Worldwide, many productive rivers are dam-regulated and rely on flow management strategies that must balance support of ecological processes with human water use. One component of evaluating this balance is to understand ecological consequences of alternative flow management strategies, which has often been accomplished by coupling population dynamics models with models that relate streamflow to habitat availability and quality. Numerous methods assign habitat availability to locations within a river basin: These include fine-scale field-measured values that are extrapolated to other locations within the basin having similar physical characteristics or equation-driven values created by functions of model-predicted values of physical characteristics. The array of options for creating habitat models is evolving rapidly as high-resolution remote-sensing data becomes more accessible and computational capacity improves. Our objective was to identify trade-offs among approaches that assign habitat relationships to large rivers and to create a decision support tool to supplement choices of extent and granularity. Using a selection of case studies that represent a breadth of scales and diverse trade-offs, we demonstrate the need for a transparent process of data evaluation and assessment to determine the appropriate fit for model scope or context that best supports management needs and recognize sources of uncertainty. The structured approach proposed here aims at improving future model development and refine population dynamics models that inform the management of rivers.
Agent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (autonomous units, such as wildlife or people); agent characteristics, decision-making, adaptive behavior, and mobility; and agent-environment interactions. STSMs are flexible and intuitive stochastic landscape models that can track scenarios and integrate diverse data. Both can be run spatially and track metrics of management success.
Due to the complementarity of these approaches, we sought to couple them through a dynamic linkage and demonstrate the relevance of this advancement for modeling landscape processes and patterns.
We developed analytical techniques and software tools to couple these modeling approaches using NetLogo, R, and the ST-Sim package for SyncroSim. We demonstrated the capabilities and value of this coupled approach through a proof-of-concept case study of bison-vegetation interactions in Badlands National Park.
The coupled ABM-STSM: (1) streamlined handling of model inputs and outputs; (2) allowed representation of processes at multiple temporal scales; (3) minimized assumptions; and (4) generated spatial and temporal patterns that better reflected agent-environment interactions.
These developments constitute a new approach for representing agent-environment feedbacks; modelers can now use output from an ABM to dictate landscape changes within an STSM that in turn influence agents. This facilitates experimentation across domains (agent and environment) and creation of more realistic and management-relevant projections, and opens new opportunities for communicating models and linking to other methods.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01282-y","usgsCitation":"Miller, B.W., and Frid, L., 2022, A new approach for representing agent-environment feedbacks: Coupled agent-based and state-and-transition simulation models: Landscape Ecology, v. 37, p. 43-58, https://doi.org/10.1007/s10980-021-01282-y.","productDescription":"16 p.","startPage":"43","endPage":"58","ipdsId":"IP-119604","costCenters":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":436047,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R98PPB","text":"USGS data release","linkHelpText":"Coupled Agent-Based and State-and-Transition Simulation Model"},{"id":390809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2021-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":825579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frid, Leonardo","contributorId":196604,"corporation":false,"usgs":false,"family":"Frid","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":825580,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230025,"text":"70230025 - 2022 - Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests","interactions":[],"lastModifiedDate":"2022-03-25T13:43:11.24047","indexId":"70230025","displayToPublicDate":"2021-10-15T10:55:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests","docAbstract":"Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously account for the effects of climate, tree size, and other drivers on individual growth, which has limited the potential to use tree rings to understand forest productivity, its climate sensitivity, and its global change responses. Here, we develop and apply a new method to simultaneously model non-linear effects of primary climate drivers, reconstructed tree diameter (DBH), and year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree’s growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥ 3-month seasonal windows) and negative to temperature (usually over ≤ 3-month seasonal windows), with both included in 78% of top models, and with non-linear responses prevalent (63% of relationships). Climate sensitivity commonly varied with DBH (44% of cases tested). Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently peaked at intermediate DBH and declined thereafter. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15934","usgsCitation":"Anderson-Teixeira, K.J., Herrmann, V., Rollinson, C., Gonzales, B., Gonzalez-Akre, E.B., Pederson, N., Alexander, M.R., Allen, C., Alfaro-Sanchez, R., Awada, T., Baltzer, J.L., Baker, P.J., Birch, J.D., Bunyavejchewin, S., Cherubini, P., Davies, S.J., Dow, C., Helcoski, R., Kaspar, J., Lutz, J.A., Margolis, E.Q., Maxwell, J., McMahon, S.M., Piponiot, C., Russo, S.E., Šamonil, P., Sniderhan, A.E., Tepley, A.J., Vasickova, I., Vlam, M., and Zuidema, P.A., 2022, Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests: Global Change Biology, v. 28, p. 245-266, https://doi.org/10.1111/gcb.15934.","productDescription":"21 p.","startPage":"245","endPage":"266","ipdsId":"IP-130293","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":449625,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.15934","text":"External Repository"},{"id":397528,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Czech Republic, Panama, Thailand, United States","state":"Indiana, Massachusetts, New Mexico, Nebraska, Utah, 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These surveys often contain spatial–temporal dependencies that can greatly influence conclusions drawn from analyses. Pygmy whitefish (PWF, Prosopium coulterii) populations in Lake Superior were recently assessed as Threatened by the Committee on the Status of Endangered Species in Canada, which motivated a thorough analysis of available data to improve our understanding of its population status. The US Geological Survey conducts annual bottom trawl surveys in Lake Superior that commonly capture PWF. We used these data (1989–2018) to model temporal trends in PWF biomass density and make lake-wide population projections. We used a Bayesian approach, integrated nested Laplace approximation (INLA), and compared the impact of including different random structures on model fit. Inclusion of spatial structure improved model fit and conclusions differed from models omitting random effects. 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Lee","given":"Adam","email":"","middleInitial":"S","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":866881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":866882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koops, Marten A.","contributorId":16715,"corporation":false,"usgs":false,"family":"Koops","given":"Marten","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":866883,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225701,"text":"70225701 - 2022 - Predicting regional fluoride concentrations at public and domestic supply depths in basin-fill aquifers of the western United States using a random forest model","interactions":[],"lastModifiedDate":"2021-12-10T17:13:59.830723","indexId":"70225701","displayToPublicDate":"2021-10-14T07:37:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Predicting regional fluoride concentrations at public and domestic supply depths in basin-fill aquifers of the western United States using a random forest model","docAbstract":"A random forest regression (RFR) model was applied to over 12,000 wells with measured fluoride (F) concentrations in untreated groundwater to predict F concentrations at depths used for domestic and public supply in basin-fill aquifers of the western United States. The model relied on twenty-two regional-scale environmental and surficial predictor variables selected to represent factors known to control F concentrations in groundwater. The testing model fit R2 and RMSE were 0.52 and 0.78 mg/L. Comparisons of measured to predicted proportions of four F-concentrations categories (<0.7 mg/L, 0.7–2 mg/L, >2 mg/L – 4 mg/L, and > 4 mg/L) indicate that the model performed well at making regional-scale predictions. Differences between measured and predicted proportions indicate underprediction of measured F at values by between 4 and 20 mg/L, representing less than 1% of the regional scale predicted values. These residuals most often map to geographic regions where local-scale processes including evaporative discharge in closed basins or intermittent streams concentrate fluoride in shallow groundwater. Despite this, the RFR model provides spatially continuous F predictions across the basin-fill aquifers where discrete samples are missing. Further, the predictions capture documented areas that exceed the F maximum contaminant level for drinking water of 4 mg/L and areas that are below the oral-health benchmark of 0.7 mg/L. These predictions can be used to estimate fluoride concentrations in unmonitored areas and to aid in identifying geographic areas that may require further investigation at localized scales.
The main objective of this study is to develop physics‐based constraints on the spatiotemporal variation of the slip‐rate function using a simplified dynamic rupture model. First, we performed dynamic rupture modeling of the 2019 Mw 7.1 Ridgecrest, California, earthquake, to analyze the effects of depth‐dependent stress and material friction on slip rate. Then, we used our modeling results to guide refinements to the slip‐rate function that were implemented in the Graves–Pitarka kinematic rupture generation technique. The dynamic ruptures were computed on a surface‐rupturing, planar strike‐slip fault that includes a weak (negative to low‐stress‐drop) zone in the upper 4 km of the crust. Below the weak zone, we placed high‐stress‐drop patches designed to mirror the large‐slip areas seen in various rupture model inversions of the event. The locations of the high‐stress‐drop patches and the hypocenter were varied in multiple realizations to investigate how changing the dynamic conditions affected the resulting rupture kinematics, in particular, the slip rate. From these simulations, we observed a systematic change in the shape of the slip‐rate function from Kostrov type below the weak zone to a predominantly symmetric shape within the weak zone, along with a depth‐dependent reduction of peak slip rate. We generalized these shallow rupture features into a depth‐dependent parametric variation of the slip‐rate function and implemented it in the Graves–Pitarka kinematic rupture model generator. The performance of the updated kinematic approach was then verified in 0–4 Hz simulations of the Mw 7.1 Ridgecrest earthquake, which showed that incorporating the depth‐dependent variation in the shape of the slip‐rate function improves the fit to the observed near‐fault ground motions in the 0.5–3 s period range.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210138","usgsCitation":"Pitarka, A., Graves, R., Irikura, K., Miyakoshi, K., Wu, C., Kawase, H., Rodgers, A., and McCallen, D., 2022, Refinements to the Graves–Pitarka kinematic rupture generator, including a dynamically consistent slip‐rate function, applied to the 2019 Mw 7.1 Ridgecrest earthquake: Bulletin of the Seismological Society of America, v. 112, no. 1, p. 287-306, https://doi.org/10.1785/0120210138.","productDescription":"20 p.","startPage":"287","endPage":"306","ipdsId":"IP-128577","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":449648,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1827522","text":"External Repository"},{"id":390657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.1414794921875,\n 35.285984736065764\n ],\n [\n -117.1636962890625,\n 35.285984736065764\n ],\n [\n -117.1636962890625,\n 36.03577394783581\n ],\n [\n -118.1414794921875,\n 36.03577394783581\n ],\n [\n -118.1414794921875,\n 35.285984736065764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Pitarka, Arben","contributorId":184062,"corporation":false,"usgs":false,"family":"Pitarka","given":"Arben","email":"","affiliations":[],"preferred":false,"id":825452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":825453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irikura, Kojiro","contributorId":197122,"corporation":false,"usgs":false,"family":"Irikura","given":"Kojiro","email":"","affiliations":[],"preferred":false,"id":825454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miyakoshi, Ken","contributorId":261915,"corporation":false,"usgs":false,"family":"Miyakoshi","given":"Ken","email":"","affiliations":[{"id":53080,"text":"Georesearch Institute","active":true,"usgs":false}],"preferred":false,"id":825455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Changjiang","contributorId":267867,"corporation":false,"usgs":false,"family":"Wu","given":"Changjiang","email":"","affiliations":[{"id":55521,"text":"Nuclear Regulatory Authority, Japan","active":true,"usgs":false}],"preferred":false,"id":825456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kawase, Hiroshi","contributorId":267868,"corporation":false,"usgs":false,"family":"Kawase","given":"Hiroshi","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":825457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rodgers, Arthur","contributorId":197124,"corporation":false,"usgs":false,"family":"Rodgers","given":"Arthur","affiliations":[],"preferred":false,"id":825458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McCallen, David","contributorId":267869,"corporation":false,"usgs":false,"family":"McCallen","given":"David","email":"","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":825459,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70225552,"text":"70225552 - 2022 - Hazard characterization for alternative intensity measures using the total probability theorem","interactions":[],"lastModifiedDate":"2022-05-13T14:04:38.668436","indexId":"70225552","displayToPublicDate":"2021-10-12T07:34:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Hazard characterization for alternative intensity measures using the total probability theorem","docAbstract":"Since their inception in the 1980s, simplified procedures for the analysis of liquefaction hazards have typically characterized seismic loading using a combination of peak ground acceleration and earthquake magnitude. However, more recent studies suggest that certain evolutionary intensity measures (IMs) such as Arias intensity or cumulative absolute velocity may be more efficient and sufficient predictors of liquefaction triggering and its consequences. Despite this advantage, widespread hazard characterizations for evolutionary IMs are not yet feasible due to a relatively incomplete representation of the ground motion models (GMMs) needed for probabilistic seismic hazard analysis (PSHA). Without widely available hazard curves for evolutionary IMs, current design codes often rely on spectral targets for ground motion selection and scaling, which are shown in this study to indirectly result in low precision of evolutionary IMs often associated with liquefaction hazards. This study presents a method to calculate hazard curves for arbitrary intensity measures, such as evolutionary IMs for liquefaction hazard analyses, without requiring an existing GMM. The method involves the conversion of a known IM hazard curve into an alternative IM hazard curve using the total probability theorem. The effectiveness of the method is illustrated by comparing hazard curves calculated using the total probability theorem to the results of a PSHA to demonstrate that the proposed method does not result in additional uncertainty under idealized conditions and provides a range of possible hazard values under most practical conditions. The total probability theorem method can be utilized by practitioners and researchers to select ground motion time series that target alternative IMs for liquefaction hazard analyses or other geotechnical applications. This method also allows researchers to investigate the efficiency, sufficiency, and predictability of new, alternative IMs without necessarily requiring GMMs.
Coastal wetlands along the Gulf of Mexico support a wide diversity of wildlife, are important nurseries for sport and commercial fisheries, provide erosion and flood control, and serve many other ecological functions and services. These marshes have been declining in area and degrading at alarming rates since the 1930s. Effective conservation planning is vital to protect these ecosystems, but decision makers often lack knowledge of expected future conditions to strategically target conservation actions. To address this issue, we focus on a species of conservation concern, the mottled duck (<i>Anas fulvigula</i>), that resides year-round in the coastal marshes of the Gulf of Mexico. We used location data collected from radiomarked hen mottled ducks from 2006 to 2011 to create an ensemble model of habitat selection for 2010. We then projected future habitat states using models of sea-level rise and human development. By combining future predictions with our ensemble model, we predict future habitat for mottled ducks through 2100, in 20-year time steps beginning with 2020. Sea-level rise models predicted reductions in coastal marsh habitats and our ensemble model predict corresponding declines in overall habitat quantity and quality for mottled ducks, with the largest rate of habitat loss predicted within the Chenier Plain of Louisiana, USA at 71%. In some areas, particularly the Texas Mid-Coast, USA, future urbanization and human development is expected to reduce the ability of wetland habitat to migrate inland with rising sea-levels. Our results also highlight areas of coastal marsh particularly vulnerable to sea-level rise; and conversely, identify areas most likely to persist into the future that could be targeted for habitat conservation to help mottled ducks persist on the landscape.
","language":"English","publisher":"Wiley","doi":"10.1016/j.ecolind.2021.108276","usgsCitation":"Moon, J., Lehnen, S., Metzger, K., Squires, M., Brasher, M., Wilson, B., Conway, W., Haukos, D.A., Davis, B., Rohwer, F., Wehland, E., and Ballard, B., 2022, Projected impact of sea-level rise and urbanization on mottled duck (Anas fulvigula) habitat along the Gulf Coast of Louisiana and Texas through 2100: Ecological Indicators, v. 132, 108276, 28 p., https://doi.org/10.1016/j.ecolind.2021.108276.","productDescription":"108276, 28 p.","ipdsId":"IP-132508","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":449655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108276","text":"Publisher Index Page"},{"id":397158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.94287109375,\n 27.254629577800063\n ],\n [\n -91.49414062499999,\n 27.254629577800063\n ],\n [\n -91.49414062499999,\n 31.062345409804408\n ],\n [\n -98.94287109375,\n 31.062345409804408\n ],\n [\n -98.94287109375,\n 27.254629577800063\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moon, J.A.","contributorId":288507,"corporation":false,"usgs":false,"family":"Moon","given":"J.A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lehnen, S.E.","contributorId":288508,"corporation":false,"usgs":false,"family":"Lehnen","given":"S.E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Metzger, K.L.","contributorId":288509,"corporation":false,"usgs":false,"family":"Metzger","given":"K.L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Squires, M.A.","contributorId":288511,"corporation":false,"usgs":false,"family":"Squires","given":"M.A.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brasher, M.G.","contributorId":288514,"corporation":false,"usgs":false,"family":"Brasher","given":"M.G.","email":"","affiliations":[{"id":61782,"text":"3Ducks Unlimited, Inc","active":true,"usgs":false}],"preferred":false,"id":838039,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, B.C.","contributorId":288516,"corporation":false,"usgs":false,"family":"Wilson","given":"B.C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":838040,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conway, W.C.","contributorId":288517,"corporation":false,"usgs":false,"family":"Conway","given":"W.C.","email":"","affiliations":[{"id":61784,"text":"Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838041,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838034,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davis, B.E.","contributorId":288518,"corporation":false,"usgs":false,"family":"Davis","given":"B.E.","affiliations":[{"id":61785,"text":"Minnesota Deptartment of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":838042,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rohwer, F.C.","contributorId":288519,"corporation":false,"usgs":false,"family":"Rohwer","given":"F.C.","affiliations":[{"id":61786,"text":"Delta Waterfowl Foundation","active":true,"usgs":false}],"preferred":false,"id":838043,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wehland, E.M.","contributorId":288665,"corporation":false,"usgs":false,"family":"Wehland","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":838182,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ballard, B.M.","contributorId":95028,"corporation":false,"usgs":true,"family":"Ballard","given":"B.M.","email":"","affiliations":[],"preferred":false,"id":838183,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70230488,"text":"70230488 - 2022 - Genome-wide SNP analysis of three moose subspecies at the southern range limit in the contiguous United States","interactions":[],"lastModifiedDate":"2023-06-06T16:36:38.703583","indexId":"70230488","displayToPublicDate":"2021-10-08T06:49:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Genome-wide SNP analysis of three moose subspecies at the southern range limit in the contiguous United States","docAbstract":"Genome-wide evaluations of genetic diversity and population structure are important for informing management and conservation of trailing-edge populations. North American moose (Alces alces) are declining along portions of the southern edge of their range due to disease, species interactions, and marginal habitat, all of which may be exacerbated by climate change. We employed a genotyping by sequencing (GBS) approach in an effort to collect baseline information on the genetic variation of moose inhabiting the species’ southern range periphery in the contiguous United States. We identified 1920 single nucleotide polymorphisms (SNPs) from 155 moose representing three subspecies from five states: A. a. americana (New Hampshire), A. a. andersoni (Minnesota), and A. a. shirasi (Idaho, Montana, and Wyoming). Molecular analyses supported three geographically isolated clusters, congruent with currently recognized subspecies. Additionally, while moderately low genetic diversity was observed, there was little evidence of inbreeding. Results also indicated > 20% shared ancestry proportions between A. a. shirasi samples from northern Montana and A. a. andersoni samples from Minnesota, indicating a putative hybrid zone warranting further investigation. GBS has proven to be a simple and effective method for genome-wide SNP discovery in moose and provides robust data for informing herd management and conservation priorities. With increasing disease, predation, and climate related pressure on range edge moose populations in the United States, the use of SNP data to identify gene flow between subspecies may prove a powerful tool for moose management and recovery, particularly if hybrid moose are more able to adapt.
We use the Third Uniform California Earthquake Rupture Forecast (UCERF3) epidemic‐type aftershock sequence (ETAS) model (UCERF3‐ETAS) to evaluate the effects of declustering and Poisson assumptions on seismic hazard estimates. Although declustering is necessary to infer the long‐term spatial distribution of earthquake rates, the question is whether it is also necessary to honor the Poisson assumption in classic probabilistic seismic hazard assessment. We use 500,000 yr, M ≥ 2.5 synthetic catalogs to address this question, for which UCERF3‐ETAS exhibits realistic spatiotemporal clustering effects (e.g., aftershocks). We find that Gardner and Knopoff (1974) declustering, used in the U.S. Geological Survey seismic hazard models, lowers 2% in 50 yr and risk‐targeted ground‐motion hazard metrics by about 4% on average (compared with the full time‐dependent [TD] model), with the reduction being 5% at 40% in 50 yr ground motions. Keeping all earthquakes and treating them as a Poisson process increases these same hazard metrics by about 3%–12%, on average, due to the removal of relatively quiet time periods in the full TD model. In the interest of model simplification, bias minimization, and consideration of the probabilities of multiple exceedances, we agree with others (Marzocchi and Taroni, 2014) that we are better off keeping aftershocks and treating them as a Poisson process rather than removing them from hazard consideration via declustering. Honoring the true time dependence, however, will likely be important for other hazard and risk metrics, and this study further exemplifies how this can now be evaluated more extensively.
We derive approximate expressions for the ellipticity (i.e. horizontal-to-vertical or vertical-to-horizontal ratio) of Rayleigh waves propagating in a layered medium. The approximation is based on the generalized energy equation for Rayleigh waves, which has been used previously to obtain perturbational results for ellipticity. For a medium with weakly heterogeneous layers, we obtain an approximation from the perturbational result by taking the background medium to be homogeneous. The generalized energy equation also requires an auxiliary function and we discuss how the various possible functions are related to the homogeneous Rayleigh-wave eigenfunction. The analysis reveals that, within the weak approximation, the product of ellipticity and squared phase velocity is linearly related to squared shear wave velocity in the subsurface. We show the accuracy of the approximation with a simple layer-over-half-space model and then demonstrate its utility in a linear inversion scheme for shear wave velocity.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggab395","usgsCitation":"Haney, M.M., and Tsai, V.C., 2022, Rayleigh-wave ellipticity in weakly heterogeneous layered media: Geophysical Journal International, v. 228, no. 2, p. 1313-1323, https://doi.org/10.1093/gji/ggab395.","productDescription":"11 p.","startPage":"1313","endPage":"1323","ipdsId":"IP-130168","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggab395","text":"Publisher Index Page"},{"id":406672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"228","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":851700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tsai, Victor C. 0000-0003-1809-6672","orcid":"https://orcid.org/0000-0003-1809-6672","contributorId":199684,"corporation":false,"usgs":false,"family":"Tsai","given":"Victor","email":"","middleInitial":"C.","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":851701,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226957,"text":"70226957 - 2022 - Estimating urban air pollution contribution to South Platte River nitrogen loads with National Atmospheric Deposition Program data and SPARROW model","interactions":[],"lastModifiedDate":"2021-12-22T13:00:51.139878","indexId":"70226957","displayToPublicDate":"2021-10-01T06:57:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating urban air pollution contribution to South Platte River nitrogen loads with National Atmospheric Deposition Program data and SPARROW model","docAbstract":"Air pollution is commonly disregarded as a source of nutrient loading to impaired surface waters managed under the Clean Water Act per states’ 303(d) list programs. The contribution of air pollution to 2017–2018 South Platte River nitrogen (N) loads was estimated from the headwaters to the gage at Weldona, Colorado, USA (100 km downstream of Denver), using data from the National Atmospheric Deposition Program (NADP) and the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model. The NADP offers wet-deposition raster created by spatial interpolation of data collected from regionally representative monitoring sites, excluding the influences from urban site data. For this study, NADP wet-deposition data obtained from sites within the Denver-Boulder, Colorado, urban corridor were included and excluded in new spatial interpolations of wet-deposition raster, which were used as input for SPARROW to model the influence of urban air pollution sources on South Platte River loads. Because urban air pollution is already incorporated into the NADP Total Deposition modeling methodology, dry N deposition was held constant for each SPARROW modeling scenario when dry deposition was included. By including the urban wet-deposition data in the model, estimated N loading to the South Platte River at Denver increased by 9–11 percent. Factoring in dry deposition at a 1:1.8 dry:wet ratio obtained from the results, urban air pollution was estimated to contribute as much as 20 percent of the nitrate Total Maximum Daily Load for Segment 14 of the South Platte River.
The Cascadia subduction zone in the Pacific Northwest of the United States of America capable of producing magnitude ∼9 earthquakes, likely often accompanied by tsunamis. An outstanding question in this region is the degree and spatial extent of interseismic strain accumulation on the subduction megathrust. Seafloor geodetic methods combining GNSS and underwater acoustic ranging (GNSS-A) are capable of imaging this strain accumulation on the offshore portion of the subduction zone and therefore anticipating the potential size and rupture pattern of a future earthquake. However, the high cost of seafloor geodesy means that only a limited number of stations may be deployed and monitored. To facilitate expansion of current geodetic networks offshore, we develop a quantitative recommendation of optimal locations for future seafloor geodetic observations, based on the amount of new information provided by that observation. The optimal network depends on the problem that one is trying to solve with those observations (mapping subduction locking rates, coupling rates, constraining total moment rate, etc.), and on a number of modelling and data uncertainty assumptions. In particular, data uncertainty assumptions will change over time, as more position observations reduce velocity uncertainties. We find that near-trench observations on the megathrust hangingwall, distributed along-strike, consistently provide significant reduction in differential entropy over a large suite of assumptions, and that a well-placed seafloor observation can provide up to ∼30 times the information gain of the most optimal onshore observation.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggab360","usgsCitation":"Evans, E., Minson, S.E., and Chadwell, D., 2022, Imaging the next Cascadia earthquake: Optimal design for a seafloor GNSS- A network: Geophysical Journal International, v. 228, no. 2, p. 944-957, https://doi.org/10.1093/gji/ggab360.","productDescription":"14 p.","startPage":"944","endPage":"957","ipdsId":"IP-130354","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407600,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washington","otherGeospatial":"Cascadia subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -132,\n 38.13455657705411\n ],\n [\n -120,\n 38.13455657705411\n ],\n [\n -120,\n 51.508742458803326\n ],\n [\n -132,\n 51.508742458803326\n ],\n [\n -132,\n 38.13455657705411\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"228","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Eileen L. 0000-0002-7290-5269","orcid":"https://orcid.org/0000-0002-7290-5269","contributorId":297103,"corporation":false,"usgs":false,"family":"Evans","given":"Eileen L.","affiliations":[{"id":36305,"text":"CSU Northridge","active":true,"usgs":false}],"preferred":false,"id":853343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chadwell, David 0000-0002-9741-6656","orcid":"https://orcid.org/0000-0002-9741-6656","contributorId":297105,"corporation":false,"usgs":false,"family":"Chadwell","given":"David","email":"","affiliations":[{"id":37799,"text":"SCRIPPS","active":true,"usgs":false}],"preferred":false,"id":853345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224540,"text":"70224540 - 2022 - Targeted and non-targeted analysis of young-of-year smallmouth bass using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry","interactions":[],"lastModifiedDate":"2021-10-06T16:04:22.992337","indexId":"70224540","displayToPublicDate":"2021-09-16T10:03:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Targeted and non-targeted analysis of young-of-year smallmouth bass using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry","docAbstract":"Smallmouth bass in the Susquehanna River Basin, Chesapeake Bay Watershed, USA, have been exhibiting clinical signs of disease and reproductive endocrine disruption (e.g., intersex, male plasma vitellogenin) for over fifteen years. Previous histological and targeted chemical analyses have identified infectious agents and pollutants in fish tissues including organic contaminants, mercury, and perfluorinated compounds, but a common causative link for the observed signs of disease across this widespread area has not been determined. This study examines 146 young-of-year smallmouth bass collected from 14 sampling sites in the Susquehanna River Basin, Pennsylvania, USA with varying levels of disease prevalence. Whole fish were extracted by a recently developed modification to the quick, easy, cheap, effective, rugged, and safe extraction method and analyzed by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry. A targeted analysis was conducted to identify the presence and quantity of 127 known contaminants, including polychlorinated biphenyls, brominated diphenyl ethers, organochlorinated pesticides, and pharmaceutical and personal care products. A non-targeted analysis was conducted on the same data set to identify analytes of interest not included on routine target compound lists. Chromatographic alignment through Statistical Compare (ChromaTOF GC) was followed by Fisher ratio and principal component analysis to reduce the data set from thousands of peaks per sample to a final data set of 65 analytes of interest. Comparisons of these 65 compounds between Normal (no observed health anomalies) and Lesioned (observed health anomaly at time of collection) fish revealed increased levels of three chemical families in Lesioned fish including esters, ketones, and nitrogen containing compounds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.150378","usgsCitation":"Teehan, P., Schall, M., Blazer, V., and Dorman, F.L., 2022, Targeted and non-targeted analysis of young-of-year smallmouth bass using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry: Science of the Total Environment, v. 806, no. 2, 150378, 10 p., https://doi.org/10.1016/j.scitotenv.2021.150378.","productDescription":"150378, 10 p.","ipdsId":"IP-130510","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":389815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay watershed, Susquehanna River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n 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vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":823987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dorman, Frank L","contributorId":236876,"corporation":false,"usgs":false,"family":"Dorman","given":"Frank","email":"","middleInitial":"L","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":823988,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236513,"text":"70236513 - 2022 - The 6 May 1947 Milwaukee, Wisconsin, earthquake","interactions":[],"lastModifiedDate":"2022-09-09T11:58:51.284302","indexId":"70236513","displayToPublicDate":"2021-09-15T06:56:30","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":"The 6 May 1947 Milwaukee, Wisconsin, earthquake","docAbstract":"The State of Wisconsin is not known for earthquake activity. The authoritative public‐facing U.S. Geological Survey Comprehensive Catalog of earthquakes includes only three small (magnitude < 2) earthquakes in the state, all instrumentally recorded. Although other catalogs include more events in Wisconsin, experience has shown that many types of events, such as explosions and cryoseisms, have made their way into earthquake catalogs in this region. In this short report, I summarize available information about an earthquake that was felt in eastern Wisconsin at 15:27 local time on 6 May 1947. As what appears to be the largest historical earthquake in the State of Wisconsin, it is of public interest, its modest size notwithstanding. It appears that no useful instrumental records exist, due in part to a teleseismic event that occurred approximately 3 min later, generating surface waves that were recorded on early long‐period instruments in the region. Instrumental data may exist for this event but have not been found. Comparing the felt area with information from recent earthquakes in the region, I estimate an intensity magnitude of 3.8 for the event, with a subjectively estimated uncertainty range 3.5–4.1. Relatively strong effects, including reports of broken dishes in Milwaukee, and shaking described as short but especially sharp, suggest that the event may have been among the sprinkling of shallow earthquakes now known to occur in the upper Great Lakes region.
We investigate whether assuming a fixed shallow depth in the ShakeAlert network‐based earthquake early warning system is sufficient to produce accurate ground‐motion based alerts for intraslab earthquakes. ShakeAlert currently uses a fixed focal depth of 8 km to estimate earthquake location and magnitude. This is an appropriate way to reduce computational costs without compromising alert accuracy in California, where earthquakes typically occur on shallow crustal faults. In the Pacific Northwest (PNW), however, the most common moderate‐magnitude events occur within the subducting Juan de Fuca slab at depths between ∼35 and 65 km. Using a dataset of seismic recordings from 37 Mw 4.5+ intraslab earthquakes from the PNW and Chile, we replay events through the Earthquake Point‐Source Integrated Code and eqInfo2GM algorithms to estimate source parameters and compute modified Mercalli intensity (MMI) alert threshold contours. Each event is replayed twice—once using a fixed 8 km depth and a second time using the actual catalog earthquake depth. For each depth scenario, we analyze MMI III and IV contours using various performance metrics to determine the number of correctly alerted sites and measure warning times. We determine that shallow depth replays are more likely to produce errors in location estimates of greater than 50 km if the event is located outside of a seismic network. When located within a seismic network, shallow and catalog depth replays have similar epicenter estimates. Results show that applying catalog earthquake depth does not improve the accuracy of magnitude estimates or MMI alert threshold contours, or increase warning times. We conclude that using a fixed shallow earthquake depth for intraslab earthquakes will not significantly impact alert accuracy in the PNW.
Modern microfossil distributions reflect site-specific habitats and provide an opportunity to assess sediment transport pathways in the nearshore environment. When applied to overwash deposits in the geological record, they provide insight into sediment provenance and transport, factors important for understanding patterns of frequency and intensity of past storms and tsunamis. Modern distribution studies are rare and often the first established ones occur immediately after an overwash event as part of a post-event field survey. This is problematic because it is unclear what effect overwash events have on nearshore microfossil assemblages and what time interval is necessary for them to return to pre-event conditions. This study documents the impacts of Hurricane Irma on nearshore sediments off the coast of Anegada, British Virgin Islands, using distributions of Homotrema rubrum, an encrusting foraminifer with a defined provenance in coral reefs. At four sampling intervals spanning two years, from six months pre-Hurricane Irma to eighteen months after, surface sediment was collected from three transects on the northern and southern shores of the island. Partitioning Around Medoids cluster analysis revealed that Hurricane Irma introduced an influx of well-preserved fragments into the reef flat and made the sediments more uniform, limiting the foraminifer’s utility as a known sediment transport indicator. The mixing of sediments along the two northern transects (reef proximal) persisted for seven to eighteen months before returning to near pre-hurricane conditions. However, the southern transect (absence of reef), where Homotrema rubrum concentrations are significantly less, failed to recover within the time period assessed by this study, indicating a variable recovery period between Atlantic Ocean and Caribbean Sea facing shorelines. Results from this study suggest that a waiting period of at least eighteen months after a major storm is recommended before collecting surface sediment from the nearshore environments of reef-dominated coastlines.
Vernal pools of the northeastern United States provide important breeding habitat for amphibians but may be sensitive to droughts and climate change. These seasonal wetlands typically fill by early spring and dry by mid-to-late summer. Because climate change may produce earlier and stronger growing-season evapotranspiration combined with increasing droughts and shifts in precipitation timing, management concerns include the possibility that some pools will increasingly become dry earlier in the year, potentially interfering with amphibian life-cycle completion. In this context, a subset of pools that continue to provide wetland habitat later into the year under relatively dry conditions might function as ecohydrologic refugia, potentially supporting species persistence even as summer conditions become warmer and droughts more frequent. We used approximately 3,000 field observations of inundation from 449 pools to train machine-learning models that predict the likelihood of pool inundation based on pool size, day of the year, climate conditions, short-term weather patterns, and soil, geologic, and landcover attributes. Models were then used to generate predictions of pool wetness across five seasonal time points, three short-term weather scenarios, and four sets of downscaled climate projections. Model outputs are available through a website allowing users to choose the inundation thresholds, time points, weather scenarios, and future climate projections most relevant to their management needs. Together with long-term monitoring of individual pools at the site scale, this regional-scale study can support amphibian conservation by helping to identify which pools may be most likely to function as ecohydrologic refugia from droughts and climate change.
The 2019
Environmental water management often benefits from a risk-based approach where information on the area of interest is characterized, assembled, and incorporated into a decision model considering uncertainty. This includes prior information from literature, field measurements, professional interpretation, and data assimilation resulting in a decision tool with a posterior uncertainty assessment accounting for prior understanding and what is learned through model development and data assimilation. Model construction and data assimilation are time consuming and prone to errors, which motivates a repeatable workflow where revisions resulting from new interpretations or discovery of errors can be addressed and the analyses repeated efficiently and rigorously. In this work, motivated by the real world application of delineating risk-based (probabilistic) sources of water to supply wells in a humid temperate climate, a scripted workflow was generated for groundwater model construction, data assimilation, particle-tracking and post-processing. The workflow leverages existing datasets describing hydrogeology, hydrography, water use, recharge, and lateral boundaries. These specific data are available in the United States but the tools can be applied to similar datasets worldwide. The workflow builds the model, performs ensemble-based history matching, and uses a posterior Monte Carlo approach to provide probabilistic capture zones describing source water to wells in a risk-based framework. The water managers can then select areas of varying levels of protection based on their tolerance for risk of potential wrongness of the underlying models. All the tools in this workflow are open-source and free, which facilitates testing of this repeatable and transparent approach to other environmental problems.
Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (
Subsidence and accelerated sea level rise impact nesting area availability and flood probabilities of breeding islands for colonial nesting waterbirds. In 2017 and 2018, we monitored 855 nests of four species of colonial nesting waterbirds on Rabbit Island, LA, to determine factors affecting nest and chick success. Based on logistic exposure models of nests, tricolored herons had the greatest likelihood of survival to hatch (mean (95% confidence interval)) (77% (65.9–83.1%)), followed by brown pelicans (70% (59.9–98.5%)), roseate spoonbills (70% (38.9–83.8%)), and Forster’s terns (12% (10.7–12.2%)). Likelihood of survival to fledge was highest for tricolored herons (32% (12.8–40.7%)), followed by brown pelicans (28% (19.5–28.6%)), roseate spoonbills (47% (43.7–53.3%)), and Forster’s terns (0% (0.005–0.01%)). Nesting strategy and nest timing impacted survival rate; however, the effect depended on timing of inundation events as the timing of inundation events varied across years. Flooding was the primary cause of nest failure for most species. In 2003–2012, rapid expansion in brown pelican colony numbers and significant chick production occurred at Rabbit Island, but hydrologic records indicate no island inundation occurred during the breeding season from the beginning of the hydrologic record (2006) through 2011. Thus, our results contrast with those of previous studies conducted under different hydrologic conditions and demonstrate the challenges of short-term studies informing coastal restoration in a system that is influenced by multi-year to multi-decadal climatic cycles.
Earthquake hazards in the U.S. Pacific Northwest (PNW) are increased by the presence of deep sedimentary basins that amplify and prolong ground shaking. To better understand basin and site effects on ground motions, we compile a database of recordings from crustal and intraslab earthquakes. We process 8028 records with magnitudes from 3.5 to 6.8 and hypocentral depths up to 62 km to compute Fourier amplitude spectra of ground acceleration for frequencies of 0–20 Hz. We compute residuals relative to the Bayless and Abrahamson (2019; hereafter, BA18) ground‐motion model and perform a series of linear, crossed, mixed‐effects regressions. In addition to estimating the bias, event, and site terms, we incorporate groupings for broad regionalized site response in three different regions (Seattle basin, Puget Lowland, non‐Puget Lowland), for effects from seismotectonic regime (crustal and intraslab sources), and for interactions between the regions and seismotectonic regimes. We find that the scaling of site response with respect to VS30 (time‐averaged shear‐wave velocity from the surface to a depth of 30 m) and to basin depth indicators Z1.0 and Z2.5 (depths to the 1.0 and 2.5 km/s shear‐wave velocity horizons) is generally consistent with BA18; however, the region terms display strong spatial amplification patterns. For frequencies less than 5 Hz, the Seattle basin amplifies ground motions up to a factor of four, relative to the non‐Puget Lowland, with a maximum amplification around near 0.5 Hz. Sites in the Puget Lowland amplify low frequencies up to a factor of 2.5. At higher frequencies (f>5 Hz), the Puget Lowland and Seattle basin show regional deamplification of ground motions, with the smallest average amplification factor of 0.65 occurring at 10.0 Hz. Although we observe slight differences in the seismotectonic regime terms, we find that the region terms are significantly more important for modeling earthquake hazard in the PNW.