{"pageNumber":"46","pageRowStart":"1125","pageSize":"25","recordCount":40769,"records":[{"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":70261691,"text":"70261691 - 2025 - Hypothetical CO2 leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO2 storage facility, Kemper County, Mississippi, USA","interactions":[],"lastModifiedDate":"2024-12-18T16:53:53.989977","indexId":"70261691","displayToPublicDate":"2024-12-16T10:48:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1541,"text":"Environmental Geosciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hypothetical CO<sub>2</sub> leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO<sub>2</sub> storage facility, Kemper County, Mississippi, USA","title":"Hypothetical CO2 leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO2 storage facility, Kemper County, Mississippi, USA","docAbstract":"<p><span>A large Geologic Carbon Sequestration (GCS) hub has been proposed in Kemper County, Mississippi. The target injection interval consists of numerous Cretaceous-aged deep saline aquifers overlain by a competent and extensive regional sealing layer. Above the seal, the deepest Underground Source of Drinking Water (USDW) at the site is the Eutaw aquifer of the Eutaw Group and McShan Formation, undifferentiated. To assess potential risks of leakage from the deep sequestration reservoir, a model of a portion of the Cretaceous Eutaw Group was constructed in this study. Simulations tested various permeabilities, hypothetical leakage rates, and plume mitigation strategies utilizing existing wells. Results suggest that, under the influence of regional groundwater flow fields, leaking CO</span><sub>2</sub><span>&nbsp;would effectively bypass the existing wells, and to influence this migration would require very large water extraction rates. Therefore, to ensure plume detection, monitoring for leakage at the injection wells themselves is very important.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12665-024-11973-9","usgsCitation":"Plampin, M.R., and Merrill, M., 2025, Hypothetical CO2 leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO2 storage facility, Kemper County, Mississippi, USA: Environmental Geosciences, v. 84, 18, 11 p., https://doi.org/10.1007/s12665-024-11973-9.","productDescription":"18, 11 p.","ipdsId":"IP-155011","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":466678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12665-024-11973-9","text":"Publisher Index Page"},{"id":465284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","county":"Kemper County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3461,32.9278],[-88.3559,32.8499],[-88.3727,32.7042],[-88.3883,32.5778],[-88.5413,32.5771],[-88.5538,32.5772],[-88.7878,32.5763],[-88.8014,32.576],[-88.8134,32.5761],[-88.8167,32.5762],[-88.9135,32.5753],[-88.9161,32.8272],[-88.9158,32.8463],[-88.9169,32.9228],[-88.8131,32.9241],[-88.5676,32.9263],[-88.3461,32.9278]]]},\"properties\":{\"name\":\"Kemper\",\"state\":\"MS\"}}]}","volume":"84","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":921444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":921445,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261692,"text":"70261692 - 2025 - Deformation of Mauna Loa volcano before, during, and after its 2022 eruption","interactions":[],"lastModifiedDate":"2024-12-18T16:28:52.412428","indexId":"70261692","displayToPublicDate":"2024-12-16T10:24:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Deformation of Mauna Loa volcano before, during, and after its 2022 eruption","docAbstract":"<p><span>Mauna Loa on the Island of Hawaiʻi erupted on 27 November 2022, the first eruption since 1984, which marked the culmination of decades-long period of non-eruptive unrest and relative quiescence. We briefly describe the evolution of the USGS Hawaiian Volcano Observatory’s geodetic monitoring network at Mauna Loa and show patterns of deformation as measured by Global Navigation Satellite Systems (GNSS), interferometric synthetic aperture radar (InSAR), and borehole tilt. We highlight the long-term buildup and the imminent pre-eruptive geodetic signals, including subtle changes observed in early 2021 that suggested a potential eruption. We then describe the significant ramp up of activity in September 2022 that provided strong evidence of likely impending eruptive activity. Of particular importance are the first borehole tilt excursions related to magma movement measured at Mauna Loa’s summit, which began in 2021 and were accompanied by increased rates of seismicity. In addition to describing the evolution of surface displacements, we also model the co-eruption deformation, which can be fit by dike-like opening that matches the geometry of the surface eruptive fissures.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-024-01788-8","usgsCitation":"Ellis, A.P., Johanson, I.A., and Poland, M.P., 2025, Deformation of Mauna Loa volcano before, during, and after its 2022 eruption: Bulletin of Volcanology, v. 86, 8, 21 p., https://doi.org/10.1007/s00445-024-01788-8.","productDescription":"8, 21 p.","ipdsId":"IP-166686","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.77858977944825,\n              19.66170435533985\n            ],\n            [\n              -155.77858977944825,\n              19.292719970106006\n            ],\n            [\n              -155.33491746947445,\n              19.292719970106006\n            ],\n            [\n              -155.33491746947445,\n              19.66170435533985\n            ],\n            [\n              -155.77858977944825,\n              19.66170435533985\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"86","noUsgsAuthors":false,"publicationDate":"2024-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, Andria P. 0000-0003-2543-0640","orcid":"https://orcid.org/0000-0003-2543-0640","contributorId":305983,"corporation":false,"usgs":true,"family":"Ellis","given":"Andria","email":"","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":921446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":921447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":921448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"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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,{"id":70261670,"text":"70261670 - 2025 - Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (Oreamnos americanus)","interactions":[],"lastModifiedDate":"2025-01-27T16:44:31.632325","indexId":"70261670","displayToPublicDate":"2024-12-13T09:50:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (<i>Oreamnos americanus</i>)","title":"Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (Oreamnos americanus)","docAbstract":"<p><span>Climate change is occurring at an accelerated rate in high-elevation alpine and mountain ecosystems. Cold-adapted, mountain species are at risk due to forecasted change and knowledge is needed to respond to current and future conservation challenges. Mountain goats (</span><i>Oreamnos americanus</i><span>) are an iconic species of North American mountain cultures and landscapes, and due to specialized adaptations for life in cold, mountainous environments they are particularly sensitive to changes in weather and climate. As sentinels of change in alpine ecosystems, the study of mountain goats offers insight into the ecological effects and conservation challenges associated with climate change in these sensitive and biodiverse environments. Here, we synthesize existing knowledge about how climate change is expected to influence environmental conditions experienced by mountain goats and associated mechanistic changes to behavior, nutritional ecology, demography, health, and interspecific interactions. In many instances, climate change effects are likely to be negative and additive to existing threats (such as human disturbance, hunting, disease, predation) though benefits are expected in some cases. Changes in climate and mountain environments will necessitate re-examination and modification of population monitoring, management, and conservation strategies. Specifically, spatiotemporal (and other) aspects of monitoring and management may need to be adjusted to accommodate emerging and novel conservation challenges. Yet, key data and knowledge gaps remain and should be addressed to advance conservation and decision-making capabilities. For mountain goats and similarly climate-sensitive alpine herbivores, effective conservation will ultimately benefit from collaborations among diverse networks guided by well-planned, strategic visions focused on common ground – namely the resiliency and persistence of culturally and ecologically significant mountain species and the alpine environment they inhabit.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2024.e03364","usgsCitation":"White, K., Cadsand, B., Cote, S.D., Graves, T., Hamel, S., Harris, R.B., Hayes, F., Hood, E., Hurley, K., Jessen, T., Jex, B., Peitzsch, E.H., Sarmento, W., Schwantje, H.M., and Berger, J., 2025, Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (Oreamnos americanus): Global Ecology and Conservation, v. 57, e03364, 19 p., https://doi.org/10.1016/j.gecco.2024.e03364.","productDescription":"e03364, 19 p.","ipdsId":"IP-166738","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466717,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2024.e03364","text":"Publisher Index Page"},{"id":465278,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Alberta, British Columbia, Idaho, Montana, Northwest Territories, Oregon, Washington, Yukon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.52740428045206,\n              43.126862105716015\n            ],\n            [\n              -112.52625648619443,\n              43.10805069125277\n            ],\n            [\n              -110.41656112208216,\n              46.00411624911669\n            ],\n            [\n              -122.41072033247411,\n              63.43014069463413\n            ],\n            [\n              -148.6622869536442,\n              61.80821876885935\n            ],\n            [\n              -152.1644301328432,\n              59.3980192805023\n            ],\n            [\n              -147.75430481085388,\n              59.95192283531884\n            ],\n            [\n              -143.9376556572404,\n              60.14020171501804\n            ],\n            [\n              -138.16173053060783,\n              59.17713932003667\n            ],\n            [\n              -134.98292774303908,\n              56.29039401011454\n            ],\n            [\n              -131.16827590575502,\n              55.350886192731\n            ],\n            [\n              -128.0089454906319,\n              50.475368698966435\n            ],\n            [\n              -122.93240762130674,\n              46.57509255373344\n            ],\n            [\n              -120.52740428045206,\n              43.126862105716015\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"57","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Kevin 0000-0002-5231-6045","orcid":"https://orcid.org/0000-0002-5231-6045","contributorId":336590,"corporation":false,"usgs":false,"family":"White","given":"Kevin","email":"","affiliations":[{"id":80796,"text":"1Program on the Environment, University of Alaska Southeast; 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,{"id":70267351,"text":"70267351 - 2025 - Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups","interactions":[],"lastModifiedDate":"2025-05-20T16:12:45.6849","indexId":"70267351","displayToPublicDate":"2024-12-12T10:20:46","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}},"displayTitle":"Intrinsic and environmental drivers of pairwise cohesion in wild <i>Canis</i> social groups","title":"Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups","docAbstract":"<p><span>Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus&nbsp;</span><i>Canis</i><span>&nbsp;in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (</span><i>Canis</i><span>&nbsp;spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across&nbsp;</span><i>Canis</i><span>&nbsp;species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.4492","usgsCitation":"Benson, J.F., Keiter, D.A., Mahoney, P., Allen, B.L., Allen, L.R., Álvares, F., Anderson, M., Barber-Meyer, S., Barocas, A., Beasley, J.C., Behrendorff, L., Belant, J., Beyer, D., Boitani, L., Borg, B.L., Boutin, S., Boydston, E., Brown, J.L., Bump, J.K., Cepek, J., Chamberlain, M.J., Chenaux-Ibrahim, Y., Cherry, S., Ćirović, D., Ciucci, P., Cluff, H., Cooper, S.M., Crooks, K., Dupont, D., Fisher, R., Fortin, D., Gable, T.D., Garcia, E., Geffen, E., Gehrt, S., Gillingham, M., Heard, D., Hebblewhite, M., Hinton, J.W., Homkes, A., Howden, C., Huber, D., Jackson, P.J., Joly, K., Kelly, A.P., Kelly, M., Kingdon, K., Kulkarni, A., Kusak, J., Kuzyk, G., Lake, B.C., Llaneza, L., Lopez-Bao, J.V., MacNulty, D., McLaren, A., McLoughlin, P., Merrill, E.H., Mills, K., Mitchell, N., Moore, S., Mumma, M., Murray, M., Musiani, M., Nakamura, M., Neilson, E., Neufeld, L., Newsome, T., Oakleaf, J., Palacios, V., Perdicas, M., Perry, T., Petroelje, T., Piper, C., Prokopenko, C., Prugh, L., Riley, S.P., Rio-Maior, H., Roffler, G., Rollins, D., Sand, H., Schmiegelow, F.K., Seip, D.R., Sorum, M.S., St. Clair, C., Steenweg, R., Strohbach, M., Tatler, J., Thaker, M., Thompson, C., Turner, J., Vanak, A.T., Vander Wal, E., Wabakken, P., Walter, S., Webster, S., Wheeldon, T., Wikenros, C., Windels, S.K., Young, J., Zabihi-Seissan, S., Zimmermann, B., and Patterson, B., 2025, Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups: Ecology, v. 106, no. 1, e4492, 22 p., https://doi.org/10.1002/ecy.4492.","productDescription":"e4492, 22 p.","ipdsId":"IP-151194","costCenters":[{"id":651,"text":"Western Ecological Research 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,{"id":70261941,"text":"70261941 - 2025 - Late Amazonian ice near Athabasca Valles, Mars: Recent megaflood or climate change?","interactions":[],"lastModifiedDate":"2025-01-06T15:05:14.621649","indexId":"70261941","displayToPublicDate":"2024-12-12T09:02:08","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Late Amazonian ice near Athabasca Valles, Mars: Recent megaflood or climate change?","docAbstract":"<p><span>The Athabasca Valles outflow channel system is among the youngest such channels on Mars, with the Athabasca Valles flood lava (AVFL) covering the channel floor and reaching far beyond. Volcanic rootless cones on the AVFL indicate the presence of H</span><sub>2</sub><span>O in the shallow subsurface at the time of lava emplacement. However, Athabasca Valles are near the equator, where ice would rapidly sublime in the current climate. Therefore, the source of water for the rootless cones is uncertain: the leading hypotheses are that it was deposited (i) from the atmosphere in a different climate, or (ii) by a large aqueous flood shortly before the lava was erupted. Here we test the aqueous flood hypothesis, using numerical models of floods traversing Athabasca Valles to determine whether they can provide water to the locations of observed rootless cones. A secondary test is to determine whether flood waters are available to carve Lethe Vallis, a distal channel likely carved by the same event that formed Athabasca Valles. We find that floods with volumes and fluxes based on previously published estimates are unable to reach the distal rootless cones or Lethe Vallis. This suggests either that the climate allowed equatorial ice to be present in the subsurface at the time of the AVFL, or that geologically recent aqueous floods in Athabasca Valles were much larger than indicated by published models.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2024.116406","usgsCitation":"Dundas, C., Keszthelyi, L., and Williams, K.E., 2025, Late Amazonian ice near Athabasca Valles, Mars: Recent megaflood or climate change?: Icarus, v. 429, no. 3, 116406, 17 p., https://doi.org/10.1016/j.icarus.2024.116406.","productDescription":"116406, 17 p.","ipdsId":"IP-167274","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":498063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2024.116406","text":"Publisher Index Page"},{"id":465667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Athabasca Valles, Mars","volume":"429","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":922358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":922359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Kaj E. 0000-0003-1755-1872 kewilliams@usgs.gov","orcid":"https://orcid.org/0000-0003-1755-1872","contributorId":196988,"corporation":false,"usgs":true,"family":"Williams","given":"Kaj","email":"kewilliams@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":922360,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"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 Page"},{"id":484852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, 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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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","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":70262436,"text":"70262436 - 2025 - Roles of host and environment in shift of primary anthrax host species in Kruger National Park","interactions":[],"lastModifiedDate":"2025-01-22T17:26:50.190108","indexId":"70262436","displayToPublicDate":"2024-12-06T11:18:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Roles of host and environment in shift of primary anthrax host species in Kruger National Park","docAbstract":"<p><span>Environmental and climatic factors, as well as host demographics and behaviour, significantly influence the exposure of herbivorous mammalian hosts to pathogens such as&nbsp;</span><i>Bacillus anthracis</i><span>, the causative agent of anthrax. Until the early 1990s in Kruger National Park (KNP), kudu (</span><i>Tragelaphus strepsiceros</i><span>) was the host species most affected by anthrax, with outbreaks occurring predominantly in the dry season, particularly during drought cycles. However, the most affected host species has shifted to impala (</span><i>Aepyceros melampus</i><span>), with more frequent anthrax outbreaks during the wet season. This study investigates the roles of environmental variation and other host species in this shift. Temporal trends in environmental variables such as precipitation, soil moisture, temperature, and normalised difference vegetation index (NDVI) were analyzed in relation to anthrax occurrence (presence/ absence and counts). Additionally, correlations between host species’ densities and anthrax mortalities over time were examined. Anthrax cases in 1990 were concentrated in the central and northern regions of KNP(excluding Pafuri), primarily affected kudus; while subsequent mortalities affected mostly impala and were restricted to the far north, in Pafuri. Significant correlations were found between kudu anthrax mortality and a decrease in NDVI, average temperature, SPI-6 and SPI-12 (Standardised Precipitation Index in various time intervals. Conversely, anthrax occurrence in impalas was associated with a decline in SPI-3, and temperature rise, with increased mortality during the rainy season. Elephant density correlated negatively with kudu mortality, but a positive correlation with both impala mortality and impala density. The study concludes that environmental variables and species’ densities may alter the diversity and frequency of hosts exposed to&nbsp;</span><i>B</i><span>.&nbsp;</span><i>anthracis</i><span>. Climate extremes and alterations therein may exacerbate anthrax severity by modifying species susceptibility and their probability of exposure over time.</span></p>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0314103","usgsCitation":"Ochai, S.O., Snyman, L., Dolfi, A., Ramoelo, A., Reilly, B., Botha, J., Dekker, E., van Schalkwyk, O., Kamath, P., Archer, E., Turner, W.C., and Heerden, H.V., 2025, Roles of host and environment in shift of primary anthrax host species in Kruger National Park: PLoS ONE, v. 19, no. 12, e0314103, 20 p., https://doi.org/10.1371/journal.pone.0314103.","productDescription":"e0314103, 20 p.","ipdsId":"IP-167470","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481035,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0314103","text":"Publisher Index Page"},{"id":480940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Africa","otherGeospatial":"Kruger National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              31.06582138167292,\n              -22.416075336478343\n            ],\n            [\n              30.859117075132964,\n              -22.738484839932983\n            ],\n            [\n              30.891662008503246,\n              -23.060894343387623\n            ],\n            [\n              31.34226541868827,\n              -24.890478750913203\n            ],\n            [\n              31.98207203141098,\n              -24.929702162871806\n            ],\n            [\n              32.08691048237788,\n              -24.790395342372864\n            ],\n            [\n              31.58260787913791,\n              -23.200094425169404\n            ],\n            [\n              31.287064700425418,\n              -22.399809244114635\n            ],\n            [\n              31.06582138167292,\n              -22.416075336478343\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"19","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ochai, Sunday O.","contributorId":342466,"corporation":false,"usgs":false,"family":"Ochai","given":"Sunday","email":"","middleInitial":"O.","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snyman, Lourens","contributorId":349287,"corporation":false,"usgs":false,"family":"Snyman","given":"Lourens","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dolfi, Amelie C.","contributorId":342314,"corporation":false,"usgs":false,"family":"Dolfi","given":"Amelie C.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":924193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramoelo, Abel","contributorId":349288,"corporation":false,"usgs":false,"family":"Ramoelo","given":"Abel","affiliations":[{"id":48053,"text":"University of Pretoria","active":true,"usgs":false}],"preferred":false,"id":924194,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reilly, Brian K.","contributorId":349290,"corporation":false,"usgs":false,"family":"Reilly","given":"Brian K.","affiliations":[{"id":83464,"text":"University of Free State","active":true,"usgs":false}],"preferred":false,"id":924195,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Botha, Judith M.","contributorId":349292,"corporation":false,"usgs":false,"family":"Botha","given":"Judith M.","affiliations":[{"id":48535,"text":"South African National Parks","active":true,"usgs":false}],"preferred":false,"id":924196,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dekker, Edgar H.","contributorId":343067,"corporation":false,"usgs":false,"family":"Dekker","given":"Edgar H.","affiliations":[{"id":81972,"text":"Government of South Africa","active":true,"usgs":false}],"preferred":false,"id":924197,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"van Schalkwyk, O. 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,{"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 States","state":"Oregon, 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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":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"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":70261615,"text":"70261615 - 2025 - Sea level rise threatens Florida’s insular vertebrate biodiversity","interactions":[],"lastModifiedDate":"2025-02-24T16:52:59.393638","indexId":"70261615","displayToPublicDate":"2024-12-05T08:44:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Sea level rise threatens Florida’s insular vertebrate biodiversity","docAbstract":"<p><span>Islands are some of the most biodiverse places on earth, but they are also hotspots of biodiversity loss. The coastline of Florida, U.S.A., is surrounded by thousands of islands, many of which are home to species that occur nowhere else. A rapidly emerging threat to these low-lying islands is inundation as sea levels rise. The capacity of island-dwelling species to adapt to climate change and sea level rise may be limited because many species do not have the ability to shift their distribution off the island to track favorable conditions. We assessed the vulnerability of Florida’s islands to inundation from sea level rise and estimated the terrestrial biodiversity on Florida’s islands that could be lost. Our models predicted that by 2100, over 80% and up to 90% of Florida’s islands could be completely inundated from sea level rise, depending on the sea level rise projection (1.2&nbsp;m or 2.2&nbsp;m). Of the 85 mammalian, reptilian, and amphibian species on our subset list of Florida’s Species of Greatest Conservation Need, over half occur on Florida’s islands for at least part of their range, highlighting the importance of these islands for housing Florida’s rich biodiversity. Notably, at least 12 mammal species and 7 reptile species have their entire distribution on Florida’s islands, and this count is likely an underestimate. Projections of future sea level rise mean that these island-endemic species face the threat of extinction in the wild if their island habitat is submerged.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10531-024-02984-w","usgsCitation":"Koen, E.L., Barichivich, W.J., Braun De Torrez, E., and Walls, S., 2025, Sea level rise threatens Florida’s insular vertebrate biodiversity: Biodiversity and Conservation, v. 34, p. 513-530, https://doi.org/10.1007/s10531-024-02984-w.","productDescription":"18 p.","startPage":"513","endPage":"530","ipdsId":"IP-158013","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":466726,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10531-024-02984-w","text":"Publisher Index Page"},{"id":465186,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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0000-0002-8903-6776","orcid":"https://orcid.org/0000-0002-8903-6776","contributorId":347039,"corporation":false,"usgs":false,"family":"Braun De Torrez","given":"Elizabeth","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":921197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walls, Susan 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":216235,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":921198,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70263683,"text":"70263683 - 2025 - Hurricane wave energy dissipation and wave-driven currents over a fringing reef","interactions":[],"lastModifiedDate":"2025-02-20T15:50:37.166016","indexId":"70263683","displayToPublicDate":"2024-12-04T09:46:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Hurricane wave energy dissipation and wave-driven currents over a fringing reef","docAbstract":"<p><span>In 2018, two successive tropical cyclones, Hurricane Hector and Hurricane Lane, generated waves that impacted the Hawaiian Islands. This study investigates wave breaking over a broad fringing reef and aims to quantify the magnitudes and length scales of the corresponding wave-driven circulation using detailed field observations and numerical models corresponding to these wave events. Detailed wave and current measurements were collected across a 1200-m wide cross-reef transect off the coral reef-lined south coast of Moloka’i, Hawai’i. High-resolution numerical model grids were developed to resolve reef features and the coupled Delft3D-SWAN modeling system was applied to simulate spectral wave transformation and wave-driven currents for these two energetic ocean wave events generated by distant passing hurricanes. The results indicate that the wave-driven circulation is generally weak, with current speeds typically less than 0.15&nbsp;m/s for the wave conditions generated by Hurricane Lane, with significant wave heights up to 1.9&nbsp;m. Higher energy dissipation rates from larger waves up to 2.5&nbsp;m breaking during Hurricane Hector resulted in stronger observed currents up to approximately 0.3&nbsp;m/s. However, the model results show that these currents are confined to the wave-breaking region over the upper fore reef in a narrow (100–300&nbsp;m) region near the reef crest, and weaker flows of less than 0.1&nbsp;m/s are generated over the shallow and wide reef flat. Wave heights across the reef flat are less than 0.5&nbsp;m and are controlled by the tidal water levels. The coral reef structures therefore provide significant protection for the coastline even during large wave and variable sea level conditions. Climate change is likely to increase sea level and storm intensity, the combination of which will influence wave transmission over fringing reefs that may degrade habitat, fueling the need for further research on changing conditions on coral reef-lined coasts.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00338-024-02604-7","usgsCitation":"Zimmerman, Z., Mulligan, R., and Storlazzi, C.D., 2025, Hurricane wave energy dissipation and wave-driven currents over a fringing reef: Coral Reefs, v. 44, p. 291-308, https://doi.org/10.1007/s00338-024-02604-7.","productDescription":"18 p.","startPage":"291","endPage":"308","ipdsId":"IP-154227","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":482275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Moloka'i","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -157.25144019635636,\n              21.108414838715447\n            ],\n            [\n              -157.25144019635636,\n              21.065649812518444\n            ],\n            [\n              -157.1105420908326,\n              21.065649812518444\n            ],\n            [\n              -157.1105420908326,\n              21.108414838715447\n            ],\n            [\n              -157.25144019635636,\n              21.108414838715447\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2024-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Zoe","contributorId":351060,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Zoe","affiliations":[{"id":83909,"text":"U.Queens","active":true,"usgs":false}],"preferred":false,"id":927812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Ryan","contributorId":330362,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":927813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927814,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70261308,"text":"70261308 - 2025 - Assessing the sustainability of Pacific walrus harvest in a changing environment","interactions":[{"subject":{"id":70261311,"text":"70261311 - 2024 - Assessing the sustainability of Pacific walrus harvest in a changing environment","indexId":"70261311","publicationYear":"2024","noYear":false,"title":"Assessing the sustainability of Pacific walrus harvest in a changing environment"},"predicate":"SUPERSEDED_BY","object":{"id":70261308,"text":"70261308 - 2025 - Assessing the sustainability of Pacific walrus harvest in a changing environment","indexId":"70261308","publicationYear":"2025","noYear":false,"title":"Assessing the sustainability of Pacific walrus harvest in a changing environment"},"id":1}],"lastModifiedDate":"2024-12-26T17:01:54.834482","indexId":"70261308","displayToPublicDate":"2024-12-03T09:18:15","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":"Assessing the sustainability of Pacific walrus harvest in a changing environment","docAbstract":"<p><span>Harvest sustainability is a primary goal of wildlife management and conservation, and in a changing world, it is increasingly important to consider environmental drivers of population dynamics alongside harvest in cohesive management plans. This is particularly pertinent for harvested species that acutely experience effects of climate change. The Pacific walrus (</span><i>Odobenus rosmarus divergens</i><span>), a crucial subsistence resource for Indigenous communities, is simultaneously subject to rapid habitat loss associated with diminishing sea ice and an increasing anthropogenic footprint in the Arctic. We developed a theta-logistic population modeling-management framework to evaluate various harvest scenarios combined with 4 potential climate and disturbance scenarios (ranging from optimistic to pessimistic, based largely on sea ice projections from general circulation models) to simulate Pacific walrus population dynamics to the end of the twenty-first century, focusing on the independent-aged female subset of the population. We considered 2 types of harvest strategies: 1) state-dependent harvest scenarios wherein we calculated harvest as a percentage of the population and updated annual harvests at set intervals as the population was reassessed, and 2) annually consistent harvest scenarios wherein annual harvest levels remain consistent into the future. All climate and disturbance scenarios indicated declines of varying severity in Pacific walrus abundance to the end of the twenty-first century, even in the absence of harvest. However, we found that a state-dependent annual harvest of 1.23% of the independent-aged female subset of the population (e.g., 1,280 independent-aged females harvested in 2020, similar to contemporary harvest levels) met our criterion for sustainability under all climate and disturbance scenarios, considering a medium risk tolerance level of 25%. This indicates that the present rate of Pacific walrus harvest is sustainable and will continue to be—provided the population is assessed at regular intervals and harvest is adapted to match changes in population dynamics. Our simulations indicate that a sustainable annually-consistent harvest is also possible but only at low levels if the population declines as expected. Applying a constant annual harvest of 1,280 independent-aged females failed to meet our criterion for sustainability under 3 of the 4 climate and disturbance scenarios we evaluated and had a higher probability of quasi-extinction than an equivalent state-dependent harvest scenario (1.23%). We highlight the importance of state-dependent management strategies and suggest our modeling framework is useful for managing harvest sustainability in a changing climate.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22686","usgsCitation":"Johnson, D.L., Eisaguirre, J.M., Taylor, R.L., Andersen, E.M., and Garlich-Miller, J.L., 2025, Assessing the sustainability of Pacific walrus harvest in a changing environment: Journal of Wildlife Management, v. 89, no. 1, e22686, 24 p., https://doi.org/10.1002/jwmg.22686.","productDescription":"e22686, 24 p.","ipdsId":"IP-154405","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":466682,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22686","text":"Publisher Index Page"},{"id":464804,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Devin L.","contributorId":340459,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"L.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":920328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eisaguirre, Joseph Michael 0000-0002-0450-8472","orcid":"https://orcid.org/0000-0002-0450-8472","contributorId":301980,"corporation":false,"usgs":true,"family":"Eisaguirre","given":"Joseph","email":"","middleInitial":"Michael","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":920329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":920330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andersen, Erik M.","contributorId":346944,"corporation":false,"usgs":false,"family":"Andersen","given":"Erik","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":920331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garlich-Miller, Joel L.","contributorId":288799,"corporation":false,"usgs":false,"family":"Garlich-Miller","given":"Joel","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":920332,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"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":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest 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":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 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,{"id":70263582,"text":"70263582 - 2025 - International data gaps at the Center for Engineering Strong Motion Data","interactions":[],"lastModifiedDate":"2025-02-18T16:53:20.52639","indexId":"70263582","displayToPublicDate":"2024-12-01T10:50:55","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"International data gaps at the Center for Engineering Strong Motion Data","docAbstract":"<p>The Center for Engineering Strong Motion Data (CESMD) is utilized by seismologists, engineers, and disaster management professionals in the US and has historically achieved and distributed waveforms from across the globe for significant earthquakes. The increased access to the waveforms via Web API (Application Programming Interface) offers a unique opportunity to provide the community complete datasets, sampling a variety of tectonic environments and geologic conditions, increasing the number of available ground motion records for use in ground motion models (GMMs) and improving the accuracy of earthquake engineering evaluations. The objective of this study is to programmatically identify gaps in global event data from the past decade and backfill missing data gaps at CESMD. We first compare the CESMD catalog with the Advanced National Seismic System (ANSS) Comprehensive Earthquake Catalog identifying regions and time periods where strong-motion data is limited or inadequate. To backfill datasets at CESMD for significant events, we pinpoint regions and time intervals that lack information, creating a list of events for which we’d like to obtain data. An important facet of this work is identifying the source of data and metadata across earthquake repositories around the world and integrating these data repositories into our current strong-motion data processing workflow. In parallel with these newly processed datasets, we are developing a script to produce data origination citations to include provenance and attribution information to associate with respective datasets at CESMD. We showcase our methodology for identifying and filling data gaps at CESMD using three case studies (the 2018 Anchorage Alaska earthquake sequence, seismicity associated with the 2018 Hawaiian Kilauea volcano eruption, and several earthquakes in Turkey) and then outline our strategy to apply our data gap backfilling methods on an international scale.</p>","conferenceTitle":"18th World Conference on Earth Engineering 2024","conferenceDate":"June 30-Jul 5, 2024","conferenceLocation":"Milan, Italy","language":"English","publisher":"International Association for Earthquake Engineering","usgsCitation":"Shao, H., Brody, J., Schleicher, L.S., Marano, K., Steidl, J.H., Thompson, E.M., Hearne, M., and Blair, J., 2025, International data gaps at the Center for Engineering Strong Motion Data, 18th World Conference on Earth Engineering 2024, Milan, Italy, June 30-Jul 5, 2024, 12 p.","productDescription":"12 p.","ipdsId":"IP-162021","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":482092,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://proceedings-wcee.org/view.html?id=24960&conference=18WCEE"},{"id":482172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shao, Han 0000-0003-3906-0943","orcid":"https://orcid.org/0000-0003-3906-0943","contributorId":333675,"corporation":false,"usgs":true,"family":"Shao","given":"Han","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brody, Jeff 0000-0001-8324-1261","orcid":"https://orcid.org/0000-0001-8324-1261","contributorId":201880,"corporation":false,"usgs":true,"family":"Brody","given":"Jeff","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schleicher, Lisa Sue 0000-0001-6528-1753","orcid":"https://orcid.org/0000-0001-6528-1753","contributorId":264892,"corporation":false,"usgs":true,"family":"Schleicher","given":"Lisa","email":"","middleInitial":"Sue","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marano, Kristin 0000-0002-0420-2748 kmarano@usgs.gov","orcid":"https://orcid.org/0000-0002-0420-2748","contributorId":207906,"corporation":false,"usgs":true,"family":"Marano","given":"Kristin","email":"kmarano@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steidl, Jamison Haase 0000-0003-0612-7654","orcid":"https://orcid.org/0000-0003-0612-7654","contributorId":239709,"corporation":false,"usgs":true,"family":"Steidl","given":"Jamison","email":"","middleInitial":"Haase","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927433,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blair, James Luke 0000-0003-1678-5634","orcid":"https://orcid.org/0000-0003-1678-5634","contributorId":333670,"corporation":false,"usgs":true,"family":"Blair","given":"James Luke","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927434,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
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