Tree-derived dissolved organic matter (DOM) comprises a significant carbon flux within forested watersheds. Few studies have assessed the optical properties of tree-derived DOM. To increase understanding of the factors controlling tree-derived DOM quality, we measured DOM optical properties, dissolved organic carbon (DOC) and calcium concentrations in throughfall and stemflow for 17 individual rain events during summer and fall in a temperate deciduous forest in Vermont, United States. DOC and calcium fluxes in throughfall and stemflow were enriched on average 4 to 70 times incident fluxes in rain. A multiway model was developed using absorbance and fluorescence spectroscopy to further characterize DOM optical properties. Throughfall contained a higher percentage of protein-like DOM fluorescence than stemflow while stemflow was characterized by a higher percentage of humic-like DOM fluorescence. DOM absorbance spectral slopes in yellow birch (Betula alleghaniensis) stemflow were significantly higher than in sugar maple (Acer saccharum) stemflow. DOM optical metrics were not influenced by rainfall volume, but percent protein-like fluorescence increased in throughfall during autumn when leaves senesced. Given the potential influence of tree-derived DOM fluxes on receiving soils and downstream ecosystems, future modeling of DOM transport and soil biogeochemistry should represent the influence of differing DOM quality in throughfall and stemflow across tree species and seasons.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10533-022-00985-x","usgsCitation":"Ryan, K.A., Adler, T., Chalmers, A.T., Perdrial, J., Sebestyen, S., Shanley, J.B., and Stubbins, A., 2023, Optical properties of dissolved organic matter in throughfall and stemflow vary across tree species and season in a temperate headwater forest: Biogeochemistry, v. 164, p. 53-72, https://doi.org/10.1007/s10533-022-00985-x.","productDescription":"20 p.","startPage":"53","endPage":"72","ipdsId":"IP-142839","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":445339,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-022-00985-x","text":"Publisher Index Page"},{"id":408608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Sleepers River Research Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.05866635329214,\n 44.34647865583793\n ],\n [\n -72.40758066011205,\n 44.34647865583793\n ],\n [\n -72.40758066011205,\n 44.188052738709075\n ],\n [\n -72.05866635329214,\n 44.188052738709075\n ],\n [\n -72.05866635329214,\n 44.34647865583793\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"164","noUsgsAuthors":false,"publicationDate":"2022-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryan, Kevin A 0000-0003-1202-3616","orcid":"https://orcid.org/0000-0003-1202-3616","contributorId":270682,"corporation":false,"usgs":false,"family":"Ryan","given":"Kevin","email":"","middleInitial":"A","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":855449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Thomas","contributorId":244156,"corporation":false,"usgs":false,"family":"Adler","given":"Thomas","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":855450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalmers, Ann T. 0000-0002-5199-8080 chalmers@usgs.gov","orcid":"https://orcid.org/0000-0002-5199-8080","contributorId":1443,"corporation":false,"usgs":true,"family":"Chalmers","given":"Ann","email":"chalmers@usgs.gov","middleInitial":"T.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perdrial, Julia","contributorId":190445,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","affiliations":[],"preferred":false,"id":855452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sebestyen, Stephen","contributorId":298358,"corporation":false,"usgs":false,"family":"Sebestyen","given":"Stephen","affiliations":[{"id":64539,"text":"U.S. Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":855453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stubbins, Aron","contributorId":80949,"corporation":false,"usgs":true,"family":"Stubbins","given":"Aron","affiliations":[],"preferred":false,"id":855455,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238860,"text":"70238860 - 2023 - Hydrologic modeling of a perennial firn aquifer in southeast Greenland","interactions":[],"lastModifiedDate":"2023-05-25T15:34:49.215581","indexId":"70238860","displayToPublicDate":"2022-10-20T06:56:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic modeling of a perennial firn aquifer in southeast Greenland","docAbstract":"A conceptual model, based on field observations and assumed physics of a perennial firn aquifer near Helheim Glacier (southeast Greenland), is evaluated via steady-state 2-D simulation of liquid water flow and energy transport with phase change. The simulation approach allows natural representation of flow and energy advection and conduction that occur in vertical meltwater recharge through the unsaturated zone and in lateral flow within the saturated aquifer. Agreement between measured and simulated aquifer geometry, temperature, and recharge and discharge rates confirms that the conceptual field-data-based description of the aquifer is consistent with the primary physical processes of groundwater flow, energy transport and phase change. Factors that are found to control simulated aquifer configuration include surface temperature, meltwater recharge rate, residual total-water saturation and capillary fringe thickness. Simulation analyses indicate that the size of perennial firn aquifers depends primarily on recharge rates from surface snowmelt. Results also imply that the recent aquifer expansion, likely due to a warming climate, may eventually produce lakes on the ice-sheet surface that would affect the surface energy balance.
The numerical estimation of the position of the water table in unconfined aquifers is important for many practical applications. Its determination through observations or analytical methods is restricted to a few cases. Therefore, it is often estimated through numerical simulations, which may be affected by numerical artifacts and/or poor stability. We use MODFLOW to estimate the position of the water table for a seemingly simple example problem and demonstrate difficulties that can be faced when performing this kind of numerical simulation. We explain the causes for the numerical challenges that originate from the properties of the mathematical equations that must be solved. Based on the results of more than 600 steady-state simulations, we show how the stability of the numerical solution can be affected by the values of physical parameters that define the problem (e.g., recharge rate, anisotropy ratio, and other parameters that control the numerical algorithm such as settings of the linear and nonlinear solution methods). Finally, we comment on some best practices to apply numerical simulations to estimate the water table position.
Population monitoring is essential to management and conservation efforts for migratory birds, but traditional low-altitude aerial surveys with human observers are plagued by individual observer bias and risk to flight crews. Aerial surveys that use remote sensing can reduce bias and risk, but manual counting of wildlife in imagery is laborious and may be cost-prohibitive. Therefore, automated methods for counting are critical to cost-efficient application of remote sensing for wildlife surveys covering large areas. We conducted nocturnal surveys of sandhill cranes (Antigone canadensis) during spring migration in the Central Platte River Valley of Nebraska, USA, using midwave thermal infrared sensors. We developed a framework for automated counting of sandhill cranes from thermal imagery using deep learning, assessed and compared the performance of two automated counting models, and quantified the effect of spatial resolution on counting accuracy. Aerial thermal imagery data were collected in March 2018 and 2021; 40 images were analyzed. We applied two deep learning models: an object detection approach, Faster R-CNN and a recently developed pixel-density estimation approach, ASPDNet. Model performance was determined using data independent of the training imagery. The effect of spatial resolution was quantified with a beta regression on relative error. Our results showed model accuracy of 9% mean percent error for ASPDNet and 18% for Faster R-CNN. Most error was related to the undercounting of sandhill cranes. ASPDNet had <50% of the error of Faster R-CNN as measured by mean percent error, root-mean-squared error and mean absolute error. Spatial resolution affected accuracy of both models, with error rate increasing with coarser resolution, particularly with Faster R-CNN. Deep learning models, particularly pixel-density estimators, can accurately automate counting of migratory birds in a dense, aggregate setting such as nocturnal roosting sites.
","language":"English","publisher":"Zoological Society of London","doi":"10.1002/rse2.301","usgsCitation":"Luz-Ricca, E., Landolt, K.L., Pickens, B.A., and Koneff, M.D., 2023, Automating sandhill crane counts from nocturnal thermal aerial imagery using deep learning: Remote Sensing in Ecology and Conservation, v. 9, no. 2, p. 182-194, https://doi.org/10.1002/rse2.301.","productDescription":"13 p.","startPage":"182","endPage":"194","ipdsId":"IP-137740","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445346,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.301","text":"Publisher Index Page"},{"id":435568,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DZKFQ3","text":"USGS data release","linkHelpText":"Aerial thermal imagery of the Central Platte River Valley and bounding box annotations of sandhill cranes"},{"id":419747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.4602621702348,\n 40.829394227542565\n ],\n [\n -99.14401866960671,\n 40.829394227542565\n ],\n [\n -99.14401866960671,\n 40.57838905213882\n ],\n [\n -98.4602621702348,\n 40.57838905213882\n ],\n [\n -98.4602621702348,\n 40.829394227542565\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Luz-Ricca, Emilio","contributorId":298780,"corporation":false,"usgs":false,"family":"Luz-Ricca","given":"Emilio","email":"","affiliations":[{"id":6686,"text":"College of William and Mary","active":true,"usgs":false}],"preferred":false,"id":880036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landolt, Kyle Lawrence 0000-0002-6738-8586","orcid":"https://orcid.org/0000-0002-6738-8586","contributorId":298782,"corporation":false,"usgs":true,"family":"Landolt","given":"Kyle","email":"","middleInitial":"Lawrence","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":880037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pickens, Bradley A.","contributorId":140926,"corporation":false,"usgs":false,"family":"Pickens","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":880038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koneff, Mark D.","contributorId":191128,"corporation":false,"usgs":false,"family":"Koneff","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":880039,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237725,"text":"70237725 - 2023 - Ontogenetic development of pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) from hatch through yolk absorption","interactions":[],"lastModifiedDate":"2022-12-15T15:06:41.256","indexId":"70237725","displayToPublicDate":"2022-10-12T10:19:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ontogenetic development of pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) from hatch through yolk absorption","title":"Ontogenetic development of pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) from hatch through yolk absorption","docAbstract":"Sturgeons have a complex free-embryo period extending from hatch to the initiation of exogenous feeding. Although available for some sturgeon species of the genus Acipenser, descriptions of the developmental stages of free embryos of the genus Scaphirhynchus are lacking. We characterised the ontogenetic development of pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (S. platorynchus) free embryos from hatch through melanin plug expulsion. The rate of development was similar between Scaphirhynchus species among free embryos from 4 pallid sturgeon and 7 shovelnose sturgeon crosses reared separately in the laboratory at a mean temperature of 17.8°C. Free embryos required a mean of 18.2 days postfertilisation (DPF; 323.5 cumulative thermal units; CTU) to reach melanin plug expulsion for pallid sturgeon and 17.9 DPF (318.3 CTU) for shovelnose sturgeon. Free embryos of both species showed overlap in lengths among developmental stages indicating that length of free embryos alone is insufficient to estimate age. Description of pallid sturgeon and shovelnose sturgeon free-embryo development provides a template to develop more sophisticated models incorporating length and stage to estimate the age of field-collected specimens. Improved estimates of free-embryo developmental stage and age may aid in the identification of timing and location of spawning and better inform flow manipulation and habitat management actions tailored to increase survival of early life-stage pallid sturgeon.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12680","usgsCitation":"Chojnacki, K., Dodson, M., George, A.E., Candrl, J., and Delonay, A.J., 2023, Ontogenetic development of pallid sturgeon (Scaphirhynchus albus) and shovelnose sturgeon (Scaphirhynchus platorynchus) from hatch through yolk absorption: Ecology of Freshwater Fish, v. 32, no. 1, p. 209-231, https://doi.org/10.1111/eff.12680.","productDescription":"23 p.","startPage":"209","endPage":"231","ipdsId":"IP-140861","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":445359,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12680","text":"Publisher Index Page"},{"id":435571,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGYSFJ","text":"USGS data release","linkHelpText":"Developmental stage and length of Pallid Sturgeon and Shovelnose Sturgeon free embryos reared at a constant temperature"},{"id":408611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Chojnacki, Kimberly 0000-0001-6091-3977 kchojnacki@usgs.gov","orcid":"https://orcid.org/0000-0001-6091-3977","contributorId":221080,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Kimberly","email":"kchojnacki@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dodson, Marlene J 0000-0003-4510-5757","orcid":"https://orcid.org/0000-0003-4510-5757","contributorId":298314,"corporation":false,"usgs":false,"family":"Dodson","given":"Marlene J","affiliations":[{"id":64528,"text":"USGS Former Employee","active":true,"usgs":false}],"preferred":false,"id":855368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Candrl, James 0000-0002-1464-2931 jcandrl@usgs.gov","orcid":"https://orcid.org/0000-0002-1464-2931","contributorId":192165,"corporation":false,"usgs":true,"family":"Candrl","given":"James","email":"jcandrl@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeLonay, Aaron J. 0000-0002-3752-2799 adelonay@usgs.gov","orcid":"https://orcid.org/0000-0002-3752-2799","contributorId":2725,"corporation":false,"usgs":true,"family":"DeLonay","given":"Aaron","email":"adelonay@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":855371,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237800,"text":"70237800 - 2023 - Predictive accuracy of post-fire conifer death declines over time in models based on crown and bole injury","interactions":[],"lastModifiedDate":"2023-03-15T14:26:19.594571","indexId":"70237800","displayToPublicDate":"2022-10-11T10:52:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predictive accuracy of post-fire conifer death declines over time in models based on crown and bole injury","docAbstract":"A key uncertainty of empirical models of post-fire tree mortality is understanding the drivers of elevated post-fire mortality several years following fire, known as delayed mortality. Delayed mortality can represent a substantial fraction of mortality, particularly for large trees that are a conservation focus in western US coniferous forests. Current post-fire tree mortality models have undergone limited evaluation of how injury level and time since fire interact to influence model accuracy and predictor variable importance. Less severe injuries potentially serve as an indicator for vulnerability to additional stressors such as bark beetle attack or moisture stress. We used a collection of 164,293 individual tree records to examine post-fire tree mortality in eight western USA conifers: Abies concolor, A. grandis, Calocedrus decurrens, Larix occidentalis, Pinus contorta, P. lambertiana, P. ponderosa, and Pseudotsuga menziesii. We evaluated the importance of fire injury predictors on discriminating between surviving trees versus immediate and delayed post-fire mortality. We fit balanced random forest models for each species using cumulative tree mortality from 1–5-years post-fire. We compared these results to multi-class random forest models using first-year mortality, 2–5-year mortality, and survival 5-years post-fire as a response variable. Crown volume scorched, diameter at breast height, and relative bark char height, were used as predictor variables. The cumulative mortality models all predicted trees that died within 1-year of fire with high accuracy but failed to predict 2–5-year mortality. The multi-class models were an improvement but had lower accuracy for predicting 2–5-year mortality. Multi-class model accuracies ranged from 85–95% across all species for predicting 1-year post-fire mortality, 42–71% for predicting 2–5-year mortality, and 64–85% for predicting trees that lived past 5-years. Our study highlights the differences in tree species tolerance to fire injury and suggests that including second-order predictors such as beetle attack or climatic water stress before and after fire will be critical to improve accuracy and better understand the mechanisms and patterns of fire-caused tree death. Random forest models have potential for management applications such as post-fire harvesting and simulating future stand dynamics.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2760","usgsCitation":"Shearman, T.M., Varner, J., Hood, S.M., van Mantgem, P., Cansler, C.A., and Wright, M., 2023, Predictive accuracy of post-fire conifer death declines over time in models based on crown and bole injury: Ecological Applications, v. 33, no. 2, e2760, 22 p., https://doi.org/10.1002/eap.2760.","productDescription":"e2760, 22 p.","ipdsId":"IP-139321","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445366,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2760","text":"Publisher Index Page"},{"id":408651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -126.7480336449919,\n 48.97503075637249\n ],\n [\n -126.7480336449919,\n 31.808209566487548\n ],\n [\n -101.34747698085148,\n 31.808209566487548\n ],\n [\n -101.34747698085148,\n 48.97503075637249\n ],\n [\n -126.7480336449919,\n 48.97503075637249\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Shearman, Timothy M.","contributorId":229060,"corporation":false,"usgs":false,"family":"Shearman","given":"Timothy","email":"","middleInitial":"M.","affiliations":[{"id":41540,"text":"Tall Timbers Research Station, 13093 Henry Beadel Drive, Tallahassee, FL, 32312, USA","active":true,"usgs":false}],"preferred":false,"id":855674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varner, J. Morgan","contributorId":298476,"corporation":false,"usgs":false,"family":"Varner","given":"J. Morgan","affiliations":[{"id":64585,"text":"Tall Timbers, Tallahassee, FL, USA","active":true,"usgs":false}],"preferred":false,"id":855675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hood, Sharon M.","contributorId":221183,"corporation":false,"usgs":false,"family":"Hood","given":"Sharon","email":"","middleInitial":"M.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":855676,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":204320,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":855677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cansler, C. Alina","contributorId":298477,"corporation":false,"usgs":false,"family":"Cansler","given":"C.","email":"","middleInitial":"Alina","affiliations":[{"id":64587,"text":"School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA","active":true,"usgs":false}],"preferred":false,"id":855678,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, Micah C. 0000-0002-5324-1110","orcid":"https://orcid.org/0000-0002-5324-1110","contributorId":229071,"corporation":false,"usgs":true,"family":"Wright","given":"Micah","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":855679,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249531,"text":"70249531 - 2023 - Repeat bathymetric surveys and model simulation of sedimentation processes near fish spawning placements, Detroit and St. Clair Rivers, Michigan","interactions":[],"lastModifiedDate":"2023-10-13T12:05:49.827709","indexId":"70249531","displayToPublicDate":"2022-10-10T07:02:53","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Repeat bathymetric surveys and model simulation of sedimentation processes near fish spawning placements, Detroit and St. Clair Rivers, Michigan","docAbstract":"Nine rock-rubble fish spawning placements, or artificial reef complexes, constructed in the \nDetroit and St. Clair Rivers between 2004 to 2018 were surveyed periodically with multibeam \nsonar. These serial bathymetric surveys, conducted in 2015, 2018, 2021, and 2022, identified \nactive sand bedform fields impinging two reef complexes: Fighting Island in the Detroit River \nand Middle Channel in the St. Clair River delta. The spatial extent over which the bedforms \ninteracted with these reef complexes differed. The Fighting Island reef complex, which was \ncomprised of twelve reef beds oriented across the river channel, experienced partial \nsedimentation that can be attributed to the streamwise translation and lateral encroachment of \na bedform field on several of the eastern reef beds. The Middle Channel reef complex was \ncomprised of nine reef beds also oriented across the river channel. Sedimentation of the Middle \nChannel reef complex was more comprehensive compared to the Fighting Island reef complex as \nmost of the beds in the Middle Channel reef complex were within a translating bedform field. \nWe simulated the temporal evolution of reef sedimentation at the Middle Channel reef complex \nusing the Wilcock-Kenworthy (WK) two-fraction sediment transport model. In the WK \nsimulation, sand available upstream of the reef migrated into the 36-meter-long gravel reef beds \nover 10 days of model simulation. The rate of sediment infill predicted by the model was more \nrapid than the speed of bedform slip face translation measured in the field, approximately 0.3 \nmeters per day. Further, as the supply of sediment from upstream is continuous, once a reef bed \nfills with sediment it generally remains in place, although some small variations (+/- 0.2 m) in \nthe elevation of the sand overlying the reef beds were observed. Taken together, bathymetric \nsurveys and modeling could be used to identify, monitor, and simulate potential sources of \nbedload sediment that could impair the longevity of future spawning reef placements. Efforts \ndirected toward enhancement and/or maintenance of reefs impaired by sedimentation could \nbenefit from continued monitoring through periodic high-resolution bathymetric surveys, \ndetailed inspection by diving, and collection of underwater imagery.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the SEDHYD 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"May 2023","conferenceLocation":"St. Louis, Missouri, USA","language":"English","publisher":"SEDHYD","usgsCitation":"Kinzel, P.J., Kennedy, G.W., and Dudunake, T., 2023, Repeat bathymetric surveys and model simulation of sedimentation processes near fish spawning placements, Detroit and St. Clair Rivers, Michigan, in Proceedings of the SEDHYD 2023, St. Louis, Missouri, USA, May 2023, 13 p.","productDescription":"13 p.","ipdsId":"IP-147516","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":421903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421897,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/past/2023Proceedings/22.pdf"}],"country":"United States","state":"Michigan","otherGeospatial":"Detroit River, St. Clair River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.30276185834879,\n 42.0286133036347\n ],\n [\n -82.90725404584906,\n 42.0286133036347\n ],\n [\n -82.90725404584906,\n 42.36232360308355\n ],\n [\n -83.30276185834879,\n 42.36232360308355\n ],\n [\n -83.30276185834879,\n 42.0286133036347\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.86330873334916,\n 42.581121335761054\n ],\n [\n -82.06130678022406,\n 42.581121335761054\n ],\n [\n -82.06130678022406,\n 43.064598528454496\n ],\n [\n -82.86330873334916,\n 43.064598528454496\n ],\n [\n -82.86330873334916,\n 42.581121335761054\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":886096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Gregory W. 0000-0003-1686-6960 gkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-6960","contributorId":3700,"corporation":false,"usgs":true,"family":"Kennedy","given":"Gregory","email":"gkennedy@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dudunake, Taylor 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":191564,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":886098,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70238008,"text":"70238008 - 2023 - Guide for interpreting and reporting luminescence dating results","interactions":[],"lastModifiedDate":"2023-05-01T15:32:48.383588","indexId":"70238008","displayToPublicDate":"2022-09-29T11:54:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Guide for interpreting and reporting luminescence dating results","docAbstract":"The development and application of luminescence dating and dosimetry techniques have grown exponentially in the last several decades. Luminescence methods provide age control for a broad range of geological and archaeological contexts and can characterize mineral and glass properties linked to geologic origin, Earth-surface processes, and past exposure to light, heat, and ionizing radiation. The applicable age range for luminescence methods spans the last 500,000 years or more, which covers the period of modern human evolution, and provides context for rates and magnitudes of geological processes, hazards, and climate change. Given the growth in applications and publications of luminescence data, there is a need for unified, community-driven guidance regarding the publication and interpretation of luminescence results.
This paper presents a guide to the essential information necessary for publishing and archiving luminescence ages as well as supporting data that is transportable and expandable for different research objectives and publication outlets. We outline the information needed for the interpretation of luminescence data sets, including data associated with equivalent dose, dose rate, age models, and stratigraphic context. A brief review of the fundamentals of luminescence techniques and applications, including guidance on sample collection and insight into laboratory processing and analysis steps, is presented to provide context for publishing and data archiving.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36404.1","usgsCitation":"Mahan, S.A., Rittenour, T.M., Nelson, M., Ataee, N., Brown, N.D., DeWitt, R., Durcan, J., Evans, M., Feathers, J.K., Frouin, M., Guerin, G., Heydari, M., Huot, S., Jain, M., Keen-Zebert, A., Li, B., Lopez, G.I., Neudorf, C., Porat, N., Rodrigues, K., Sawakuchi, A.O., Spencer, J.Q., and Thomsen, K., 2023, Guide for interpreting and reporting luminescence dating results: GSA Bulletin, v. 135, no. 5-6, p. 1480-1502, https://doi.org/10.1130/B36404.1.","productDescription":"23 p.","startPage":"1480","endPage":"1502","ipdsId":"IP-130448","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445389,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36404.1","text":"Publisher Index 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University","active":true,"usgs":false}],"preferred":false,"id":856535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Michelle S.","contributorId":140753,"corporation":false,"usgs":false,"family":"Nelson","given":"Michelle S.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":856536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ataee, Nina","contributorId":298822,"corporation":false,"usgs":false,"family":"Ataee","given":"Nina","email":"","affiliations":[{"id":16758,"text":"Aberystwyth University","active":true,"usgs":false}],"preferred":false,"id":856537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Nathan D. 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Survey","active":true,"usgs":false}],"preferred":false,"id":856550,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Neudorf, Christina","contributorId":298831,"corporation":false,"usgs":false,"family":"Neudorf","given":"Christina","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":856551,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Porat, Naomi","contributorId":201778,"corporation":false,"usgs":false,"family":"Porat","given":"Naomi","email":"","affiliations":[{"id":13093,"text":"Geological Survey of Israel ","active":true,"usgs":false}],"preferred":false,"id":856552,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Rodrigues, Kathleen","contributorId":298832,"corporation":false,"usgs":false,"family":"Rodrigues","given":"Kathleen","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":856553,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sawakuchi, Andre O.","contributorId":298833,"corporation":false,"usgs":false,"family":"Sawakuchi","given":"Andre","email":"","middleInitial":"O.","affiliations":[{"id":48623,"text":"University of Sao Paulo","active":true,"usgs":false}],"preferred":false,"id":856554,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Spencer, Joel Q. G","contributorId":298834,"corporation":false,"usgs":false,"family":"Spencer","given":"Joel","email":"","middleInitial":"Q. 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For Chinook salmon (Oncorhynchus tshawytscha), variation in their migration and habitat use complicate predicting how restoring habitats could impact total recruitment. To evaluate how juvenile life history variation affects a population’s response to potential restoration, we developed a stage-structured model for a Chinook salmon population in a northern California river with a seasonally closed estuary. We modeled the timing of juvenile migration and estuarine use as a function of freshwater conditions and fish abundance. We used the model to evaluate the sensitivity of the population to different estuary and freshwater restoration scenarios that could affect population parameters at different life stages. The population’s run size increased most in response to freshwater restoration that enhanced spawning productivity (egg and fry survival), followed by spawner capacity. In contrast, estuary restoration scenarios affected only a subset of Chinook salmon (average 15%), and as a result, did not have a large impact on the total recruitment of a cohort. Under current condition, estuary rearing fish were over six times less likely to survive than fish that migrate to the ocean in the spring or early summer before estuary closure. Because estuary residents experienced low survival in the estuary and in the ocean, improvements to both estuary survival and growth would be needed to increase their total survival. When life cycle monitoring data is available, life cycle models such as ours generate predictions at scales relevant to conservation and are an advantageous approach to managing and conserving anadromous salmon that use multiple habitats throughout their life cycle.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2022.106511","usgsCitation":"Chen, E.K., Som, N.A., Deibner-Hanson, J., Anderson, D.G., and Henderson, M., 2023, A life cycle model for evaluating estuary residency and restoration potential in Chinook salmon: Fisheries Research, v. 257, 106511, 12 p., https://doi.org/10.1016/j.fishres.2022.106511.","productDescription":"106511, 12 p.","ipdsId":"IP-135740","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2022.106511","text":"Publisher Index Page"},{"id":429651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt County","otherGeospatial":"Redwood Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.10880012967473,\n 41.33028967561785\n ],\n [\n -124.10880012967473,\n 41.09072792742461\n ],\n [\n -123.87469855224558,\n 41.09072792742461\n ],\n [\n -123.87469855224558,\n 41.33028967561785\n ],\n [\n -124.10880012967473,\n 41.33028967561785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"257","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Emily K.","contributorId":337295,"corporation":false,"usgs":false,"family":"Chen","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":902335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Som, Nicholas A.","contributorId":36039,"corporation":false,"usgs":true,"family":"Som","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":902336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deibner-Hanson, John","contributorId":337299,"corporation":false,"usgs":false,"family":"Deibner-Hanson","given":"John","email":"","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":902337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, David G.","contributorId":337301,"corporation":false,"usgs":false,"family":"Anderson","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":81007,"text":"Redwood National and State Parks","active":true,"usgs":false}],"preferred":false,"id":902338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":902339,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240136,"text":"70240136 - 2023 - Prioritizing pesticides of potential concern and identifying potential mixture effects in Great Lakes tributaries using passive samplers","interactions":[],"lastModifiedDate":"2023-01-30T12:46:08.681028","indexId":"70240136","displayToPublicDate":"2022-09-27T06:42:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing pesticides of potential concern and identifying potential mixture effects in Great Lakes tributaries using passive samplers","docAbstract":"To help meet the objectives of the Great Lakes Restoration Initiative with regard to increasing knowledge about toxic substances, 223 pesticides and pesticide transformation products were monitored in 15 Great Lakes tributaries using polar organic chemical integrative samplers. A screening-level assessment of their potential for biological effects was conducted by computing toxicity quotients (TQs) for chemicals with available US Environmental Protection Agency (USEPA) Aquatic Life Benchmark values. In addition, exposure activity ratios (EAR) were calculated using information from the USEPA ToxCast database. Between 16 and 81 chemicals were detected per site, with 97 unique compounds detected overall, for which 64 could be assessed using TQs or EARs. Ten chemicals exceeded TQ or EAR levels of concern at two or more sites. Chemicals exceeding thresholds included seven herbicides (2,4-dichlorophenoxyacetic acid, diuron, metolachlor, acetochlor, atrazine, simazine, and sulfentrazone), a transformation product (deisopropylatrazine), and two insecticides (fipronil and imidacloprid). Watersheds draining agricultural and urban areas had more detections and higher concentrations of pesticides compared with other land uses. Chemical mixtures analysis for ToxCast assays associated with common modes of action defined by gene targets and adverse outcome pathways (AOP) indicated potential activity on biological pathways related to a range of cellular processes, including xenobiotic metabolism, extracellular signaling, endocrine function, and protection against oxidative stress. Use of gene ontology databases and the AOP knowledgebase within the R-package ToxMixtures highlighted the utility of ToxCast data for identifying and evaluating potential biological effects and adverse outcomes of chemicals and mixtures. Results have provided a list of high-priority chemicals for future monitoring and potential biological effects warranting further evaluation in laboratory and field environments. Environ Toxicol Chem 2023;42:340–366. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Pollen and spores were recovered from the Paleocene Fort Union Formation and Paleocene–Eocene Willwood Formation of the Bighorn Basin (BHB), northwestern Wyoming, USA. In many local stratigraphic sections in the BHB, the base of the Eocene has been identified by the characteristic negative carbon isotope excursion (CIE) that marks the beginning of the Paleocene–Eocene Thermal Maximum (PETM). The palynotaxa from outcrop samples were examined using light microscopy (LM) and scanning electron microscopy (SEM). Seven new species are formally described (Tricolpites vegrandis, Rousea spatium, Striatricolporites astutus, Striatopollis calidarius, Friedrichipollis geminus, Retistephanocolporites modicrassus and Retistephanocolporites pergrandis). The temporal and geographic distributions of many of these palynotaxa suggest that hotter and more seasonally dry climates facilitated their northward range shifts during the PETM from the tropics or subtropics of the USA. For the temperate palynotaxa, the hotter and seasonally dry conditions resulted in local extirpation. A re-evaluation of the palynostratigraphic schemes established for the Paleocene–Eocene boundary confirms that the first appearance of Platycarya platycaryoides denotes the Paleocene–Eocene boundary in the Rocky Mountains region. A new Striatopollis calidarius Subzone, associated with early Wasatchian (Wa) Wa-0 and Wa-R faunas, is also recognized for CIE body localities in the BHB.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01916122.2022.2115159","usgsCitation":"Korasidis, V.A., Wing, S.L., Harrington, G.J., Demchuk, T., Gfavendyck, J., Jardine, P.E., and Willard, D., 2023, Biostratigraphically significant palynofloras from the Paleocene–Eocene boundary of the USA: Palynology, v. 47, no. 1, 2115159, https://doi.org/10.1080/01916122.2022.2115159.","productDescription":"2115159","ipdsId":"IP-143511","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":407959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bighorn Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.44030761718749,\n 43.42898792344155\n ],\n [\n -107.26501464843749,\n 43.42898792344155\n ],\n [\n -107.26501464843749,\n 45.058001435398275\n ],\n [\n -109.44030761718749,\n 45.058001435398275\n ],\n [\n -109.44030761718749,\n 43.42898792344155\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Korasidis, Vera A.","contributorId":297212,"corporation":false,"usgs":false,"family":"Korasidis","given":"Vera","email":"","middleInitial":"A.","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":853660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wing, Scott L.","contributorId":297213,"corporation":false,"usgs":false,"family":"Wing","given":"Scott","email":"","middleInitial":"L.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":853661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, Guy J.","contributorId":297214,"corporation":false,"usgs":false,"family":"Harrington","given":"Guy","email":"","middleInitial":"J.","affiliations":[{"id":64318,"text":"Petrostrat Ltd.","active":true,"usgs":false}],"preferred":false,"id":853662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demchuk, Thomas","contributorId":297215,"corporation":false,"usgs":false,"family":"Demchuk","given":"Thomas","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":853663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gfavendyck, J.","contributorId":297217,"corporation":false,"usgs":false,"family":"Gfavendyck","given":"J.","email":"","affiliations":[{"id":64319,"text":"Leibniz University","active":true,"usgs":false}],"preferred":false,"id":853664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jardine, Phillip E.","contributorId":297219,"corporation":false,"usgs":false,"family":"Jardine","given":"Phillip","email":"","middleInitial":"E.","affiliations":[{"id":64320,"text":"University of Munster","active":true,"usgs":false}],"preferred":false,"id":853665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Willard, Debra A. 0000-0003-4878-0942","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":269840,"corporation":false,"usgs":true,"family":"Willard","given":"Debra A.","affiliations":[],"preferred":true,"id":853666,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237086,"text":"70237086 - 2023 - Taking steps to address inequities in open-access publishing through an early career publication honor","interactions":[],"lastModifiedDate":"2023-05-25T15:21:11.5395","indexId":"70237086","displayToPublicDate":"2022-09-23T09:36:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Taking steps to address inequities in open-access publishing through an early career publication honor","docAbstract":"Access to resources—whether human, financial, or social—is a key indicator of research output and, in turn, academic career progression. However, resources are not equally distributed among scientists and disparities often stem from external factors. This reality is particularly impactful for early career researchers (ECRs) who have limited control over the resources available to them to advance their careers. The resources needed to fund open-access (OA) publishing are a well-known source of academic inequity (Ross-Hellauer 2022). Despite this, wide support for OA publishing exists across the scientific community, largely because OA articles increase access to the scientific literature by removing costly paywalls (Piwowar et al. 2018). Benefits of OA publishing also exist for individual researchers; OA studies are read and cited more, so much so that an “open access citation advantage” has been described (McCabe and Snyder 2014). Depending on the methods and journals studied, this advantage ranges from an 8 to 40% increase in citation rate (Piwowar et al. 2018). The OA publishing model is set to expand further, with influential groups seeking to mandate OA publishing (e.g., Plan S; Else 2021) including recent guidance from the United States Office of Science and Technology Policy (The White House 2022). However, OA publishing remains expensive, often prohibitively so, and OA fees deter ECRs broadly (Sarabipour et al. 2019), and particularly those from the Global South (Kwon 2022; Santidrián Tomillo et al. 2022).
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10283","usgsCitation":"Hotaling, S., Deemer, B., Poulson-Ellestad, K., and Falkenberg, L.J., 2023, Taking steps to address inequities in open-access publishing through an early career publication honor: Limnology and Oceanography Letters, v. 8, no. 3, p. 385-387, https://doi.org/10.1002/lol2.10283.","productDescription":"3 p.","startPage":"385","endPage":"387","ipdsId":"IP-142599","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445419,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10283","text":"Publisher Index Page"},{"id":407597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hotaling, Scott","contributorId":202050,"corporation":false,"usgs":false,"family":"Hotaling","given":"Scott","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":853292,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulson-Ellestad, Kelsey","contributorId":297098,"corporation":false,"usgs":false,"family":"Poulson-Ellestad","given":"Kelsey","email":"","affiliations":[{"id":64292,"text":"Department of Biological, Physical, and Health Sciences, Roosevelt University, Chicago, IL, USA","active":true,"usgs":false}],"preferred":false,"id":853294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falkenberg, Laura J.","contributorId":297099,"corporation":false,"usgs":false,"family":"Falkenberg","given":"Laura","email":"","middleInitial":"J.","affiliations":[{"id":64294,"text":"Simon F.S. Li Marine Science Laboratory, School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR, Hong Kong","active":true,"usgs":false}],"preferred":false,"id":853295,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242723,"text":"70242723 - 2023 - High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles","interactions":[],"lastModifiedDate":"2023-05-10T19:15:20.332938","indexId":"70242723","displayToPublicDate":"2022-09-23T06:57:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles","docAbstract":"We test the behavior of the United States (US) West Coast ShakeAlert earthquake early warning (EEW) system during temporally close earthquake pairs to understand current performance and limitations. We consider performance metrics based on source parameter and ground‐motion forecast accuracy, as well as on alerting timeliness. We generate ground‐motion times series for synthesized earthquake sequences from real data by combining the signals from pairs of well‐recorded earthquakes (4.4≤M≤7.1) using time shifts ranging from −60 to +180 s. We examine fore‐ and aftershock sequences, near‐simultaneous events in different source regions, and simulated out‐of‐network and offshore earthquakes. We find that the operational ShakeAlert algorithms Earthquake Point‐source Integrated Code (EPIC) and Finite‐Fault Rupture Detector (FinDer) and the Propagation of Local Undamped Motion (PLUM) method perform largely as expected: EPIC provides the best source location estimates and is often fastest but can underestimate magnitudes or, in extreme cases, miss large earthquakes; FinDer provides real‐time line‐source models and unsaturated magnitude estimates for large earthquakes but currently cannot process concurrent events and may mislocate offshore earthquakes; PLUM identifies pockets of strong ground motion, but can overestimate alert areas. Implications for system performance are: (1) spatially and temporally close events are difficult to identify separately; (2) challenging scenarios with foreshocks that are close in space and time can lead to missed alerts for large earthquakes; and (3) in these situations the algorithms can often estimate ground motion better than source parameters. To improve EEW, our work suggests revisiting the current algorithm weighting in ShakeAlert, to continue developments that focus on using ground‐motion data to aggregate alerts from multiple algorithms, and to investigate methods to optimally leverage algorithm ground‐motion estimates. For testing and certification of EEW performance in ShakeAlert and other EEW systems where applicable, we also suggest that 25 of our 73 scenarios become part of the baseline data set.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220088","usgsCitation":"Bose, M., Andrews, J., O’Rourke, C.T., Kilb, D.L., Lux, A., Bunn, J., and McGuire, J., 2023, Testing the ShakeAlert earthquake early warning system using synthesized earthquake sequences: Seismological Research Letters, v. 94, no. 1, p. 243-259, https://doi.org/10.1785/0220220088.","productDescription":"17 p.","startPage":"243","endPage":"259","ipdsId":"IP-141699","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.12875665417036,\n 32.529141687918056\n ],\n [\n -114.63698449380014,\n 32.72614838079981\n ],\n [\n -114.48442701459375,\n 32.93979339517037\n ],\n [\n -114.66749598964131,\n 33.12737512996701\n ],\n [\n -114.66749598964131,\n 33.365536989744484\n ],\n [\n -114.50476801182128,\n 33.79765966999783\n ],\n [\n -114.37255152984241,\n 34.135061265713915\n ],\n [\n -114.16914155756731,\n 34.269646597615036\n ],\n [\n -114.62681399518621,\n 35.006011225518876\n ],\n [\n -116.50835623873114,\n 36.49168810234471\n ],\n [\n -121.76650402204325,\n 36.26240794936248\n ],\n [\n -120.71894266482627,\n 35.105916993794835\n ],\n [\n -120.92235263710137,\n 34.546539072317\n ],\n [\n -120.92235263710137,\n 34.303292988567804\n ],\n [\n -120.8816706426466,\n 33.79765966999783\n ],\n [\n -119.4171188422655,\n 32.477677373072126\n ],\n [\n -117.12875665417036,\n 32.529141687918056\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"94","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Bose, Maren","contributorId":222639,"corporation":false,"usgs":false,"family":"Bose","given":"Maren","email":"","affiliations":[{"id":40575,"text":"Swiss Seismological Service, Swiss Federal Institute of Technology Zürich (ETH Zürich), Zürich, Switzerland","active":true,"usgs":false}],"preferred":false,"id":853549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, Jennifer","contributorId":187764,"corporation":false,"usgs":false,"family":"Andrews","given":"Jennifer","affiliations":[],"preferred":false,"id":853550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Rourke, Colin T 0000-0001-5403-4685","orcid":"https://orcid.org/0000-0001-5403-4685","contributorId":290635,"corporation":false,"usgs":true,"family":"O’Rourke","given":"Colin","email":"","middleInitial":"T","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kilb, Deborah L.","contributorId":216380,"corporation":false,"usgs":false,"family":"Kilb","given":"Deborah","email":"","middleInitial":"L.","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":853552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lux, Angela","contributorId":297155,"corporation":false,"usgs":false,"family":"Lux","given":"Angela","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":853553,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bunn, Julian","contributorId":216379,"corporation":false,"usgs":false,"family":"Bunn","given":"Julian","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":853554,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853555,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256637,"text":"70256637 - 2023 - Variation in Prairie Chub hatch relationships across wet and dry years in the upper Red River basin","interactions":[],"lastModifiedDate":"2024-08-28T11:03:02.81242","indexId":"70256637","displayToPublicDate":"2022-09-19T06:00:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Variation in Prairie Chub hatch relationships across wet and dry years in the upper Red River basin","docAbstract":"The Prairie Chub Macrhybopsis australis is a poorly studied minnow species endemic to the upper Red River basin and is of both state and federal conservation interest due to uncertainty about its life history and potential listing status. The upper Red River basin of Oklahoma and Texas is a harsh environment where drought and extreme flow events are exacerbated by human alterations. As an assumed pelagic-broadcast-spawning minnow, the Prairie Chub is capable of a protracted spawning season and larval fish survival is assumed to be linked to discharge and streamflow variability.
We systematically collected 2,017 age-0 Prairie Chub from seven sites (North Fork Red River, Salt Fork Red River, Pease River, Red River, Prairie Dog Town Fork Red River, North Wichita River, and South Wichita River) with variable flow patterns during April–September 2019 and May–August 2020. We used otolith age estimates and back calculations to determine successful spawning dates. We used a hurdle model framework to examine relationships between hatch probability and hatch frequency.
Hatch probability had a negative relationship with calendar day and declined as calendar day increased. Hatch counts peaked in late June and early July and declined thereafter in 2019 but showed no discernible peak during the spawning season in 2020. Hatch probability during the spawning season increased with relative flow and air temperature. Increased hatch counts were also positively related to discharge variability (CV) for the 10 d prior to hatch dates.
Our findings indicated that successful hatches had considerable spatial and temporal variability, with some sites contributing minimally to the population during some years. Spatial and temporal variability of hatch probability and hatch frequencies pose a variety of considerations for future conservation and management efforts, particularly given the pending federal listing status of the species.
The Glen Torridon (GT) region is positioned in terrains with strong clay mineral signatures, as inferred from orbital spectroscopy. The GT campaign confirmed orbital distinctions with in situ measurements by the Mars Science Laboratory rover, Curiosity, and the CheMin X-ray diffraction instrument with of some of the highest clay mineral abundances to date. Additionally, GT is unique because of distinct phase identifications for the first time by CheMin, including: (i) Fe-carbonates, and (ii) a novel peak in the XRD patterns of some GT samples, with an interplanar spacing of at 9.2 Å. Fe-carbonates have been previously suggested from other instruments onboard, but this is the first definitive reporting by CheMin of multiple samples with Fe-carbonate. This new phase has never been observed in Gale crater with the CheMin instrument and may be a new mineral for Mars, but discrete identification still remains enigmatic because no single phase on Earth is able to account the mineralogical, geochemical, and sedimentological constraints in the GT region. Here, we modeled XRD profiles and propose an interstratified clay mineral, specifically greenalite-minnesotaite (G-M), as a reasonable candidate. The coexistence of Fe-carbonate and Fe-rich clay minerals in the GT samples, supports a conceptual model of a lacustrine groundwater mixing environment in the ancient Gale crater lake. Groundwater interaction with percolating lake waters in the sediments is common in terrestrial lacustrine settings, and the diffusion of two distinct water bodies within the subsurface can create a geochemical gradient and unique mineral front in the sediments. Ultimately, the proximity to this mixing zone controlled the secondary minerals preserved in the Jura, Knockfarril Hill, and Glasgow members of the Mt. Sharp group exposed in GT.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JE007099","usgsCitation":"Thorpe, M.T., Bristow, T.F., Rampe, E., Tosca, N., Grotzinger, J.P., Bennett, K.A., Achilles, C., Blake, D.F., Chipera, S.J., Downs, G., Downs, R.T., Morrison, S.M., Tu, V., Castle, N., Craig, P., Des Marais, D.J., Hazen, R.M., Ming, D.W., Morris, R.V., Treiman, A.H., Vaniman, D.T., Yen, A.S., Vasavada, A.R., Dehouck, E., Bridges, J., Berger, J., McAdam, A., Peretyazhko, T., Siebach, K., Bryk, A.B., Fox, V.F., and Fedo, C.M., 2023, Mars Science Laboratory CheMin data from the Glen Torridon region and the significance of lake-groundwater interactions in interpreting mineralogy and sedimentary history: Journal of Geophysical Research E: Planets, v. 127, e2021JE007099, 33 p., https://doi.org/10.1029/2021JE007099.","productDescription":"e2021JE007099, 33 p.","ipdsId":"IP-132887","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":445437,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021je007099","text":"Publisher Index Page"},{"id":421608,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gale crater, Mars","volume":"127","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Thorpe, Michael T.","contributorId":261804,"corporation":false,"usgs":false,"family":"Thorpe","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":53022,"text":"Jacobs Technology","active":true,"usgs":false}],"preferred":false,"id":885104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bristow, T. F.","contributorId":265190,"corporation":false,"usgs":false,"family":"Bristow","given":"T.","email":"","middleInitial":"F.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":885105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rampe, E.","contributorId":265192,"corporation":false,"usgs":false,"family":"Rampe","given":"E.","affiliations":[{"id":27073,"text":"NASA JSC","active":true,"usgs":false}],"preferred":false,"id":885106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tosca, Nicholas","contributorId":330493,"corporation":false,"usgs":false,"family":"Tosca","given":"Nicholas","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":885107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grotzinger, John P.","contributorId":181502,"corporation":false,"usgs":false,"family":"Grotzinger","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":885108,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennett, Kristen A. 0000-0001-8105-7129","orcid":"https://orcid.org/0000-0001-8105-7129","contributorId":237068,"corporation":false,"usgs":true,"family":"Bennett","given":"Kristen","email":"","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":885109,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Achilles, C. N.","contributorId":265204,"corporation":false,"usgs":false,"family":"Achilles","given":"C. N.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":885110,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blake, D. F.","contributorId":265206,"corporation":false,"usgs":false,"family":"Blake","given":"D.","email":"","middleInitial":"F.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":885111,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chipera, S. 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B.","contributorId":265239,"corporation":false,"usgs":false,"family":"Bryk","given":"A.","email":"","middleInitial":"B.","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":885134,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Fox, V. F.","contributorId":330485,"corporation":false,"usgs":false,"family":"Fox","given":"V.","email":"","middleInitial":"F.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":885135,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Fedo, Christopher M.","contributorId":229497,"corporation":false,"usgs":false,"family":"Fedo","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":885136,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}} ,{"id":70238577,"text":"70238577 - 2023 - Improved method for simulating groundwater inundation using the MODFLOW 6 Lake Transport Package","interactions":[],"lastModifiedDate":"2023-05-25T15:31:45.649171","indexId":"70238577","displayToPublicDate":"2022-09-14T06:35:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Improved method for simulating groundwater inundation using the MODFLOW 6 Lake Transport Package","docAbstract":"Groundwater inundation due to sea level rise can affect island and coastal freshwater resources by exposing water tables to direct, continuous evaporation. Numerical simulations of groundwater inundation effects on coastal and island aquifers have been limited by an inability to simulate solute transport and variable density flow between the aquifer and lakes formed by groundwater inundation. Consequently, we contributed to the development of a new tool, the Lake Transport Package, for MODFLOW 6 that can calculate solute concentrations within lakes and allows for variable density flow between lakes and aquifers. Here we use groundwater inundation as an example application to showcase the functionality of the Lake Transport Package and the advantages of using this tool over past methods of representing groundwater inundation. We developed hypothetical island simulations based on hydrogeological characteristics of the Bahamas. Multiple sea level rise and lake evaporation rates were simulated to evaluate the effects of groundwater inundation on freshwater lens size for different climates. The results demonstrate the ability of the Lake Transport Package to calculate the solute concentration of the lake for transient simulations, including hypersaline concentrations. Higher sea level rise and greater lake evaporation rates lead to a greater loss of the freshwater lens and higher lake salinity. The formation of a lake and corresponding expansion due to groundwater inundation increases the loss of freshwater by 6–36%, depending on the lake evaporation rate. These simulations validate the performance and demonstrate usefulness of the Lake Transport Package as a tool in representing groundwater inundation.
Climate change is occurring rapidly in the Arctic, and an improved understanding of the response of aquatic biota and ecosystems will be important for this data-limited region. Here, we applied biochronology techniques and mixed-effects modelling to assess relationships among growth increments found on lake trout (Salvelinus namaycush) otoliths (N = 49) captured from 13 lakes on the Arctic Coastal Plain of northern Alaska, observed and modelled climate patterns, and individual-level fish and lake characteristics. We found that annual growth varied by year, fish growth slowed significantly as individuals aged, and females grew faster than males. Lake trout had higher growth in flow-through lakes relative to lakes that were perennially or seasonally connected. Annual growth was positively correlated with observed air temperature measurements from a local weather station for the period 1998–2014, but no clear warming trend was evident for this period. Modelled August air temperatures from 1978–2014 predicted lake trout annual growth (root mean squared error = 0.045 mm) and indicated increasing temperatures and annual lake trout growth over the period 1950–2014. This study demonstrated that biochronology techniques can reconstruct recent climate patterns and provide a better understanding of trends in Arctic lake ecosystems under a changing climate.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12678","usgsCitation":"Torvinen, E., Falke, J.A., Arp, C.D., Jones, B.M., Whitman, M.S., and Zimmerman, C.E., 2023, Lake trout (Salvelinus namaycush) otoliths indicate effects of climate and lake morphology on growth patterns in Arctic lakes: Ecology of Freshwater Fish, v. 32, no. 1, p. 166-180, https://doi.org/10.1111/eff.12678.","productDescription":"15 p.","startPage":"166","endPage":"180","ipdsId":"IP-103948","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -151,\n 70.5\n ],\n [\n -154,\n 70.5\n ],\n [\n -154,\n 69.5\n ],\n [\n -151,\n 69.5\n ],\n [\n -151,\n 70.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"32","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Torvinen, Eric","contributorId":191061,"corporation":false,"usgs":false,"family":"Torvinen","given":"Eric","email":"","affiliations":[],"preferred":false,"id":935556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":935557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M.","contributorId":305542,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":935558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Matthew S.","contributorId":338574,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":81170,"text":"Arctic Field Office","active":true,"usgs":false}],"preferred":false,"id":935559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":935555,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70240169,"text":"70240169 - 2023 - A novel origin for PGE reefs: A case study of the J-M Reef","interactions":[],"lastModifiedDate":"2023-02-22T15:54:25.079132","indexId":"70240169","displayToPublicDate":"2022-09-08T09:52:27","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A novel origin for PGE reefs: A case study of the J-M Reef","docAbstract":"The origin of meter scale stratiform layers of disseminated sulfides in enriched platinum group element (PGE) tenors and grades, called reef-type deposits, are the world’s most significant source of PGEs. Their origin in layered mafic intrusions remains debated, but in general, most researchers favor an orthomagmatic origin for reef-type deposits and agree that their formation requires the equilibration of an immiscible sulfide liquid with a significantly larger mass of silicate magma (i.e., silicate:sulfide mass ratios of 104 to 106). However, where, and how this chemical equilibration process takes place in the magmatic system is poorly constrained. In this contribution, we propose a new model for the origin of PGE reef deposits. We demonstrate that finely disseminated, resident sulfide liquid hosted within cumulate mush can be upgraded by incoming batches of S-undersaturated and PGE-undepleted silicate melt. We demonstrate this model through a case study of the J-M Reef deposit of the Stillwater Complex, the world’s highest-grade PGE deposit (14 ppm Pd over 1.8 m).","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Applied Earth Science","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/25726838.2022.2084233","usgsCitation":"Jenkins, M., Mungall, J.E., Zientek, M., Costin, G., and Yao, Z., 2023, A novel origin for PGE reefs: A case study of the J-M Reef, in Applied Earth Science, v. 131, no. 3, p. 147-148, https://doi.org/10.1080/25726838.2022.2084233.","productDescription":"2 p.","startPage":"147","endPage":"148","ipdsId":"IP-138074","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":413287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"131","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mungall, James E. 0000-0001-9726-8545","orcid":"https://orcid.org/0000-0001-9726-8545","contributorId":269537,"corporation":false,"usgs":false,"family":"Mungall","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":862834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zientek, Michael L. 0000-0002-8522-9626","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":210763,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Costin, Gelu 0000-0003-3054-7886","orcid":"https://orcid.org/0000-0003-3054-7886","contributorId":269538,"corporation":false,"usgs":false,"family":"Costin","given":"Gelu","email":"","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":862836,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yao, Zhuo-sen 0000-0002-5075-0745","orcid":"https://orcid.org/0000-0002-5075-0745","contributorId":269539,"corporation":false,"usgs":false,"family":"Yao","given":"Zhuo-sen","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":862837,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250894,"text":"70250894 - 2023 - Structural properties of the Southern San Andreas fault zone in northern Coachella Valley from magnetotelluric imaging","interactions":[],"lastModifiedDate":"2024-01-11T13:56:43.841598","indexId":"70250894","displayToPublicDate":"2022-09-08T07:53:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Structural properties of the Southern San Andreas fault zone in northern Coachella Valley from magnetotelluric imaging","docAbstract":"The Southern San Andreas fault (SSAF) poses one of the largest seismic risks in California. Yet, there is much ambiguity regarding its deeper structural properties around Coachella Valley, in large part due to the relative paucity of everyday seismicity. Here, we image a multistranded section of the SSAF using a non-seismic method, namely magnetotelluric (MT) soundings, to help inform depth-dependent fault zone geometry, fluid content and porosity. The acquired MT data and resultant inversion models highlight a conductive column encompassing the SSAF zone that includes a 2–3 km wide vertical to steeply northeast dipping conductor down to ∼4 km depth (maximum of ∼1 Ω·m at 2 km depth) and another prominent conductor in the ductile crust (∼1 Ω·m at 12 km depth and slightly southwest of the surface SSAF). We estimate porosities of 18–44 per cent for the conductive uppermost 500 m, a 10–15 per cent porosity at 2 km depth and that small amounts (0.1–3 per cent) of interconnected hypersaline fluids produce the deeper conductor. Located northeast of this conductive region is mostly resistive crust indicating dry crystalline rock that extends down to ∼20 km in places. Most of the local seismicity is associated with this resistive region. Located farther northeast still is a conductive region at >13 km depth and separate from the one to the southwest. The imaged anomalies permit two interpretations. The SSAF zone is vertical to steeply northeast dipping in the upper crust and (1) is near vertical at greater depth creating mostly an impermeable barrier for northeast fluid migration or (2) continues to dip northeast but is relatively dry and resistive up to ∼13 km depth where it manifests as a secondary deep ductile crustal conductor. Taken together with existing knowledge, the first interpretation is more likely but more MT investigations are required.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggac356","usgsCitation":"Share-MacParland, P., Peacock, J., Constable, S.C., Vernon, F.L., and Wang, S., 2023, Structural properties of the Southern San Andreas fault zone in northern Coachella Valley from magnetotelluric imaging: Geophysical Journal International, v. 232, no. 1, p. 694-704, https://doi.org/10.1093/gji/ggac356.","productDescription":"11 p.","startPage":"694","endPage":"704","ipdsId":"IP-124157","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":445442,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/11250/3051610","text":"External Repository"},{"id":424322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"northern Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.0,\n 34.25\n ],\n [\n -117.0,\n 33.5\n ],\n [\n -115.75,\n 33.5\n ],\n [\n -115.75,\n 34.25\n ],\n [\n -117.0,\n 34.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"232","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Share-MacParland, Pieter-Ewald 0000-0001-6674-1491","orcid":"https://orcid.org/0000-0001-6674-1491","contributorId":299108,"corporation":false,"usgs":false,"family":"Share-MacParland","given":"Pieter-Ewald","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":891962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Constable, Steve C. 0000-0001-6324-3470","orcid":"https://orcid.org/0000-0001-6324-3470","contributorId":333113,"corporation":false,"usgs":false,"family":"Constable","given":"Steve","email":"","middleInitial":"C.","affiliations":[{"id":79733,"text":"Institute of Geophysics and Planetary Physics, University of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":891964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vernon, Frank L. 0000-0002-9379-4000","orcid":"https://orcid.org/0000-0002-9379-4000","contributorId":333114,"corporation":false,"usgs":false,"family":"Vernon","given":"Frank","email":"","middleInitial":"L.","affiliations":[{"id":79734,"text":"Institute of Geophysics and Planetary Science, University of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":891965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Shunguo","contributorId":333115,"corporation":false,"usgs":false,"family":"Wang","given":"Shunguo","email":"","affiliations":[{"id":79736,"text":"Department of Electronic Systems, Norwegian University of Science and Technology, Trondheim, Norway","active":true,"usgs":false}],"preferred":false,"id":891966,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238426,"text":"70238426 - 2023 - Fires, floods and other extreme events – How watershed processes under climate change will shape our coastlines","interactions":[],"lastModifiedDate":"2022-11-22T12:48:30.808774","indexId":"70238426","displayToPublicDate":"2022-09-08T06:41:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12971,"text":"Cambridge Prisms: Coastal Futures","active":true,"publicationSubtype":{"id":10}},"title":"Fires, floods and other extreme events – How watershed processes under climate change will shape our coastlines","docAbstract":"Ongoing sea-level rise has brought renewed focus on terrestrial sediment supply to the coast because of its strong influence on whether and how long beaches, marshes and other coastal landforms may persist into the future. Here, we summarise findings of sediment discharge from several coastal rivers, revealing that infrequent, large-magnitude events have disproportionate influence on the morphodynamics of coastal landforms and littoral cells. These event-dominated effects are most pronounced for small, steep mountainous rivers that supply beach and wetland sediment along the world’s active tectonic margins, although infrequent events are important drivers of sediment discharge for rivers worldwide. Additionally, extreme events (recurrence intervals of decades to centuries) that follow wildfires, earthquakes, volcanic eruptions, extreme precipitation or – most notably – combinations of these factors can redefine coastal sediment budgets and morphology. Some of these extreme events (e.g., wildfires plus rainfall) are increasing in magnitude and frequency under modern climate warming, with the likely result of increasing sediment flux to affected coastlines. Climate change is also altering watershed processes in both high latitudes and high altitudes, resulting in increased sediment supply to downstream catchments. We conclude that sediment inputs to coastal systems are highly variable with time, and that the variability and trends in sediment input are as important to characterise as long-term averages.
No abstract available.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13250","usgsCitation":"Fienen, M., 2023, Book review: Analytical groundwater modeling: Theory and applications using Python: Groundwater, v. 61, no. 1, p. 4-5, https://doi.org/10.1111/gwat.13250.","productDescription":"2 p.","startPage":"4","endPage":"5","ipdsId":"IP-142834","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":406609,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":849932,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239910,"text":"70239910 - 2023 - Using machine learning techniques with incomplete polarity datasets to improve earthquake focal mechanism determination","interactions":[],"lastModifiedDate":"2023-01-25T12:41:17.885197","indexId":"70239910","displayToPublicDate":"2022-09-07T06:40:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Using machine learning techniques with incomplete polarity datasets to improve earthquake focal mechanism determination","docAbstract":"Earthquake focal mechanisms are traditionally produced using P‐wave first‐motion polarities and commonly require well‐recorded seismicity. A recent approach that is less dependent on high signal‐to‐noise exploits similar waveforms to produce relative polarity measurements between earthquake pairs. Utilizing these relative polarity measurements, it is possible to produce composite focal mechanisms for clusters within microseismic sequences using regional networks. However, missing or low‐confidence polarity measurements still limit our ability to calculate high‐quality composite focal mechanisms. Here, we replaced unreliable polarity measurements with estimates using iterative random forests, an unsupervised ensemble machine learning method. Using the imputed (“replaced”) polarity data, we then categorically clustered the events into families. As a case study, we applied this modified composite mechanism workflow to a multistation template matched catalog of an earthquake swarm that occurred during 2020 near the Maacama fault in northern California. We found that our modified methodology produced higher‐quality earthquake families and improved composite focal mechanisms, with fault‐plane uncertainties <35° for 94% of the families compared with 34% of families using the previous methodology.
Rarely are sufficient resources available to support the full suite of management actions to promote recovery of a species across their entire distribution. Decision support models are a tool that can inform natural resource management decisions with consideration of the perspectives from a variety of stakeholders who work across large geographic and jurisdictional extents. We offer an example of a decision support model that was developed by several Federal and State natural resource agencies to rank Bull Trout Salvelinus confluentus core areas for prioritizing conservation investment within Oregon, USA. We engaged State level decision makers to identify parameters believed to be influential in determining funding allocations for Bull Trout core areas. Parameters were linked in a model framework that was further refined with input from local Bull Trout experts with knowledge specific to the various core areas. The model produces a relative priority value that is a combination of the conservation risk to the species and the management capacity to address threats. A series of sensitivity analyses suggests that Bull Trout persistence and threat score are most influential in determining the relative priority of a core area, and life-history and genetic diversity are least influential. One of the more powerful products from this work is an interactive web-based application (https://das.ecosphere.fws.gov/public/obts/) that anyone can use to explore how their beliefs in parameter values will affect the relative priority of Bull Trout core areas across Oregon. Our modeling effort is an example of engaging stakeholders with different roles in species recovery and across a large geographic area to create a clearer path forward in allocating limited resources for species recovery. This approach can be employed to address a number of natural resource management situations across species and habitats.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10834","usgsCitation":"Brignon, W.R., Davis, M.B., Gunkel, S., Dunham, J.B., Meeuwig, M.H., Allen, C.S., and Clements, S., 2023, Engaging stakeholders to develop a decision support model of conservation risk and management capacity to prioritize investments in Bull Trout recovery: North American Journal of Fisheries Management, v. 43, no. 3, p. 821-838, https://doi.org/10.1002/nafm.10834.","productDescription":"18 p.","startPage":"821","endPage":"838","ipdsId":"IP-140598","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":407511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Monitoring data, though, is prone to instrumental noise, wide ranging extrema, and nonstationary response to rainfall where ground conditions change. Furthermore, existing soil moisture models generally forecast poorly for time periods greater than a few hours. To improve such forecasts, we introduce two data-driven models, the Naive Accumulative Representation (NAR) and the Additive Exponential Accumulative Representation (AEAR). Both of these models are rooted in deterministic, physically based hydrology, and we study their capabilities in forecasting soilmoisture over time periods longer than a fewhours. Learned\nmodel parameters represent the physically based unsaturated hydrological redistribution processes of gravity and suction. We validate our models using soil moisture and rainfall time series data collected from a steep gradient, post-wildfire site in southern California. Data analysis is complicated by rapid landscape change observed in steep, burned hillslopes in response to even small to moderate rain events. The proposed NAR and AEAR models are, in forecasting experiments, shown to be competitive with several established and state-of-the-art baselines. The AEAR model fits the data well for three distinct soil textures at variable depths below the ground surface (5, 15, and 30 cm). Similar robust results are demonstrated in controlled, laboratory-based experiments. Our AEAR model includes readily interpretable hydrologic parameters and provides more accurate forecasts than existing models for time horizons of 10–24 h. Such extended periods of warning for natural disasters, such as floods and landslides, provide actionable knowledge to reduce loss of life and property.","language":"English","publisher":"Springer","doi":"10.1007/s41060-022-00347-8","usgsCitation":"Basak, A., Schmidt, K.M., and Mengshoel, O., 2023, From data to interpretable models: Machine learning for soil moisture forecasting: International Journal of Data Science and Analytics, v. 15, p. 9-32, https://doi.org/10.1007/s41060-022-00347-8.","productDescription":"24 p.","startPage":"9","endPage":"32","ipdsId":"IP-073246","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":445452,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s41060-022-00347-8","text":"Publisher Index Page"},{"id":435577,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CZB0Z7","text":"USGS data release","linkHelpText":"Field measurements of rainfall and soil moisture data used to support understanding of infiltration and runoff following the 2007 Canyon Fire, Malibu, CA, USA"},{"id":406219,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2022-08-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Basak, Aniruddha","contributorId":156329,"corporation":false,"usgs":false,"family":"Basak","given":"Aniruddha","email":"","affiliations":[{"id":20319,"text":"Carnegie Mellon University, Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":850823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mengshoel, Ole","contributorId":156331,"corporation":false,"usgs":false,"family":"Mengshoel","given":"Ole","email":"","affiliations":[{"id":20319,"text":"Carnegie Mellon University, Silicon Valley","active":true,"usgs":false}],"preferred":false,"id":850825,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}