Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7: Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm7C29","programNote":"Mineral Resources Program","usgsCitation":"Ellefsen, K.J., Wang, B., and Goldman, M.A., 2025, Bayesian mapping of regionally grouped, sparse, univariate earth science data: U.S. Geological Survey Techniques and Methods, book 7, chap. C29, 20 p., https://doi.org/10.3133/tm7C29.","productDescription":"iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-148248","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":485233,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c29/coverthb2.jpg"},{"id":485714,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm7C29/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"T and M 7C29"},{"id":485567,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/07/c29/tm7c29.xml"},{"id":485566,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/07/c29/images"},{"id":485235,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P14X4CKG","text":"USGS software release","linkHelpText":"Software for Bayesian mapping of regionally grouped, sparse, univariate earth science data (program BMRGSU)"},{"id":485234,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c29/tm7c29.pdf","text":"Report","size":"9.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 7C29"}],"country":"United States","state":"Alaska","otherGeospatial":"Taylor Mountains quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159,\n 61\n ],\n [\n -159,\n 60\n ],\n [\n -156,\n 60\n ],\n [\n -156,\n 61\n ],\n [\n -159,\n 61\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
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Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/eds.2025.3","usgsCitation":"Reyes, J., Oh, G., McGahan, I., Ma, T., Russell, R., Walsh, D.P., and Zhu, J., 2025, Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations: Environmental Data Science, v. 4, e28, 23 p., https://doi.org/10.1017/eds.2025.3.","productDescription":"e28, 23 p.","ipdsId":"IP-160182","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490167,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/eds.2025.3","text":"Publisher Index Page"},{"id":489410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Reyes, Juan Francisco Mandujano","contributorId":356170,"corporation":false,"usgs":false,"family":"Reyes","given":"Juan Francisco Mandujano","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oh, Gina","contributorId":333634,"corporation":false,"usgs":false,"family":"Oh","given":"Gina","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGahan, Ian","contributorId":333637,"corporation":false,"usgs":false,"family":"McGahan","given":"Ian","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Ting Fung","contributorId":356257,"corporation":false,"usgs":false,"family":"Ma","given":"Ting Fung","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":938923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Robin 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":333621,"corporation":false,"usgs":false,"family":"Russell","given":"Robin","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938925,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zhu, Jun","contributorId":356177,"corporation":false,"usgs":false,"family":"Zhu","given":"Jun","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":938926,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266550,"text":"70266550 - 2025 - A partner-driven decision support model to inform the reintroduction of bull trout","interactions":[],"lastModifiedDate":"2025-05-09T15:23:24.336355","indexId":"70266550","displayToPublicDate":"2025-05-08T10:13:24","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":"A partner-driven decision support model to inform the reintroduction of bull trout","docAbstract":"Assessments of species reintroductions involve a series of complex decisions that include human perspectives and ecological contexts. Here, we present a reintroduction assessment involving bull trout (Salvelinus confluentus) using a structured decision-making process. We approached this assessment by engaging partners representing public utilities, government agencies, and Tribes with shared interests in a potential reintroduction. These individuals identified objectives, decision alternatives, and ecological scenarios that were incorporated into a co-produced simulation-based model of potential reintroduction outcomes. The model included mathematical representations of habitat availability, life history expression, and assumptions regarding constraints on potential bull trout populations. Within each recipient stream, partners chose to explore a wide range of decision alternatives and simulated scenarios affecting reintroduction success. Results suggested that 1) reintroductions using eggs or adults were most optimal, 2) adding more individuals resulted in diminishing returns, 3) access to migratory habitat could improve success, and 4) the diversity of opportunities for life history expression led to improved reintroduction opportunities. In addition, modeled scenarios indicated some recipient streams consistently produced lower abundance of reintroduced bull trout. This work contributes a novel example to a growing portfolio of reintroduction assessments that may inform future conservation for bull trout and many other species facing similar challenges.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0323427","usgsCitation":"Benjamin, J.R., Neibauer, J., Anthony, H., Vazquez, J., Rawhouser, A., and Dunham, J., 2025, A partner-driven decision support model to inform the reintroduction of bull trout: PLoS ONE, v. 20, no. 5, e0323427, 17 p., https://doi.org/10.1371/journal.pone.0323427.","productDescription":"e0323427, 17 p.","ipdsId":"IP-172949","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":490112,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0323427","text":"Publisher Index Page"},{"id":485650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Chelan watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.49036241599774,\n 48.04634063295097\n ],\n [\n -120.37067822007936,\n 48.16552254778642\n ],\n [\n -120.75794320314404,\n 48.538515779248854\n ],\n [\n -120.80213597240349,\n 48.5303354671282\n ],\n [\n -121.11319724267128,\n 48.54549059352783\n ],\n [\n -121.18989609066836,\n 48.38742171862049\n ],\n [\n -121.0025710146728,\n 48.255137103181255\n ],\n [\n -120.49036241599774,\n 48.04634063295097\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":936553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neibauer, Judith","contributorId":354836,"corporation":false,"usgs":false,"family":"Neibauer","given":"Judith","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":936554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Hugh","contributorId":354839,"corporation":false,"usgs":false,"family":"Anthony","given":"Hugh","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":936555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vazquez, Jose","contributorId":354841,"corporation":false,"usgs":false,"family":"Vazquez","given":"Jose","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":936556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rawhouser, Ashley","contributorId":243429,"corporation":false,"usgs":false,"family":"Rawhouser","given":"Ashley","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":936557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":936558,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266306,"text":"70266306 - 2025 - Variability in hydrologic response to wildfire between snow zones in forested headwaters","interactions":[],"lastModifiedDate":"2025-05-15T15:08:04.001368","indexId":"70266306","displayToPublicDate":"2025-05-08T10:02:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Variability in hydrologic response to wildfire between snow zones in forested headwaters","docAbstract":"Rising temperatures and shifting fire regimes in the western United States are pushing fires upslope into areas of deep winter snowpack, where we have little knowledge of the likely hydrologic impacts of wildfire. We quantified differences in the timing and magnitude of stormflow responses to summer rainstorms among six catchments of varying levels of burn severity and seasonal snowpack cover for years 1–3 after the 2020 Cameron Peak fire. Our objectives were to (1) examine whether responsiveness, magnitude, and timing of stormflow responses to rainfall vary between burned and unburned catchments and between snow zones, and (2) identify the factors that affect these responses. We evaluated whether differences in storm hydrograph peak flow, total flow, stage rise, and lag to peak time differed by snow zone and burn category using generalised linear models. Additional predictors in these models are the maximum 60-min rainfall intensity for each storm, the cumulative potential water deficit prior to the storm, and the year post-fire. These models showed that the high snow zone (HSZ) has higher total stormflow than the low snow zone (LSZ), likely due to the higher soil moisture content in that area. In both snow zones, the biggest driver of the magnitude of the stormflow response was MI60. Burn category did not have a clear impact on stormflow response in the HSZ, but it did impact stage rise at the severely burned catchment in the LSZ. This was the only site that had widespread overland flow post-fire. These results demonstrate that the stormflow responses to fire vary between snow zones, indicating a need to account for elevation and snow persistence in post-fire risk assessments.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70151","usgsCitation":"Miller, Q., Barnard, D.M., Sears, M., Hammond, J., and Kampf, S., 2025, Variability in hydrologic response to wildfire between snow zones in forested headwaters: Hydrological Processes, v. 39, no. 5, e70151, 16 p., https://doi.org/10.1002/hyp.70151.","productDescription":"e70151, 16 p.","ipdsId":"IP-172047","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":490124,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70151","text":"Publisher Index Page"},{"id":485996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 41\n ],\n [\n -106,\n 40.333\n ],\n [\n -105,\n 40.333\n ],\n [\n -105,\n 41\n ],\n [\n -106,\n 41\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Quinn","contributorId":354373,"corporation":false,"usgs":false,"family":"Miller","given":"Quinn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David M 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":222833,"corporation":false,"usgs":false,"family":"Barnard","given":"David","email":"","middleInitial":"M","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":935515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sears, Megan","contributorId":354374,"corporation":false,"usgs":false,"family":"Sears","given":"Megan","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":935517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kampf, Stephanie","contributorId":346221,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935518,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267309,"text":"70267309 - 2025 - Leveraging detection uncertainty to estimate Renibacterium salmoninarum infection status among multiple tissues and assays","interactions":[],"lastModifiedDate":"2025-05-20T16:55:57.977539","indexId":"70267309","displayToPublicDate":"2025-05-08T09:45:45","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":"Leveraging detection uncertainty to estimate Renibacterium salmoninarum infection status among multiple tissues and assays","docAbstract":"Effective disease surveillance relies on accurate pathogen testing and robust prevalence estimates. Diagnostic specificity (DSp), the probability that an uninfected animal tests negative, is high when false positives are low. Diagnostic sensitivity (DSe) is the probability an infected animal tests positive; higher DSe means fewer false negatives. However, sensitivity and false negatives are harder to estimate without a \"gold standard\", an assay that can detect between 90 - 100% of true positive infections. Occupancy estimation of infection prevalence offers one solution by allowing for imperfect detection of the pathogen. Testing potentially infected tissues multiple times allows for the use of a Bayesian multistate occupancy model to estimate the probability of pathogen infection in tissues [Formula: see text] and detection probabilities [Formula: see text] for different assays. Using [Formula: see text] and [Formula: see text] from the posterior distribution, the conditional probability of detecting the pathogen can be modeled, allowing for the calculation of DSe. Renibacterium salmoninarum is a bacterial pathogen causing bacterial kidney disease among salmonid species and was the model pathogen we used to train our model. The current testing standard for salmonids combines initial screening for antibodies using direct fluorescent antibody test (DFAT) with polymerase chain reaction (PCR) confirmation to detect R. salmoninarum. However, detection of R. salmoninarum still varies between species, tissues, and assays. Here, a multi-state occupancy model was used to estimate detection probability among individual and dual kidney/liver infections with DFAT and qPCR in fish with an unknown infection status. Both assays produced false negatives, but qPCR had fewer than DFAT and a higher DSe. Infection state was often misclassified, but multiple surveys per individual or combining tissues for testing improved DSe for both assays.
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models improves inference","interactions":[],"lastModifiedDate":"2025-05-09T15:11:57.95249","indexId":"70266525","displayToPublicDate":"2025-05-08T08:01:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Marginalizing time in habitat selection and species distribution models improves inference","docAbstract":"Aim
Recent methodological advances for studying how animals move and use space with telemetry data have focused on fine-scale, more mechanistic inference. However, in many cases, researchers and managers remain interested in larger scale questions regarding species distribution and habitat use across study areas, landscapes, or seasonal ranges. Point processes offer a unified framework for many methods applied in studies of species distribution and resource selection; however, challenges remain in terms of dealing with temporal autocorrelation common in many types of telemetry data collected from animal locations.
Innovation
Space–time point processes (STPPs) have a unique property, in that marginalising time offers a connection between individual animal movement and broader point processes, yet this property has seen little attention in both statistical and applied research. In this paper, we first present some of the details of this marginalisation property and methods for applying marginalised STPPs (mSTTPs) to autocorrelated telemetry data and then apply a mSTTP in a case study on the summer space use and habitat selection of female caribou (Rangifer tarandus) in Denali National Park and Preserve, Alaska.
Main Conclusions
The case study demonstrated that an mSTPP approach can improve inference over other commonly used methods in terms of its ability to account for temporal autocorrelation and offers greater precision in parameter estimates and improved predictions of space use. As this method fits conveniently into the existing point process frameworks, it offers a practical solution to dealing with temporal autocorrelation inherent to many types of telemetry data when research questions center around broader scale patterns of animal habitat selection and space use.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.70028","usgsCitation":"Eisaguirre, J.M., Adams, L., Borg, B., and Johnson, H.E., 2025, Marginalizing time in habitat selection and species distribution models improves inference: Diversity and Distributions, v. 31, no. 5, e70028, 9 p., https://doi.org/10.1111/ddi.70028.","productDescription":"e70028, 9 p.","ipdsId":"IP-170546","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":488294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.70028","text":"Publisher Index Page"},{"id":485648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali National Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151.66979451782657,\n 64.15039809953939\n ],\n [\n -151.66979451782657,\n 63.132768852129516\n ],\n [\n -147.1767819339525,\n 63.132768852129516\n ],\n [\n -147.1767819339525,\n 64.15039809953939\n ],\n [\n -151.66979451782657,\n 64.15039809953939\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"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":936464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":936465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borg, Bridget","contributorId":173862,"corporation":false,"usgs":false,"family":"Borg","given":"Bridget","affiliations":[{"id":27306,"text":"Denali Natil Park and Preserve","active":true,"usgs":false}],"preferred":false,"id":936466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":936467,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266848,"text":"70266848 - 2025 - Organic matter composition versus microbial source: Controls on carbon loss from fen wetland and permafrost soils","interactions":[],"lastModifiedDate":"2025-05-13T15:35:55.063862","indexId":"70266848","displayToPublicDate":"2025-05-07T10:26:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9326,"text":"JGR Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Organic matter composition versus microbial source: Controls on carbon loss from fen wetland and permafrost soils","docAbstract":"Wetland and permafrost soils contain some of Earth's largest reservoirs of organic carbon, and these stores are threatened by rapid warming across the Arctic. Nearly half of northern wetlands are affected by permafrost. As these ecosystems warm, the cycling of dissolved organic matter (DOM) and the opportunities for microbial degradation are changing. This is particularly evident as the relationship between wetland and permafrost DOM dynamics evolves, especially with the introduction of permafrost-derived DOM into wetland environments. Thus, understanding the interplay of DOM composition and microbial communities from wetlands and permafrost is critical to predicting the impact of released carbon on global carbon cycling. As little is understood about the interactions between wetland active layer and permafrost-derived sources as they intermingle, we conducted experimental bioincubations of mixtures of DOM and microbial communities from two fen wetland depths (shallow: 0–15 cm, and deep: 15–30 cm) and two ages of permafrost soil (Holocene and Pleistocene). We found that the source of microbial inoculum was not a significant driver of dissolved organic carbon (DOC) degradation across treatments; rather, DOM source and specifically, DOM molecular composition, controlled the rate of DOC loss over 100 days of bioincubations. DOC loss across all treatments was negatively correlated with modified aromaticity index, O/C, and the relative abundance of condensed aromatic and polyphenolic formula, and positively correlated with H/C and the relative abundance of aliphatic and peptide-like formula. Pleistocene permafrost-derived DOC exhibited ∼70% loss during the bioincubation driven by its initial molecular-level composition, highlighting its high bioavailability irrespective of microbial source.
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University","active":true,"usgs":false}],"preferred":false,"id":936907,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":936908,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mackelprang, Rachel","contributorId":200882,"corporation":false,"usgs":false,"family":"Mackelprang","given":"Rachel","email":"","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":936909,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shade, Ashley L.","contributorId":355140,"corporation":false,"usgs":false,"family":"Shade","given":"Ashley L.","affiliations":[{"id":16636,"text":"CNRS","active":true,"usgs":false}],"preferred":false,"id":936910,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Spencer, Robert G.M.","contributorId":173304,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert G.M.","affiliations":[{"id":16705,"text":"Woods Hole Research Center","active":true,"usgs":false}],"preferred":false,"id":936911,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70266527,"text":"70266527 - 2025 - No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone","interactions":[],"lastModifiedDate":"2025-05-09T14:56:49.904737","indexId":"70266527","displayToPublicDate":"2025-05-07T09:48:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17454,"text":"Seismica","active":true,"publicationSubtype":{"id":10}},"title":"No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone","docAbstract":"It has been previously proposed that a megasplay fault within the Cascadia accretionary wedge, spanning from offshore Vancouver Island to Oregon, has the potential to slip during a future Cascadia subduction zone earthquake. This hypothetical fault has major implications for tsunami size and arrival times and is included in disaster-planning scenarios currently in use in the region. This hypothesis is evaluated in this study using CASIE21 deep-penetrating and U.S. Geological Survey high-resolution seismic reflection profiles. We map changes in wedge structural style and seismic character to identify the inner-outer wedge transition zone where a megasplay fault has been previously hypothesized to exist and evaluate evidence for active faulting within this zone. Our results indicate that there is not an active, through-going megasplay fault in Cascadia, but instead, the structure and activity of faulting at the inner-outer wedge transition zone is highly variable and segmented along strike, consistent with the segmentation of other physical and mechanical properties in Cascadia. Wedge sedimentation, plate dip, and subducting topography are proposed to play a major role in controlling megasplay fault development and evolution. Incorporating updated megasplay fault location, geometry, and activity into modeling of Cascadia earthquakes and tsunamis could help better constrain associated hazards.
","language":"English","publisher":"McGill University Libraries","doi":"10.26443/seismica.v2i4.1477","usgsCitation":"Lucas, M.C., Ledeczi, A., Tobin, H., Carbotte, S.M., Watt, J., Han, S., Boston, B., and Jiang, D., 2025, No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone: Seismica, v. 2, no. 4, 1477, 28 p., https://doi.org/10.26443/seismica.v2i4.1477.","productDescription":"1477, 28 p.","ipdsId":"IP-171867","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.26443/seismica.v2i4.1477","text":"Publisher Index Page"},{"id":485645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -129.8333,\n 49.5\n ],\n [\n -129.8333,\n 42\n ],\n [\n -123,\n 42\n ],\n [\n -123,\n 49.5\n ],\n [\n -129.8333,\n 49.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":936468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ledeczi, Anna M.","contributorId":354806,"corporation":false,"usgs":false,"family":"Ledeczi","given":"Anna M.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":936469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tobin, Harold J.","contributorId":354808,"corporation":false,"usgs":false,"family":"Tobin","given":"Harold J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":936470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carbotte, Suzanne M.","contributorId":339692,"corporation":false,"usgs":false,"family":"Carbotte","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":936471,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":936472,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Han, Shuoshuo","contributorId":339693,"corporation":false,"usgs":false,"family":"Han","given":"Shuoshuo","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":936473,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boston, Brian","contributorId":252937,"corporation":false,"usgs":false,"family":"Boston","given":"Brian","email":"","affiliations":[{"id":40272,"text":"Japan Agency for Marine-Earth Science and Technology","active":true,"usgs":false}],"preferred":false,"id":936474,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jiang, D.","contributorId":354811,"corporation":false,"usgs":false,"family":"Jiang","given":"D.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":936475,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70270858,"text":"70270858 - 2025 - Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs","interactions":[],"lastModifiedDate":"2025-08-26T15:34:04.782936","indexId":"70270858","displayToPublicDate":"2025-05-07T08:27:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs","docAbstract":"On 6 February 2023, Southern Türkiye was hit by devastating earthquakes, directly affecting over 14 million people in 11 cities, causing more than 50,000 deaths and the destruction of more than 800,000 buildings. This article goes beyond the physical damage imposed by the catastrophe to discuss the effects of the earthquakes on the operations of women-owned businesses. The mixed-method study with entrepreneurs belonging to a women’s business association operating in a moderately disrupted part of the region explores their struggles and recovery expectations. Thirty-five questionnaires were analyzed to identify the reasons for business closure, challenges, and needs faced in the post-disaster period and their recovery strategies. In addition, 23 entrepreneurs participated in roundtable discussions to provide a broader context to their responses to survey topics as well as lessons learned. Across both the survey and roundtables, while many respondents reported minor physical damage to their building, they also experienced financial and personal challenges from disruption to equipment, infrastructure, services, supply chains, institutional decisions, employee well-being, and customer base. Many used their business resources and personal savings to assist employees and others in the community. The women entrepreneurs often felt their recovery needs were ignored by government and private relief organizations and encountered barriers to receiving assistance from public and private institutions. Organizing together as women in business, even informally, provided mutual support during the crisis and recovery periods and catalyzed their role in support of their communities. The results illuminate functional community recovery as a balance of recovery of built infrastructure functionality and recovery of the broader social and economic fabric of the community.
","language":"English","publisher":"Sage","doi":"10.1177/87552930251330921","usgsCitation":"Orhan, E., Wein, A., Kroll, C., and Fung, J., 2025, Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs: Earthquake Spectra, v. 41, no. 3, p. 1910-1940, https://doi.org/10.1177/87552930251330921.","productDescription":"31 p.","startPage":"1910","endPage":"1940","ipdsId":"IP-166964","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":494904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Turkey","otherGeospatial":"southern Turkey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 34.331004781765444,\n 37.920957650366006\n ],\n [\n 34.331004781765444,\n 36.747538006336825\n ],\n [\n 40.125738345242354,\n 36.747538006336825\n ],\n [\n 40.125738345242354,\n 37.920957650366006\n ],\n [\n 34.331004781765444,\n 37.920957650366006\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Orhan, Ezgi","contributorId":360575,"corporation":false,"usgs":false,"family":"Orhan","given":"Ezgi","affiliations":[{"id":86042,"text":"Cankaya University, Turkiye","active":true,"usgs":false}],"preferred":false,"id":947222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":947223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroll, Cynthia","contributorId":360576,"corporation":false,"usgs":false,"family":"Kroll","given":"Cynthia","affiliations":[{"id":66280,"text":"Cynthia Kroll Consulting","active":true,"usgs":false}],"preferred":false,"id":947224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fung, Juan","contributorId":360577,"corporation":false,"usgs":false,"family":"Fung","given":"Juan","affiliations":[{"id":25356,"text":"National Institute of Standards and Technology","active":true,"usgs":false}],"preferred":false,"id":947225,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267683,"text":"70267683 - 2025 - Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)","interactions":[],"lastModifiedDate":"2025-05-29T15:03:15.907361","indexId":"70267683","displayToPublicDate":"2025-05-07T07:57:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)","docAbstract":"Long-term ecological studies are critical for providing insight into population dynamics and detecting population declines, particularly for species of conservation concern. However, spatiotemporal variation and logistical challenges make the identification of sudden population declines difficult. We conducted an in-water capture-mark-recapture study of mangrove diamond-backed terrapins (Malaclemys terrapin rhizophorarum) within Big Sable Creek, in Everglades National Park, Florida. We used an 18-year dataset (2001 to 2019) incorporating year, sex, hurricane occurrence, and sampling effort to estimate survival using Cormack–Jolly–Seber (CJS) models in Program Mark. Annual survivorship estimates were high from 2001 to 2003 for both sexes (91%–96%) and variable from 2006 to 2014 (77%–92%). Beginning in 2015, survival estimates exhibited a steeper decline (females: 65%, males 75%), and dropped to below 36% by 2018. Because the driver of this apparent population decline is unknown, we created a population projection matrix and used model-estimated annual survival to simulate annual terrapin population size. We then generated competing scenarios of low survival at various age classes to attempt to reproduce a simulated decline mirroring what we observed from our capture data. A scenario of low adult survival (75%–85%) from 2012 to 2018, possibly in conjunction with no reproduction after 2010, provides estimates of abundance that appear to match simulated annual population size and may indicate that adult emigration/human removal or a drastic drop in recruitment could be responsible for the apparent decline in survival. We explore reasons for this apparent decline and highlight difficulties common to long-term studies that may influence how declines are interpreted.
","language":"English","publisher":"British Ecological Society","doi":"10.1002/ece3.71347","usgsCitation":"Guzy, J.C., Smith, B., Denton, M., Cherkiss, M., Roche, D., Crowder, A., and Hart, K., 2025, Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum): Ecology and Evolution, v. 15, no. 5, e71347, 16 p., https://doi.org/10.1002/ece3.71347.","productDescription":"e71347, 16 p.","ipdsId":"IP-168394","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71347","text":"Publisher Index Page"},{"id":486731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Cape Sable, Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.29674951955056,\n 25.648529217591914\n ],\n [\n -81.29674951955056,\n 25.09922085696259\n ],\n [\n -80.79518175403075,\n 25.09922085696259\n ],\n [\n -80.79518175403075,\n 25.648529217591914\n ],\n [\n -81.29674951955056,\n 25.648529217591914\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938536,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":938537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denton, Mathew 0000-0002-1024-3722","orcid":"https://orcid.org/0000-0002-1024-3722","contributorId":210504,"corporation":false,"usgs":true,"family":"Denton","given":"Mathew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":218466,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roche, David 0000-0002-3329-2746 droche@usgs.gov","orcid":"https://orcid.org/0000-0002-3329-2746","contributorId":204332,"corporation":false,"usgs":true,"family":"Roche","given":"David","email":"droche@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":true,"id":938540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowder, Andrew G.","contributorId":355985,"corporation":false,"usgs":false,"family":"Crowder","given":"Andrew G.","affiliations":[{"id":84891,"text":"Xylem Analytics","active":true,"usgs":false}],"preferred":false,"id":938541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218324,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":938542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266883,"text":"70266883 - 2025 - Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","interactions":[],"lastModifiedDate":"2025-05-15T13:11:35.40062","indexId":"70266883","displayToPublicDate":"2025-05-06T09:26:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18328,"text":"Frontiers in Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","docAbstract":"Introduction: The Sacramento-San Joaquin River system (SSJ) of California includes both riverine, delta, and estuarine habitats and is among the most modified aquatic ecosystems in the United States. Water development projects in the system are associated with declines of many native species, including White Sturgeon Acipenser transmontanus.
Methods: We used White Sturgeon pectoral fin rays collected from 1983 to 2016 throughout the SSJ to assess long-term changes in growth and associations with thermal and hydrological conditions (i.e., temperature, discharge, salinity). Age and growth were estimated from 1,897 White Sturgeon varying in fork length from 25 to 210 cm and from age 0 to 33.
Results: Age structure varied through time with the oldest fish generally sampled during the mid-1980s. Growth of White Sturgeon in 1951–1970 was slower than growth of fish in 1971–1990 and 1991–2012. Growth of White Sturgeon during 1991–2012 was ~10% higher than during other time periods.
Discussion: Little variation in growth was explained by environmental covariates, suggesting that annual growth was likely influenced by factors not measured in our study. Alternatively, population structure and movement behavior of White Sturgeon in the SSJ may be such that the scale (i.e., spatial or temporal) of available habitat covariates was mismatched to the scale at which growth of White Sturgeon responds. Increased growth in recent times may be partly due to density-dependent processes in association with substantial declines in White Sturgeon population abundance over the last several decades. This research provides important information on long-term patterns in growth that contributes to the conservation and management of White Sturgeon in the SSJ and beyond.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffwsc.2025.1577065","usgsCitation":"Quist, M.C., Blackburn, S., Ulaski, M., and Jackson, Z., 2025, Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.: Frontiers in Freshwater Science, v. 3, 1577065, 10 p., https://doi.org/10.3389/ffwsc.2025.1577065.","productDescription":"1577065, 10 p.","ipdsId":"IP-175717","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488907,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffwsc.2025.1577065","text":"Publisher Index Page"},{"id":485931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.79850686101548,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 38.755876798924476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackburn, Shannon","contributorId":338596,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70275112,"text":"70275112 - 2025 - Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","interactions":[{"subject":{"id":70275112,"text":"70275112 - 2025 - Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","indexId":"70275112","publicationYear":"2025","noYear":false,"title":"Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70275077,"text":"ofr20261004 - 2026 - Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington","indexId":"ofr20261004","publicationYear":"2026","noYear":false,"title":"Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington"},"id":1}],"supersededBy":{"id":70275077,"text":"ofr20261004 - 2026 - Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington","indexId":"ofr20261004","publicationYear":"2026","noYear":false,"title":"Development of a two-stage lifecycle model to inform the trap-and-haul program for Oncorhynchus kisutch (coho salmon) in the Lewis River, Washington"},"lastModifiedDate":"2026-04-22T18:50:14.222897","indexId":"70275112","displayToPublicDate":"2025-05-06T09:17:38","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington","docAbstract":"Restoration of salmon populations in the upper Lewis River Basin depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (Project) operated by PacifiCorp and Cowlitz PUD (Utilities), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Coho salmon (Oncorhynchus kisutch) population upstream of the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult Coho salmon at Merwin Dam, the lower most dam within the Project, and transporting them by truck to spawn above Swift Dam, the upper most dam within the Project; and (2) the collection of out-migrating juvenile Coho salmon at the downstream collection facility at Swift Dam for transport and release below the Project. The reintroduction program began once the downstream collection facility at Swift Dam was commissioned in late-2012 with the first year of transport data being collected in 2013. Over the past decade, the Utilities have been collecting data on juvenile outmigrants and adult fish returns at the dams. The need to construct a life cycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (>15) of data collection are needed to adequately measure the life cycle production of coho salmon. Use of past data to construct models could help inform future data collection and provide a framework that can be updated annually to measure trap and haul program performance within a life cycle context (Note: Data are not currently available from PacifiCorp. Contact organization Chris Karchesky for further information).
Because Coho salmon can live as long as five years, estimating demographic parameters for Coho salmon populations over their life cycle requires at least 10 or more years of data collection. Over the past decade, PacifiCorp has been collecting data on fish collection efficiency and the numbers of adult and juvenile salmon transported around the Lewis River dams, providing sufficient data to formulate a life cycle model that can guide future data collection efforts and provide preliminary information to resource managers The goal of the statistical life cycle model was to estimate annual production and survival during two critical life-stage transitions (1) the freshwater production from escapement of adults released upstream of Swift Dam, and the collection of downstream migrating juveniles at the passage facility at Swift Dam, and (2) the smolt-to-adult survival from the time of collection at Swift Dam to their return as adults. We used the Beverton-Holt stock-recruitment model to estimate juvenile production from the number of spawners. This approach allowed us to test for density dependence at current spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. Productivity was then expressed as a function of the number of juveniles collected and transported downstream of the Project. Because juvenile Fish Collection Efficiency (FCE) directly affects the number of juveniles that survive to continue downstream migration, FCE is a primary determinant of fish production. Consequently, the modeling framework is well suited to evaluate the performance of trap and haul programs within a life cycle context.
The objectives of this study were to: (1) gather and collate available data on adult and juvenile Coho salmon at Merwin and Swift dams, (2) quantify adult escapement, juvenile abundance, and the age at outmigration and adult return, (3) describe, formulate, and fit the integrated population model (IPM) to the data, and (4) summarize our findings, identify data gaps, and identify potential opportunities for future studies that could provide information used to improve model estimation and inference. Our key findings were: (1) over and above the number of spawning females, FCE was the primary factor affecting productivity of Coho salmon above Swift Dam, (2) smolt-to-adult return (SAR) rates were relatively high considering that harvest was included in the estimate, averaging about 4.5% and ranging as high as 12.9%, and (3) juvenile capacity upriver of Swift Dam was difficult to estimate due to the limited range in spawning females over the time series of data, suggesting the model may be improved by collecting data at higher spawner abundances. In addition, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE = 1, was 64 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river versus the ocean, the model estimates should help inform fishery managers about the overall role that fish collection at Swift Dam plays in the recovery and sustainability of Lewis River Coho salmon. By providing the model with (1) more years of data, (2) higher numbers of spawning females, and (3) data on age at juvenile migration in relation to age at adult return greater certainty in the estimates of capacity and SAR can be attained. Ultimately, information provided by the model can assist in the evaluation and continued improvement of the current trap and haul program to support anadromous fishes in the Lewis River Basin.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.04.30.651546","usgsCitation":"Plumb, J., and Perry, R.W., 2025, Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington: BioRxiv, https://doi.org/10.1101/2025.04.30.651546.","productDescription":"34 p.","ipdsId":"IP-178609","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":502905,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":502978,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.04.30.651546","text":"External Repository"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":959472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":959473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70266492,"text":"70266492 - 2025 - Using long-term ecological datasets to unravel the impacts of short-term meteorological disturbances on phytoplankton communities","interactions":[],"lastModifiedDate":"2025-05-08T14:12:51.567682","indexId":"70266492","displayToPublicDate":"2025-05-06T09:07:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Using long-term ecological datasets to unravel the impacts of short-term meteorological disturbances on phytoplankton communities","docAbstract":"Extreme meteorological events such as storms are increasing in frequency and intensity, but our knowledge of their impacts on aquatic ecosystems and emergent system properties is limited. Understanding the ecological impacts of storms on the dynamics of primary producers remains a challenge that needs to be addressed to assess the vulnerability of freshwater ecosystems to extreme weather conditions and climate change.
One promising approach to gain insights into storm impacts on phytoplankton community dynamics is to analyse long-term monitoring datasets. However, such an approach requires disentangling the impacts of short-term meteorological disturbances from the effects of the seasonal trajectories of meteorological conditions. To this end, we applied boosted regression tree models to phytoplankton time series from eight relatively large lakes on four continents, coupled with a procedure adapted to detect and quantify rare events.
Overall, the patterns and potential drivers we identified provide important insights into the responses of lakes to short-term meteorological events and highlight differences in the response of phytoplankton communities according to lake morphological characteristics. Our results indicated that deepened thermoclines and lake-specific combinations of drivers describing altered thermal structures caused deviations from the typical trajectories of seasonal phytoplankton succession. For shallow polymictic lakes, shifts in phytoplankton succession also depended on changes in light availability.
Overall, our study highlights the value of long-term monitoring to improve our understanding of phytoplankton sensitivity to short-term meteorological disturbances.
Warming rivers and interactions with non-native species impact salmonid species globally. Understanding how hydroclimatic conditions synergistically and independently interact with non-native species is critical for effectively managing salmonids into the future. We used a 10-year mark–recapture dataset to assess how native Yellowstone cutthroat trout (YCT) Oncorhynchus virginalis bouvieri and non-native brown trout Salmo trutta growth rates and apparent survival were affected by hydroclimatic conditions and (for YCT) the presence of brown trout in a tributary. Growth (YCT) and survival (both species across size classes) were negatively related to warming stream temperatures. Brown trout growth was positively related to increasing daily streamflow variability (a proxy for streamflow), but this variable was not included in the top YCT growth model. Density-dependent effects appeared to be non-existent (growth) or weakly positive (survival). When sympatric with brown trout, YCT displayed worse survival than allopatric YCT across environmental conditions. Broadly, we found native and non-native trout respond to different hydroclimatic conditions that shift with changing climatic conditions, and brown trout represent an additional threat to YCT survival.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0211","usgsCitation":"Heinle, K., Al-Chokhachy, R., Sepulveda, A., and Verhille, C.E., 2025, Native Yellowstone cutthroat trout Oncorhynchus virginalis bouvieri growth and survival in a headwater stream primarily driven by warming stream temperatures, with non-native brown trout Salmo trutta posing an additional threat to survival: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-17, https://doi.org/10.1139/cjfas-2024-0211.","productDescription":"17 p.","startPage":"1","endPage":"17","ipdsId":"IP-168237","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":490403,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1WUVM5S","text":"USGS data release","linkHelpText":"Trout mark-recapture and stream temperature and streamflow data from Duck Creek, Montana"},{"id":486636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"East Fork Duck Creek, Henry Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.38754194568855,\n 45.95593917254632\n ],\n [\n -110.38754194568855,\n 45.80046830120395\n ],\n [\n -110.17467211725662,\n 45.80046830120395\n ],\n [\n -110.17467211725662,\n 45.95593917254632\n ],\n [\n -110.38754194568855,\n 45.95593917254632\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Heinle, Kadie B.","contributorId":355955,"corporation":false,"usgs":false,"family":"Heinle","given":"Kadie B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":938444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":222450,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":938445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":938446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verhille, Christine E.","contributorId":174642,"corporation":false,"usgs":false,"family":"Verhille","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":13461,"text":"U.C. Davis","active":true,"usgs":false}],"preferred":false,"id":938447,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268784,"text":"70268784 - 2025 - Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA","interactions":[],"lastModifiedDate":"2025-07-08T15:50:15.049077","indexId":"70268784","displayToPublicDate":"2025-05-06T08:46:13","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":"Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA","docAbstract":"In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.","language":"English","publisher":"Springer Nature","doi":"10.1007/s11069-025-07262-8","usgsCitation":"Triplett, L., Hammer, M.N., DeLong, S.B., Gran, K.B., Jennings, C.E., Engle, Z.T., Bartley, J., Blumentritt, D., Breckenridge, A., Day, S., Kohout, M., Larson, P., McDermott, J., and Richard, E., 2025, Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA: Natural Hazards, v. 121, p. 11799-11827, https://doi.org/10.1007/s11069-025-07262-8.","productDescription":"29 p.","startPage":"11799","endPage":"11827","ipdsId":"IP-176536","costCenters":[{"id":237,"text":"Earthquake Science 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sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":941944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gran, Karen B.","contributorId":288093,"corporation":false,"usgs":false,"family":"Gran","given":"Karen","email":"","middleInitial":"B.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":true,"id":941945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jennings, Carrie E.","contributorId":288092,"corporation":false,"usgs":false,"family":"Jennings","given":"Carrie","email":"","middleInitial":"E.","affiliations":[],"preferred":true,"id":941946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Engle, Zachary T. 0000-0002-6412-7727","orcid":"https://orcid.org/0000-0002-6412-7727","contributorId":300814,"corporation":false,"usgs":true,"family":"Engle","given":"Zachary","email":"","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":941947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bartley, Julie K.","contributorId":353117,"corporation":false,"usgs":false,"family":"Bartley","given":"Julie K.","affiliations":[{"id":84345,"text":"Gustavus Adolphus College","active":true,"usgs":false}],"preferred":false,"id":941948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blumentritt, Dylan J.","contributorId":353118,"corporation":false,"usgs":false,"family":"Blumentritt","given":"Dylan J.","affiliations":[{"id":61757,"text":"Winona State University","active":true,"usgs":false}],"preferred":false,"id":941949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Breckenridge, Andy","contributorId":357609,"corporation":false,"usgs":false,"family":"Breckenridge","given":"Andy","affiliations":[{"id":33516,"text":"University of Wisconsin-Superior","active":true,"usgs":false}],"preferred":false,"id":941950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Day, Stephanie","contributorId":353120,"corporation":false,"usgs":false,"family":"Day","given":"Stephanie","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":941951,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kohout, Melissa A.","contributorId":353121,"corporation":false,"usgs":false,"family":"Kohout","given":"Melissa A.","affiliations":[{"id":84347,"text":"Mankato State University","active":true,"usgs":false}],"preferred":false,"id":941952,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Larson, Philip H.","contributorId":353122,"corporation":false,"usgs":false,"family":"Larson","given":"Philip H.","affiliations":[{"id":84348,"text":"Minnesota State University Mankato","active":true,"usgs":false}],"preferred":false,"id":941953,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDermott, Jeni A.","contributorId":353123,"corporation":false,"usgs":false,"family":"McDermott","given":"Jeni A.","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":941954,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Richard, Emilie","contributorId":300815,"corporation":false,"usgs":false,"family":"Richard","given":"Emilie","email":"","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":941955,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70267313,"text":"70267313 - 2025 - Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system","interactions":[],"lastModifiedDate":"2025-06-16T14:01:42.236379","indexId":"70267313","displayToPublicDate":"2025-05-06T08:31:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system","docAbstract":"Objective
Lampreys are an ecologically important group of fishes. Several species are imperiled and lack key distribution and habitat data. The terminal Goose Lake Basin, U.S.A. is home to two such species, the Goose Lake Lamprey, Entosphenus sp. (formally undescribed), and the Pit-Klamath Brook Lamprey, E. lethophagus. Species distribution models (SDMs) are useful for identifying key habitats; however, SDMs are subject to accuracy impairments caused by scale mismatches and spatial autocorrelation—both exacerbated by the hierarchical structure of dendritic stream networks. Our goal was to relate lamprey presence–absence to ecological drivers and predict the distribution of lampreys across the Goose Lake Basin.
Methods
Using a dataset pooling approach, we integrated count and presence–absence data from five surveys and relevant habitat variables from publicly available, geospatial datasets to build logistic regression models. To account for potential mismatches of scale, we compared three sample grains for slope and sinuosity (i.e., stream segment lengths: 250, 500, and 1,000 m), and two scales of elevation (site and watershed). We accounted for spatial autocorrelation by incorporating network-based and Euclidean spatial dependencies using a spatial stream network (SSN) modeling approach. Using the best-fit spatial and non-spatial models, we predicted basin-wide lamprey distribution.
Result
Flow, sinuosity at our largest sample grain (1,000 m), and watershed-scale elevation were positively associated with lamprey presence, whereas slope was negatively associated. The non-spatial model predicted lamprey presence among sinuous, low-gradient streams, whereas the spatial model, which identified Euclidean and flow-connected spatial relationships, predicted contiguous patches with a high probability of occurrence near areas with previously observed presences.
Conclusions
Our study revealed ecological relationships and produced an accurate basinwide SDM. Prediction and inference improved after accounting for spatial relationships across multiple scales. Developing accurate and efficient modeling strategies that incorporate the hierarchical structure inherent to stream ecosystems aids in the management and conservation of native fishes such as lampreys.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnaf017","usgsCitation":"Dickey, J., Clemens, B.J., Dumelle, M., and Davis, M.J., 2025, Modeling lamprey distribution using flow, geomorphology, and elevation in a terminal lake system: Transactions of the American Fisheries Society, v. 154, no. 3, p. 322-338, https://doi.org/10.1093/tafafs/vnaf017.","productDescription":"17 p.","startPage":"322","endPage":"338","ipdsId":"IP-170580","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":504380,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12180746/","text":"External Repository"},{"id":486248,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"154","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Dickey, Jacob C.","contributorId":350824,"corporation":false,"usgs":false,"family":"Dickey","given":"Jacob C.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":937699,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":937700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumelle, Michael 0000-0002-3393-5529","orcid":"https://orcid.org/0000-0002-3393-5529","contributorId":355601,"corporation":false,"usgs":false,"family":"Dumelle","given":"Michael","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":937701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937702,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266474,"text":"70266474 - 2025 - Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","interactions":[{"subject":{"id":70266474,"text":"70266474 - 2025 - Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","indexId":"70266474","publicationYear":"2025","noYear":false,"title":"Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design"},"predicate":"SUPERSEDED_BY","object":{"id":70272628,"text":"70272628 - 2025 - When do single-species occupancy models outperform multispecies models?","indexId":"70272628","publicationYear":"2025","noYear":false,"title":"When do single-species occupancy models outperform multispecies models?"},"id":1}],"supersededBy":{"id":70272628,"text":"70272628 - 2025 - When do single-species occupancy models outperform multispecies models?","indexId":"70272628","publicationYear":"2025","noYear":false,"title":"When do single-species occupancy models outperform multispecies models?"},"lastModifiedDate":"2025-11-26T14:27:45.5494","indexId":"70266474","displayToPublicDate":"2025-05-06T08:30:40","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design","docAbstract":"Bayesian hierarchical models are ubiquitous in ecology. Random effect model structures are often employed that treat individual effects as deviations from larger population-level effects. In this way individuals are assumed to be \"exchangeable\" samples. Ecologists may address this exchangeability assumption intuitively, but might in certain modeling contexts ignore it altogether, including in situations where it may have large implications for study design. Multispecies occupancy models based on detection/non-detection data are an approach that can be utilized by those tasked with monitoring rare and endangered species because most literature suggests that, compared to single species occupancy models, improved parameter estimates are assured. Yet, we illustrate through a power analysis how sampling requirements to detect experimental treatment effects vary tremendously depending on whether the species exchangeability assumption is met. The degree to which species in a community respond similarly to covariates governs the ability to accurately estimate parameters using multispecies occupancy models. Detecting small or moderate changes in occupancy resulting from habitat restoration treatments may be impossible for small datasets (e.g., < 36 sampling locations, each surveyed < 8 times) even with a paired treatment-control design if the exchangeability assumption is violated. By contrast, when the assumption is met, small effects may be confidently estimated with as few as 12 sampling locations (6 pairs) and 6-8 survey events. Often, it may be impossible to know whether the exchangeability assumption is met. The statistical power needed to accurately estimate species-specific effects using detection/non-detection multispecies occupancy models depends on the unknown values of treatment effects and whether responses by species in the community diverge. When the species exchangeability assumption is violated, and at lower levels of sampling effort, multispecies occupancy models may provide worse inference than single species occupancy models.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.04.30.651473","usgsCitation":"Cotterill, G.G., Keinath, D.A., and Graves, T., 2025, Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design: BioRxiv, preprint posted May 06, 2025, https://doi.org/10.1101/2025.04.30.651473.","productDescription":"31 p.","ipdsId":"IP-176524","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488154,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1101/2025.04.30.651473","text":"Publisher Index Page"},{"id":485549,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Cotterill, Gavin G. 0000-0002-1408-778X","orcid":"https://orcid.org/0000-0002-1408-778X","contributorId":346534,"corporation":false,"usgs":true,"family":"Cotterill","given":"Gavin","middleInitial":"G.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keinath, Douglas A.","contributorId":274356,"corporation":false,"usgs":false,"family":"Keinath","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":936158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":936159,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266399,"text":"70266399 - 2025 - Rhenium-osmium and oxygen isotope homogeneity during the 2022 Mauna Loa eruption and implications for basaltic magma storage","interactions":[],"lastModifiedDate":"2025-05-06T15:22:14.58738","indexId":"70266399","displayToPublicDate":"2025-05-05T10:17:33","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":"Rhenium-osmium and oxygen isotope homogeneity during the 2022 Mauna Loa eruption and implications for basaltic magma storage","docAbstract":"Mauna Loa is one of the largest and most active volcanoes on Earth. The most recent eruption of Mauna Loa started on 27 November 2022, lasted for 13 days, and was preceded by the longest repose time of 38 years in its modern history. In this contribution, new trace- and highly siderophile-element (HSE: Os, Ir, Ru, Pt, Pd, Re) abundances, 187Re-187Os, and 18O/16O data are reported for the 2022 lavas. These lavas have a limited range of MgO (6.2 ± 0.1 wt.%) and Ni (83 ± 2 µg/g), with a broader range of Re (0.3 to 1.3 ng/g) and consistent Os (0.031 to 0.080 ng/g) contents. They have 187Os/188Os ratios (0.1345 to 0.1385) which are, on average, more radiogenic than Mauna Loa picrites (0.1331 to 0.1349) and are similar in composition to more differentiated Mauna Loa tholeiite lavas (0.1340 to 0.1381). The oxygen isotope compositions of glassy samples are 5.35 ± 0.15‰ (n = 13) and span a range in δ18O of + 5.0 to + 5.5‰, with an average composition 0.2 to 0.3‰ lower than MORB. The δD value is − 81 ± 11‰ (n = 5) at very low (0.03 ± 0.015 wt.%) H2O concentrations. The 2022 Mauna Loa eruption is similar in terms of δ18O but contrasts in terms of 187Os/188Os variability, with the recent longer-lived eruptions on La Palma (Canary Islands; 85 days) in 2021 and on the Reykjanes Peninsula (Iceland) that began in 2021 and are still ongoing. Initial lavas were more fractionated for both the Canary Islands and Iceland eruptions, producing more radiogenic Os isotope compositions than later erupted products. The 2022 Mauna Loa eruption showed no such trends. The limited range in isotope compositions of the 2022 Mauna Loa lavas and their strongly fractioned HSE patterns reflect long-term storage, crystal fractionation, and assimilation of related basaltic volcanic edifice materials by the parent magma beneath the volcano prior to eruption triggering. Eruption of differentiated and homogeneous tholeiite lavas at the summit caldera and high on the volcano’s flank, with emplacement of accumulative picrites lower on the volcano, are consistent with neutral buoyancy arguments.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01825-0","usgsCitation":"Rhoads, E., Kutyrev, A., Bindeman, I.N., Lynn, K.J., Trusdell, F., Downs, D.T., Edwards, H., Cook, G., and Day, J., 2025, Rhenium-osmium and oxygen isotope homogeneity during the 2022 Mauna Loa eruption and implications for basaltic magma storage: Bulletin of Volcanology, v. 87, 38, 19 p., https://doi.org/10.1007/s00445-025-01825-0.","productDescription":"38, 19 p.","ipdsId":"IP-169680","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01825-0","text":"Publisher Index Page"},{"id":485454,"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 -155.70545026795776,\n 19.707077790926633\n ],\n [\n -155.70545026795776,\n 19.36043617244789\n ],\n [\n -155.41439917963822,\n 19.36043617244789\n ],\n [\n -155.41439917963822,\n 19.707077790926633\n ],\n [\n -155.70545026795776,\n 19.707077790926633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Rhoads, Emily A.","contributorId":354537,"corporation":false,"usgs":false,"family":"Rhoads","given":"Emily A.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":935828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kutyrev, Anton","contributorId":354538,"corporation":false,"usgs":false,"family":"Kutyrev","given":"Anton","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":935831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":935832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":935833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Edwards, Hunter R.","contributorId":354541,"corporation":false,"usgs":false,"family":"Edwards","given":"Hunter R.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":935834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Geoffrey W.","contributorId":354544,"corporation":false,"usgs":false,"family":"Cook","given":"Geoffrey W.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":935835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Day, James M.D.","contributorId":354545,"corporation":false,"usgs":false,"family":"Day","given":"James M.D.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":935836,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70268080,"text":"70268080 - 2025 - Finding the hidden orogeny – The Proterozoic polymetamorphic history of northern New Mexico","interactions":[],"lastModifiedDate":"2025-09-22T15:19:55.957196","indexId":"70268080","displayToPublicDate":"2025-05-05T09:19:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3531,"text":"Terra Nova","active":true,"publicationSubtype":{"id":10}},"title":"Finding the hidden orogeny – The Proterozoic polymetamorphic history of northern New Mexico","docAbstract":"Pressure–temperature–time-deformation histories provide key constraints on orogenic processes but can be affected by later overprinting. This is exemplified in the Proterozoic orogenic belts of southwestern Laurentia where competing tectonic models involve either a single progressive Mesoproterozoic event, the Picuris orogeny, or a polyorogenic history that also includes the ~1.65 Ga Mazatzal orogeny. We address this controversy with structural analysis and petrochronology in the type locality of the Picuris orogeny. Xenotime and monazite domains associated with the greenschist-facies axial planar fabric of early F1 folds yield 1644 ± 11 Ma (xenotime) and 1641 ± 15 Ma (monazite) ages and 450°C–482°C temperatures recording metamorphism and shortening associated with the Mazatzal orogeny. This Palaeoproterozoic greenschist-facies assemblage was overprinted by higher grade, protracted (1470–1350 Ma) tectonism that included the Picuris orogeny. Our results document the complex polyphase crustal assembly of Laurentia and highlight how petrochronology can effectively see through higher grade overprints to identify a more complete orogenic evolution.
","language":"English","publisher":"Wiley","doi":"10.1111/ter.12778","usgsCitation":"Hillenbrand, I.W., Williams, M., Gilmer, A.K., Karlstrom, K.E., Jercinovic, M.J., and Young, D., 2025, Finding the hidden orogeny – The Proterozoic polymetamorphic history of northern New Mexico: Terra Nova, v. 37, no. 5, p. 304-315, https://doi.org/10.1111/ter.12778.","productDescription":"12 p.","startPage":"304","endPage":"315","ipdsId":"IP-172431","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490508,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.85,\n 36.308\n ],\n [\n -105.85,\n 36.1667\n ],\n [\n -105.6333,\n 36.1667\n ],\n [\n -105.6333,\n 36.308\n ],\n [\n -105.85,\n 36.308\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":940153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Michael L","contributorId":356814,"corporation":false,"usgs":false,"family":"Williams","given":"Michael L","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":940154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":940155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karlstrom, Karl E.","contributorId":228844,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","email":"","middleInitial":"E.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":940156,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jercinovic, Michael J.","contributorId":316620,"corporation":false,"usgs":false,"family":"Jercinovic","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":68659,"text":"University of Massachusetts - Amherst","active":true,"usgs":false}],"preferred":false,"id":940157,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Daniel J","contributorId":356815,"corporation":false,"usgs":false,"family":"Young","given":"Daniel J","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":940158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273074,"text":"70273074 - 2025 - Stable occupancy of conservation-priority birds amid community shifts across 16 years on Iowa wetland easements","interactions":[],"lastModifiedDate":"2025-12-12T18:40:08.446372","indexId":"70273074","displayToPublicDate":"2025-05-04T11:33:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Stable occupancy of conservation-priority birds amid community shifts across 16 years on Iowa wetland easements","docAbstract":"Intensive agriculture in the Prairie Pothole Region of Iowa, USA has resulted in significant wetland drainage and wildlife population declines. However, easement programs are increasingly used to protect and restore wetlands and revitalize biodiversity. Short-term responses (i.e., 1–5 years) of birds to wetland restorations are well-documented, but long-term trends are less understood. We surveyed wetland easements in Iowa during 2007–2009 and 2022–2023 to assess changes in breeding bird communities and occupancy for conservation-priority species. We conducted bird point counts and vegetation surveys at 55 wetland easements. We used species accumulation curves to estimate overall breeding bird richness by guild, and site-occupancy models to estimate occupancy for 20 conservation-priority species. Species richness remained stable between time periods, but community composition shifted, with fewer grassland and more forest bird species despite no change in woody vegetation cover estimates (2007–2009: 3.2%, standard deviation [SD] = 5.9; 2022–2023: 3.1%, SD = 3.8). Occupancy for most species at wetland easements remained stable over time; however, 4 species declined (e.g., Cistothorus stellaris [Sedge Wren]). Six grassland bird species (e.g., Sturnella magna [Eastern Meadowlark]) exhibited positive or stable occupancy trends. Forest-dependent species generally maintained or increased in occupancy (e.g., Icterus galbula [Baltimore Oriole]). Increased forest bird richness despite stable woody vegetation cover may indicate changing structural characteristics as existing forests mature, whereas management to control woody encroachment at wetland easements may explain our observations of stable forest bird occupancy. Wetland easements may be strongholds for some grassland bird species, which are in precipitous decline across North America. Our study highlights the importance of wetland easements in an agricultural landscape to breeding bird communities and emphasizes the value of continued monitoring to track changes over time.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf034","usgsCitation":"Gapinski, L.A., Kinkead, K.E., Janke, A.K., Dinsmore, S.J., Bishop, T., and Tucker, A.M., 2025, Stable occupancy of conservation-priority birds amid community shifts across 16 years on Iowa wetland easements: Ornithological Applications, v. 127, no. 3, duaf034, 15 p., https://doi.org/10.1093/ornithapp/duaf034.","productDescription":"duaf034, 15 p.","ipdsId":"IP-169149","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497713,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duaf034","text":"Publisher Index Page"},{"id":497497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.75770786982824,\n 43.54695571723664\n ],\n [\n -95.75770786982824,\n 40.01246322199273\n ],\n [\n -91.52690414553632,\n 40.01246322199273\n ],\n [\n -91.52690414553632,\n 43.54695571723664\n ],\n [\n -95.75770786982824,\n 43.54695571723664\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gapinski, Lindsey A.W.","contributorId":364117,"corporation":false,"usgs":false,"family":"Gapinski","given":"Lindsey","middleInitial":"A.W.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":952240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinkead, Karen E.","contributorId":364120,"corporation":false,"usgs":false,"family":"Kinkead","given":"Karen","middleInitial":"E.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":952241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Janke, Adam K.","contributorId":364123,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","middleInitial":"K.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":952242,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dinsmore, Stephen J.","contributorId":364126,"corporation":false,"usgs":false,"family":"Dinsmore","given":"Stephen","middleInitial":"J.","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":952243,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bishop, Todd","contributorId":364129,"corporation":false,"usgs":false,"family":"Bishop","given":"Todd","affiliations":[{"id":24495,"text":"Iowa Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":952244,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":952245,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267823,"text":"70267823 - 2025 - Metal fingerprints of Eocene rhyolite magmas coincident with Carlin-type gold deposition in Nevada USA","interactions":[],"lastModifiedDate":"2025-06-03T15:34:51.475791","indexId":"70267823","displayToPublicDate":"2025-05-04T08:28:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Metal fingerprints of Eocene rhyolite magmas coincident with Carlin-type gold deposition in Nevada USA","docAbstract":"Eocene magmatic systems contemporaneous with world-class Carlin-type Au deposits in Nevada (USA) have been proposed by some researchers as a key ingredient for Au mineralization, though evidence conclusively demonstrating their genetic relationship remains tenuous. This study provides the first direct evidence of the pre-eruptive metal budget of volatile- and metal-charged silicic magmas coincident in time (~41 to 34 Ma) and space (within 5 km) with Carlin-type Au deposits. We characterize the pre-eruptive metal fingerprints of these diverse magmatic systems to assess their potential as sources of metals for Carlin-type Au mineralization. Metal abundances from quartz-hosted melt inclusions (Au, Te, Ag, Sb, Tl, Mo, W, Sn, As, Pb, Co, Cu, Ni, and Zn) characterized in situ by SHRIMP-RG and LA-ICP-MS represent our best (and only) estimates for the pre-eruptive metal budget in these systems. Median metal concentrations are generally within one order of magnitude of average upper crust and average continental rhyolite values. But there are two notable exceptions, with median Au contents extending >1 order of magnitude higher than average upper crust and median Cu contents ranging >1 order of magnitude lower than upper crust. Despite this, melts contain lower Au/Cu (<0.1), Au/Ag (<5), and Au/Tl (<0.3) than most ore-grade Carlin-type rock samples and quartz-hosted fluid inclusions, regardless of their age and timing relative to nearby Carlin-type Au mineralization. The metal fingerprints of these magmatic systems, de-fined both by traditional and multivariate compositional data analysis techniques, are distinct from one another. Yet none are particularly specialized, e.g., high Au/Cu, in terms of being ideal ingredients as postulated by magmatic models for Carlin-type Au mineralization. Magmatic Au contents do not appear to be correlated with rhyolite “flavors” in the way that Cu, Sn, and Nb contents are. Fluid/melt partitioning modeling and magma volume estimates support the idea that a diverse array of non-specialized silicic magmas could feasibly contribute some or potentially all of the Au, Ag, and Cu in Carlin-type systems. The compositional diversity among contemporaneous magmatic systems could possibly contribute to some of the diversity observed across Carlin-type Au districts in Nevada.","language":"English","publisher":"MDPI","doi":"10.3390/min15050479","usgsCitation":"Mercer, C.N., Babel, H., Mercer, C.M., and Hofstra, A.H., 2025, Metal fingerprints of Eocene rhyolite magmas coincident with Carlin-type gold deposition in Nevada USA: Minerals, v. 15, no. 5, 479, 29 p., https://doi.org/10.3390/min15050479.","productDescription":"479, 29 p.","ipdsId":"IP-170125","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":490665,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min15050479","text":"Publisher Index Page"},{"id":490404,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UWAW28","text":"USGS data release","linkHelpText":"Melt inclusion and mineral geochemical analyses supporting the evaluation of petrogenesis, degassing, and metallogenic potential of mid-Cenozoic rhyolite magmas in northern Nevada, USA (ver. 2.0, March 2025)"},{"id":489471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":939032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Babel, Hannah R.","contributorId":356285,"corporation":false,"usgs":false,"family":"Babel","given":"Hannah R.","affiliations":[{"id":40814,"text":"University of Bergen, Norway","active":true,"usgs":false}],"preferred":false,"id":939033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mercer, Cameron Mark 0000-0003-0534-848X","orcid":"https://orcid.org/0000-0003-0534-848X","contributorId":301880,"corporation":false,"usgs":true,"family":"Mercer","given":"Cameron","email":"","middleInitial":"Mark","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":939035,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266466,"text":"70266466 - 2025 - Geomorphological evidence of near-surface ice at candidate landing sites in northern Amazonis Planitia, Mars","interactions":[],"lastModifiedDate":"2025-05-07T18:18:46.33843","indexId":"70266466","displayToPublicDate":"2025-05-03T11:14:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9967,"text":"JGR Planets","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphological evidence of near-surface ice at candidate landing sites in northern Amazonis Planitia, Mars","docAbstract":"This work presents geomorphological analyses of an area at the boundary between Arcadia Planitia and northern Amazonis Planitia, situated in the northern mid-latitudes of Mars. Recent studies have indicated the presence of substantial volumes of near-surface excess ice in Arcadia Planitia, making this region a promising candidate for future human and robotic exploration. This study focuses on three specific candidate landing sites adjacent to the Arcadia Planitia: AP-1, AP-8, and AP-9. We have identified a wide range of ice-related morphologies, providing further evidence for the occurrence of excess ice in the study area. We have mapped and measured ∼9,000 thermal contraction polygons. We estimate ice beneath these polygons to be on the order of tens of cm from the surface, which is sufficiently shallow to be accessible for potential in situ resource utilization (ISRU). Recent impact craters that have been excavated into ice further suggest the presence of near-surface ice. Finally, the occurrence of ice and processes such as ice sublimation are likely responsible for the formation and subsequent modification of several observed features, including expanded craters, brain coral terrain, arcuate ridges, and thermal contraction polygons modified by sublimation. These results provide valuable insights into the ice distribution in the northern mid-latitudes and support the potential utilization of accessible ice resources for future human exploration efforts.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JE008724","usgsCitation":"Luzzi, E., Heldmann, J.L., Williams, K.E., Nodjoumi, G., Deutsch, A., and Sehlke, A., 2025, Geomorphological evidence of near-surface ice at candidate landing sites in northern Amazonis Planitia, Mars: JGR Planets, v. 130, no. 5, e2024JE008724, 38 p., https://doi.org/10.1029/2024JE008724.","productDescription":"e2024JE008724, 38 p.","ipdsId":"IP-163826","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":490104,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024je008724","text":"Publisher Index Page"},{"id":485515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Luzzi, Erica","contributorId":354637,"corporation":false,"usgs":false,"family":"Luzzi","given":"Erica","affiliations":[{"id":84643,"text":"Bay Area Environmental Research Institute","active":true,"usgs":false}],"preferred":false,"id":936045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heldmann, Jennifer L.","contributorId":197096,"corporation":false,"usgs":false,"family":"Heldmann","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":936046,"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":936048,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nodjoumi, Giacomo","contributorId":354639,"corporation":false,"usgs":false,"family":"Nodjoumi","given":"Giacomo","affiliations":[{"id":84644,"text":"Constructor University, Bremen, Germany","active":true,"usgs":false}],"preferred":false,"id":936049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deutsch, Ariel","contributorId":354640,"corporation":false,"usgs":false,"family":"Deutsch","given":"Ariel","affiliations":[{"id":84643,"text":"Bay Area Environmental Research Institute","active":true,"usgs":false}],"preferred":false,"id":936050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sehlke, Alexander","contributorId":354638,"corporation":false,"usgs":false,"family":"Sehlke","given":"Alexander","affiliations":[{"id":84643,"text":"Bay Area Environmental Research Institute","active":true,"usgs":false}],"preferred":false,"id":936047,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266346,"text":"70266346 - 2025 - One-hundred fundamental, open questions to integrate methodological approaches in lake ice research","interactions":[],"lastModifiedDate":"2025-05-05T14:19:08.992831","indexId":"70266346","displayToPublicDate":"2025-05-03T09:11:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"One-hundred fundamental, open questions to integrate methodological approaches in lake ice research","docAbstract":"The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.
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Understanding reproductive traits of vulnerable species, particularly long-lived species, may provide insight for implementing management actions to respond to potential overharvest. This study aimed to assess the reproductive characteristics of a stable population of long-lived blue suckers (Cycleptus elongatus) in the unchannelized Missouri River in South Dakota. We obtained demographic information and gonads from 182 blue suckers collected in trammel nets in March 2021 and 2022. We used Bayesian generalized linear mixed-effects models to assess length and weight relationships with gonadosomatic index (GSI) and fecundity and used spawning potential ratios to model the influence of four minimum length limit scenarios. Total lengths of sampled fish ranged from 560 to 821 mm. Female GSI increased with length to ∼730 mm before declining, and male GSI remained consistent across lengths. Fecundity increased linearly with weight and with length to around 750 mm, after which the rate of increase slowed. Using a recent natural mortality estimate for this population, the spawning potential ratio under current no-limit regulations decreased rapidly as fishing mortality approached 0.10 but implementing a minimum length limit (e.g. 610- or 660 mm) could prevent the spawning potential ratio from falling below acceptable limits (0.2–0.3) at moderate-to-high fishing mortality values. This study provides necessary information about the reproductive characteristics of vulnerable, non-game species and demonstrates how spawning potential ratio modeling can be used for species that receive less management focus.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107386","usgsCitation":"LaBrie, L.A., Carlson, T., Wesner, J., Pasbrig, C., Chipps, S.R., and Schall, B., 2025, Reproductive characteristics and spawning potential ratio modeling of a vulnerable riverine specialist in the lower unchannelized Missouri River, USA: Fisheries Research, v. 286, 107386, 11 p., https://doi.org/10.1016/j.fishres.2025.107386.","productDescription":"107386, 11 p.","ipdsId":"IP-171427","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493714,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.4400699587332,\n 43.13427424948017\n ],\n [\n -98.4400699587332,\n 42.33478692919812\n ],\n [\n -96.64857711623827,\n 42.33478692919812\n ],\n [\n -96.64857711623827,\n 43.13427424948017\n ],\n [\n -98.4400699587332,\n 43.13427424948017\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"286","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LaBrie, Lindsey A.P.","contributorId":349677,"corporation":false,"usgs":false,"family":"LaBrie","given":"Lindsey","middleInitial":"A.P.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":945065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Tanner L.","contributorId":359232,"corporation":false,"usgs":false,"family":"Carlson","given":"Tanner L.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":945066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wesner, Jeff S.","contributorId":342343,"corporation":false,"usgs":false,"family":"Wesner","given":"Jeff S.","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":945067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pasbrig, Chelsey A.","contributorId":359233,"corporation":false,"usgs":false,"family":"Pasbrig","given":"Chelsey A.","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":945068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":945069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schall, Benjamin J.","contributorId":359236,"corporation":false,"usgs":false,"family":"Schall","given":"Benjamin J.","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":945070,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264176,"text":"70264176 - 2025 - Overview of The SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest earthquake sequence","interactions":[],"lastModifiedDate":"2025-05-28T15:02:07.197713","indexId":"70264176","displayToPublicDate":"2025-05-02T10:46:42","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":"Overview of The SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest earthquake sequence","docAbstract":"We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress‐drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude‐spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress‐drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two‐week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. In this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite‐fault modeling, ground‐motion‐based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between‐method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress‐drop values.
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