoes infected with incompatible <i>Wolbachia</i>, wild mosquito populations can be suppressed. To meet regulatory approval for large-scale releases and achieve successful deployment and suppression, key ecological parameters (population density, dispersal, and survivorship) need to be assessed. Mark-release-recapture (MRR) techniques are commonly used to estimate these parameters outside of the Hawaiian Islands. Mark-release-recapture entails the capture of a portion of the population which is marked by a harmless method and then released back into the wild. The results of a subsequent or multiple recapture event(s) provide the proportion of marked individuals to unmarked individuals that can be mathematically analyzed to estimate populations size, survival, and dispersal. In this study, a MRR trial with wild-captured and laboratory-reared <i>C. quinquefasciatus</i> was conducted in a native forest on the Island of Hawai`i. The results provide some of the first estimates for (1) population abundance, (2) survivorship, and (3) movement of <i>C. quinquefasciatus</i> in forest bird habitat to support regulatory approvals and to advance and improve IIT mosquito control efforts in the State of Hawaii.</p>","language":"English","publisher":"Pacific Islands Climate Adaptation Science Center","usgsCitation":"Lapointe, D., 2024, Assessing mosquito populations to limit the spread of avian disease and inform the conservation of Hawaiian forest birds: Final Project Report, 11 p.","productDescription":"11 p.","ipdsId":"IP-172863","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":482886,"rank":1,"type":{"id":15,"text":"Index 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,{"id":70274739,"text":"70274739 - 2024 - Heart of the West: Wyoming’s commitment to conservation of migratory ungulates","interactions":[],"lastModifiedDate":"2026-04-09T15:24:19.392049","indexId":"70274739","displayToPublicDate":"2024-10-31T10:18:46","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Heart of the West: Wyoming’s commitment to conservation of migratory ungulates","docAbstract":"<p><span>The small town of Superior, Wyoming, used to be a booming coal town. Pictures from the 1920s reveal sparkling new cars, a bowling alley, and other amenities supported by the wealth of the coal mines. Today, those prosperous days are nowhere to be seen. Superior doesn’t have a grocery store or a gas station, and the local bar is only open occasionally. Aside from the low-slung, modest houses built into the hills around town, the most prominent structure is the county road maintenance shop.</span></p><p><span>But those hills are also dotted with mule deer—lots of them. Superior represents&nbsp;the southern terminus of the world’s longest-recorded mule deer migration. The study of these deer has shaped how wildlife biologists think about migration, and the conservation of their corridor illustrates how science informs the management of iconic Western wildlife populations. These deer, and their story, may also represent what is possible when we recognize the habitat needs of wildlife that move across the same landscapes where we live and work.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"A watershed moment: The American West in the age of limits","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of Utah Press","usgsCitation":"Reed, E., and Kauffman, M.J., 2024, Heart of the West: Wyoming’s commitment to conservation of migratory ungulates, chap. <i>of</i> A watershed moment: The American West in the age of limits, p. 248-262.","productDescription":"15 p.","startPage":"248","endPage":"262","ipdsId":"IP-166746","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":502355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.02791442700837,\n              45.00491516402994\n            ],\n            [\n              -111.02791442700837,\n              40.995252415428496\n            ],\n            [\n              -104.0279534875161,\n              40.995252415428496\n            ],\n            [\n              -104.0279534875161,\n              45.00491516402994\n            ],\n            [\n              -111.02791442700837,\n              45.00491516402994\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Emily","contributorId":299809,"corporation":false,"usgs":false,"family":"Reed","given":"Emily","affiliations":[{"id":63974,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":958899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":210786,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":958900,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261810,"text":"70261810 - 2024 - Distribution of yellow crazy ants (Anoplolepis gracilipes) and notes on other ant species at Wake Atoll, 6-21 October, 2023","interactions":[],"lastModifiedDate":"2024-12-26T15:40:23.525243","indexId":"70261810","displayToPublicDate":"2024-10-31T09:33:28","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":6053,"text":"Hawaii Cooperative Studies Unit Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"HCSU-111","displayTitle":"Distribution of yellow crazy ants (<i>Anoplolepis gracilipes</i>) and notes on other ant species at Wake Atoll, 6-21 October, 2023","title":"Distribution of yellow crazy ants (Anoplolepis gracilipes) and notes on other ant species at Wake Atoll, 6-21 October, 2023","docAbstract":"<p>Wake Atoll, located in the central Pacific Ocean, is a tropical coral atoll comprised of three islands totaling 696 ha of emergent land. Wake Atoll supports at least 17 species of non-native ants, but one species, the yellow crazy ant (<i>Anoplolepis gracilipes</i>), is especially harmful to ecosystems, including seabirds, which are federally protected species and nest throughout Wake Atoll. Our objective was to map the distribution of yellow crazy ants (YCA) across Wake Atoll to provide U.S. Air Force managers with information that could inform an eradication strategy for this species. In addition, we documented the presence of other ant species identified during our survey. We used a 50 x 50-m cell-based sampling grid to survey for YCA and other ant species. YCA were widespread across the atoll, occupying all three islands and were detected in 566 of the 3,675 (15.4%) cells surveyed, covering an area of about 142 ha. The highest proportion of cells containing YCA was on Wilkes Island (99 of 400 cells or 24.8%), followed by Wake Island (395 of 2,760 cells or 14.3%) and Peale Island (72 of 518 cells or 14.0%). YCA detections on Wilkes Island were restricted to Wilkes South (99 of 202 cells or 49.0%); no YCA were found on Wilkes North, an important area that supports the most diverse assemblage of nesting seabirds on Wake Atoll. Based on technologies developed to eradicate YCA from Johnston Atoll and elsewhere, eradicating YCA from Wake Atoll appears technically feasible. The occurrence of discrete populations (i.e., clusters of occupied cells separated from other clusters of occupied cells) within and among islands could allow a stepwise strategy where the short-term outcome of the treatment of one population is independent of the outcome of another treatment. Without action, the high-density YCA population on Wilkes South could breach the narrow (~50 m), sometimes dry, channel separating Wilkes North and South, posing a serious threat to nesting seabirds present on Wilkes North. Eradicating YCA from Wilkes South would create a buffer from YCA and reduce the threat of northward movement of YCA. We also detected 12 ant species other than YCA during our survey, including <i>Lepisiota frauenfeldi</i>, a new record for the atoll. </p>","language":"English","publisher":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","usgsCitation":"Plentovich, S., Peck, R., and Sachs, E., 2024, Distribution of yellow crazy ants (Anoplolepis gracilipes) and notes on other ant species at Wake Atoll, 6-21 October, 2023: Hawaii Cooperative Studies Unit Technical Report HCSU-111, iii, 17 p.","productDescription":"iii, 17 p.","ipdsId":"IP-164112","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":465449,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://hdl.handle.net/10790/5394","linkFileType":{"id":5,"text":"html"}},{"id":465461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Wake Atoll","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              166.58332885043876,\n              19.32932614247504\n            ],\n            [\n              166.58332885043876,\n              19.258901384875912\n            ],\n            [\n              166.6703092664876,\n              19.258901384875912\n            ],\n            [\n              166.6703092664876,\n              19.32932614247504\n            ],\n            [\n              166.58332885043876,\n              19.32932614247504\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Plentovich, Sheldon M.","contributorId":173992,"corporation":false,"usgs":false,"family":"Plentovich","given":"Sheldon M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":921884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":921885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sachs, Elyse","contributorId":347510,"corporation":false,"usgs":false,"family":"Sachs","given":"Elyse","affiliations":[{"id":55513,"text":"USFWS - Pacific Islands Fish and Wildlife Office","active":true,"usgs":false}],"preferred":false,"id":921886,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70264786,"text":"70264786 - 2024 - Foreword","interactions":[],"lastModifiedDate":"2025-03-24T14:03:05.388933","indexId":"70264786","displayToPublicDate":"2024-10-31T09:00:21","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Foreword","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bayesian analysis of spatially structured population dynamics","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Royle, A., 2024, Foreword, chap. <i>of</i> Bayesian analysis of spatially structured population dynamics, p. vii-ix.","productDescription":"3 p.","startPage":"vii","endPage":"ix","ipdsId":"IP-169465","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483706,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/book/10.1007/978-3-031-64518-1","linkFileType":{"id":5,"text":"html"}},{"id":483707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Zhao, Qing","contributorId":292852,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","affiliations":[{"id":25644,"text":"Bird Conservancy of the Rockies","active":true,"usgs":false}],"preferred":false,"id":931745,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":931678,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70260921,"text":"70260921 - 2024 - Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making","interactions":[],"lastModifiedDate":"2024-11-15T14:01:02.523252","indexId":"70260921","displayToPublicDate":"2024-10-31T09:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making","docAbstract":"<p>The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making.</p><p>The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system.</p><p>There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world.</p><p>Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties.</p><p>Best practices include:</p><p><strong>Use multiple scenarios</strong> to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making.</p><p><strong>Use multiple climate models within each scenario</strong> to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average.</p><p><strong>Use relevant climate data</strong>. Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application.</p><p><strong>Clearly describe key analysis uncertainties</strong> (including with any climate observations, models, and scenarios used), <strong>and how they were addressed</strong> in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.</p>","language":"English","publisher":"Department of the Interior","doi":"10.21429/hjgj-j073","usgsCitation":"Terando, A.J., Tucker, A.M., Runyon, A.N., Miller, J., Perkins, J.L., Kimbrel, S.W., Cross, A.S., and Boyles, R.P., 2024, Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making, iv, 72 p., https://doi.org/10.21429/hjgj-j073.","productDescription":"iv, 72 p.","ipdsId":"IP-166512","costCenters":[],"links":[{"id":464070,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/unnumbered/70260921/coverthb.jpg"},{"id":464071,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/unnumbered/70260921/70260921.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Terando, Adam J. 0000-0002-9280-043X aterando@usgs.gov","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":173447,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","email":"aterando@usgs.gov","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":918516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":918517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runyon, Amber N. 0000-0002-7282-1217","orcid":"https://orcid.org/0000-0002-7282-1217","contributorId":346252,"corporation":false,"usgs":false,"family":"Runyon","given":"Amber","email":"","middleInitial":"N.","affiliations":[{"id":36976,"text":"U.S. National Park Service","active":true,"usgs":false}],"preferred":false,"id":918518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, James A.","contributorId":346253,"corporation":false,"usgs":false,"family":"Miller","given":"James A.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":918519,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Perkins, Judy L.","contributorId":266176,"corporation":false,"usgs":false,"family":"Perkins","given":"Judy","email":"","middleInitial":"L.","affiliations":[{"id":54938,"text":"U.S. Bureau of Land Management, California State Office, 2800 Cottage Way, Sacramento, CA 95825","active":true,"usgs":false}],"preferred":false,"id":918520,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kimbrel, Sean W.","contributorId":346255,"corporation":false,"usgs":false,"family":"Kimbrel","given":"Sean","email":"","middleInitial":"W.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":918521,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cross, Amanda S.","contributorId":346256,"corporation":false,"usgs":false,"family":"Cross","given":"Amanda","email":"","middleInitial":"S.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":918522,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyles, Ryan P. 0000-0001-9272-867X rboyles@usgs.gov","orcid":"https://orcid.org/0000-0001-9272-867X","contributorId":197670,"corporation":false,"usgs":true,"family":"Boyles","given":"Ryan","email":"rboyles@usgs.gov","middleInitial":"P.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":918523,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70260440,"text":"70260440 - 2024 - Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland","interactions":[],"lastModifiedDate":"2024-11-01T13:42:47.123347","indexId":"70260440","displayToPublicDate":"2024-10-31T08:35:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland","docAbstract":"<p><span>Mineral-rich hardgrounds, such as ferromanganese (FeMn) crusts and phosphorites, occur on seamounts and continental margins, gaining attention for their resource potential due to their enrichment in valuable metals in some regions. This study focuses on the Southern California Borderland (SCB), an area characterized by uneven and heterogeneous topography featuring FeMn crusts, phosphorites, basalt, and sedimentary rocks that occur at varying depths and are exposed to a range of oxygen concentrations. Due to its heterogeneity, this region serves as an optimal setting for investigating the relationship between mineral-rich hardgrounds and benthic fauna. This study characterizes the density, diversity, and community composition of macrofauna (&gt;300 μm) on hardgrounds as a function of substrate type and environment (depth and oxygen ranges). Rocks and their macrofauna were sampled quantitatively using remotely operated vehicles (ROVs) during expeditions in 2020 and 2021 at depths above, within, and below the oxygen minimum zone (OMZ). A total of 3,555 macrofauna individuals were counted and 416 different morphospecies (excluding encrusting bryozoans and hydrozoans) were identified from 82 rocks at depths between 231 and 2,688 m. Average density for SCB macrofauna was 11.08 ± 0.87 ind. 200 cm</span><sup>−2</sup><span>&nbsp;and mean Shannon-Wiener diversity per rock (H′</span><sub>[loge]</sub><span>) was 2.22 ± 0.07. A relationship was found between substrate type and macrofaunal communities. Phosphorite rocks had the highest H′ of the four substrates compared on a per-rock basis. However, when samples were pooled by substrate, FeMn crusts had the highest H′ and rarefaction diversity. Of all the environmental variables examined, water depth explained the largest variance in macrofaunal community composition. Macrofaunal density and diversity values were similar at sites within and outside the OMZ. This study is the first to analyze the macrofaunal communities of mineral-rich hardgrounds in the SCB, which support deep-ocean biodiversity by acting as specialized substrates for macrofaunal communities. Understanding the intricate relationships between macrofaunal assemblages and mineral-rich substrates may inform effects from environmental disruptions associated with deep-seabed mining or climate change. The findings contribute baseline information useful for effective conservation and management of the SCB and will support scientists in monitoring changes in these communities due to environmental disturbance or human impact in the future.</span></p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.18290","usgsCitation":"Guraieb, M., Mendoza, G., Mizell, K., Rouse, G.W., McCarthy, R., Pereira, O.S., and Levin, L.A., 2024, Deep-ocean macrofaunal assemblages on ferromanganese and phosphorite-rich substrates in the Southern California Borderland: PeerJ, v. 12, e18290, 33 p., https://doi.org/10.7717/peerj.18290.","productDescription":"e18290, 33 p.","ipdsId":"IP-166431","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466792,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.18290","text":"Publisher Index Page"},{"id":463531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Southern California Borderlands","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.5,\n              34\n            ],\n            [\n              -121.5,\n              31.5\n            ],\n            [\n              -117,\n              31.5\n            ],\n            [\n              -117,\n              34\n            ],\n            [\n              -121.5,\n              34\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Guraieb, Michelle","contributorId":345846,"corporation":false,"usgs":false,"family":"Guraieb","given":"Michelle","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Guillermo F","contributorId":156382,"corporation":false,"usgs":false,"family":"Mendoza","given":"Guillermo F","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":917696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rouse, Gregory W.","contributorId":345848,"corporation":false,"usgs":false,"family":"Rouse","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCarthy, R.A.","contributorId":345849,"corporation":false,"usgs":false,"family":"McCarthy","given":"R.A.","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pereira, Olivia S.","contributorId":340132,"corporation":false,"usgs":false,"family":"Pereira","given":"Olivia","email":"","middleInitial":"S.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Levin, Lisa A.","contributorId":330607,"corporation":false,"usgs":false,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":917701,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70260810,"text":"70260810 - 2024 - Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing","interactions":[],"lastModifiedDate":"2024-12-10T15:33:45.478559","indexId":"70260810","displayToPublicDate":"2024-10-31T06:56:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing","docAbstract":"<p><span>Many freshwater forested wetlands along the southeastern United States coastline are rapidly transitioning from forest to marsh or open water, due to climate change-related disturbances. Recent studies have found early warning signals (EWS) of regime shifts in other ecosystems, but it is unclear if these can be detected for coastal wetlands. In this study, we examined the ability to detect EWS of regime shifts in coastal wetlands within the Albemarle Pamlico peninsula (APP), North Carolina, U.S.A. We used the Landsat record (1985–2021) to examine trends of normalized difference vegetation index (NDVI) time series for selected areas known to have undergone regime shifts. We found that while 77% of the APP was either stable or revegetating, 22% of the landscape underwent a decrease in NDVI that would indicate a transition from forest to marsh or open water. Of the areas that transitioned, about half (11%) experienced an abrupt decrease in NDVI and 10% experienced a gradual decline. Increasing standard deviation and skewness of time series could serve as EWS of abrupt transitions, but can also provide false negative and positives. Our results suggest that ecosystem transitions from a forest to a marsh or open water can occur both rapidly and slowly, and remote sensing of NDVI time series can help identify EWS for some areas, but not all. Our results allow for prioritization of conservation/restoration of coastlines which will become important in the face of climate change and sea level rise.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10021-024-00938-5","usgsCitation":"Martinez, M., Ardon, M.L., and Gray, J., 2024, Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing: Ecosystems, v. 27, p. 1060-1075, https://doi.org/10.1007/s10021-024-00938-5.","productDescription":"16 p.","startPage":"1060","endPage":"1075","ipdsId":"IP-133828","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":463847,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Albemarle Pamlico Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.63541246515713,\n              36.06271479689754\n            ],\n            [\n              -77.19335586830498,\n              36.06271479689754\n            ],\n            [\n              -77.19335586830498,\n              35.278844140439915\n            ],\n            [\n              -75.63541246515713,\n              35.278844140439915\n            ],\n            [\n              -75.63541246515713,\n              36.06271479689754\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"27","noUsgsAuthors":false,"publicationDate":"2024-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Melinda 0000-0001-6652-9220","orcid":"https://orcid.org/0000-0001-6652-9220","contributorId":290467,"corporation":false,"usgs":true,"family":"Martinez","given":"Melinda","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ardon, Marcelo L","contributorId":346120,"corporation":false,"usgs":false,"family":"Ardon","given":"Marcelo","email":"","middleInitial":"L","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":918160,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Joshua","contributorId":346121,"corporation":false,"usgs":false,"family":"Gray","given":"Joshua","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":918161,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70260817,"text":"70260817 - 2024 - Early detection of wildlife disease pathogens using CRISPR-Cas system methods","interactions":[],"lastModifiedDate":"2024-12-26T16:53:43.313328","indexId":"70260817","displayToPublicDate":"2024-10-31T06:41:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19828,"text":"The CRISPR Journal","active":true,"publicationSubtype":{"id":10}},"title":"Early detection of wildlife disease pathogens using CRISPR-Cas system methods","docAbstract":"Wildlife diseases are a considerable threat to human health, conservation, and the economy. Surveillance is a critical component to mitigate the impact of animal diseases in these sectors. To monitor human diseases, CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated protein) biosensors have proven instrumental as diagnostic tools capable of detecting unique DNA and RNA sequences related to their associated pathogens. However, despite the significant advances in the general development of CRISPR-Cas biosensors, their use to support wildlife disease management is lagging. In some cases, wildlife diseases of concern could be rapidly surveyed using these tools with minimal technical, operational, or cost requirements to end users. This review explores the potential to further leverage this technology to advance wildlife disease monitoring and highlights how concerted standardization of protocols can help to ensure data reliability.","language":"English","publisher":"Mary Ann Liebert, Inc.","doi":"10.1089/crispr.2024.0030","usgsCitation":"Perez, A.A., Vazquez-Meves, G., and Hunter, M., 2024, Early detection of wildlife disease pathogens using CRISPR-Cas system methods: The CRISPR Journal, v. 7, no. 6, p. 327-342, https://doi.org/10.1089/crispr.2024.0030.","productDescription":"16 p.","startPage":"327","endPage":"342","ipdsId":"IP-162277","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":498262,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/crispr.2024.0030","text":"Publisher Index Page"},{"id":463845,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Perez, Adam Alberto 0000-0001-5057-1133","orcid":"https://orcid.org/0000-0001-5057-1133","contributorId":332516,"corporation":false,"usgs":true,"family":"Perez","given":"Adam","email":"","middleInitial":"Alberto","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez-Meves, Guelaguetza 0000-0001-8100-2945","orcid":"https://orcid.org/0000-0001-8100-2945","contributorId":346127,"corporation":false,"usgs":true,"family":"Vazquez-Meves","given":"Guelaguetza","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":918206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207584,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918207,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70259877,"text":"ofr20241055 - 2024 - Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","interactions":[],"lastModifiedDate":"2025-12-22T20:25:53.918489","indexId":"ofr20241055","displayToPublicDate":"2024-10-30T13:10:08","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1055","displayTitle":"Sand Supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","title":"Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California","docAbstract":"<p>Sediment from the Central Valley via the Sacramento-San Joaquin Delta (Delta) and Suisun Bay is a primary source of sand to San Francisco Bay, California. Sand is mined from San Francisco Bay for commercial purposes, such as for use in concrete for construction. To better understand the supply of sand to Suisun Bay and San Francisco Bay, the U.S. Geological Survey (USGS), in cooperation with the San Francisco Bay Estuary Institute (SFEI) and the San Francisco Bay Conservation Development Commission (BCDC), initiated this study to compile and synthesize historical data and estimate the total sediment and sand portion of sediment exiting the Delta to Suisun Bay for a 20-year period between water years 2001 and 2020.</p><p>Sediment exiting the Delta is a combination of suspended sediment and bedload sediment. Seaward bedload transport was estimated using bedload transport equations and available hydraulic data at the two downstream-most streamgages in the Delta (where velocity is measured). Those two streamgages are about 25 kilometers upstream from the “exit” of the Delta at Mallard Island. The combined average annual net (seaward) bedload at these two streamgages was estimated to be 0.102 million cubic meters per year (Mm<sup>3</sup>/yr) for the study period. This volume of bedload is equivalent to 0.155 million metric tons per year (Mt/yr), assuming a bulk density of 1.517 metric tons per cubic meter (t/m<sup>3</sup>). The bedload composition was estimated to be 88 percent sand.</p><p>Between the two streamgages and Mallard Island, an annual average of 0.076 Mm<sup>3</sup>/yr of material was removed through mining during the study period, of which 97.5 percent was sand. In addition, 0.053 Mm<sup>3</sup>/yr was removed through dredging to support shipping and navigation, of which 76 percent was sand. The total volume of mined and dredged sediment material was approximately 0.128 Mm<sup>3</sup>/yr, equivalent to 0.194 Mt/yr, assuming a bulk density of 1.517 t/m<sup>3</sup>.</p><p>Assuming the estimated bedload reaching Mallard Island was reduced by mining and dredging, a mean bedload flux of −0.009 Mm<sup>3</sup>/yr was computed (using a bulk density of 1.517 t/m<sup>3</sup>), suggesting a deficit or landward transport of bedload. However, the total suspended-sediment and suspended-sand flux was in the seaward direction. The average total suspended flux of sediment to Suisun Bay through the cross section at the Mallard Island streamgage was estimated to be 0.482 million metric tons per year (Mt/yr; 0.015 Mt/yr sand) in the seaward direction. The results indicate a net flux out of the Delta of 0.469 Mt/yr of total sediment and 0.003 Mt/yr of sand.</p><p>The primary limitation of the study was the lack of physical bedload measurements to validate the bedload estimates. To better refine the estimates of bedload, physical measurements of bedload or repeat bathymetry would be necessary for a range of flow conditions. Such measurements could be used to calibrate transport equations and quantify the uncertainty in such estimates.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241055","collaboration":"Prepared in cooperation with the San Francisco Estuary Institute Aquatic Science Center, the California State Coastal Conservancy, and the San Francisco Bay Conservation and Development Commission","programNote":"Water Availability and Use Science Program","usgsCitation":"Marineau, M.D., Hart, D., Ely, C.P., and McKee, L., 2024, Sand supply to San Francisco Bay from the Sacramento and San Joaquin Rivers of the Central Valley, California: U.S. Geological Survey Open-File Report 2024–1055, 18 p., https://doi.org/10.3133/ofr20241055.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-157560","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":463205,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1055/images"},{"id":463204,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.xml"},{"id":463203,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1055/ofr20241055.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463201,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I18RGG","text":"USGS Data Release","description":"Ely, C.P., and Marineau, M.D., 2023, Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9I18RGG.","linkHelpText":"Estimated bedload transport rates at Rio Vista and Jersey Point, California, 2011–2020"},{"id":497888,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117739.htm","linkFileType":{"id":5,"text":"html"}},{"id":463206,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/ofr20241055/full"},{"id":463202,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1055/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.29538442038356,\n              38.56577858557708\n            ],\n            [\n              -122.29538442038356,\n              37.65383277017135\n            ],\n            [\n              -121.19683028697757,\n              37.65383277017135\n            ],\n            [\n              -121.19683028697757,\n              38.56577858557708\n            ],\n            [\n              -122.29538442038356,\n              38.56577858557708\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Data Collection and Analysis</li><li>Results</li><li>Discussion</li><li>References Cited</li><li>Appendix 1</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2024-10-30","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":916825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, David 0000-0002-1700-5524","orcid":"https://orcid.org/0000-0002-1700-5524","contributorId":345512,"corporation":false,"usgs":true,"family":"Hart","given":"David","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":916826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ely, Christopher P. 0000-0001-5276-5046","orcid":"https://orcid.org/0000-0001-5276-5046","contributorId":219282,"corporation":false,"usgs":true,"family":"Ely","given":"Christopher P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":916827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKee, Lester","contributorId":205882,"corporation":false,"usgs":false,"family":"McKee","given":"Lester","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":916828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261886,"text":"70261886 - 2024 - Patterns and drivers of cottonwood mortality in the middle Rio Grande, New Mexico, USA","interactions":[],"lastModifiedDate":"2024-12-31T16:05:59.249922","indexId":"70261886","displayToPublicDate":"2024-10-30T11:05:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and drivers of cottonwood mortality in the middle Rio Grande, New Mexico, USA","docAbstract":"<p>Riparian ecosystems are some of the most valuable and vulnerable on the planet. Riparian tree mortality is increasing in the western United States, where altered streamflows are combining with warming climate. Between 2011 and 2013, one third of an extensive stand of <i>Populus deltoides</i> var. <i>wislizeni</i> (Rio Grande cottonwood) died along the middle Rio Grande on the Pueblo of Santa Ana in New Mexico. Mortality coincided with a severe drought that followed a decade of decreasing streamflow, but it was heterogeneous, with adjacent patches of dead and live trees. The goal of this research was to determine the drivers of mortality to provide insights into future risks of die-off and potential management interventions. We compared tree age, competition, tree-ring widths, sediment particle size and climate influences between live and dead forest patches in a nested plot design. Live and dead trees had similar age, stand density and particle sizes of shallow sediments. Tree-ring widths had the highest correlations with July–September streamflow (1932–2013). All trees had declining ring growth since 1992, coinciding with declining late summer streamflow. An accelerated decline in growth began in 2002, corresponding to recent warmer droughts. Trees that died had lower ring growth 3 years prior to death and in the mid-1900s. Dead trees also had coarser deep sediments 2.4–3.7 m below ground, suggesting that reduced water holding capacity was an important factor for mortality. Water management to increase streamflow during the late summer, especially during times of extended drought, could reduce mortality risk in the face of projected increasingly warm droughts.</p>","language":"English","publisher":"Wiley","doi":"10.1002/eco.2692","usgsCitation":"Varani, H., Margolis, E.Q., Muldavin, E., and Pockman, W.T., 2024, Patterns and drivers of cottonwood mortality in the middle Rio Grande, New Mexico, USA: Ecohydrology, v. 17, no. 8, e2692, 13 p., https://doi.org/10.1002/eco.2692.","productDescription":"e2692, 13 p.","ipdsId":"IP-164113","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":466793,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eco.2692","text":"External Repository"},{"id":465568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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,{"id":70260103,"text":"sir20245097 - 2024 - Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","interactions":[],"lastModifiedDate":"2025-12-22T20:23:35.597848","indexId":"sir20245097","displayToPublicDate":"2024-10-30T10:46:09","publicationYear":"2024","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":"2024-5097","displayTitle":"Use of Continuous Water-Quality Time-Series Data to Compute Total Phosphorus Concentrations and Loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","title":"Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22","docAbstract":"<p>In support of Missouri’s Nutrient Loss Reduction Strategy, which was created to reduce the nutrient contamination of Missouri’s waterways from point and nonpoint sources, total phosphorus concentrations and loads were computed for the Missouri River at St. Joseph, Missouri, streamgage (U.S. Geological Survey station 06818000) and the Missouri River at Hermann, Mo., streamgage (U.S. Geological Survey station 06934500) for October 2007 to September 2022 using surrogate models and continuous turbidity sensor data. To obtain a more complete total phosphorus record for the study period, LOAD ESTimator (LOADEST) regression models using flow were used when turbidity sensor data were unavailable to estimate daily total phosphorus loads. This report presents the methods and results for the computed total phosphorus concentrations, loads, and yields for the two study sites on the Missouri River. With continued data collection and ongoing model evaluation and maintenance, the surrogate models may be useful into the future for computing total phosphorus concentrations and loads.</p><p>Daily mean total phosphorus concentrations calculated using a surrogate model at the Missouri River at St. Joseph, Mo., streamgage during the 15-year study period (water years 2008 through 2022) ranged from 0.104 to 4.56 milligrams per liter (mg/L; median of 0.272 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 5.19 to 1,760 tons per day (tons/d; median of 36.5 tons/d). Annual loads ranged from 9,570 tons in water year 2022 to 50,500 tons in water year 2019. The total load for the study period was 437,000 tons.</p><p>For the Missouri River at Hermann, Mo., streamgage during the same 15-year study period, daily mean total phosphorus concentrations, calculated using surrogate models applied to low and high turbidity values, ranged from 0.183 to 1.97 mg/L (median of 0.319 mg/L), and computed total phosphorus daily loads (with gaps in the daily record filled using the LOADEST regression model) ranged from 12.7 to 1,970 tons/d (median of 76.8 tons/d). Annual loads ranged from 22,600 tons in water year 2022 to 101,000 tons in water year 2019. The total load for the study period was 833,000 tons, which is nearly twice that at the Missouri River at St. Joseph, Mo., streamgage.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245097","collaboration":"Prepared in cooperation with Missouri Department of Natural Resources","usgsCitation":"Markland, K.M., 2024, Use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22: U.S. Geological Survey Scientific Investigations Report 2024–5097, 26 p., https://doi.org/10.3133/sir20245097.","productDescription":"Report: vii, 26 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-161927","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463254,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":463253,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245097/full"},{"id":463252,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5097/images/"},{"id":463251,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5097/sir20245097.XML"},{"id":463250,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5097/sir20245097.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5097"},{"id":463249,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5097/coverthb.jpg"},{"id":497886,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117740.htm","linkFileType":{"id":5,"text":"html"}},{"id":463255,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P17PHYDZ","text":"USGS data release","linkHelpText":"Data and model archive summaries to support use of continuous water-quality time-series data to compute total phosphorus concentrations and loads for the Missouri River at St. Joseph and Hermann, Missouri, 2007–22"}],"country":"United States","state":"Missouri","city":"Hermann, St. Joseph","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.48454431267173,\n              38.7389466373896\n            ],\n            [\n              -91.48454431267173,\n              38.678901791033724\n            ],\n            [\n              -91.40123726792416,\n              38.678901791033724\n            ],\n            [\n              -91.40123726792416,\n              38.7389466373896\n            ],\n            [\n              -91.48454431267173,\n              38.7389466373896\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.002636709889,\n              39.854445017011784\n            ],\n            [\n              -95.002636709889,\n              39.62967769348404\n            ],\n            [\n              -94.65186218929263,\n              39.62967769348404\n            ],\n            [\n              -94.65186218929263,\n              39.854445017011784\n            ],\n            [\n              -95.002636709889,\n              39.854445017011784\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Water-Quality Sample and Sensor Data</li><li>Surrogate Models</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supplemental Figures</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-10-30","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Markland, Kendra M. 0000-0002-0276-8684 kmarkland@usgs.gov","orcid":"https://orcid.org/0000-0002-0276-8684","contributorId":306212,"corporation":false,"usgs":true,"family":"Markland","given":"Kendra","email":"kmarkland@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":916997,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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