We present a geostatistics-based stochastic salinity estimation framework for the Montebello Oil Field that capitalizes on available total dissolved solids (TDS) data from groundwater samples as well as electrical resistivity (ER) data from borehole logging. Data from TDS samples (n = 4924) was coded into an indicator framework based on falling below four selected thresholds (500, 1000, 3000, and 10,000 mg/L). Collocated TDS-ER data from the surrounding groundwater basin were then employed to produce a kernel density estimator to establish conditional probabilities for ER data (n = 8 boreholes) falling below the selected TDS thresholds within the Montebello Oil Field area. Directional variograms were estimated from these indicator coded data, and 500 TDS realizations from conditional indicator simulation were generated for the subsurface region above the Montebello Oil Field reservoir. Simulations were summarized as 3D maps of median TDS, most likely salinity class, and probability for exceeding each of the specified TDS thresholds. Results suggested TDS was below 500 mg/L in most of the study area, with a trend toward higher values (500 to 1000 mg/L) to the southwest; consistent with the average regional groundwater flow direction. Discrete localized zones of TDS greater than 1000 mg/L were observed, with one of these zones in the greater than 10,000 mg/L range; however, these areas were not prevalent. The probabilistic approach used here is adaptable and is readily modified to include additional data and types and can be employed in time-lapse salinity modeling through Bayesian updating.
Hybridization is a natural process at species-range boundaries that may variably promote the speciation process or break down species barriers but minimally will influence management outcomes of distinct populations. White-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) have broad and overlapping distributions in North America and a recognized capacity for interspecific hybridization. In response to contemporary environmental change to any of one or multiple still-unknown factors, mule deer range is contracting westward accompanied by a westward expansion of white-tailed deer, leading to increasing interactions, opportunities for gene flow, and associated conservation implications. To quantify genetic diversity, phylogenomic structure, and dynamics of hybridization in sympatric populations of white-tailed and mule deer, we used mitochondrial cytochrome b data coupled with SNP loci discovered with double-digest restriction site-associated DNA sequencing. We recovered 25,018 SNPs across 92 deer samples from both species, collected from two regions of western Kansas. Eight individuals with unambiguous external morphology representing both species were of hybrid origin (8.7%), and represented the product of multi-generational backcrossing. Mitochondrial data showed both ancient and recent directional discordance with morphological species assignments, reflecting a legacy of mule deer males mating with white-tailed deer females. Mule deer had lower genetic diversity than white-tailed deer, and both mitochondrial and nuclear data suggest contemporary mule deer effective population decline. Landscape genetic analyses show relative isolation between the two study regions for white-tailed deer, but greater connectivity among mule deer, with predominant movement from north to south. Collectively, our results suggest a long history of gene flow between these species in the Great Plains and hint at evolutionary processes that purge incompatible functional genomic elements as a result of hybridization. Surviving hybrids evidently may be reproductive, but with unknown consequences for the future integrity of these species, population trajectories, or relative susceptibility to emerging pathogens.
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\"}}]}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Combe, Fraser J.","contributorId":288530,"corporation":false,"usgs":false,"family":"Combe","given":"Fraser","email":"","middleInitial":"J.","affiliations":[{"id":33062,"text":"Division of Biology, Kansas State University","active":true,"usgs":false}],"preferred":false,"id":838057,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaster, Levi","contributorId":288531,"corporation":false,"usgs":false,"family":"Jaster","given":"Levi","email":"","affiliations":[{"id":61790,"text":"Kansas Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":838058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ricketts, Andrew","contributorId":288532,"corporation":false,"usgs":false,"family":"Ricketts","given":"Andrew","email":"","affiliations":[{"id":61791,"text":"Wildlife and Outdoor Enterprise Management, Department of Horticulture and Natural Sciences","active":true,"usgs":false}],"preferred":false,"id":838059,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":838056,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hope, Andrew G.","contributorId":288533,"corporation":false,"usgs":false,"family":"Hope","given":"Andrew G.","affiliations":[{"id":33062,"text":"Division of Biology, Kansas State University","active":true,"usgs":false}],"preferred":false,"id":838060,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229712,"text":"70229712 - 2022 - Warming conditions boost reproductive output for a northern gopher tortoise population","interactions":[],"lastModifiedDate":"2022-03-16T15:47:19.149065","indexId":"70229712","displayToPublicDate":"2021-12-02T11:45:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Warming conditions boost reproductive output for a northern gopher tortoise population","docAbstract":"The effects of climate change on at-risk species will depend on how life history processes respond to climate and whether the seasonal timing of local climate changes overlaps with species-specific windows of climate sensitivity. For long-lived, iteroparous species like gopher tortoises Gopherus polyphemus, climate likely has a greater influence on reproduction than on adult survival. Our objective was to estimate the timing, magnitude, and direction of climate-driven effects on gopher tortoise reproductive output using a 25 yr dataset collected in southeastern Georgia, USA, near the northern edge of the species’ range. We assessed the timing of climate effects on reproductive output (both probability of reproduction and clutch size) by fitting models with climate covariates (maximum temperature, precipitation, and temperature range) summarized at all possible time intervals (in 1 mo increments) within the 24 mo period prior to the summer census date. We then fit a final model of reproductive output as a function of the identified climate variables and time windows using a Bayesian mixture model. Probability of reproduction was positively correlated with the prior year’s April-May maximum temperature, and clutch size was positively correlated with the prior year’s June maximum temperature. April-May and June maximum temperatures have increased over the past 3 decades at the study site, which likely led to an increase in clutch size of approximately 1 egg (15% increase over a mean of 6.5 eggs). However, the net effect of climate change on gopher tortoise population dynamics will depend on whether there are opposing or reinforcing climate responses for other demographic rates.
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These water bodies provide aesthetic, cultural, and ecosystem services to surrounding wildlife and human communities. Lakes are warming, resulting in the loss of many native fish. In order to manage economically valuable fisheries and other ecosystem services provided by lakes, it is important for managers to have access to accurate estimates of water temperature to better understand past change and to plan for potential future further warming. These data are invaluable for making decisions such as whether to continue stocking plans as usual in certain lakes or how to set specific harvest limits. 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Dakota\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854190,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237342,"text":"70237342 - 2022 - Physics-guided machine learning from simulation data: An application in modeling lake and river systems","interactions":[],"lastModifiedDate":"2022-10-11T16:20:24.97395","indexId":"70237342","displayToPublicDate":"2021-12-01T11:12:09","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Physics-guided machine learning from simulation data: An application in modeling lake and river systems","docAbstract":"This paper proposes a new physics-guided machine learning approach that incorporates the scientific knowledge in physics-based models into machine learning models. Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. Although they are built based on general physical laws that govern the relations from input to output variables, these models often produce biased simulations due to inaccurate parameterizations or approximations used to represent the true physics. In this paper, we aim to build a new data-driven framework to monitor dynamical systems by extracting general scientific knowledge embodied in simulation data generated by the physics-based model. To handle the bias in simulation data caused by imperfect parameterization, we propose to extract general physical relations jointly from multiple sets of simulations generated by a physics-based model under different physical parameters. In particular, we develop a spatio-temporal network architecture that uses its gating variables to capture the variation of physical parameters. We initialize this model using a pre-training strategy that helps discover common physical patterns shared by different sets of simulation data. Then we fine-tune it using limited observation data via a contrastive learning process. By leveraging the complementary strength of machine learning and domain knowledge, our method has been shown to produce accurate predictions, use less training samples and generalize to out-of-sample scenarios. We further show that the method can provide insights about the variation of physical parameters over space and time in two domain applications: predicting temperature in streams and predicting temperature in lakes.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"IEEE International Conference on Data Mining","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"IEEE International Conference on Data Mining","conferenceDate":"December 7-10, 2021","conferenceLocation":"Auckland, New Zealand","language":"English","publisher":"Institute of Electrical and Electronics Engineers","doi":"10.1109/ICDM51629.2021.00037","usgsCitation":"Jia, X., Xie, Y., Li, S., Chen, S., Zwart, J.A., Sadler, J.M., Appling, A.P., Oliver, S.K., and Read, J., 2022, Physics-guided machine learning from simulation data: An application in modeling lake and river systems, in IEEE International Conference on Data Mining, Auckland, New Zealand, December 7-10, 2021, p. 270-279, https://doi.org/10.1109/ICDM51629.2021.00037.","productDescription":"10 p.","startPage":"270","endPage":"279","ipdsId":"IP-126776","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":408164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":854197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Sheng","contributorId":297449,"corporation":false,"usgs":false,"family":"Li","given":"Sheng","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":854198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":854199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854202,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":854201,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854203,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854204,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70236035,"text":"70236035 - 2022 - Data resources for NGA-subduction project","interactions":[],"lastModifiedDate":"2024-02-28T16:15:16.891191","indexId":"70236035","displayToPublicDate":"2021-12-01T10:09:11","publicationYear":"2022","noYear":false,"publicationType":{"id":26,"text":"Extramural-Authored Publication Paper"},"publicationSubtype":{"id":31,"text":"Extramural-Authored Publication"},"title":"Data resources for NGA-subduction project","docAbstract":"A relational database was developed over a five-year period to support ground motion model (GMM) development for the Next Generation Attenuation-Subduction (NGA-Sub) project. The relational database has components that interact according to a database schema, including a source and path component used to describe attributes of seismic sources in global subduction regions and to compute source-to-site distances, a site component that describes attributes of sites where recordings have been made, and a ground motion component.
The source component of the database has information for 1880 earthquakes, mainly from the following regions: the Pacific Northwest region of North America, Alaska and the Aleutian Islands, Japan, Taiwan, New Zealand, South America, Central America, and Mexico. Of the 1880 earthquakes, 88 have finite fault models (FFMs) from the literature that were systematically reviewed, distilled to one more rectangular shapes, and trimmed according to procedures based on percentage of total slip. For earthquakes without FFMs, a simulation routine is used to represent finite fault effects required for distance calculations. This simulation routine was adjusted and made more uniform in its application than in prior NGA projects. All earthquakes are classified as interface, intraslab, shallow crustal, or outer rise, using uniform protocols developed for this project. All earthquakes are also assigned class designations adapted from a prior NGA project for active regions, that allows foreshock, mainshock, and aftershock events to be distinguished.
The site component of the database is described in a companion paper (Ahdi et al. 2020 [1]).
The ground motion component of the database consists of median – and maximum – horizontal component peak parameters (peak ground acceleration, PGA and peak ground velocity, PGV) and pseudo-spectral accelerations (PSa) at 111 oscillator periods and 11 damping ratios. Response spectra were also computed for the vertical component. Fourier amplitude spectra (FAS) and duration metrics were also computed. The ground motion recordings were obtained from collaborating organizations world-wide as uncorrected (Vol 1) digital recordings, that were corrected (componentspecific low – and high – pass filters and baseline correction, as needed) following Pacific Earthquake Engineering Research Center (PEER)/NGA protocols.
The relational database operates on each of these (and other) database components to dynamically draw relevant parameters into a single file, known as a flatfile, that is used by researchers engaged in GMM development. The flatfiles used in model development are being published with the NGA-Sub GMMs as products of the NGA-Sub project.
","conferenceTitle":"The 17th World Conference on Earthquake Engineering","conferenceDate":"September 13-18, 2020","conferenceLocation":"Sendai, Japan","language":"English","publisher":"Japan Association of Earthquake Engineering","usgsCitation":"Contreras, V., Mazzoni, S., Kishida, T., Ahdi, S., Darragh, R.B., Youngs, R., Chiou, B., Kuehn, N., Wooddell, K., Bozorgnia, Y., and Stewart, J.P., 2022, Data resources for NGA-subduction project, 12 p.","productDescription":"12 p.","ipdsId":"IP-130876","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":426071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426069,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wcee.nicee.org/wcee/seventeenth_conf_sendai_japan/"}],"noUsgsAuthors":true,"publicationStatus":"PW","contributors":{"authors":[{"text":"Contreras, V.","contributorId":295706,"corporation":false,"usgs":false,"family":"Contreras","given":"V.","email":"","affiliations":[{"id":63911,"text":"University of California, Los Angeles, USA","active":true,"usgs":false}],"preferred":false,"id":849767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mazzoni, S.","contributorId":270337,"corporation":false,"usgs":false,"family":"Mazzoni","given":"S.","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":849765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kishida, T.","contributorId":203476,"corporation":false,"usgs":false,"family":"Kishida","given":"T.","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":849768,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahdi, S.K.","contributorId":334403,"corporation":false,"usgs":false,"family":"Ahdi","given":"S.K.","affiliations":[{"id":80128,"text":"Exponent Failure Analysis, Los Angeles, CA","active":true,"usgs":false}],"preferred":false,"id":849764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Darragh, Robert B.","contributorId":25188,"corporation":false,"usgs":false,"family":"Darragh","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":895558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Youngs, R.R.","contributorId":75312,"corporation":false,"usgs":true,"family":"Youngs","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":895559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chiou, B.S.J.","contributorId":74119,"corporation":false,"usgs":true,"family":"Chiou","given":"B.S.J.","email":"","affiliations":[],"preferred":false,"id":895560,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuehn, N.","contributorId":334404,"corporation":false,"usgs":false,"family":"Kuehn","given":"N.","affiliations":[],"preferred":false,"id":895561,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wooddell, Kathryn","contributorId":47674,"corporation":false,"usgs":false,"family":"Wooddell","given":"Kathryn","email":"","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":895562,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bozorgnia, Y.","contributorId":51427,"corporation":false,"usgs":true,"family":"Bozorgnia","given":"Y.","affiliations":[],"preferred":false,"id":895563,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":849773,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70226760,"text":"70226760 - 2022 - The impact of 3D finite‐fault information on ground‐motion forecasting for earthquake early warning","interactions":[],"lastModifiedDate":"2022-03-28T16:28:59.512213","indexId":"70226760","displayToPublicDate":"2021-11-30T06:33:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The impact of 3D finite‐fault information on ground‐motion forecasting for earthquake early warning","docAbstract":"We identify aspects of finite‐source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite‐fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D‐source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line‐source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D‐source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground‐motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.
Populations of Brook Trout Salvelinus fontinalis exhibit large variation in annual recruitment (abundance of young of the year [age 0]), which is likely a product of density-dependent and density-independent factors. Quantifying the importance of each of these mechanisms in regulating Brook Trout recruitment would be valuable to managers that are responsible for the conservation of this iconic species throughout its native range. We analyzed a time series of age-0 and adult Brook Trout density data collected from 10 streams in the Sinnemahoning Creek watershed, north-central Pennsylvania (2010–2019), using Bayesian hierarchical modeling to partition the density-dependent effects of adult density and the density-independent effects of elevated streamflow on Brook Trout recruitment. Multiple models were examined, and the top-ranked model showed that Brook Trout recruitment followed a Ricker stock–recruitment relationship, with annual recruitment negatively influenced by maximum streamflow during the spring season (March–April). This model will be useful in predicting future variation in Brook Trout recruitment under climate change scenarios in which the frequency and intensity of high-flow events are expected to increase.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10347","usgsCitation":"Sweka, J., and Wagner, T., 2022, Influence of seasonal extreme flows on Brook Trout recruitment: North American Journal of Fisheries Management, v. 151, no. 2, p. 231-244, https://doi.org/10.1002/tafs.10347.","productDescription":"14 p.","startPage":"231","endPage":"244","ipdsId":"IP-130483","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":397180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Sinnemahoning Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.64013671875,\n 41.22824901518529\n ],\n [\n -77.67333984375,\n 41.22824901518529\n ],\n [\n -77.67333984375,\n 41.96765920367816\n ],\n [\n -78.64013671875,\n 41.96765920367816\n ],\n [\n -78.64013671875,\n 41.22824901518529\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"151","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Sweka, John A.","contributorId":288581,"corporation":false,"usgs":false,"family":"Sweka","given":"John A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":838108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838107,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240333,"text":"70240333 - 2022 - Accuracy and precision of otolith-derived age Interpretations for known-age lake trout","interactions":[],"lastModifiedDate":"2023-02-06T13:21:49.565349","indexId":"70240333","displayToPublicDate":"2021-11-27T07:18:55","publicationYear":"2022","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":"Accuracy and precision of otolith-derived age Interpretations for known-age lake trout","docAbstract":"Catch-at-age data are used to inform important management decisions for recovering populations of Lake Trout Salvelinus namaycush. Age data for Lake Trout are commonly derived from interpretation of annual growth marks (annuli) on the fish’s otoliths. Due to the tendency for annuli to vary in appearance and the subjectivity that is inherent to any age interpretation method, it is important that the common sources of interpretation error be well understood for any aging method used to inform management plans. In this study, coded wire tags were used to establish true ages for 153 Lake Trout to measure the precision and accuracy of age interpretations made from transverse-sectioned otoliths and to identify sources of potential age interpretation error that researchers and managers may encounter when using this method. Precision of age interpretations, as measured by average coefficient of variation, ranged from 7.9% to 9.2%. Accuracy of age interpretations varied among readers, with exact matches ranging from 41.8% to 53.6% and accuracy within ±1 year ranging from 81.0% to 83.0%. Age interpretation errors were more likely to be overestimates of true age for Lake Trout under age 7 and underestimates for Lake Trout over age 13. However, only reader 1 exhibited significant systematic bias in their age interpretations. Poor clarity of the first annuli, growth checks resembling annuli, and faintness of narrow annuli near otolith margins in older fish were identified as likely sources of interpretation error in this study. A digital reference collection of known-age Lake Trout otoliths is provided as supplemental material in the online version of this article. This collection can be used for training new readers, measuring the accuracy of age interpretations, and monitoring for aging bias by anyone using otoliths to obtain age data for Lake Trout.
Bedrock river-gorge incision represents a fundamental landscape-shaping process, but a dearth of observational data at >10 yr timescales impedes understanding of gorge formation. I quantify 102 yr rates and processes of gorge incision using historical records, field observations, and topographic and image analysis of a human-caused bedrock meander cutoff along the North Fork Fortymile River in Alaska (USA). Miners cut off the meander in 1900 CE, abruptly lowering local base level by 6 m and forcing narrowing and steepening of the channel across a knickpoint that rapidly incised upstream. Tectonic quiescence, consistent rock erosivity, and low millennial erosion rates provide ideal boundary conditions for this 102 yr gorge-formation experiment. Initial fast knickpoint propagation (23 m/yr; 1900–1903 CE) slowed (4 m/yr; 1903–1981 CE) to diffusion (1981–2019 CE) as knickpoint slope decreased, yielding an ~350-m-long, 6-m-deep gorge within the pre–1900 CE channel. Today, diffusion dominates incision of a 500-m-long knickzone upstream of the gorge, where sediment transport likely limits ongoing adjustments to the anthropogenic cutoff. Results elucidate channel width, slope, discharge, and sediment dynamics consistent with a gradual transition from detachment- to transport-limited incision in fluvial adjustment to local base-level lowering.
Historical mine and mineral deposit datasets are routinely used to inform quantitative mineral assessment models, but they also can contain a wealth of supplementary qualitative information that is generally underutilized. We present a workflow that uses correspondence analysis, an exploratory tool commonly applied to multivariate abundance data, to better utilize qualitative data in these historical datasets. The workflow involves extraction of qualitative information on ore mineralogy from a mineral deposit database, attaches those data to a target geological feature, and analyzes the underlying data structure with correspondence analysis and hierarchical clustering. The output of correspondence analysis is inversely weighted to the relative frequency of ore minerals, and therefore rare mineral species (i.e., those with unusually low frequencies) can disproportionately contribute to the total variance of the dataset. We present a novel technique for aggregating frequencies of rare mineral species that minimizes this effect. We apply this workflow to evaluate how ore mineral assemblages in former and active mines vary in spatial relation to silicic calderas in the southwestern United States. The most common ore mineral associations observed spatially and genetically associated to calderas include those related to polymetallic, base metal-rich systems and epithermal Au–Ag systems. Three other groups of mineralized calderas were identified, including: (1) Hg–Sb mineralized calderas in the northern Great Basin and western Nevada volcanic field; (2) calderas associated with elevated abundances of Mn oxides/hydroxides, fluorite, and Be-minerals, mostly in eastern Utah and New Mexico; and (3) calderas with numerous U ± F deposits, which are located in central Colorado, the eastern Great Basin and in northern Nevada. The latter three groups are associated with economically significant critical mineral resources, including the Li resources of the McDermitt complex and Be associated with the Spor Mountain on the margin of the Thomas caldera complex. We conclude that correspondence analysis is a promising technique that can enhance data exploration of the qualitative information held within mineral deposit datasets. Consequently, it could have numerous applications for mineral potential mapping, resource assessment projects, and characterization of mineral systems.
Wave energy converters (WECs) will have to be arranged into arrays of many devices to extract commercially viable amounts of energy. To understand the potential coastal impacts of WEC arrays, most research to date has relied on wave-averaged models given their computational efficiency. However, it is unknown how accurate wave-averaged model predictions are given a lack of validation data and their inherent simplifications of various hydrodynamic processes (e.g., diffraction). This paper compares the predictions of coastal wave farm impacts from a coupled wave-averaged and flow model (Delft3D-SNL-SWAN), to a wave-resolving wave-flow model (SWASH) that intrinsically accounts for more of the relevant physics. Model predictions were compared using an idealized coastal bathymetry over a range of wave conditions and wave farm geometries. Both models predicted the largest impacts (changes to the nearshore hydrodynamics) for large and dense wave farms located close to the shore (1 km) and the smallest impacts for the small and widely spaced farm at a greater offshore distance (3 km). However, the wave-resolving model generally predicted somewhat larger impacts (i.e., changes to the nearshore wave heights, mean velocities and mean water levels). We also found that coupling the wave-averaged model to a flow model resulted in more realistic downstream predictions than the stand-alone wave-averaged model.
Estimating abundance of migrating fishes is challenging. While sonars can be deployed continuously, improper assumptions about unidirectional migration and complete spatial coverage can lead to inaccurate estimates. To address these challenges, we present a framework for combining fixed-location count data from a dual-frequency identification sonar (DIDSON) with movement data from acoustic telemetry to estimate spawning run abundance of lake sturgeon (Acipenser fulvescens). Acoustic telemetry data were used to estimate the probability of observing a lake sturgeon on the DIDSON and to determine the probability that a lake sturgeon passing the DIDSON site had passed the site previously during the season. Combining probabilities with DIDSON counts, using a Bayesian integrated model, we estimated the following abundances: 99 (42–215 credible interval, CI) in 2017, 131 (82–248 CI) in 2018, and 92 (47–184 CI) in 2019. Adding movement data generated better inferences on count data by incorporating fish behavior (e.g., multiple migrations in a single season) and its uncertainty into abundance estimates. This framework can be applied to count and movement data to estimate abundance of spawning runs of other migratory fishes in riverine systems.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0140","usgsCitation":"Izzo, L., Zydlewski, G.B., and Parrish, D.L., 2022, Combining fixed-location count data and movement data to estimate abundance of a lake sturgeon spawning run: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 6, p. 925-935, https://doi.org/10.1139/cjfas-2021-0140.","productDescription":"11 p.","startPage":"925","endPage":"935","ipdsId":"IP-127748","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":449533,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/51632","text":"External Repository"},{"id":397240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Winooski River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.28910827636717,\n 44.3768766587829\n ],\n [\n -72.93342590332031,\n 44.3768766587829\n ],\n [\n -72.93342590332031,\n 44.54448397425684\n ],\n [\n -73.28910827636717,\n 44.54448397425684\n ],\n [\n -73.28910827636717,\n 44.3768766587829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Izzo, Lisa K.","contributorId":288673,"corporation":false,"usgs":false,"family":"Izzo","given":"Lisa K.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":838211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zydlewski, Gayle Barbin","contributorId":288674,"corporation":false,"usgs":false,"family":"Zydlewski","given":"Gayle","email":"","middleInitial":"Barbin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":838212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":838210,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231551,"text":"70231551 - 2022 - Aquatic vegetation dynamics in the Upper Mississippi River over 2 decades spanning vegetation recovery","interactions":[],"lastModifiedDate":"2022-05-13T11:47:38.827389","indexId":"70231551","displayToPublicDate":"2021-11-18T06:43:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Aquatic vegetation dynamics in the Upper Mississippi River over 2 decades spanning vegetation recovery","docAbstract":"Macrophytes have recovered in rivers across the world, but long-term data and studies are lacking regarding community assembly and diversity changes coincident with macrophyte recovery. We investigated patterns of aquatic vegetation species composition and diversity in thousands of sites in the Upper Mississippi River, USA, spanning 21 y of monitoring and a period of vegetation recovery. We analyzed site-level compositional dissimilarity and environmental associations using non-metric multidimensional scaling, compared stability of lake-level assemblages over time with convex hulls, and assessed shared trends in assemblage dissimilarity at the pool scale using dynamic factor analysis. Site-level differences in aquatic vegetation assemblage structure were associated with water depth and substrate, and a gradient of species abundance and diversity was apparent. A common trend in assemblage dissimilarity over time and across contiguous floodplain lakes indicate that assemblage composition changed and diversity increased with considerable synchrony within the past 21 y. Shared trends across the 400-km study reach are indicative of 1 or more widespread, common drivers; however, neither hydrologic extremes nor turbidity explained vegetation assemblage patterns. Following several years of strong changes in composition and increased diversity, the vegetation assemblage displayed signs of increasing stability in some pools but not others. Further research is needed to identify drivers and mechanisms of aquatic vegetation assemblage expansion, assembly, and resilience, all of which will be applicable to the recovery of aquatic vegetation in floodplain systems worldwide.
During rock friction experiments at large displacement, room temperature and humidity, and following a hold test, the fracture energy increases approximately as the square of the logarithm of hold duration. While it's been long known that failure strength increases with log hold time, here the slip weakening distance, dh, also increases. The weakening distance increase is large, hundreds of percent change over a few thousand seconds. The initial bare surface and simulated fault gouge experiments were conducted in rotary shear at 25 MPa normal stress, 21 MPa confining stress and at displacements greater than 100 mm. In contrast, initially bare surface experiments at 5 MPa normal stress, unconfined at displacements less than 10 mm show effectively no change in dh. We attribute the difference to the presence of an appreciable shear zone that develops due to wear over significant displacements, confined at elevated normal stress. Prior published studies of sheared simulated fault gouge at short displacement show both acknowledged and unacknowledged increases in dh that may relate to our observations. Since natural faults have well-developed shear zones, the observations have more direct relevance to earthquake nucleation than prior laboratory studies that use short displacement data and focus on frictional strength recovery alone. However, the physics underlying this increase in weakening distance are not known; candidates are compaction (Nakatani, 1998) and delocalization (Sleep et al., 2000). Additional caveats are that these are room temperature and humidity experiments, at a single normal stress that have not yet been reproduced in other laboratories.
The East Rift Zone (ERZ) of Kīlauea Volcano, Hawai'i, represents one of the most volcanically active regions in the world. The 2007 Father's Day (FD) dike intrusion, eruption, and accompanying slow-slip event (SSE) has been previously modeled using geodetic data to constrain the geometry of the intrusion and the timing and magnitude of the SSE. Here, we perform inversions of three interferometric synthetic aperture radar (InSAR) datasets and a new intensity offset tracking dataset to assess the effect of integrating intensity cross-correlation offsets into inversion problems and explore additional potential models for the intrusion geometry of the FD event based on this additional data. The overall lowest misfit single Okada model for all datasets opens 2.3 m, strikes 73 degrees while dipping sub-vertically at 83 degrees, and extends approximately 2.9 km to the ENE and 2.4 km downdip. The differences are minor between complex en-echelon distributed Okada and decollement model of (Montgomery-Brown et al., 2010) or 3D-MBEM breaching models including multiple surface breaches and free-slipping decollement movement. Finally, we examine the static Coulomb stress changes for the proposed decollement fault created by our preferred model and a representative model of deep rift opening and find that deep rift zones dilation, not shallow ERZ intrusions, are likely modulating slip on the decollement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107425","usgsCitation":"Leeburn, J., Wauthier, C., Montgomery-Brown, E.K., and Gonzalez-Santana, J., 2022, New insights on faulting and intrusion processes during the June 2007, East Rift Zone eruption of Kilauea volcano, Hawai'i: Journal of Volcanology and Geothermal Research, v. 421, 107425, 14 p., https://doi.org/10.1016/j.jvolgeores.2021.107425.","productDescription":"107425, 14 p.","ipdsId":"IP-125424","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488262,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107425","text":"Publisher Index Page"},{"id":484584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2908512348302,\n 19.41341967491155\n ],\n [\n -155.2908512348302,\n 19.401793724963014\n ],\n [\n -155.27525765813795,\n 19.401793724963014\n ],\n [\n -155.27525765813795,\n 19.41341967491155\n ],\n [\n -155.2908512348302,\n 19.41341967491155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"421","noUsgsAuthors":false,"publicationDate":"2021-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Leeburn, J.","contributorId":353406,"corporation":false,"usgs":false,"family":"Leeburn","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wauthier, C.","contributorId":353409,"corporation":false,"usgs":false,"family":"Wauthier","given":"C.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":933491,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gonzalez-Santana, J.","contributorId":353412,"corporation":false,"usgs":false,"family":"Gonzalez-Santana","given":"J.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":933492,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226477,"text":"70226477 - 2022 - Local variations in broadband sensor installations: Orientations, sensitivities, and noise levels","interactions":[],"lastModifiedDate":"2022-01-25T17:16:42.963846","indexId":"70226477","displayToPublicDate":"2021-11-11T07:23:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Local variations in broadband sensor installations: Orientations, sensitivities, and noise levels","docAbstract":"As seismologists continue to place more stringent demands on data quality, accurately described metadata are becoming increasingly important. In order to better constrain the orientation and sensitivities of seismometers deployed in U.S. Geological Survey networks, the Albuquerque Seismological Laboratory (ASL) has recently begun identifying true north with a fiber optic gyroscope (FOG) and has developed methodologies to constrain mid-band, vertical component sensitivity levels to less than 1% in a controlled environment. However, questions remain regarding the accuracy of this new alignment technique as well as if instrument sensitivities and background noise levels are stable when the seismometers are installed in different environmental settings. In this study, we examine the stability and repeatability of these parameters by reinstalling two high-quality broadband seismometers (Streckeisen STS-2.5 and Nanometrics T-360 Global Seismographic Network (GSN) version) at different locations around the ASL and comparing them to each other and a reference STS-6 seismometer that stayed stationary for the duration of the experiment. We find that even in different environmental conditions, the sensitivities of the two broadband seismometers stayed stable to within 0.1% and that orientations attained using the FOG are generally accurate to within a degree. However, one install was off by 5° due to a mistake made by the installation team. These results indicate that while technology and methodologies are now in place to calibrate and orient a seismometer to within 1°, human error both during the installation and while producing the metadata is often a limiting factor. Finally, we find that background noise levels at short periods (0.1–1 s) become noisier when the sensors are emplaced in unconsolidated materials, whereas the noise levels at long periods (30–100 s) are not sensitive to local geological structure on the vertical components.
Clock accuracy is a basic parameter of any seismic station and has become increasingly important for seismology as the community seeks to refine structures and dynamic processes of the Earth. In this study, we measure the arrival time differences of moderate repeating earthquakes with magnitude 5.0–5.9 in the time range of 1991–2017 at the same seismic stations by cross‐correlating their highly similar waveforms and thereby identify potential timing errors from the outliers of the measurements. The method has very high precision of about 10 ms and shows great potential to be used for routine inspection of the timing accuracy of historical and future digital seismic data. Here, we report 5131 probable cases of timing errors from 451 global and regional stations available from the Incorporated Research Institutions for Seismology Data Management Center, ranging from several tens of milliseconds to over 10 s. Clock accuracy seems to be a prevailing problem in permanent stations with long‐running histories. Although most of the timing errors have already been tagged with low timing quality, there are quite a few exceptions, which call for greater attention from network operators and the seismological community. In addition, seismic studies, especially those on temporal changes of the Earth’s media from absolute arrival times, should be careful to avoid misinterpreting timing errors as temporal changes, which is indeed a problem in some previous studies of the Earth’s inner core boundary.
Environmental (e)DNA methods have enabled rapid, sensitive and specific inferences of taxa presence throughout diverse fields of ecological study. However, use of eDNA results for decision-making has been impeded by uncertainties associated with false positive tests putatively caused by sporadic or systemic contamination. Sporadic contamination is a process that is inconsistent across samples and systemic contamination occurs consistently over a group of samples. Here, we used empirical data and laboratory experiments to (i) estimate the sporadic contamination rate for each stage of a common, targeted eDNA workflow employing best practice quality control measures under simulated conditions of rare and common target DNA presence, (ii) determine the rate at which negative controls (i.e., “blanks”) detect varying concentrations of systemic contamination, and (iii) estimate the effort that would be required to consistently detect sporadic and systemic contamination. Sporadic contamination rates were very low across all eDNA workflow steps, and, therefore, an intractably high number of negative controls (>100) would be required to determine occurrence of sporadic contamination with any certainty. Contrarily, detection of intentionally introduced systemic contamination was more consistent; therefore, very few negative controls (<5) would be needed to consistently alert to systemic contamination. These results have considerable implications to eDNA study design when resources for sample analyses are constrained.
We thank David Wald (Wald, 2021; henceforth, W21) for his interest in our recent article (Hough and Martin, 2021; henceforth, HM21). Although different perspectives are vital in science, we are concerned that W21 misrepresents HM21 as an oblique criticism of the U.S. Geological Survey “Did You Feel It?” (DYFI) system, calling for HM21 to be retracted. Readers who are interested in the issues raised by HM21 and the statements made by us therein are referred to that article. In this brief reply, we respond to specific accusations made by W21 and return to the focus of HM21, calling attention to the extent to which macroseismic data sets and inferences drawn from them can be shaped by a lack of representation among individuals whose observations are available to science. HM21 never questioned the benefits of the community science DYFI project to science. HM21 noted, however, and we reiterate here, that community science also potentially benefits the community. Whether or not it matters for science, if participation in community science projects is unrepresentative across socioeconomic groups, it underscores the need for the scientific community to be proactive in its efforts to reach out to groups that have been underserved by current outreach and education programs. We appreciate this opportunity to continue the important conversation about representation.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210142","usgsCitation":"Hough, S.E., and Martin, S.S., 2022, Reply to “comment on ‘which earthquake accounts matter?’ by Susan E. Hough and Stacey S. Martin” by David J. Wald: Seismological Research Letters, v. 93, no. 1, p. 506-511, https://doi.org/10.1785/0220210142.","productDescription":"6 p.","startPage":"506","endPage":"511","ipdsId":"IP-130640","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Stacey S.","contributorId":140021,"corporation":false,"usgs":false,"family":"Martin","given":"Stacey","email":"","middleInitial":"S.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":927676,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230085,"text":"70230085 - 2022 - Comment on “Which earthquake accounts matter” by Susan E. Hough and Stacey S. Martin","interactions":[],"lastModifiedDate":"2022-03-28T13:14:00.30453","indexId":"70230085","displayToPublicDate":"2021-11-03T08:10:07","publicationYear":"2022","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":"Comment on “Which earthquake accounts matter” by Susan E. Hough and Stacey S. Martin","docAbstract":"In their analysis of the U.S. Geological Survey’s (USGS) “Did You Feel It?” (DYFI) data Hough and Martin (2021) claim, among other assertions, that the following:
Socioeconomic and geopolitical factors can introduce biases in the USGS’ characterization of earthquakes and their effects, especially if online data collection systems are not designed to be broadly accessible;
These biases can, in turn, potentially cascade in myriad ways, potentially shaping our understanding of an earthquake’s impact and the characterization of seismic hazard; and
Caution should be urged when relying on data from the DYFI system to characterize the distribution of shaking from large earthquakes in India and other parts of the world (outside of the United States).
Claims of inequity in access, systematic data biases, or urging caution in the usage of data from critical governmental earthquake information systems should not be made, nor taken, lightly. Several assertions made by Hough and Martin (hereafter, H&M) about the nature of DYFI contributors—and the data they provide—leave a false narrative concerning DYFI system accessibility and quality that H&M have not adequately substantiated.
I describe several shortcomings of H&M’s demographic statistics and methodology, focusing on four main concerns. First, DYFI has revolutionized and greatly facilitated access to reporting intensities, in contrast to H&M claims to the contrary. Second, because DYFI does not directly collect demographic data other than the observer’s location, any demographic analyses require extraordinary inferences, well outside the normal bounds of sociodemographic analyses. Third, independent of accessibility and the geographic distribution of contributions from the public, the macroseismic data collected are nonetheless representative of the shaking and impact at each location, of quality, rapid, and thus extremely useful. Lastly, H&M fail to cite critical and pertinent prior, highly relevant scholarly studies, and as such, they misrepresent the novelty of their own work as well as miss key practical matters detailed in those prior studies. Prior to rebutting what H&M claim DYFI does not do, I will remind the reader the ways in which DYFI excels.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210072","usgsCitation":"Wald, D.J., 2022, Comment on “Which earthquake accounts matter” by Susan E. Hough and Stacey S. Martin: Seismological Research Letters, v. 93, no. 1, p. 500-505, https://doi.org/10.1785/0220210072.","productDescription":"6 p.","startPage":"500","endPage":"505","ipdsId":"IP-127085","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":397684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":838970,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70225740,"text":"70225740 - 2022 - Techniques to improve ecological interpretability of black box machine learning models","interactions":[],"lastModifiedDate":"2023-03-24T16:57:11.274452","indexId":"70225740","displayToPublicDate":"2021-10-28T08:45:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Techniques to improve ecological interpretability of black box machine learning models","docAbstract":"Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s
Optimal design procedures provide a framework to leverage the learning generated by ecological models to flexibly and efficiently deploy future monitoring efforts. At the same time, Bayesian hierarchical models have become widespread in ecology and offer a rich set of tools for ecological learning and inference. However, coupling these methods with an optimal design framework can become computationally intractable. Recursive Bayesian computation offers a way to substantially reduce this computational burden, making optimal design accessible for modern Bayesian ecological models. We demonstrate the application of so-called prior-proposal recursive Bayes to optimal design using a simulated data binary regression and the real-world example of monitoring and modeling sea otters in Glacier Bay, Alaska. These examples highlight the computational gains offered by recursive Bayesian methods and the tighter fusion of monitoring and science that those computational gains enable.