{"pageNumber":"43","pageRowStart":"1050","pageSize":"25","recordCount":46619,"records":[{"id":70261771,"text":"70261771 - 2025 - Practical application of time-lapse camera imagery to develop water-level data for three hydrologic monitoring sites in Wisconsin during water year 2020","interactions":[],"lastModifiedDate":"2024-12-30T21:17:43.800451","indexId":"70261771","displayToPublicDate":"2024-12-19T11:03:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5836,"text":"Journal of Hydrology X","onlineIssn":"2589-9155","active":true,"publicationSubtype":{"id":10}},"title":"Practical application of time-lapse camera imagery to develop water-level data for three hydrologic monitoring sites in Wisconsin during water year 2020","docAbstract":"Using camera imagery to measure water level (camera-stage) is a well-researched area of study. Previous camera-stage studies have shown promising results when implementing this technology with tight constraints on test conditions. However, there is a need for a more comprehensive evaluation of the extensibility of camera-stage to practical applications. Therefore, the aim of this study was to test a camera-stage method under a wide variety of test conditions to better understand the successes and challenges of using this technology in real-world scenarios. In this study, this approach was tested during Water Year 2020 at three existing U.S. Geological Study (USGS) stream gaging stations in south central Wisconsin that had existing USGS water-level instrumentation. The specific reference objects tested were white pipes and a concrete wall. Since successful application of camera-stage relies on use of suitable images, all captured images in this study were visually inspected to determine suitability for application of camera-stage. Camera-stage measurements were then computed only on images deemed suitable and the results were compared with ground-truth stage values to determine the accuracy. For the purposes of this study, camera-stage values within ±0.10 ft of the actual stage were considered acceptable. One major challenge highlighted was the potential difficulty in obtaining suitable imagery, with the proportion of suitable images varying greatly between the four trials from 38 % to 92 %. The results from applying camera-stage to suitable images were encouraging though, with 79 % to 99 % of evaluated camera-stage values qualifying as acceptable among the four test trials.","language":"English","publisher":"Elsevier","doi":"10.1016/j.hydroa.2024.100199","usgsCitation":"Johnson, K.E., Reneau, P., and Komiskey, M.J., 2025, Practical application of time-lapse camera imagery to develop water-level data for three hydrologic monitoring sites in Wisconsin during water year 2020: Journal of Hydrology X, v. 26, 100199, 12 p., https://doi.org/10.1016/j.hydroa.2024.100199.","productDescription":"100199, 12 p.","ipdsId":"IP-152041","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466673,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hydroa.2024.100199","text":"Publisher Index Page"},{"id":465442,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Sauk County","otherGeospatial":"Lake Redstone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.10509451311265,\n              43.649948800545786\n            ],\n            [\n              -90.10509451311265,\n              43.58310310760555\n            ],\n            [\n              -90.07129958906278,\n              43.58310310760555\n            ],\n            [\n              -90.07129958906278,\n              43.649948800545786\n            ],\n            [\n              -90.10509451311265,\n              43.649948800545786\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"26","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Keegan Eland 0000-0003-1940-4542","orcid":"https://orcid.org/0000-0003-1940-4542","contributorId":332782,"corporation":false,"usgs":true,"family":"Johnson","given":"Keegan","email":"","middleInitial":"Eland","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reneau, Paul 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":217293,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Komiskey, Matthew J. 0000-0003-2962-6974 mjkomisk@usgs.gov","orcid":"https://orcid.org/0000-0003-2962-6974","contributorId":1776,"corporation":false,"usgs":true,"family":"Komiskey","given":"Matthew","email":"mjkomisk@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":921735,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263701,"text":"70263701 - 2025 - Evaluating approaches for integrating species distributions in spatial conservation planning","interactions":[],"lastModifiedDate":"2025-02-24T14:14:51.37261","indexId":"70263701","displayToPublicDate":"2024-12-19T09:17:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating approaches for integrating species distributions in spatial conservation planning","docAbstract":"Map-based decision support tools (DSTs) that use species distributions are an important means of identifying priority areas for conservation. The 2020 Wisconsin Waterfowl Habitat Conservation Strategy (WWHCS) uses a DST to identify priority ecological landscapes and watersheds to guide waterfowl habitat projects. The WWHCS DST relies on waterfowl habitat suitability layers derived through expert opinion in lieu of species distributions, a common approach in DSTs. Given the inherent subjectivity of expert opinion, data-driven species distributions such as those available from citizen science projects, could provide more accurate information and better identify areas important for waterfowl conservation. Here, we explore the application of relative abundance products available through the eBird Status and Trends project as an alternative to expert-derived habitat suitability layers in the WWHCS DST. Our objectives were to compare seasonal species distributions derived from habitat suitability models (expert-derived) and species distribution models (eBird-derived) and determine whether differences influenced DST prioritizations. Correlations between expert- and eBird-derived distributions were generally low to moderate for the breeding and fall layers (ρ: -0.03–0.76), and least for the spring (ρ: -0.49–0.72). There was minimal agreement among top-ranked ecological landscapes (40%) and watersheds (28%) between the expert- and eBird-derived versions of the DST. Overall, our results suggest the DST may benefit from incorporating data-driven species distributions. However, additional work validating eBird relative abundance against professional surveys (e.g., aerial counts) and empirical studies evaluating waterfowl habitat selection and vital rates are important future considerations for the WWHCS DST and waterfowl habitat conservation in Wisconsin.","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.13281","usgsCitation":"Winiarski, J., Shipley, A., Fowler, D., Palumbo, M., and Straub, J., 2025, Evaluating approaches for integrating species distributions in spatial conservation planning: Conservation Science and Practice, v. 7, no. 1, e13281, 15 p., https://doi.org/10.1111/csp2.13281.","productDescription":"e13281, 15 p.","ipdsId":"IP-154437","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487659,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.13281","text":"Publisher Index Page"},{"id":482268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Winiarski, Jason M.","contributorId":351090,"corporation":false,"usgs":false,"family":"Winiarski","given":"Jason M.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":927891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shipley, Amy A.","contributorId":351091,"corporation":false,"usgs":false,"family":"Shipley","given":"Amy A.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":927892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowler, Drew Nathan 0000-0001-9347-4579","orcid":"https://orcid.org/0000-0001-9347-4579","contributorId":341123,"corporation":false,"usgs":true,"family":"Fowler","given":"Drew Nathan","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":927893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palumbo, Matthew D.","contributorId":351092,"corporation":false,"usgs":false,"family":"Palumbo","given":"Matthew D.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":927894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Straub, Jacob N.","contributorId":351093,"corporation":false,"usgs":false,"family":"Straub","given":"Jacob N.","affiliations":[{"id":83917,"text":"Jacob N. 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,{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","interactions":[{"subject":{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261121","publicationYear":"2024","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"predicate":"SUPERSEDED_BY","object":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"id":1}],"lastModifiedDate":"2025-05-27T15:27:07.879775","indexId":"70261880","displayToPublicDate":"2024-12-18T10:28:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","docAbstract":"<p><span>The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security, and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using boosted regression tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.</span></p>","language":"English","publisher":"Nordic Society Oikos","doi":"10.1111/jav.03296","usgsCitation":"Hardy, M., Williams, C.K., Ladman, B.S., Pitesky, M.E., Overton, C.T., Casazza, M.L., Matchett, E., Prosser, D., and Buler, J.J., 2025, Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways: Journal of Avian Biology, v. 2025, no. 3, e03296, 16 p., https://doi.org/10.1111/jav.03296.","productDescription":"e03296, 16 p.","ipdsId":"IP-164600","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":465576,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466708,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jav.03296","text":"External Repository"}],"country":"United States","state":"California, Delaware, Maryland, New Jersey, North Carolina, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.80539700167103,\n              35.24130047209148\n            ],\n            [\n              -118.52455880536989,\n              35.705136039724024\n            ],\n            [\n              -119.16293845153683,\n              36.70091248537601\n            ],\n            [\n              -121.62299624153891,\n          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K.","contributorId":202263,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":922122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":922123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":922124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":922127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":922128,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":922129,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70266203,"text":"70266203 - 2025 - Effects of Mycoplasma ovipneumoniae, abundance, and environmental conditions on bighorn sheep lamb:ewe ratios and adult survival in New Mexico","interactions":[],"lastModifiedDate":"2025-04-30T15:22:40.392123","indexId":"70266203","displayToPublicDate":"2024-12-18T08:15:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effects of Mycoplasma ovipneumoniae, abundance, and environmental conditions on bighorn sheep lamb:ewe ratios and adult survival in New Mexico","docAbstract":"<p><i>Mycoplasma ovipneumoniae</i><span>&nbsp;is a primary causative agent responsible for initiating polymicrobial pneumonia in bighorn sheep (</span><i>Ovis canadensis</i><span>). Infections of bighorn sheep populations are typically characterized by initial all-age epizootics followed by long-term periods of repressed juvenile (lamb) survival. Populations of bighorn sheep in New Mexico, USA, were thought to be free of this pathogen prior to 2017 but recent infection of multiple herds raised concerns regarding impacts on population size and juvenile:female ratios. Using aerial survey, survival, and disease sampling data in an exploratory framework, we (1) characterize age-related differences in&nbsp;</span><i>M. ovipneumoniae</i><span>&nbsp;prevalence and seroprevalence, (2) quantify differences in lamb:ewe ratios pre- and post-</span><i>M. ovipneumoniae</i><span>&nbsp;detection, and (3) investigate differences in survival between previously exposed and naïve individuals. From 2007 to 2022, we sampled 466 bighorn sheep across 19 populations in New Mexico for&nbsp;</span><i>M. ovipneumoniae</i><span>&nbsp;exposure. While the timing of initial herd infections varied across populations, one population sustained active infections for over 15 years. We found reduced juvenile:female ratios post&nbsp;</span><i>M. ovipneumoniae</i><span>&nbsp;exposure for both desert (</span><i>O. c. mexicana</i><span>) and Rocky Mountain (</span><i>O. c. canadensis</i><span>) bighorn sheep populations. Post-exposure ratio declines ranged from 20% to 69%. Evaluation of population size and environmental condition effects on juvenile:female ratios indicated varying impacts for each subspecies. Notably, population size was negatively related to Rocky Mountain juvenile:female ratios only after populations were exposed to&nbsp;</span><i>M. ovipneumoniae</i><span>. Additionally, climatic conditions in the previous lambing season and pre-parturition time frame were associated with juvenile:female ratios for Rocky Mountain populations, while juvenile:female ratios of desert bighorn appeared to only be affected by pre-parturition climatic conditions. Kaplan–Meier survival estimation of previously exposed, but putatively recovered, individuals (</span><i>n</i><span> = 31) and naïve individuals (</span><i>n</i><span> = 70) revealed lower (75%; 95% CI: 62%–93%) but not statistically significant (</span><i>p</i><span> = 0.2) 1-year survival rates for individuals that were seropositive but not actively infected, when compared to seronegative individuals (88%; 95% CI: 81%–97%). These results collectively suggest that following&nbsp;</span><i>M. ovipneumoniae</i><span>&nbsp;introduction, bighorn sheep populations in New Mexico could be limited by lamb survival.</span></p>","language":"English","publisher":"Ecological Society of  America","doi":"10.1002/ecs2.70095","usgsCitation":"Padilla, C., Ruhl, C., Cain, J.W., and Gompper, M., 2025, Effects of Mycoplasma ovipneumoniae, abundance, and environmental conditions on bighorn sheep lamb:ewe ratios and adult survival in New Mexico: Ecosphere, v. 15, no. 12, e70095, 16 p., https://doi.org/10.1002/ecs2.70095.","productDescription":"e70095, 16 p.","ipdsId":"IP-160978","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487888,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70095","text":"Publisher Index Page"},{"id":485206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.10493017089716,\n              36.99701123533072\n            ],\n            [\n              -109.10493017089716,\n              31.32626702398963\n            ],\n            [\n              -108.04838374726572,\n              31.294505749181546\n            ],\n            [\n              -108.10578472127759,\n              31.655212435608266\n            ],\n            [\n              -103.0558174759306,\n              31.858449691798413\n            ],\n            [\n              -102.86724609707606,\n              36.99701123533072\n            ],\n            [\n              -109.10493017089716,\n              36.99701123533072\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Padilla, Colton J.","contributorId":353982,"corporation":false,"usgs":false,"family":"Padilla","given":"Colton J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":934909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruhl, Caitlin Q.","contributorId":353983,"corporation":false,"usgs":false,"family":"Ruhl","given":"Caitlin Q.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":934910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gompper, Matthew E.","contributorId":353984,"corporation":false,"usgs":false,"family":"Gompper","given":"Matthew E.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":934912,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263384,"text":"70263384 - 2025 - SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters","interactions":[],"lastModifiedDate":"2025-05-28T14:46:30.935116","indexId":"70263384","displayToPublicDate":"2024-12-17T11:33:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters","docAbstract":"<p>Spectral source parameters used to estimate an earthquake’s stress drop (Δσ) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress-Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low-frequency displacement (Ω0) and corner frequency (<i>f</i><sub>c</sub> ) by fitting a smooth function to benchmark displacement spectra. Participants used linear- or log-sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate Ω0, <i>f</i><sub>c</sub> , and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in Ω0 and f c can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade-off between Ω0 and <i>f</i><sub>c</sub> may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω0 and somewhat higher f c compared to those assuming a Brune model, although resulting Δσ estimates are similar. When compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240140","usgsCitation":"Cochran, E.S., Baltay Sundstrom, A.S., Chu, S., Abercrombie, R., Bindi, D., Chen, X., Parker, G.A., Pennington, C., Shearer, P.M., and Trugman, D.T., 2025, SCEC/USGS Community Stress Drop Validation Study: How spectral fitting approaches influence measured source parameters: Bulletin of the Seismological Society of America, v. 115, no. 3, p. 760-776, https://doi.org/10.1785/0120240140.","productDescription":"17 p.","startPage":"760","endPage":"776","ipdsId":"IP-167281","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.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              -118.0604945971769,\n              36.16526962047753\n            ],\n            [\n              -118.0604945971769,\n              35.25143920487821\n            ],\n            [\n              -116.9963574607869,\n              35.25143920487821\n            ],\n            [\n              -116.9963574607869,\n              36.16526962047753\n            ],\n            [\n              -118.0604945971769,\n              36.16526962047753\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"115","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chu, Shanna","contributorId":350708,"corporation":false,"usgs":false,"family":"Chu","given":"Shanna","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":926728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abercrombie, Rachel E.","contributorId":293131,"corporation":false,"usgs":false,"family":"Abercrombie","given":"Rachel E.","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":926729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bindi, Dino","contributorId":264168,"corporation":false,"usgs":false,"family":"Bindi","given":"Dino","email":"","affiliations":[],"preferred":false,"id":926730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, X.","contributorId":203813,"corporation":false,"usgs":false,"family":"Chen","given":"X.","email":"","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":926731,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926732,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pennington, Colin","contributorId":329842,"corporation":false,"usgs":false,"family":"Pennington","given":"Colin","affiliations":[{"id":16721,"text":"LLNL","active":true,"usgs":false}],"preferred":false,"id":926733,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shearer, Peter M.","contributorId":197012,"corporation":false,"usgs":false,"family":"Shearer","given":"Peter","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":926734,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Trugman, Daniel T.","contributorId":197011,"corporation":false,"usgs":false,"family":"Trugman","given":"Daniel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":926735,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70261946,"text":"70261946 - 2025 - Intra-urban variations in land surface phenology in a semi-arid environment","interactions":[],"lastModifiedDate":"2025-01-06T15:37:37.483741","indexId":"70261946","displayToPublicDate":"2024-12-17T09:28:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Intra-urban variations in land surface phenology in a semi-arid environment","docAbstract":"<p><span>Urban vegetation is growing in importance as cities use 'green infrastructure' to mitigate the impacts of climate change, reduce extreme heat, and improve human health and comfort. However, due to the heterogeneity of city landscapes, urban vegetation experiences a diverse range of environmental conditions, potentially leading to differences in growing season timing and length within cities. Here, we investigate physical drivers of urban land surface phenology and timing within a semi-arid city (Denver, CO, USA) using four years (2018–2021) of remotely sensed vegetation indices, modelled air temperature, and land cover datasets. Within the metropolitan region study area, satellite-based vegetation index measurements indicate that growing season length is variable on sub-neighborhood spatial scales. This variability is largely due to differences in the timing of fall senescence, as opposed to early season growth. Areas with substantial fractions of irrigated land cover tend to remain greener for longer, while unirrigated and cooler areas are correlated with an earlier end to the growing season (up to ∼two months shorter). These findings complement those from non-arid cities where surface and air temperature are the dominant environmental control on phenological timing. Results here indicate the importance of soil moisture for phenology in semi-arid regions and suggest unique semi-arid urban growing season dynamics and temperature-vegetation feedbacks. These interactions have implications for water, heat, and vegetation management strategies to maximize ecosystem services in water-limited environments.</span></p>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ad9759","usgsCitation":"Crawford, B., Kelsey, K., Ibsen, P.C., Rees, A., and Charobee, A., 2025, Intra-urban variations in land surface phenology in a semi-arid environment: Environmental Research Letters, v. 20, no. 1, 014036, 12 p., https://doi.org/10.1088/1748-9326/ad9759.","productDescription":"014036, 12 p.","ipdsId":"IP-162227","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":466676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ad9759","text":"Publisher Index Page"},{"id":465673,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.26461885813289,\n              39.98298361550752\n            ],\n            [\n              -105.26461885813289,\n              39.07785819197471\n            ],\n            [\n              -104.18241816311294,\n              39.07785819197471\n            ],\n            [\n              -104.18241816311294,\n              39.98298361550752\n            ],\n            [\n              -105.26461885813289,\n              39.98298361550752\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Crawford, Ben","contributorId":347747,"corporation":false,"usgs":false,"family":"Crawford","given":"Ben","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":922372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelsey, Kathy","contributorId":347748,"corporation":false,"usgs":false,"family":"Kelsey","given":"Kathy","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":922373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":922374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rees, Amanda","contributorId":347749,"corporation":false,"usgs":false,"family":"Rees","given":"Amanda","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":922375,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charobee, Amanda","contributorId":347770,"corporation":false,"usgs":false,"family":"Charobee","given":"Amanda","affiliations":[],"preferred":false,"id":922411,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70266432,"text":"70266432 - 2025 - First records distribution models to guide biosurveillance for non-native species","interactions":[],"lastModifiedDate":"2025-05-06T13:48:33.176393","indexId":"70266432","displayToPublicDate":"2024-12-16T08:44:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"First records distribution models to guide biosurveillance for non-native species","docAbstract":"<p><span>Quickly locating new populations of non-native species can reduce the ecological and economic costs of species invasions. However, the difficulty of predicting which new non-native species will establish, and where, has limited active post-border biosurveillance efforts. Because pathways of introduction underlie spatial patterns of establishment risk, an intuitive approach is to search for new non-native species in areas where many non-native species have first been detected in the past. We formalize this intuition via first records distribution models (FRDMs), which apply species distribution modeling methods to the collection of first occurrence records across species (i.e. one record per species). We define FRDMs as statistical models that quantify environmental conditions associated with species' first naturalized records to predict spatial patterns of establishment risk. We model the first records of non-native plants in the conterminous USA as a proof-of-concept. The novelty of FRDMs is that their inferences apply not just to the species that contributed data; they provide a rigorous framework for predicting hotspots of invasion for new non-native taxa that share a pathway of introduction with the modeled species. FRDMs can guide survey efforts for new non-native taxa at multiple scales and across ecosystems.</span></p>","language":"English","publisher":"Nordic Society Oikos","doi":"10.1111/ecog.07522","usgsCitation":"Sofaer, H., Williams, D.A., Jarnevich, C.S., Shadwell, K.S., Kittle, C., Pearse, I.S., Fortini, L., and Brock, K., 2025, First records distribution models to guide biosurveillance for non-native species: Ecography, v. 2025, no. 4, e07522, 10 p., https://doi.org/10.1111/ecog.07522.","productDescription":"e07522, 10 p.","ipdsId":"IP-162607","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":490101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.07522","text":"Publisher Index Page"},{"id":485441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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]\n}","volume":"2025","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":935917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Demetra A. 0000-0002-5171-8640","orcid":"https://orcid.org/0000-0002-5171-8640","contributorId":332472,"corporation":false,"usgs":false,"family":"Williams","given":"Demetra","email":"","middleInitial":"A.","affiliations":[{"id":79471,"text":"Student contractor to the U.S. Geological Survey, Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":935918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":935919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shadwell, Keana S. 0000-0001-6835-425X","orcid":"https://orcid.org/0000-0001-6835-425X","contributorId":332473,"corporation":false,"usgs":false,"family":"Shadwell","given":"Keana","email":"","middleInitial":"S.","affiliations":[{"id":79471,"text":"Student contractor to the U.S. Geological Survey, Fort Collins Science Center","active":true,"usgs":false}],"preferred":false,"id":935920,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kittle, Caroline","contributorId":354586,"corporation":false,"usgs":false,"family":"Kittle","given":"Caroline","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":935921,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":935922,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":935923,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brock, Kelsey C.","contributorId":354589,"corporation":false,"usgs":false,"family":"Brock","given":"Kelsey C.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":935924,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70262818,"text":"70262818 - 2025 - Participatory engagement to reduce communication gaps","interactions":[],"lastModifiedDate":"2025-04-28T14:58:06.529283","indexId":"70262818","displayToPublicDate":"2024-12-14T08:57:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Participatory engagement to reduce communication gaps","docAbstract":"<p><span>Underserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underserved coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. Here we outline our participatory engagement framework and process, along with two specific resources developed with the information collected from this effort. These resources are available in English and Spanish and consist of user-friendly, non-technical information products. Among them are: (1) a website where users can learn about USGS research on landslides, hurricanes, earthquakes, water resources, coastal hazards, tsunamis, and ecosystem hazards and environmental contaminants, and (2) a geonarrative highlighting shoreline changes in Puerto Rico with sections on historical shoreline trends, hurricane impacts, and potential solutions that could help protect communities and mitigate coastal hazards. Continuing participatory engagement in future projects could enhance the accessibility and usability of natural hazards resources within the community.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-024-06860-2","usgsCitation":"Torres-Garcia, L.M., Valdés Pizzini, M., Valdés-Calderón, K., Frank-Gilchrist, D.P., Kotowicz, D., Maldonado, E., and Vargas-Babilonia, P., 2025, Participatory engagement to reduce communication gaps: Natural Hazards, v. 121, p. 6367-6390, https://doi.org/10.1007/s11069-024-06860-2.","productDescription":"24 p.","startPage":"6367","endPage":"6390","ipdsId":"IP-158218","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":480984,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":481045,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11069-024-06860-2","text":"Publisher Index Page"}],"country":"United States","city":"San Juan","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -66.0659062782679,\n              18.46319106779258\n            ],\n            [\n              -66.0659062782679,\n              18.449924094571088\n            ],\n            [\n              -66.03964964413582,\n              18.449924094571088\n            ],\n            [\n              -66.03964964413582,\n              18.46319106779258\n            ],\n            [\n              -66.0659062782679,\n              18.46319106779258\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"121","noUsgsAuthors":false,"publicationDate":"2024-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Torres-Garcia, Legna M. 0000-0002-6786-5944 ltorresgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-5944","contributorId":196150,"corporation":false,"usgs":true,"family":"Torres-Garcia","given":"Legna","email":"ltorresgarcia@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":924895,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valdés Pizzini, Manuel 0000-0001-5288-9903","orcid":"https://orcid.org/0000-0001-5288-9903","contributorId":349831,"corporation":false,"usgs":false,"family":"Valdés Pizzini","given":"Manuel","affiliations":[{"id":83520,"text":"Interdisciplinary Center for Coastal Studies (CIEL) at the University of Puerto Rico in Mayagüez","active":true,"usgs":false}],"preferred":false,"id":924896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valdés-Calderón, Krystalliá 0009-0000-1209-9245","orcid":"https://orcid.org/0009-0000-1209-9245","contributorId":349832,"corporation":false,"usgs":false,"family":"Valdés-Calderón","given":"Krystalliá","affiliations":[{"id":83520,"text":"Interdisciplinary Center for Coastal Studies (CIEL) at the University of Puerto Rico in Mayagüez","active":true,"usgs":false}],"preferred":false,"id":924897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frank-Gilchrist, Donya P. 0000-0002-7146-0069","orcid":"https://orcid.org/0000-0002-7146-0069","contributorId":292926,"corporation":false,"usgs":true,"family":"Frank-Gilchrist","given":"Donya","email":"","middleInitial":"P.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":924898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kotowicz, Dawn Marie 0000-0003-4614-9049","orcid":"https://orcid.org/0000-0003-4614-9049","contributorId":315551,"corporation":false,"usgs":true,"family":"Kotowicz","given":"Dawn Marie","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":924899,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maldonado, Emmanuel 0009-0001-6519-0146","orcid":"https://orcid.org/0009-0001-6519-0146","contributorId":349833,"corporation":false,"usgs":false,"family":"Maldonado","given":"Emmanuel","affiliations":[{"id":83520,"text":"Interdisciplinary Center for Coastal Studies (CIEL) at the University of Puerto Rico in Mayagüez","active":true,"usgs":false}],"preferred":false,"id":924900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vargas-Babilonia, Priscila 0000-0003-3913-9010","orcid":"https://orcid.org/0000-0003-3913-9010","contributorId":292925,"corporation":false,"usgs":true,"family":"Vargas-Babilonia","given":"Priscila","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":924901,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70274208,"text":"70274208 - 2025 - Co-mast: Harmonized seed production data for woody plants across US long-term research sites","interactions":[],"lastModifiedDate":"2026-03-13T14:19:50.792136","indexId":"70274208","displayToPublicDate":"2024-12-12T09:07:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Co-mast: Harmonized seed production data for woody plants across US long-term research sites","docAbstract":"<p><span>Plants display a range of temporal patterns of inter-annual reproduction, from relatively constant seed production to “mast seeding,” the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long-lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community-level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long-Term Ecological Research (LTER) or long-term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community-level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent-scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.4463","usgsCitation":"Nigro, K.M., Barton, J.H., Macias, D., Chaudhary, V.B., Pearse, I., Bell, D.M., Chen, A., Cleavitt, N.L., Crone, E., Greene, D.F., Holland, E.P., Johnstone, J.F., Koenig, W.D., Lyon, N.J., Miller, T.E., Schulze, M., Snell, R.S., Zimmerman, J.K., Knops, J.M., McNulty, S., Parmenter, R.R., Winterstein, M., Zlotin, R.I., LaMontagne, J., and Redmond, M., 2025, Co-mast: Harmonized seed production data for woody plants across US long-term research sites: Ecology, v. 106, e4463, 3 p., https://doi.org/10.1002/ecy.4463.","productDescription":"e4463, 3 p.","ipdsId":"IP-162499","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":501358,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.4463","text":"Publisher Index Page"},{"id":501128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","noUsgsAuthors":false,"publicationDate":"2024-12-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Nigro, Katherine M.","contributorId":189487,"corporation":false,"usgs":false,"family":"Nigro","given":"Katherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":956998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barton, Jessica H.","contributorId":302438,"corporation":false,"usgs":false,"family":"Barton","given":"Jessica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":956999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macias, Diana","contributorId":256880,"corporation":false,"usgs":false,"family":"Macias","given":"Diana","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":957000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaudhary, V. 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,{"id":70265938,"text":"70265938 - 2025 - Great Lakes mallard population dynamics","interactions":[],"lastModifiedDate":"2025-04-22T17:12:00.317697","indexId":"70265938","displayToPublicDate":"2024-12-11T12:04:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Great Lakes mallard population dynamics","docAbstract":"<p><span>Breeding mallard (</span><i>Anas platyrhynchos</i><span>) populations in the Great Lakes region (Michigan, Minnesota, Wisconsin, USA) declined by &gt;40% between 2000–2022 based on abundance data collected during spring aerial surveys. Mallards are an important waterfowl species in this region, where an estimated 60–80% of the mallard harvest is composed of locally banded birds. Extensive population monitoring datasets are available for mallards, presenting an opportunity to address complex questions such as estimating productivity at large spatial and temporal scales, identifying the effects of harvest on mallard demography, quantifying mechanisms for harvest compensation, and integrating multiple datasets to quantify the demographic drivers of population change. Our objective was to simultaneously examine factors affecting demographic parameters and their relative contribution to Great Lakes mallard population dynamics. We used 32 years of banding, band recovery, and aerial survey data collected for mallards from Michigan and Wisconsin to develop an integrated population model (IPM). We used age ratios at banding to estimate productivity, band recoveries from hunter-harvested birds to estimate annual survival and cause-specific mortality (i.e., harvest or non-hunting), and modeled abundance using aerial survey and demographic parameter estimates from 1991–2022. The IPM results indicated the decline in Great Lakes mallard abundance was caused by increased non-hunting mortality and a decline in productivity. Productivity varied spatially but temporally declined with the loss of Conservation Reserve Program area. Moreover, our productivity assessment provided evidence of density dependence in reproduction. Non-hunting mortality was 3.5–6.7 times and 1.3–4.2 times greater than harvest mortality for adult and juvenile female mallards, respectively, indicating environmental factors during spring and summer, not harvest, most greatly influenced annual mortality for female mallards. Our IPM reduced uncertainty in the factors affecting Great Lakes mallard population dynamics and indicated management actions that address non-hunting mortality and productivity would be most effective in increasing Great Lakes mallard abundance.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22702","usgsCitation":"Luukkonen, B., Winterstein, S., Hayes, D., Fowler, D., Soulliere, G., Coluccy, J., Shipley, A., Simpson, J., Shirkey, B., Winiarski, J., O’Neal, B., Avers, B., Urquhart, G., and Lavretsky, P., 2025, Great Lakes mallard population dynamics: Journal of Wildlife Management, v. 89, no. 2, e22702, 21 p., https://doi.org/10.1002/jwmg.22702.","productDescription":"e22702, 21 p.","ipdsId":"IP-169638","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22702","text":"Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":934094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fowler, Drew Nathan 0000-0001-9347-4579","orcid":"https://orcid.org/0000-0001-9347-4579","contributorId":341123,"corporation":false,"usgs":true,"family":"Fowler","given":"Drew Nathan","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934095,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soulliere, Gregory J.","contributorId":353609,"corporation":false,"usgs":false,"family":"Soulliere","given":"Gregory J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":934096,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coluccy, John M.","contributorId":353610,"corporation":false,"usgs":false,"family":"Coluccy","given":"John M.","affiliations":[{"id":84443,"text":"Ducks Unlimited 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Resources","active":true,"usgs":false}],"preferred":false,"id":934103,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Urquhart, Gerald R.","contributorId":353617,"corporation":false,"usgs":false,"family":"Urquhart","given":"Gerald R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":934104,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lavretsky, Philip","contributorId":353618,"corporation":false,"usgs":false,"family":"Lavretsky","given":"Philip","affiliations":[{"id":68346,"text":"University of Texas El Paso","active":true,"usgs":false}],"preferred":false,"id":934105,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70264860,"text":"70264860 - 2025 - Sampling for disease surveillance: Assessing effects on blue-winged teal survival and recovery","interactions":[],"lastModifiedDate":"2025-03-26T14:52:46.805137","indexId":"70264860","displayToPublicDate":"2024-12-11T09:47:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Sampling for disease surveillance: Assessing effects on blue-winged teal survival and recovery","docAbstract":"<p><span>Outbreaks of highly pathogenic avian influenza virus in wild animals highlight the need for disease surveillance in wild birds to improve our understanding of their role as reservoirs and dispersers, and potential threats to domestic poultry and wild bird populations. Surveillance for avian influenza varies in its approach, objectives, and coordination with other monitoring efforts. For waterfowl, a common host to avian influenza viruses, banding represents a concerted effort of capturing and marking thousands of individuals annually to estimate survival and harvest rates, but users of these data have generally taken a conservative approach to remove any banded birds from analyses that had a sample taken for disease surveillance during capture. We tested for differences in survival and encounter probabilities of blue-winged teal (</span><i>Spatula discors</i><span>) marked (</span><i>n</i><span> = 21,702 teal) and sampled for disease surveillance (</span><i>n</i><span> = 4,216) during the nonbreeding season in Louisiana, USA, from 2016 to 2023. Although we found no consistent effect of collecting biological samples on survival probability, including an additional test showing no detectable effects of sampling for disease surveillance with oropharyngeal and cloacal swabs versus sampling with swabs and a syringe-drawn blood sample, wide 95% credible intervals on the posterior survival estimates (mean 0.36 difference between upper and lower values across all year-sex-sampling groups; 0.44 for sampling type groups) indicated low statistical power to detect an effect. Seber recovery probability during the first interval following sampling was lower among birds sampled using swabs only, but we assume this stems from low sample sizes rather than an effect of collecting biological samples. Because recovery probabilities can vary as a function of individual covariates, we also examined direct recovery probabilities and observed no meaningful effect of disease surveillance sampling type but strong effects of capture date, suggesting the effect on Seber recovery probability may have been due to heterogeneity in exposure to natural and harvest mortality risks. Although we suggest that aligning disease surveillance sample collection efforts with landscape-scale waterfowl banding efforts may have little effect on observed demographic rates, additional studies with larger sample sizes are likely needed to provide the statistical power necessary to formally conclude no effect of biological sampling on survival probabilities.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22708","usgsCitation":"Swift, R.J., Arnold, T., Carter, D.L., Link, P.K., Poulson, R., Stallknecht, D., and Pearse, A.T., 2025, Sampling for disease surveillance: Assessing effects on blue-winged teal survival and recovery: Journal of Wildlife Management, v. 89, no. 3, e22708, 14 p., https://doi.org/10.1002/jwmg.22708.","productDescription":"e22708, 14 p.","ipdsId":"IP-166455","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":498247,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22708","text":"Publisher Index Page"},{"id":483873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Grand Chenier, Krotz Springs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.98756060983055,\n              30.65597997684506\n            ],\n            [\n              -91.98756060983055,\n              30.58594442939689\n            ],\n            [\n              -91.90986695702321,\n              30.58594442939689\n            ],\n            [\n              -91.90986695702321,\n              30.65597997684506\n            ],\n            [\n              -91.98756060983055,\n              30.65597997684506\n      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0000-0001-7044-6196","orcid":"https://orcid.org/0000-0001-7044-6196","contributorId":212082,"corporation":false,"usgs":true,"family":"Swift","given":"Rose","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":932074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Todd W.","contributorId":340512,"corporation":false,"usgs":false,"family":"Arnold","given":"Todd W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":932075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Deborah L.","contributorId":335924,"corporation":false,"usgs":false,"family":"Carter","given":"Deborah","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":932076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Link, Paul K.","contributorId":271204,"corporation":false,"usgs":false,"family":"Link","given":"Paul","email":"","middleInitial":"K.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":932077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":932078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David 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,{"id":70263499,"text":"70263499 - 2025 - Characterizing directivity in small (M 2.4-5) aftershocks of the Ridgecrest sequence","interactions":[],"lastModifiedDate":"2025-05-28T14:47:51.520376","indexId":"70263499","displayToPublicDate":"2024-12-10T08:34:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing directivity in small (M 2.4-5) aftershocks of the Ridgecrest sequence","docAbstract":"<p><span>Directivity, or the focusing of energy along the direction of an earthquake rupture, is a common property of earthquakes of all sizes and can cause increased hazard due to azimuthally dependent ground‐motion amplification. For small earthquakes, the effects of directivity are generally less pronounced due to reduced rupture size, yet the directivity in small events can bias source property estimates and provide important insights into general regional faulting patterns. However, due to observational limitations, directivity is usually only measured and modeled for large events. As such, many studies of small earthquakes either ignore directivity altogether or assume a constant rupture direction for all events in a cluster. In our study, we apply a refined directivity fitting method constrained with two separate methods of source deconvolution to the dataset of aftershocks of the 2019 Ridgecrest earthquakes, which contain a large number of well‐recorded small‐to‐mid sized earthquakes occurring in close proximity to each other. The revealed directivity of 100+ small (M 2.4–5) earthquakes is highly heterogeneous and primarily oblique to and away from the main fault strike, suggesting a complex postseismic stress redistribution. In addition, the energy focusing effect of directivity appears to bias the selection of high‐quality data from stations in the direction of rupture, leading to average stress‐drop increases of 50% if directivity is not accounted for.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240146","usgsCitation":"Chu, S., Baltay Sundstrom, A.S., and Abercrombie, R., 2025, Characterizing directivity in small (M 2.4-5) aftershocks of the Ridgecrest sequence: Bulletin of the Seismological Society of America, v. 115, no. 3, p. 1177-1188, https://doi.org/10.1785/0120240146.","productDescription":"12 p.","startPage":"1177","endPage":"1188","ipdsId":"IP-167693","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481972,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Ridgecrest sequence","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.9,\n              36\n            ],\n            [\n              -117.9,\n              35.5\n            ],\n            [\n              -117.3,\n              35.5\n            ],\n            [\n              -117.3,\n              36\n            ],\n            [\n              -117.9,\n              36\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"115","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Chu, Shanna","contributorId":350708,"corporation":false,"usgs":false,"family":"Chu","given":"Shanna","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":927166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abercrombie, Rachel E.","contributorId":293131,"corporation":false,"usgs":false,"family":"Abercrombie","given":"Rachel E.","affiliations":[{"id":7208,"text":"Department of Earth and Environment, Boston University","active":true,"usgs":false}],"preferred":false,"id":927168,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263855,"text":"70263855 - 2025 - Drought before fire increases tree mortality after fire","interactions":[],"lastModifiedDate":"2025-02-26T20:49:58.489965","indexId":"70263855","displayToPublicDate":"2024-12-09T13:44:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Drought before fire increases tree mortality after fire","docAbstract":"<p><span>Fire and drought are expected to increase in frequency and severity in temperate forests due to climate change. To evaluate whether drought increases the likelihood of post-fire tree mortality, we used a large database of tree survival and mortality from 32 years of wildland fires covering four dominant western North American conifers. We used Bayesian hierarchical modeling to predict the probability of individual tree mortality after fire based on species—</span><i>Pinus contorta</i><span>&nbsp;(lodgepole pine),&nbsp;</span><i>Abies concolor</i><span>&nbsp;(white fir),&nbsp;</span><i>Pseudotsuga menziesii</i><span>&nbsp;(Douglas-fir), and&nbsp;</span><i>Pinus ponderosa</i><span>&nbsp;(ponderosa pine)—bark thickness, bark char, percentage live tree crown scorched or consumed crown volume scorch (CVS), and mean annual climatic water deficit (CWD) anomalies the year pre-fire and fire year relative to the 1985–2015 reference period. Although&nbsp;</span><i>crown injury</i><span>&nbsp;was the primary determinant of tree mortality after fire,&nbsp;</span><i>drought</i><span>&nbsp;increased likelihood of death, with a 2-SD increase in CWD (+115.7) resulting in a 78% increase in the probability of mortality. We assessed the crown scorch level expected to result in &gt;50% probability of mortality under different CWD scenarios: observed CWD, CWD of +2, and +4°C warming scenarios. Increased climatic moisture stress amplified tree death, reducing the threshold that causes tree mortality across all conifers under +4°C warming, with more subtle and species-specific reductions for the +2°C scenario. Models predicting post-fire tree mortality are components of global and regional carbon estimates, habitat suitability assessments, and forest management planning and decision support systems. The amplifying effects of drought on post-fire tree mortality and predicted future climates are likely to lead to higher tree mortality following fires in forested landscapes of western North America and may have cascading effects on ecosystem services and future forest resilience.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70083","usgsCitation":"Cansler, C.A., Wright, M., van Mantgem, P., Shearman, T.M., Varner, J., and Hood, S.M., 2025, Drought before fire increases tree mortality after fire: Ecosphere, v. 15, no. 12, e70083, 18 p., https://doi.org/10.1002/ecs2.70083.","productDescription":"e70083, 18 p.","ipdsId":"IP-141643","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":486900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70083","text":"Publisher Index Page"},{"id":482503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.54358044928802,\n              48.48322783092678\n            ],\n            [\n              -125.54358044928802,\n              31.839699908457078\n            ],\n            [\n              -100.5819546029139,\n              31.839699908457078\n            ],\n            [\n              -100.5819546029139,\n              48.48322783092678\n            ],\n            [\n              -125.54358044928802,\n              48.48322783092678\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Cansler, C. Alina 0000-0002-2155-4438","orcid":"https://orcid.org/0000-0002-2155-4438","contributorId":225029,"corporation":false,"usgs":false,"family":"Cansler","given":"C.","email":"","middleInitial":"Alina","affiliations":[{"id":41022,"text":"Missoula Fire Science Lab","active":true,"usgs":false}],"preferred":false,"id":928704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Micah C. 0000-0002-5324-1110","orcid":"https://orcid.org/0000-0002-5324-1110","contributorId":229071,"corporation":false,"usgs":true,"family":"Wright","given":"Micah","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":928706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shearman, Timothy M.","contributorId":229060,"corporation":false,"usgs":false,"family":"Shearman","given":"Timothy","email":"","middleInitial":"M.","affiliations":[{"id":41540,"text":"Tall Timbers Research Station, 13093 Henry Beadel Drive, Tallahassee, FL, 32312, USA","active":true,"usgs":false}],"preferred":false,"id":928707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Varner, J. Morgan","contributorId":265933,"corporation":false,"usgs":false,"family":"Varner","given":"J. Morgan","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":928708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hood, Sharon M.","contributorId":221183,"corporation":false,"usgs":false,"family":"Hood","given":"Sharon","email":"","middleInitial":"M.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":928709,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70261697,"text":"70261697 - 2025 - Global patterns of coseismic landslide runout mobility differ from aseismic landslide trends","interactions":[],"lastModifiedDate":"2024-12-18T17:47:39.005361","indexId":"70261697","displayToPublicDate":"2024-12-09T11:43:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1517,"text":"Engineering Geology","active":true,"publicationSubtype":{"id":10}},"title":"Global patterns of coseismic landslide runout mobility differ from aseismic landslide trends","docAbstract":"<p><span>Coseismic landslides significantly contribute to human and economic losses during and immediately following earthquakes, yet very little data on the runout of such landslides exist. While well-established behavior of aseismic (e.g., hydrologically triggered) landslide runout mobility suggests strong correlation between landslide size and mobility, limited studies of coseismic landslide runout find conflicting mobility trends. We present a global dataset of runout lengths produced from a new automated method for estimating landslide runout, developed and validated using 1726 manually mapped landslides from five unique earthquakes. We then apply the automated runout tool to 23 global earthquake-induced landslide inventories, producing a compiled database of 73,665 measured and estimated runout lengths of coseismic landslides to assess mobility trends. We find a significant divergence between well-established aseismic mobility trends and that of coseismic landslides, with far greater scatter and more complex mobility patterns in earthquake-triggered landslides. As a function of landslide size, we observe global coseismic landslide mobility patterns are bilinear, becoming increasingly less mobile with increasing size above some threshold. This discordance between aseismic and coseismic landslide mobility may be a function of landslide type, kinematics, hydrology, and or setting that systematically differ between triggering mechanisms and should be explored in more depth to develop predictive models of these unique runout patterns. These results suggest hazard and risk models for coseismic landslides may significantly under-predict or over-predict impacts, depending on the size of triggered landslides.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.enggeo.2024.107824","usgsCitation":"Grant, A.R., and Culhane, N.K., 2025, Global patterns of coseismic landslide runout mobility differ from aseismic landslide trends: Engineering Geology, v. 344, 107824, 14 p., https://doi.org/10.1016/j.enggeo.2024.107824.","productDescription":"107824, 14 p.","ipdsId":"IP-158255","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":466679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.enggeo.2024.107824","text":"Publisher Index Page"},{"id":465290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"344","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":921470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Culhane, Natalie K.","contributorId":347352,"corporation":false,"usgs":false,"family":"Culhane","given":"Natalie","email":"","middleInitial":"K.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":921471,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70267749,"text":"70267749 - 2025 - Invisible hand of sampling for management: Underlying needs to survey a threatened seabird can bias aggregated data","interactions":[],"lastModifiedDate":"2025-05-30T16:10:09.562422","indexId":"70267749","displayToPublicDate":"2024-12-09T11:05:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Invisible hand of sampling for management: Underlying needs to survey a threatened seabird can bias aggregated data","docAbstract":"<h3 id=\"jbi15068-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Surveying for a species of concern ahead of proposed activities that alter its habitat is routine practice in conservation and management. Such surveys may accumulate large datasets that could further elucidate trends in abundance and distribution. However, the as-needed surveying of proposed activities may impart a sample site selection bias on the data if used for another purpose. Management of a threatened, forest-nesting seabird offered an example of this. Here we assessed how resource management planning and survey requirements can bias clearance monitoring survey data collected prior to proposed timber harvests, if those data are used for other purposes.</p><h3 id=\"jbi15068-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Oregon and Washington, USA.</p><h3 id=\"jbi15068-sec-0003-title\" class=\"article-section__sub-title section1\">Taxon</h3><p>Marbled Murrelet (<i>Brachyramphus marmoratus</i>).</p><h3 id=\"jbi15068-sec-0004-title\" class=\"article-section__sub-title section1\">Methods</h3><p>To assess how timber planning and other factors influenced marbled murrelet survey location selection, we used logistic regression models to examine habitat associations of marbled murrelet survey sites (<i>n</i> = 9178) encompassing proposed timber harvests, and the survey stations (<i>n</i> = 38,923) therein, across the murrelet's inland range in Washington and Oregon, USA between 1989 and 2021. We then simulated the effect this selective sampling might have on assessments of occupancy trends.</p><h3 id=\"jbi15068-sec-0005-title\" class=\"article-section__sub-title section1\">Results</h3><p>Most habitat characteristics considered did influence where surveys were located, with distance to roads often being the strongest predictor of survey location. The strength of selection for each covariate changed over time, such that a habitat characteristic strongly influenced location selection in a year but was less influential in another year. The simulation analysis suggested that the non-random selection of survey sites could profoundly bias assessments of occupancy trends.</p><h3 id=\"jbi15068-sec-0006-title\" class=\"article-section__sub-title section1\">Conclusions</h3><p>When using these clearance monitoring survey data– or any data–beyond their original purpose, careful consideration should be given to the scope of inference provided and analytical methods used, to ensure that observed trends are the product of biological processes and not biased by sampling artefacts.</p>","language":"English","publisher":"Wiley","doi":"10.1111/jbi.15068","usgsCitation":"Baumbusch, R., Duarte, A., and Peterson, J., 2025, Invisible hand of sampling for management: Underlying needs to survey a threatened seabird can bias aggregated data: Journal of Biogeography, v. 52, no. 3, p. 699-711, https://doi.org/10.1111/jbi.15068.","productDescription":"13 p.","startPage":"699","endPage":"711","ipdsId":"IP-172111","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":489291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.21754122531829,\n              41.967396517105556\n            ],\n            [\n              -122.4561695892057,\n              42.01377286465285\n            ],\n            [\n              -120.03476401689971,\n              48.13266425747176\n            ],\n            [\n              -119.82343860956016,\n              49.0128353215286\n            ],\n            [\n              -123.25786407617503,\n              49.057217103762355\n            ],\n            [\n              -123.52567701204467,\n              48.49024105803022\n            ],\n            [\n              -124.94673542155473,\n              48.575650402887135\n            ],\n            [\n              -124.1349973200926,\n              46.025151144683235\n            ],\n            [\n              -124.64641882316457,\n              42.827652538889424\n            ],\n            [\n              -124.21754122531829,\n              41.967396517105556\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Baumbusch, Ryan","contributorId":289762,"corporation":false,"usgs":false,"family":"Baumbusch","given":"Ryan","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":938729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duarte, Adam","contributorId":337608,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":938730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938731,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70263680,"text":"70263680 - 2025 - Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras","interactions":[],"lastModifiedDate":"2025-02-24T14:15:35.402463","indexId":"70263680","displayToPublicDate":"2024-12-06T16:10:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras","docAbstract":"<p><span>Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper (</span><i>Lutjanus campechanus</i><span>) at a 1.6&nbsp;km</span><sup>2</sup><span>&nbsp;reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km</span><sup>2</sup><span>, 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0373","usgsCitation":"Zulian, V., Pacifici, K., Bacheler, N., Buckel, J., Patterson III, W., Reich, B., Shertzer, K., and Hostetter, N.J., 2025, Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-11, https://doi.org/10.1139/cjfas-2023-0373.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-160698","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487656,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2023-0373","text":"Publisher Index Page"},{"id":482306,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Chicken Rock, Cape Lookout","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.27088356315956,\n              35.090471776670924\n            ],\n            [\n              -76.27088356315956,\n              34.38471805247836\n            ],\n            [\n              -75.17756810224363,\n              34.38471805247836\n            ],\n            [\n              -75.17756810224363,\n              35.090471776670924\n            ],\n            [\n              -76.27088356315956,\n              35.090471776670924\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2024-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Zulian, Viviane","contributorId":351039,"corporation":false,"usgs":false,"family":"Zulian","given":"Viviane","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":927804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pacifici, Krishna","contributorId":351041,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":927805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bacheler, Nathan M.","contributorId":351043,"corporation":false,"usgs":false,"family":"Bacheler","given":"Nathan M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":927806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buckel, Jeffrey A.","contributorId":351045,"corporation":false,"usgs":false,"family":"Buckel","given":"Jeffrey A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":927807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patterson III, William F.","contributorId":351047,"corporation":false,"usgs":false,"family":"Patterson III","given":"William F.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":927808,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reich, Brian J.","contributorId":351049,"corporation":false,"usgs":false,"family":"Reich","given":"Brian J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":927809,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shertzer, Kyle W.","contributorId":351051,"corporation":false,"usgs":false,"family":"Shertzer","given":"Kyle W.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":927810,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":927811,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70261631,"text":"70261631 - 2025 - Distinguishing natural sources from anthropogenic events in seismic data","interactions":[{"subject":{"id":70258409,"text":"70258409 - 2024 - Distinguishing natural sources from anthropogenic noise in seismic data","indexId":"70258409","publicationYear":"2024","noYear":false,"title":"Distinguishing natural sources from anthropogenic noise in seismic data"},"predicate":"SUPERSEDED_BY","object":{"id":70261631,"text":"70261631 - 2025 - Distinguishing natural sources from anthropogenic events in seismic data","indexId":"70261631","publicationYear":"2025","noYear":false,"title":"Distinguishing natural sources from anthropogenic events in seismic data"},"id":1}],"lastModifiedDate":"2025-01-13T16:23:28.276552","indexId":"70261631","displayToPublicDate":"2024-12-06T15:01:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Distinguishing natural sources from anthropogenic events in seismic data","docAbstract":"<p>As seismic data are increasingly used to investigate a diverse range of subsurface phenomena beyond regular fast-rupturing earthquakes (Peng and Gomberg, 2010; Beroza and Ide, 2011), it is important to acknowledge that human-generated ground vibrations may be mistaken for naturally generated subsurface processes (Larose et al., 2015; Li et al., 2018). Correct discrimination of natural processes from anthropogenic noise is especially pressing given the trend in seismic detection research toward automated algorithms and machine learning methods (Yoon et al., 2015; Kong et al., 2019;Mousavi and Beroza, 2022) and the growth in seismic data collection in new environments such as urban and industry settings (e.g., Díaz et al.,2017).</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240330","usgsCitation":"Maher, S., Glasgow, M.E., Cochran, E.S., and Peng, Z., 2025, Distinguishing natural sources from anthropogenic events in seismic data: Seismological Research Letters, v. 96, no. 1, p. 1-6, https://doi.org/10.1785/0220240330.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-169603","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":465224,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":921239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glasgow, Margaret Elizabeth 0000-0001-5637-5918","orcid":"https://orcid.org/0000-0001-5637-5918","contributorId":340268,"corporation":false,"usgs":true,"family":"Glasgow","given":"Margaret","email":"","middleInitial":"Elizabeth","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":921240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":921241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peng, Zhigang","contributorId":199689,"corporation":false,"usgs":false,"family":"Peng","given":"Zhigang","email":"","affiliations":[],"preferred":false,"id":921242,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70267746,"text":"70267746 - 2025 - Bayesian networks facilitate updating of species distribution and habitat suitability models","interactions":[],"lastModifiedDate":"2025-05-30T16:13:52.967062","indexId":"70267746","displayToPublicDate":"2024-12-06T11:10:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian networks facilitate updating of species distribution and habitat suitability models","docAbstract":"<p><span>Managers often rely on predictions of species distributions and habitat suitability to inform conservation and management decisions. Although numerous approaches are available to develop models to make these predictions, few approaches exist to update existing models as new data accumulate. There is a need for updatable models to ensure good modeling practices in an aim to keep pace with change in the environment and change in data availability to continue to use the best-available science to inform decisions. We demonstrated a workflow to deliver predictive models to user groups within Bayesian networks, allowing models to be used to make predictions across new sites and to be easily updated with new data. To demonstrate this workflow, we focus on species distribution and habitat suitability models given their importance to informing conservation strategies across the globe. In particular, we followed a standard process of collating species encounter data available in online databases and ancillary covariate data to develop a habitat suitability model. We then used this model to parameterize a Bayesian network and updated the model with new data to predict species presence in a new focal ecoregion. We found the network updated relatively quickly as new data were incorporated, and the overall error rate generally decreased with each model update. Our approach allows for the formal incorporation of new data into predictions to help ensure model predictions are based on all relevant data available, regardless of whether they were collected after initial model development. Although our focus is on species distribution and habitat suitability models to inform conservation efforts, the workflow we describe herein can easily be applied to any use case where model uncertainty reduction and increased model prediction accuracy are desired via model updating as new data become available. Thus, our paper describes a generalizable workflow to implement model updating, which is widely recognized as a good modeling practice but is also underutilized in applied ecology.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2024.110982","usgsCitation":"Duarte, A., Spaan, R., Peterson, J., Pearl, C., and Adams, M.J., 2025, Bayesian networks facilitate updating of species distribution and habitat suitability models: Ecological Modelling, v. 501, 110982, 11 p., https://doi.org/10.1016/j.ecolmodel.2024.110982.","productDescription":"110982, 11 p.","ipdsId":"IP-172422","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2024.110982","text":"Publisher Index Page"},{"id":489293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Forest Service","active":true,"usgs":false}],"preferred":false,"id":938725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearl, Christopher 0000-0003-2943-7321 christopher_pearl@usgs.gov","orcid":"https://orcid.org/0000-0003-2943-7321","contributorId":172669,"corporation":false,"usgs":true,"family":"Pearl","given":"Christopher","email":"christopher_pearl@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":938727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":938728,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70261545,"text":"70261545 - 2025 - Reconstructing half a century of coregonine recruitment reveals species-specific dynamics and synchrony across the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2025-02-24T16:51:44.64255","indexId":"70261545","displayToPublicDate":"2024-12-05T08:46:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing half a century of coregonine recruitment reveals species-specific dynamics and synchrony across the Laurentian Great Lakes","docAbstract":"<p><span>Understanding how multiple species and populations vary in their recruitment dynamics can elucidate the processes driving recruitment across space and time. Lake Whitefish (</span><i>Coregonus clupeaformis</i><span>) and Cisco (</span><i>C. artedi</i><span>) are socioecologically important fishes across their range; however, many Laurentian Great Lakes populations have experienced declining, poor, or sporadic recruitment in recent decades. We integrated catch and age data from 38 long-term surveys across each of the Great Lakes and Lake Simcoe, resulting in a combined time series spanning 1960–2019. We estimated Lake Whitefish and Cisco year-class strength (YCS) in each lake using longitudinal mixed-effects regressions of relative cohort abundance. We subsequently quantified interspecific, spatial, and temporal synchrony in YCS using correlation and dynamic factor analyses. Lake Whitefish YCS was positively spatially synchronous on average, and YCS in all six lakes was elevated during the 1980s–1990s. In contrast, Cisco YCS was sporadic, not spatially synchronous, and highly variable around long-term, lake-specific means. YCS was not synchronous between species in any lake. Collectively, our analyses demonstrate that these species exhibit differential recruitment dynamics that may be regulated by species-specific factors. Results from this study can be leveraged in future research on the causes and consequences of cross-species, cross-basin recruitment variability.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/icesjms/fsae160","usgsCitation":"Brown, T.A., Rudstam, L.G., Sethi, S.A., Ripple, P., Smith, J., Treska, T., Hessell, C., Olsen, E., He, J.X., Jonas, J., Rook, B.J., Blankenheim, J., Beech, S.J., Brown, E., Berglund, E.K., Cook, H., Dunlop, E.S., James, S., Pothoven, S.A., Amidon, Z., Sweka, J., Carl, D., Hansen, S., Bunnell, D.B., Weidel, B., and Honsey, A.E., 2025, Reconstructing half a century of coregonine recruitment reveals species-specific dynamics and synchrony across the Laurentian Great Lakes: ICES Journal of Marine Science, v. 82, no. 2, fsae160, 18 p., https://doi.org/10.1093/icesjms/fsae160.","productDescription":"fsae160, 18 p.","ipdsId":"IP-165453","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":465108,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466725,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsae160","text":"Publisher Index Page"}],"country":"Canada, United States","otherGeospatial":"Laurentian Great Lakes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.91552734375,\n              44.28453670601888\n            ],\n            [\n              -76.4813232421875,\n              44.319918120477425\n            ],\n            [\n              -77.113037109375,\n              44.01652134387754\n            ],\n            [\n              -77.640380859375,\n              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,{"id":70261366,"text":"70261366 - 2025 - The joint effect of changes in urbanization and climate on trends in floods: A comparison of panel and single-station quantile regression approaches","interactions":[],"lastModifiedDate":"2024-12-12T16:08:12.325121","indexId":"70261366","displayToPublicDate":"2024-12-03T09:01:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The joint effect of changes in urbanization and climate on trends in floods: A comparison of panel and single-station quantile regression approaches","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><div id=\"sp0010\" class=\"u-margin-s-bottom\"><span>Estimates of annual maximum (peak) flow quantiles are needed for basins undergoing changes in both urbanization and climate. Most previous work on the effect of urbanization on peak flows has considered urbanization alone and only the spatial variation in flood quantiles or its mean temporal effect, and most work on the effect of nonstationarity in climate has focused on single-station analyses, which give uncertain results for extreme quantiles. To address these gaps, three approaches to the statistical estimation of the joint effects of changes in impervious cover and climate on the estimation of peak-flow quantiles were compared: single-station quantile regression; a fixed effect panel-quantile regression (pQR) method using a location (mean) shift to homogenize the panel; and a location-scale panel regression model (pQRmom), which accounts for both scale (variance) and location effects. The different approaches were applied to a dataset consisting of instantaneous annual peak flows from 127 minimally nested basins in the midwestern United States with at least 4&nbsp;% change in imperviousness. The annual maximum daily discharge from a water-balance model was selected as the primary climate predictor; in addition, to provide a comparison of climate predictors, precipitation was also considered. The coefficients from single-station regressions were usually sufficiently certain to determine the effects of climate variation but usually too uncertain to estimate the effects of urbanization. The panel-quantile regression approaches give much more certain results, but their estimates of quantile dependence differ: although both indicate urbanization effects decreasing with decreasing annual exceedance probability (AEP), the pQRmom urbanization coefficients are insignificantly different from zero for AEPs less than 0.10, whereas the pQR coefficients remain positive and are significant except for AEP = 0.01, the smallest AEP value considered. Although the location-scale structure of the pQRmom approach has less flexible quantile dependence than the pQR approach, the pQRmom approach has somewhat lower overall error, and it is found that by subsetting the dataset to homogenize the scale effects, the pQR and pQRmom results become similar, indicating the insignificant urbanization coefficients for small AEPs of the pQRmom results are likely correct for the study dataset.</span></div></div></div></div><div id=\"reading-assistant-main-body-section\"><br></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2024.132281","usgsCitation":"Over, T.M., Marti, M.K., Ortiz, J., and Podzorski, H.L., 2025, The joint effect of changes in urbanization and climate on trends in floods: A comparison of panel and single-station quantile regression approaches: Journal of Hydrology, v. 648, 132281, 21 p., https://doi.org/10.1016/j.jhydrol.2024.132281.","productDescription":"132281, 21 p.","ipdsId":"IP-164495","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466683,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2024.132281","text":"Publisher Index Page"},{"id":466451,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1ZNSQSG","text":"USGS data release","linkHelpText":"Data for Investigating the Joint Effect of Changes in Impervious Cover and Climate on Trends in Floods"},{"id":464884,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.21401187752082,\n              41.78478885015073\n            ],\n            [\n              -82.44260111092109,\n              42.952139162504125\n            ],\n            [\n              -88.01051518909618,\n              44.68660103178678\n            ],\n            [\n              -93.48272842206053,\n              44.8681458501853\n            ],\n            [\n              -94.84496451109821,\n              39.9280811992401\n            ],\n            [\n              -94.63808877858959,\n              38.82734242417379\n            ],\n            [\n              -94.39334578416593,\n              35.82967467856777\n            ],\n            [\n              -89.47117528725998,\n              38.20831794765212\n            ],\n            [\n              -83.21401187752082,\n              41.78478885015073\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"648","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ortiz, Jaqueline 0000-0001-7992-385X","orcid":"https://orcid.org/0000-0001-7992-385X","contributorId":304557,"corporation":false,"usgs":true,"family":"Ortiz","given":"Jaqueline","email":"","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920431,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Podzorski, Hannah Lee 0000-0001-5204-2606 hpodzorski@usgs.gov","orcid":"https://orcid.org/0000-0001-5204-2606","contributorId":333626,"corporation":false,"usgs":true,"family":"Podzorski","given":"Hannah","email":"hpodzorski@usgs.gov","middleInitial":"Lee","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":920432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70271139,"text":"70271139 - 2025 - Restoration treatments enhance tree growth and alter climatic constraints during extreme drought","interactions":[],"lastModifiedDate":"2025-08-28T15:32:38.300191","indexId":"70271139","displayToPublicDate":"2024-12-03T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Restoration treatments enhance tree growth and alter climatic constraints during extreme drought","docAbstract":"<p><span>The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients. We used tree-ring data from a system of replicated, long-term (&gt;20 years) experiments in the southwestern United States to evaluate the effects of forest restoration treatments (i.e., evidence-based thinning and burning) on annual growth rates (i.e., basal area increment; BAI) of ponderosa pine (</span><i>Pinus ponderosa</i><span>), a broadly distributed and heavily managed species in western North America. The study sites were established at the onset of the most extreme drought event in at least 1200 years and span much of the climatic niche of Rocky Mountain ponderosa pine. Across sites, tree-level BAI increased due to treatment, where trees in treated units grew 133.1% faster than trees in paired, untreated units. Likewise, trees in treated units grew an average of 85.6% faster than their pre-treatment baseline levels (1985 to ca. 2000), despite warm, dry conditions in the post-treatment period (ca. 2000–2018). Variation in the local competitive environment promoted variation in BAI, and larger trees were the fastest-growing individuals, irrespective of treatment. Tree thinning and prescribed fire altered the climatic constraints on growth, decreasing the effects of belowground moisture availability and increasing the effects of atmospheric evaporative demand over multi-year timescales. Our results illustrate that restoration treatments can enhance tree-level growth across sites spanning ponderosa pine's climatic niche, even during recent, extreme drought events. However, shifting climatic constraints, combined with predicted increases in evaporative demand in the southwestern United States, suggest that the beneficial effects of such treatments on tree growth may wane over the upcoming decades.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.3072","usgsCitation":"Rodman, K.C., Bradford, J.B., Formanack, A.M., Fulé, P.Z., Huffman, D.W., Kolb, T.E., Miller-ter Kuile, A.T., Normandin, D.P., Ogle, K., Pederson, R.J., Schlaepfer, D.R., Stoddard, M.T., and Waltz, A.E., 2025, Restoration treatments enhance tree growth and alter climatic constraints during extreme drought: Ecological Applications, v. 35, no. 1, e3072, 18 p., https://doi.org/10.1002/eap.3072.","productDescription":"e3072, 18 p.","ipdsId":"IP-159296","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huffman, David W.","contributorId":360743,"corporation":false,"usgs":false,"family":"Huffman","given":"David","middleInitial":"W.","affiliations":[{"id":86095,"text":"Ecological Restoration Institute, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolb, Thomas E.","contributorId":360744,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","middleInitial":"E.","affiliations":[{"id":39356,"text":"School of Forestry, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller-ter Kuile, Ana T.","contributorId":360745,"corporation":false,"usgs":false,"family":"Miller-ter Kuile","given":"Ana","middleInitial":"T.","affiliations":[{"id":86098,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, 86011, USA; USDA Forest Service, Rocky Mountain Research Station, Flagstaff, AZ, 86001, USA","active":true,"usgs":false}],"preferred":false,"id":947566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Normandin, Donald P.","contributorId":360746,"corporation":false,"usgs":false,"family":"Normandin","given":"Donald","middleInitial":"P.","affiliations":[{"id":86095,"text":"Ecological Restoration Institute, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947567,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ogle, Kiona","contributorId":360747,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","affiliations":[{"id":86099,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947568,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pederson, Rory J.","contributorId":360748,"corporation":false,"usgs":false,"family":"Pederson","given":"Rory","middleInitial":"J.","affiliations":[{"id":86095,"text":"Ecological Restoration Institute, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947569,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947570,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stoddard, Michael T.","contributorId":360749,"corporation":false,"usgs":false,"family":"Stoddard","given":"Michael","middleInitial":"T.","affiliations":[{"id":86095,"text":"Ecological Restoration Institute, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947571,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Waltz, Amy E.M.","contributorId":360750,"corporation":false,"usgs":false,"family":"Waltz","given":"Amy","middleInitial":"E.M.","affiliations":[{"id":86095,"text":"Ecological Restoration Institute, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":947572,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70264674,"text":"70264674 - 2025 - Deterministic, dynamic model forecasts of storm-driven coastal erosion","interactions":[],"lastModifiedDate":"2025-04-17T15:41:02.628607","indexId":"70264674","displayToPublicDate":"2024-12-02T10:02:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Deterministic, dynamic model forecasts of storm-driven coastal erosion","docAbstract":"<p><span>The U.S. Atlantic and Gulf of Mexico coasts are vulnerable to storms, which can cause significant erosion of beaches and dunes that protect coastal communities. Real-time forecasts of storm-driven erosion are useful for decision support, but they are limited due to demands for computational resources and uncertainties in dynamic coastal systems and storm forcings. Current methods for coastal change forecasts are based on empirical calculations for wave run-up and conceptual models for erosion, which do not represent sediment transport and morphological change during the storm. However, with continued advancements in high-resolution geospatial data and computational efficiencies, there is an opportunity to apply morphodynamic models for forecasts of beach and dune erosion as a storm approaches the coast. In this study, we implement a forecast system based on a deterministic, dynamic model. The morphodynamic model is initialized with digital elevation models of the most up-to-date conditions and forced with hydrodynamics from wave and circulation model forecasts, and its predictions are categorized based on impact to the primary dune, defined in this study as the first ridge of sand landward of the beach. Results are compared spatially to the observed post-storm topography using changes to dune crest elevations and volumes, and temporally to the predicted total water level at the forecasted moment of dune impact.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-024-07012-2","usgsCitation":"Gorski, J., Dietrich, J., Passeri, D., Mickey, R.C., and Luettich, R., 2025, Deterministic, dynamic model forecasts of storm-driven coastal erosion: Natural Hazards, v. 121, p. 6257-6283, https://doi.org/10.1007/s11069-024-07012-2.","productDescription":"27 p.","startPage":"6257","endPage":"6283","ipdsId":"IP-164060","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":483528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88,\n              35\n            ],\n            [\n              -88,\n              24\n            ],\n            [\n              -76,\n              24\n            ],\n            [\n              -76,\n              35\n            ],\n            [\n              -88,\n              35\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"121","noUsgsAuthors":false,"publicationDate":"2024-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gorski, Jessica Frances 0000-0003-3476-8846","orcid":"https://orcid.org/0000-0003-3476-8846","contributorId":352431,"corporation":false,"usgs":true,"family":"Gorski","given":"Jessica Frances","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":931227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dietrich, Joel C. 0000-0001-5294-2874","orcid":"https://orcid.org/0000-0001-5294-2874","contributorId":352432,"corporation":false,"usgs":false,"family":"Dietrich","given":"Joel C.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":931228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":931229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mickey, Rangley C. 0000-0001-5989-1432 rmickey@usgs.gov","orcid":"https://orcid.org/0000-0001-5989-1432","contributorId":141016,"corporation":false,"usgs":true,"family":"Mickey","given":"Rangley","email":"rmickey@usgs.gov","middleInitial":"C.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":931230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luettich, Rick A. Jr. 0000-0002-7625-1952","orcid":"https://orcid.org/0000-0002-7625-1952","contributorId":352433,"corporation":false,"usgs":false,"family":"Luettich","given":"Rick A.","suffix":"Jr.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":931231,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70262122,"text":"70262122 - 2025 - Physical habitat is more than a sediment issue: A multi-dimensional habitat assessment indicates new approaches for river management","interactions":[],"lastModifiedDate":"2025-01-14T15:28:24.606373","indexId":"70262122","displayToPublicDate":"2024-12-02T08:20:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Physical habitat is more than a sediment issue: A multi-dimensional habitat assessment indicates new approaches for river management","docAbstract":"<p><span>Degraded physical habitat is a common stressor affecting river ecosystems and typically addressed in the United States (US) through a regulatory focus on sediment. However, a narrow regulatory focus on sediment may overlook other aspects of physical habitat and the processes for its creation, maintenance, and degradation. In addition, there exist few “ready-to-use” regional assessments of the multiple dimensions of physical habitat to better understand continuous patterns of condition and prioritize management efforts across a large spatial scale.</span></p><p><span>In this study, we use rapid habitat monitoring data to train a machine-learning (<i>i.e.,</i>&nbsp;random forest) model to predict twelve physical habitat metrics for nearly 120,000&nbsp;km of nontidal rivers and streams across the Chesapeake Bay watershed, US. We capture a range of habitat conditions driven by both natural variables and anthropogenic pressures. Covariation among habitat metrics indicated two major dimensions of habitat variation: 1) coarse bed substrate and hydromorphic heterogeneity and 2) bank stability and riparian condition. The model predicted localized changes from 2001 to 2019, and the predicted areas of deterioration roughly balanced improvements across the watershed, indicating little progress towards long-term watershed management goals.</span></p><p><span>To evaluate connections to regulatory and management endpoints, we compared our physical habitat predictions to paired estimates of sediment and flow alteration across the region. Sediment concentrations were greater in reaches with less bank stability and lower riparian quality; however, the relation was weak for coarse bed condition metrics, including embeddedness, which is frequently used for establishing regulatory sediment restrictions. For flow alteration, most habitat metrics had lower scores with altered flow metrics, but metrics of instream habitat heterogeneity and coarse substrate condition were most strongly affected. Increased flashy, high flows negatively affected most metrics, but coarse substrate metrics were also negatively affected by greater low flow severity.</span></p><p><span>This study highlights a potential disconnect between a narrow focus on regulatory sediment targets given the multiple dimensions and responses of physical habitat. A more holistic approach to physical habitat in management interventions – one that considers hydromorphic processes, diversity and variability in microhabitats, and explicit consideration of alterations to both low and high flows – may be warranted. By providing direct estimates of multiple aspects of physical habitat, this model can help support managers in the Chesapeake Bay watershed to better understand the range of habitat conditions, identify high-quality reaches for conservation, and target potential management actions tailored to localized conditions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2024.123139","usgsCitation":"Cashman, M.J., Lee, G., Staub, L.E., Katoski, M.P., and Maloney, K.O., 2025, Physical habitat is more than a sediment issue: A multi-dimensional habitat assessment indicates new approaches for river management: Journal of Environmental Management, v. 371, 123139, 19 p., https://doi.org/10.1016/j.jenvman.2024.123139.","productDescription":"123139, 19 p.","ipdsId":"IP-157208","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2024.123139","text":"Publisher Index Page"},{"id":466215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia","otherGeospatial":"Chesapeake Bay watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.03127676890098,\n              42.79659858105208\n            ],\n            [\n              -77.03127676890098,\n              36.869492666020236\n            ],\n            [\n              -75.61615482325107,\n              36.869492666020236\n            ],\n            [\n              -75.61615482325107,\n              42.79659858105208\n            ],\n            [\n              -77.03127676890098,\n              42.79659858105208\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"371","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Gina 0009-0009-9821-9492","orcid":"https://orcid.org/0009-0009-9821-9492","contributorId":345186,"corporation":false,"usgs":false,"family":"Lee","given":"Gina","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":923159,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staub, Leah Ellen 0000-0002-1460-6084","orcid":"https://orcid.org/0000-0002-1460-6084","contributorId":299035,"corporation":false,"usgs":true,"family":"Staub","given":"Leah","email":"","middleInitial":"Ellen","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923160,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Katoski, Michelle P. 0000-0001-5550-0705","orcid":"https://orcid.org/0000-0001-5550-0705","contributorId":300555,"corporation":false,"usgs":true,"family":"Katoski","given":"Michelle","middleInitial":"P.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923161,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":923162,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70263444,"text":"70263444 - 2025 - Constraining large magnitude event source and path effects using ground motion simulations","interactions":[],"lastModifiedDate":"2025-09-16T18:31:52.909078","indexId":"70263444","displayToPublicDate":"2024-12-01T12:32:02","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Constraining large magnitude event source and path effects using ground motion simulations","docAbstract":"The purpose of this study is to use ground motion simulations to investigate ways in which source and path effects for large magnitude events can be represented in non-ergodic GMMs. While we initially developed computation techniques using CyberShake simulations, the range of magnitudes and source-site combinations is not adequate to replicate what is observed empirically. We therefore designed a new ground motion simulation study, which includes earthquakes with a large range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of simulations (M4-M7), we then develop a non-ergodic GMM with the simulation data. We find that the within-site residuals are dominated by the radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within-site residuals among multiple source realizations. Finally, after removing the source effects from the within-site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site with the large events, while the second approach considers all small events on the fault plane. The results indicate that the path effects of large events cannot be satisfactorily approximated with that of small events using either approach.","conferenceTitle":"18th World Conference on Earthquake Engineering","conferenceDate":"June 30-July 5, 2025","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Meng, X., Graves, R., and Goulet, C.A., 2025, Constraining large magnitude event source and path effects using ground motion simulations, 18th World Conference on Earthquake Engineering, v. 18, Milan, Italy, June 30-July 5, 2025, 12 p.","productDescription":"12 p.","ipdsId":"IP-159550","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495604,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=24568&conference=18WCEE","linkFileType":{"id":5,"text":"html"}}],"volume":"18","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meng, Xiaofeng","contributorId":350798,"corporation":false,"usgs":false,"family":"Meng","given":"Xiaofeng","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":927014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goulet, Christine A 0000-0002-7643-357X","orcid":"https://orcid.org/0000-0002-7643-357X","contributorId":336587,"corporation":false,"usgs":true,"family":"Goulet","given":"Christine","email":"","middleInitial":"A","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927016,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70271419,"text":"70271419 - 2025 - Structural setting and geothermal potential of northeastern Reese River Valley, north-central Nevada: Highly prospective detailed study site for the INGENIOUS project","interactions":[],"lastModifiedDate":"2025-09-12T16:13:35.788555","indexId":"70271419","displayToPublicDate":"2024-12-01T11:07:58","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Structural setting and geothermal potential of northeastern Reese River Valley, north-central Nevada: Highly prospective detailed study site for the INGENIOUS project","docAbstract":"The northeastern part of the Reese River basin situated ~15 km southeast of Battle Mountain, Nevada, scored highly in the Nevada geothermal play fairway analysis (PFA) for hosting potential hidden geothermal systems. This site (also referred to as Argenta Rise) was therefore chosen for detailed study in the INGENIOUS project (INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems). The high PFA scores resulted primarily from favorable structural settings (e.g., fault intersections and pull aparts) with relatively high slip rates on Quaternary faults. The INGENIOUS project is utilizing additional parameters and more rigorous analytical techniques to further advance exploration at this site. This includes integration of geological (e.g., Quaternary fault mapping) and new geophysical datasets (e.g., gravity, magnetics, MT data, and five reprocessed seismic reflection profiles) to build a structural model and to identify specific favorable sites for potential geothermal upwellings. Two-meter temperature surveys were also conducted in the area (139 measurements).\n\nThis part of north-central Nevada is characterized by systems of intersecting northerly and ENE-striking faults within the broader Humboldt structural zone, a poorly understood belt of ENE-striking faults and relatively high heat flow extending across northern Nevada. Kinematic analysis of exposed fault surfaces shows that ENE-striking faults have accommodated sinistral-normal slip, and normal slip characterizes N- to NNE-striking faults. Northeastern Reese River Valley lies within a broad left step between major ENE-striking fault zones on the northern flanks of the Argenta Rim and Shoshone Range and thus corresponds to a broad pull-apart in the ENE-striking sinistral-normal fault system. Notably, the nearby Beowawe geothermal system in Whirlwind Valley (with abundant sinter, hot springs, and a geothermal power plant) occupies a fault intersection in a relatively small left step in a major ENE-striking sinistral-normal fault and may serve as an analogue for a potential hidden system in northeastern Reese River Valley. Existing geological maps, high-resolution lidar, and seismic reflection data demonstrate that northeastern Reese River Valley is structurally complex with multiple intersections between the ENE- and N- to NNE-striking fault systems. Some of these fault intersections correspond to low resistivity anomalies, magnetic lows, and/or very subtle 2-m temperature anomalies, which may indicate hidden geothermal upwellings. Three-dimensional modeling and temperature-gradient drilling are planned to further evaluate these sites for geothermal activity.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Rising","usgsCitation":"Faulds, J., Earney, T.E., Glen, J.M., Queen, J., Peacock, J., Hart-Wagoner, N.R., Kraal, K., Lindsey, C.R., Burgess, Q., and Giddens, M.H., 2025, Structural setting and geothermal potential of northeastern Reese River Valley, north-central Nevada: Highly prospective detailed study site for the INGENIOUS project, <i>in</i> Using the Earth to save the Earth, v. 48, p. 1240-1257.","productDescription":"18 p.","startPage":"1240","endPage":"1257","ipdsId":"IP-169386","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495402,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035050"}],"country":"United States","state":"Nevada","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Faulds, James","contributorId":344582,"corporation":false,"usgs":false,"family":"Faulds","given":"James","affiliations":[{"id":82394,"text":"Nevada Bureau of Mines and Geology, University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":948693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earney, Tait E. 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