{"pageNumber":"220","pageRowStart":"5475","pageSize":"25","recordCount":46677,"records":[{"id":70216934,"text":"70216934 - 2021 - Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","interactions":[],"lastModifiedDate":"2021-03-05T21:07:22.044536","indexId":"70216934","displayToPublicDate":"2020-11-21T12:54:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7443,"text":"Quarterly Journal of the Royal Meteorological Society","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model","docAbstract":"

The importance of wind energy as an alternative energy source has increased over the latest years with more focus on offshore winds. A good estimation of the offshore winds is thus of major importance for this industry. Up to now the effect of the wind–wave (mis)alignment has not yet been taken into account in coupled atmosphere–wave models to study the vertical wind profile and power production estimations of offshore wind farms. In this study the roughness length parametrization of Drennan et al. in 2003, and its extension addressing the wind–wave (mis)alignment proposed by Porchetta et al. in 2019, are investigated in the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model. This study shows that the yearly mean wind estimation at hub height (100 m) is improved by the roughness length parametrization of Porchetta et al. compared to Drennan. This is mainly due to the increased roughness of the former parametrization compare to the latter, even in aligned wind–wave conditions. This difference in roughness is caused by the dataset used to obtain the constants, deep‐water conditions versus mixed offshore conditions. Moreover, the roughness length parametrization of Porchetta et al. performs better in two of three alignment categories. Furthermore, similar model performances are obtained if we exclude the wind directions from the wind shadow zone of the measurement mast or the wind directions from the recently built Alpha Ventus wind farm, which is in close vicinity of the measurement mast. Investigating different wind conditions shows that the new roughness length parametrization of Porchetta et al. performs best for both offshore and onshore winds. Additionally, we show that the coupled model estimations of the vertical wind are only slightly affected by significant wave height estimations. Similar model performances for different accuracies of significant wave height estimations are presented. One exception is the perpendicular alignment category where the new roughness length of Porchetta et al. outperforms the roughness length of Drennan when investigating the wind estimations related to significant wave heights with a higher accuracy. The roughness length parametrization of Porchetta et al. reduced the power production overestimation of the coupled model from 5.7 to 2.8%. We also show that the standalone atmospheric model including the roughness length of Charnock in 1955 has a degraded performance compared to the coupled model including the roughness length parametrization of Porchetta et al. for yearly average wind profiles.

","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/qj.3948","usgsCitation":"Porchetta, S., Temel, O., Warner, J., Munoz-Esparza, J., Monbaliu, J., van Beeck, J., and van Lipzig, N., 2021, Evaluation of a roughness length parametrization accounting for wind–wave alignment in a coupled atmosphere–wave model: Quarterly Journal of the Royal Meteorological Society, v. 147, no. 735, p. 825-846, https://doi.org/10.1002/qj.3948.","productDescription":"22 p.","startPage":"825","endPage":"846","ipdsId":"IP-117950","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454221,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lirias.kuleuven.be/bitstream/123456789/685815/2/COAWST_QJRMetS_rkul.docx","text":"External Repository"},{"id":381447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","issue":"735","noUsgsAuthors":false,"publicationDate":"2020-12-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Porchetta, Sara","contributorId":245775,"corporation":false,"usgs":false,"family":"Porchetta","given":"Sara","email":"","affiliations":[{"id":49315,"text":"KU Leuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temel, O.","contributorId":245776,"corporation":false,"usgs":false,"family":"Temel","given":"O.","email":"","affiliations":[{"id":49316,"text":"Royal Observatory of Belgium, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":807017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munoz-Esparza, J.C.","contributorId":245777,"corporation":false,"usgs":false,"family":"Munoz-Esparza","given":"J.C.","email":"","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":807019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Monbaliu, J","contributorId":245778,"corporation":false,"usgs":false,"family":"Monbaliu","given":"J","email":"","affiliations":[{"id":49317,"text":"KULeuven, Department of Civil Engineering, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"van Beeck, J.","contributorId":245779,"corporation":false,"usgs":false,"family":"van Beeck","given":"J.","email":"","affiliations":[{"id":49319,"text":"KULeuven, Department Earth and Environmental Sciences, Leuven, Belgium","active":true,"usgs":false}],"preferred":false,"id":807021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Lipzig, N.","contributorId":245780,"corporation":false,"usgs":false,"family":"van Lipzig","given":"N.","email":"","affiliations":[{"id":49321,"text":"von Karman Institute for Fluid Dynamics, Sint-Genesius-Rode, Belgium","active":true,"usgs":false}],"preferred":false,"id":807022,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70225590,"text":"70225590 - 2021 - Increasing comparability among coral bleaching experiments","interactions":[],"lastModifiedDate":"2021-10-26T14:31:59.549345","indexId":"70225590","displayToPublicDate":"2020-11-21T09:22:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Increasing comparability among coral bleaching experiments","docAbstract":"

Coral bleaching is the single largest global threat to coral reefs worldwide. Integrating the diverse body of work on coral bleaching is critical to understanding and combating this global problem. Yet investigating the drivers, patterns, and processes of coral bleaching poses a major challenge. A recent review of published experiments revealed a wide range of experimental variables used across studies. Such a wide range of approaches enhances discovery, but without full transparency in the experimental and analytical methods used, can also make comparisons among studies challenging. To increase comparability but not stifle innovation, we propose a common framework for coral bleaching experiments that includes consideration of coral provenance, experimental conditions, and husbandry. For example, reporting the number of genets used, collection site conditions, the experimental temperature offset(s) from the maximum monthly mean (MMM) of the collection site, experimental light conditions, flow, and the feeding regime will greatly facilitate comparability across studies. Similarly, quantifying common response variables of endosymbiont (Symbiodiniaceae) and holobiont phenotypes (i.e., color, chlorophyll, endosymbiont cell density, mortality, and skeletal growth) could further facilitate cross-study comparisons. While no single bleaching experiment can provide the data necessary to determine global coral responses of all corals to current and future ocean warming, linking studies through a common framework as outlined here, would help increase comparability among experiments, facilitate synthetic insights into the causes and underlying mechanisms of coral bleaching, and reveal unique bleaching responses among genets, species, and regions. Such a collaborative framework that fosters transparency in methods used would strengthen comparisons among studies that can help inform coral reef management and facilitate conservation strategies to mitigate coral bleaching worldwide.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2262","usgsCitation":"Grottoli, A., Toonen, R.J., van Woesik, R., Vega Thurber, R., Warner, M.E., McLachlan, R.H., Price, J., Bahr, K.D., Baums, I., Castillo, K., Coffroth, M.A., Cunning, R., Dobson, K., Donahue, M., Hench, J.L., Iglesias-Prieto, R., Kemp, D.W., Kenkel, C.D., Kline, D.I., Kuffner, I.B., Matthews, J., Mayfield, A., Padilla-Gamino, J., Palumbi, S.R., Voolstra, C., Weis, V.M., and Wu, H.C., 2021, Increasing comparability among coral bleaching experiments: Ecological Applications, v. 31, no. 4, e02262, 17 p., https://doi.org/10.1002/eap.2262.","productDescription":"e02262, 17 p.","ipdsId":"IP-114969","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2262","text":"Publisher Index Page"},{"id":390962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Grottoli, Andrea G.","contributorId":267953,"corporation":false,"usgs":false,"family":"Grottoli","given":"Andrea G.","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":825698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toonen, R. 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R.","contributorId":268003,"corporation":false,"usgs":false,"family":"Palumbi","given":"S.","email":"","middleInitial":"R.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":825721,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Voolstra, C. R.","contributorId":268006,"corporation":false,"usgs":false,"family":"Voolstra","given":"C. R.","affiliations":[{"id":55536,"text":"University of Konstanz","active":true,"usgs":false}],"preferred":false,"id":825722,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Weis, V. M.","contributorId":268008,"corporation":false,"usgs":false,"family":"Weis","given":"V.","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":825723,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Wu, H. C.","contributorId":268011,"corporation":false,"usgs":false,"family":"Wu","given":"H.","email":"","middleInitial":"C.","affiliations":[{"id":55538,"text":"Leibniz Centre for Tropical Marine Research","active":true,"usgs":false}],"preferred":false,"id":825724,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}} ,{"id":70216862,"text":"70216862 - 2021 - Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems","interactions":[],"lastModifiedDate":"2021-02-17T22:20:09.735913","indexId":"70216862","displayToPublicDate":"2020-11-21T07:39:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems","docAbstract":"

High-head dams are migration barriers for Pacific salmon Oncorhynchus spp. in many river systems and recovery measures for impacted stocks are limited. Trap-and-haul has been widely used in attempts to facilitate recovery but information from existing programs has not been synthesized to inform improvements to aid recovery of salmonids in systems with high-head dams. We reviewed 17 trap-and-haul programs regarding Pacific salmon to: (1) summarize information about facility design, operation and biological effects; (2) identify critical knowledge gaps; and (3) evaluate trap-and-haul as a current and future management tool. Existing programs are operated to address a range of management goals including restoring access to historical habitats, temporarily reducing exposure to dangerous in-river conditions, and reintroducing ecological processes upstream from dams. Information gathered from decades of operation on facility design criteria and fish handling protocols, and robust literature on fish collection and passage are available. While many aspects of trap-and-haul have been evaluated, effects on population productivity and sustainability remain poorly understood. Long-term and systematic studies of trap-and-haul outcomes are rare, and assessments can be confounded by concurrent management actions and broad ecological and climatic effects. Existing data suggest that performance and effectiveness vary among programs and over various time scales within programs. Although critical information gaps exist, trap-and-haul is an important management and conservation tool for providing Pacific salmonids access to historical habitats. Successful application of trap-and-haul programs requires long-term commitment and an adaptive management approach by dam owners and stakeholders, and careful planning of new programs.


","language":"English","publisher":"Springer","doi":"10.1007/s11160-020-09627-7","usgsCitation":"Kock, T.J., Ferguson, J.W., Keefer, M.L., and Schreck , C., 2021, Review of trap-and-haul for managing Pacific salmonids (Oncorhynchus spp.) in impounded river systems: Reviews in Fish Biology and Fisheries, v. 31, p. 53-94, https://doi.org/10.1007/s11160-020-09627-7.","productDescription":"42 p.","startPage":"53","endPage":"94","ipdsId":"IP-120120","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":454227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11160-020-09627-7","text":"Publisher Index Page"},{"id":381187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, 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treatments","interactions":[],"lastModifiedDate":"2021-04-08T14:54:11.590102","indexId":"70217871","displayToPublicDate":"2020-11-21T06:52:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating natural experiments in ecology: Using synthetic controls in assessments of remotely sensed land treatments","docAbstract":"

Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks that rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large‐scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational data sets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include (1) a discrete set of treated and untreated units, (2) a known date of treatment intervention, and (3) time series response data that include both pre‐ and post‐treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no‐action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large‐scale brush‐clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long‐term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.

","language":"English","publisher":"Wiley","doi":"10.1002/eap.2264","usgsCitation":"Fick, S.E., Nauman, T.W., Brungard, C.C., and Duniway, M.C., 2021, Evaluating natural experiments in ecology: Using synthetic controls in assessments of remotely sensed land treatments: Ecological Applications, v. 31, no. 3, e02264, 16 p., https://doi.org/10.1002/eap.2264.","productDescription":"e02264, 16 p.","ipdsId":"IP-117409","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502611,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":383142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fick, Stephen E. 0000-0002-3548-6966","orcid":"https://orcid.org/0000-0002-3548-6966","contributorId":214319,"corporation":false,"usgs":true,"family":"Fick","given":"Stephen","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":809995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":809996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brungard, Colby C.","contributorId":248822,"corporation":false,"usgs":false,"family":"Brungard","given":"Colby","email":"","middleInitial":"C.","affiliations":[{"id":50029,"text":"New Mexico State University, Department of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":809997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":809998,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216739,"text":"70216739 - 2021 - Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity","interactions":[],"lastModifiedDate":"2021-11-16T15:27:01.402874","indexId":"70216739","displayToPublicDate":"2020-11-20T08:06:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7444,"text":"Statistical Analysis and Data Mining","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity","docAbstract":"

Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.

","language":"English","publisher":"Wiley","doi":"10.1002/sam.11487","usgsCitation":"Attanasi, E., Freeman, P., and Coburn, T., 2021, Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity: Statistical Analysis and Data Mining, v. 14, no. 6203, p. 536-555, https://doi.org/10.1002/sam.11487.","productDescription":"20 p.","startPage":"536","endPage":"555","ipdsId":"IP-120246","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":380950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"6203","noUsgsAuthors":false,"publicationDate":"2020-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":806022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":224150,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":806023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coburn, Timothy","contributorId":245358,"corporation":false,"usgs":false,"family":"Coburn","given":"Timothy","affiliations":[],"preferred":false,"id":806024,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219104,"text":"70219104 - 2021 - It’s complicated…environmental DNA as a predictor of trout and char abundance in streams","interactions":[],"lastModifiedDate":"2021-04-08T15:19:49.595336","indexId":"70219104","displayToPublicDate":"2020-11-20T07:15:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"It’s complicated…environmental DNA as a predictor of trout and char abundance in streams","docAbstract":"
The potential to provide inferences about fish abundance from environmental (e)DNA samples has generated great interest. However, the accuracy of these abundance estimates is often low and variable across species and space. A plausible refinement is the use of common aquatic habitat monitoring data to account for attributes that influence eDNA dynamics. We therefore evaluated the relationships between eDNA concentration and abundance of bull trout (Salvelinus confluentus), westslope cutthroat trout (Oncorhynchus clarkii lewisi) and rainbow trout (Oncorhynchus mykiss) at 42 stream sites in the Intermountain West (USA and Canada) and tested whether accounting for site-specific habitat attributes improved the accuracy of fish abundance estimates. eDNA concentrations were positively associated with fish abundance, but these relationships varied by species and site, and there was still considerable variation unaccounted for. Random site-level differences explained much of this variation, but specific habitat attributes of those sites explained relatively small amounts of this variation. Our results underscore that either eDNA sampling or environmental characterization will require further refinement before eDNA can be used reliably to estimate fish abundance in streams.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0182","usgsCitation":"Sepulveda, A., Al-Chokhachy, R., Laramie, M., Crapster, K., Knotek, L., Miller, B.T., Zale, A.V., and Pilliod, D., 2021, It’s complicated…environmental DNA as a predictor of trout and char abundance in streams: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 4, p. 422-432, https://doi.org/10.1139/cjfas-2020-0182.","productDescription":"11 p.","startPage":"422","endPage":"432","ipdsId":"IP-119130","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501109,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/105145","text":"External Repository"},{"id":384628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Idaho, Montana, Oregon, Washington","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.4541015625,\n 43.77109381775651\n ],\n [\n -111.4013671875,\n 43.77109381775651\n ],\n [\n -111.4013671875,\n 49.439556958940855\n ],\n [\n -120.4541015625,\n 49.439556958940855\n ],\n [\n -120.4541015625,\n 43.77109381775651\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert 0000-0002-2136-5098","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":216140,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laramie, Matthew 0000-0001-7820-2583 mlaramie@usgs.gov","orcid":"https://orcid.org/0000-0001-7820-2583","contributorId":152532,"corporation":false,"usgs":true,"family":"Laramie","given":"Matthew","email":"mlaramie@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":812792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crapster, Kyle","contributorId":255674,"corporation":false,"usgs":false,"family":"Crapster","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":812793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knotek, Ladd","contributorId":255675,"corporation":false,"usgs":false,"family":"Knotek","given":"Ladd","email":"","affiliations":[{"id":51642,"text":"Montana Fish Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":812794,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Brian T.","contributorId":167683,"corporation":false,"usgs":false,"family":"Miller","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":24807,"text":"Department of Biology, Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":812795,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":812796,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":218009,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":812797,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70223679,"text":"70223679 - 2021 - Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2021-09-01T13:08:24.257546","indexId":"70223679","displayToPublicDate":"2020-11-19T08:05:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed","docAbstract":"

The Chesapeake Bay is the largest estuary in the United States and its watershed includes river drainages in six states and the District of Columbia. Sportfishing is of major economic interest, however, the rivers within the watershed provide numerous other ecological, recreational, cultural and economic benefits, as well as serving as a drinking water source for millions of people. Consequently, major fish kills and the subsequent finding of estrogenic endocrine disruption (intersex or testicular oocytes and plasma vitellogenin in male fishes) raised public and management concerns. Studies have occurred at various sites within the Bay watershed to document the extent and severity of endocrine disruption, identify risk factors and document temporal and spatial variability. Data from these focal studies, which began in 2004, were used in CART (classification and regression trees) analyses to better identify land use associations and potential management practices that influence estrogenic endocrine disruption. These analyses emphasized the importance of scale (immediate versus upstream catchment) and the complex mixtures of stressors which can contribute to surface water estrogenicity and the associated adverse effects of exposure. Both agricultural (percent cultivated, pesticide application, phytoestrogen cover crops) and developed (population density, road density, impervious surface) land cover showed positive relationships to estrogenic indicators, while percent forest and shrubs generally had a negative association. The findings can serve as a baseline for assessing ongoing restoration and management practices.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2020.129009","usgsCitation":"Blazer, V., Gordon, S.E., Jones, D.K., Iwanowicz, L., Walsh, H.L., Sperry, A., and Smalling, K., 2021, Retrospective analysis of estrogenic endocrine disruption and land-use influences in the Chesapeake Bay watershed: Chemosphere, v. 266, 129009, 16 p., https://doi.org/10.1016/j.chemosphere.2020.129009.","productDescription":"129009, 16 p.","ipdsId":"IP-119378","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":454246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2020.129009","text":"Publisher Index 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R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Heather L. 0000-0001-6392-4604 hwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":4696,"corporation":false,"usgs":true,"family":"Walsh","given":"Heather","email":"hwalsh@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822300,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sperry, Adam 0000-0002-4815-3730","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":203243,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822301,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":822302,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263342,"text":"70263342 - 2021 - Latency of waveform data delivery from the Southern California Seismic Network during the 2019 Ridgecrest earthquake sequence and its effect on ShakeAlert","interactions":[],"lastModifiedDate":"2025-02-06T17:00:47.785519","indexId":"70263342","displayToPublicDate":"2020-11-18T10:55:38","publicationYear":"2021","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":"Latency of waveform data delivery from the Southern California Seismic Network during the 2019 Ridgecrest earthquake sequence and its effect on ShakeAlert","docAbstract":"

The occurrence of the 4–6 July 2019 Mw  6.4 and Mw 7.1 Ridgecrest earthquake sequence provided the first full‐scale test of the network and telemetry readiness of the Southern California Seismic Network (SCSN), to support the ShakeAlert earthquake early warning (EEW) system in California. ShakeAlert is a U.S. Geological Survey (USGS)‐led collaboration to detect earthquakes and, when possible, to alert the public before the arrival of the strongest shaking. The SCSN performed well in its regional monitoring role for both the 4 July Mw  6.4 and the 6 July Mw  7.1 earthquakes. In the EEW role, it provided timely delivery of 5 s of P‐wave data to ShakeAlert, which issued its first alert 6.9 s after origin time. Data delivery at peak data volumes for many stations exhibited some latency, and, as a consequence, some data arrived too late for analysis by one of the EEW algorithms. We find that the average link bandwidth for each station was sufficient, because all waveform data were delivered automatically to the archive, but link capacity for many stations was insufficient for peak demand. We describe the performance of the data telemetry for the sequence, including cellular, radio, hybrid, and backhaul systems. Cellular‐based telemetry systems maintained low latency throughout strong shaking and after, but some stations, even at great distances, experienced subsequent brief increases in latency. Performance of radio links depended mostly on the signal strength of the link, with short‐distance direct shots to high‐bandwidth backhaul systems showing no latency impact, whereas stations on some long distance or marginal quality links suffered latencies of tens or hundreds of seconds. Improvements are being implemented to move telemetry links onto USGS and partner high‐bandwidth microwave systems, and to reduce dependency on less robust long‐distance radio shots.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200211","usgsCitation":"Stubailo, I., Alvarez, M., Biasi, G., Bhadha, R., and Hauksson, E., 2021, Latency of waveform data delivery from the Southern California Seismic Network during the 2019 Ridgecrest earthquake sequence and its effect on ShakeAlert: Seismological Research Letters, v. 92, no. 1, p. 170-186, https://doi.org/10.1785/0220200211.","productDescription":"17 p.","startPage":"170","endPage":"186","ipdsId":"IP-115111","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121,\n 37\n ],\n [\n -121,\n 32\n ],\n [\n -114,\n 32\n ],\n [\n -114,\n 37\n ],\n [\n -121,\n 37\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Stubailo, Igor 0000-0001-7657-2783","orcid":"https://orcid.org/0000-0001-7657-2783","contributorId":350664,"corporation":false,"usgs":false,"family":"Stubailo","given":"Igor","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alvarez, Mark 0000-0002-1361-5616","orcid":"https://orcid.org/0000-0002-1361-5616","contributorId":222021,"corporation":false,"usgs":true,"family":"Alvarez","given":"Mark","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":926574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bhadha, Rayomand","contributorId":350665,"corporation":false,"usgs":false,"family":"Bhadha","given":"Rayomand","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":926575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hauksson, Egill","contributorId":48174,"corporation":false,"usgs":false,"family":"Hauksson","given":"Egill","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":926576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217186,"text":"70217186 - 2021 - The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","interactions":[],"lastModifiedDate":"2021-01-11T16:11:26.62147","indexId":"70217186","displayToPublicDate":"2020-11-18T10:00:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser","docAbstract":"

Steamboat Geyser in Yellowstone National Park’s Norris Geyser Basin began a prolific sequence of eruptions in March 2018 after 34 y of sporadic activity. We analyze a wide range of datasets to explore triggering mechanisms for Steamboat’s reactivation and controls on eruption intervals and height. Prior to Steamboat’s renewed activity, Norris Geyser Basin experienced uplift, a slight increase in radiant temperature, and increased regional seismicity, which may indicate that magmatic processes promoted reactivation. However, because the geothermal reservoir temperature did not change, no other dormant geysers became active, and previous periods with greater seismic moment release did not reawaken Steamboat, the reason for reactivation remains ambiguous. Eruption intervals since 2018 (3.16 to 35.45 d) modulate seasonally, with shorter intervals in the summer. Abnormally long intervals coincide with weakening of a shallow seismic source in the geyser basin’s hydrothermal system. We find no relation between interval and erupted volume, implying unsteady heat and mass discharge. Finally, using data from geysers worldwide, we find a correlation between eruption height and inferred depth to the shallow reservoir supplying water to eruptions. Steamboat is taller because water is stored deeper there than at other geysers, and, hence, more energy is available to power the eruptions.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2020943118","usgsCitation":"Reed, M., Munoz-Saez, C., Hajimirza, S., Wu, S., Barth, A., Girona, T., Rasht-Behesht, M., Karplus, M., Hurwitz, S., and Manga, M., 2021, The 2018 reawakening and eruption dynamics of Steamboat Geyser, the world’s tallest active geyser: PNAS, v. 118, no. 2, e2020943118, 10 p., https://doi.org/10.1073/pnas.2020943118.","productDescription":"e2020943118, 10 p.","ipdsId":"IP-123913","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2020943118","text":"Publisher Index Page"},{"id":382060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Norris Geyser Basin, Steamboat Geyser, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.71465730667114,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.71879196233473\n ],\n [\n -110.6957745552063,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.73068351783913\n ],\n [\n -110.71465730667114,\n 44.71879196233473\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"118","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Reed, Mara","contributorId":247557,"corporation":false,"usgs":false,"family":"Reed","given":"Mara","affiliations":[],"preferred":false,"id":807890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munoz-Saez, Carolina","contributorId":131167,"corporation":false,"usgs":false,"family":"Munoz-Saez","given":"Carolina","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":807891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hajimirza, Sahand","contributorId":247558,"corporation":false,"usgs":false,"family":"Hajimirza","given":"Sahand","email":"","affiliations":[],"preferred":false,"id":807892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Sin-Mei","contributorId":175479,"corporation":false,"usgs":false,"family":"Wu","given":"Sin-Mei","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":807893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barth, Anna","contributorId":247559,"corporation":false,"usgs":false,"family":"Barth","given":"Anna","email":"","affiliations":[],"preferred":false,"id":807894,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":807895,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rasht-Behesht, Majid","contributorId":247560,"corporation":false,"usgs":false,"family":"Rasht-Behesht","given":"Majid","email":"","affiliations":[],"preferred":false,"id":807896,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Karplus, M.S","contributorId":205767,"corporation":false,"usgs":false,"family":"Karplus","given":"M.S","email":"","affiliations":[{"id":37164,"text":"University of Texas, El Paso","active":true,"usgs":false}],"preferred":false,"id":807897,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":807898,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manga, Michael","contributorId":131168,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. 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This article represents a step toward generalizing and simplifying the procedure for constructing an inversion‐based seismic hazard source model for an interconnected fault system, including the specification of adjustable segmentation constraints. A very simple example is used to maximize understandability and to counter the notion that an inversion approach is only applicable when an abundance of data is available. Also exemplified is how to construct a range of models to adequately represent epistemic uncertainties (which should be a high priority in any hazard assessment). Opportunity is also taken to address common concerns and misunderstandings associated with the third Uniform California Earthquake Rupture Forecast, including the seemingly disproportionate number of large‐magnitude events, and how well hazard is resolved given the overall problem is very underdetermined. However, the main aim of this article is to provide a general protocol for constructing such models.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200219","usgsCitation":"Field, E.H., Milner, K.R., and Page, M.T., 2021, Generalizing the inversion‐based PSHA source model for an interconnected fault system: Bulletin of the Seismological Society of America, v. 111, no. 1, p. 371-390, https://doi.org/10.1785/0120200219.","productDescription":"20 p.","startPage":"371","endPage":"390","ipdsId":"IP-122019","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":381034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":806224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":806225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":806226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249204,"text":"70249204 - 2021 - Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","interactions":[],"lastModifiedDate":"2023-10-02T11:46:50.38526","indexId":"70249204","displayToPublicDate":"2020-11-17T06:41:13","publicationYear":"2021","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":"Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.","docAbstract":"

We demonstrate successful crustal imaging via teleseismic P‐wave coda autocorrelation, using data recorded on a 261 station array of vertical‐component high‐frequency geophones in the area of the Bighorn Mountains, Wyoming, U.S.A. We autocorrelate the P‐wave coda of 30 teleseismic events and use phase‐weighted stacking to yield seismic profiles comparable to low‐passed versions of those produced via controlled‐source vertical seismic reflection. Our process recovers reflections from the bottoms of the Bighorn and Powder River basins that flank the Bighorn Mountains. We also identify a mid‐crustal reflector that aligns with a region of increased reflectivity, previously interpreted as a Precambrian province boundary. Our results demonstrate the utility of crustal imaging with teleseismic P‐wave coda energy using modern large‐array seismic data, and they corroborate previous interpretations of crustal structures in the study area.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120200177","usgsCitation":"Plescia, S., Sheehan, A., Haines, S.S., Worthington, L., Cook, S., and Ball, J., 2021, Teleseismic P‐qave coda autocorrelation imaging of crustal and basin structure, Bighorn Mountains Region, Wyoming, U.S.A.: Bulletin of the Seismological Society of America, v. 111, no. 1, p. 466-475, https://doi.org/10.1785/0120200177.","productDescription":"10 p.","startPage":"466","endPage":"475","ipdsId":"IP-108350","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":421453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bighorn Mountains Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.53036009634793,\n 45.00579338169956\n ],\n [\n -109.53036009634793,\n 43.947553823269516\n ],\n [\n -105.24569212759789,\n 43.947553823269516\n ],\n [\n -105.24569212759789,\n 45.00579338169956\n ],\n [\n -109.53036009634793,\n 45.00579338169956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"111","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Plescia, Steven","contributorId":330367,"corporation":false,"usgs":false,"family":"Plescia","given":"Steven","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":884794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Anne","contributorId":330369,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":884795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haines, Seth S. 0000-0003-2611-8165 shaines@usgs.gov","orcid":"https://orcid.org/0000-0003-2611-8165","contributorId":1344,"corporation":false,"usgs":true,"family":"Haines","given":"Seth","email":"shaines@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":884796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worthington, Lindsay","contributorId":330371,"corporation":false,"usgs":false,"family":"Worthington","given":"Lindsay","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":884797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Scott","contributorId":330373,"corporation":false,"usgs":false,"family":"Cook","given":"Scott","email":"","affiliations":[{"id":78873,"text":"Tricon Geophysics","active":true,"usgs":false}],"preferred":false,"id":884798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ball, Justin","contributorId":330374,"corporation":false,"usgs":false,"family":"Ball","given":"Justin","email":"","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":884799,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216698,"text":"70216698 - 2021 - Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","interactions":[],"lastModifiedDate":"2020-12-01T13:34:28.581683","indexId":"70216698","displayToPublicDate":"2020-11-13T07:32:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts","docAbstract":"

The Mainstems data model implements the catchment and flowpath concepts from WaterML2 Part 3: Surface Hydrology Features (HY_Features) for persistent, cross-scale, identification of hydrologic features. The data model itself provides a focused and lightweight method to describe hydrologic networks with minimum but sufficient information. The design is intended to provide a model for data integration that can be used for network navigation and persistent hydrologic indexing (hydrographic addressing) functionality. Mainstems is designed to provide long-term stability with minimal maintenance requirements. The data model is not meant to advance hydrologic process representation or uniquely represent geomorphic characteristics. The principle assumption in Mainstems is that all drainage basins have one - and only one - headwater source area and a single mainstem that flows to a single outlet. Using these base feature types, (headwater, outlet, mainstem, and drainage basin) a nested set of drainage basins - and the associated dendritic network of mainstems - can be identified.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2020.104927","usgsCitation":"Blodgett, D.L., Johnson, J.M., Sondheim, M., Wieczorek, M., and Frazier, N., 2021, Mainstems: A logical data model implementing mainstem and drainage basin feature types based on WaterML2 Part 3: HY Features concepts: Environmental Modelling and Software, v. 135, 104927, 11 p., https://doi.org/10.1016/j.envsoft.2020.104927.","productDescription":"104927, 11 p.","ipdsId":"IP-114535","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":454267,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2020.104927","text":"Publisher Index Page"},{"id":436644,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H0PTRH","text":"USGS data release","linkHelpText":"mainstems workflow: HU12 NHDPlusV2 NHDPlus HiRes Matching"},{"id":436643,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O15C70","text":"USGS data release","linkHelpText":"Mainstem Rivers of the World based on MERIT hydrography and Natural Earth names"},{"id":436642,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BTKP3T","text":"USGS data release","linkHelpText":"Mainstem Rivers of the Conterminous United States"},{"id":380907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":805916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, J. Micheal 0000-0002-5288-8350","orcid":"https://orcid.org/0000-0002-5288-8350","contributorId":245322,"corporation":false,"usgs":false,"family":"Johnson","given":"J.","email":"","middleInitial":"Micheal","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":805917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sondheim, Mark","contributorId":245323,"corporation":false,"usgs":false,"family":"Sondheim","given":"Mark","email":"","affiliations":[{"id":40433,"text":"NRCAN","active":true,"usgs":false}],"preferred":false,"id":805918,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805919,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frazier, Nels","contributorId":245324,"corporation":false,"usgs":false,"family":"Frazier","given":"Nels","email":"","affiliations":[{"id":36995,"text":"NWS","active":true,"usgs":false}],"preferred":false,"id":805920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217153,"text":"70217153 - 2021 - From satellites to frogs: Quantifying ecohydrological change, drought mitigation, and population demography in desert meadows","interactions":[],"lastModifiedDate":"2021-01-07T13:34:01.062177","indexId":"70217153","displayToPublicDate":"2020-11-12T07:32:38","publicationYear":"2021","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":"From satellites to frogs: Quantifying ecohydrological change, drought mitigation, and population demography in desert meadows","docAbstract":"

Increasing frequency and severity of droughts have motivated natural resource managers to mitigate harmful ecological and hydrological effects of drought, but drought mitigation is an emerging science and evaluating its effectiveness is difficult. We examined ecohydrological responses of drought mitigation actions aimed at conserving populations of the Columbia spotted frog (Rana luteiventris) in a semi-arid valley in Nevada, USA. Abundance of this rare frog had declined precipitously after multiple droughts. Mitigation included excavating ponds to increase available surface water and installing earthen dams to raise water tables. We assessed responses of riparian vegetation to mitigation using a 30-year time series of satellite-derived Normalized Difference Vegetation Index (NDVI) and gridded weather data. We then analyzed a 23-year mark-recapture dataset to evaluate the effects of drought mitigation and NDVI on the probability of frog survival and rates of recruitment. After accounting for interannual precipitation variability, we found that NDVI increased significantly from before to after drought mitigation, suggesting that mitigation influenced the hydrology and vegetation of the meadows. Frog survival increased with NDVI, but mitigation had a stronger effect than NDVI suggesting that excavated mitigation ponds were particularly important for frog survival during drought. In contrast, frog recruitment was associated with NDVI more than mitigation, but only in meadows where NDVI was dependent on precipitation. At meadows with available groundwater, recruitment was associated with mitigation ponds. These findings suggest that mitigation ponds are critical for juvenile frogs to recruit into the adult population, but recruitment can also be increased by raising water tables in meadows lacking groundwater sources. Lagged recruitment (i.e., effects on larvae and juveniles) was negatively associated with NDVI. This study illustrates the ecohydrological complexity of drought mitigation and demonstrates novel ways to assess the effectiveness of drought mitigation using time series of readily available satellite imagery and organismal data.



","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.143632","usgsCitation":"Pilliod, D., Hausner, M.B., and Scherer, R.D., 2021, From satellites to frogs: Quantifying ecohydrological change, drought mitigation, and population demography in desert meadows: Science of the Total Environment, v. 758, 143632, 15 p., https://doi.org/10.1016/j.scitotenv.2020.143632.","productDescription":"143632, 15 p.","ipdsId":"IP-118807","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":454274,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.143632","text":"Publisher Index Page"},{"id":381995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"758","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":807742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hausner, Mark B.","contributorId":204145,"corporation":false,"usgs":false,"family":"Hausner","given":"Mark","email":"","middleInitial":"B.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":807743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scherer, Rick D.","contributorId":97368,"corporation":false,"usgs":false,"family":"Scherer","given":"Rick","email":"","middleInitial":"D.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":807744,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229034,"text":"70229034 - 2021 - Feeling the squeeze: Adult run size and habitat availability limit juvenile river herring densities in lakes","interactions":[],"lastModifiedDate":"2022-02-28T17:27:39.106405","indexId":"70229034","displayToPublicDate":"2020-11-11T11:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Feeling the squeeze: Adult run size and habitat availability limit juvenile river herring densities in lakes","docAbstract":"

Maximum densities of juvenile river herring (Alewife Alosa pseudoharengus and Blueback Herring A. aestivalis) vary among freshwater lakes, likely due to densities of adult spawners. Differences in habitat availability and lake water quality may also contribute to variation in juvenile river herring productivity between populations, yet these relationships have not been tested across a large geographic scope. In this study we investigated relationships between juvenile river herring densities and (1) spawning adult river herring densities, (2) lake habitat availability, and (3) lake water quality in 29 freshwater lakes in the northeastern USA. Purse seines were used at night to sample juvenile river herring monthly in June–August 2014 and 2015, with concurrent collection of lake-specific physical (e.g., lake surface area, mean depth, depth to thermocline), chemical (e.g., nitrogen, phosphorus, dissolved organic carbon [DOC]), and biological (chlorophyll a, adult spawning density) data. Spawning adult density (number of adults per surface area of lake) explained 66.6% of the variation in juvenile densities using a generalized additive model. Juvenile densities increased with increasing adult density, peaking at roughly 1,000 adults/ha, and then declined at higher adult densities, suggesting a limit to carrying capacity in juvenile production. Linear mixed-effects models revealed that differences in water quality and habitat across lakes explained additional variation in juvenile densities. Specifically, DOC was negatively related to juvenile densities, suggesting that DOC limits the amount of suitable, well-oxygenated epilimnion habitat available to juvenile river herring in late summer. Our results can be used to help understand expected juvenile production based on adult density within a lake, to inform expectations about juvenile growth and survival, and to understand the mechanisms for how changes in habitat availability and water quality affect river herring populations.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10282","usgsCitation":"Devine, M.T., Rosset, J., Roy, A.H., Gahagan, B.I., Armstrong, M.P., Whiteley, A., and Jordaan, A., 2021, Feeling the squeeze: Adult run size and habitat availability limit juvenile river herring densities in lakes: Transactions of the American Fisheries Society, v. 150, no. 2, p. 207-221, https://doi.org/10.1002/tafs.10282.","productDescription":"16 p.","startPage":"207","endPage":"221","ipdsId":"IP-120456","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.66455078125,\n 44.6061127451739\n ],\n [\n -70.927734375,\n 44.62175409623324\n ],\n [\n -72.1142578125,\n 43.723474896114794\n ],\n [\n -73.4326171875,\n 41.31082388091818\n ],\n [\n -71.103515625,\n 41.1290213474951\n ],\n [\n -70.0048828125,\n 41.32732632036622\n ],\n [\n -69.54345703125,\n 41.88592102814744\n ],\n [\n -70.400390625,\n 42.827638636242284\n ],\n [\n -69.78515625,\n 43.48481212891603\n ],\n [\n -68.84033203125,\n 44.02442151965934\n ],\n [\n -68.66455078125,\n 44.6061127451739\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"150","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Devine, Matthew T.","contributorId":204986,"corporation":false,"usgs":false,"family":"Devine","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":836323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosset, Julianne","contributorId":197446,"corporation":false,"usgs":false,"family":"Rosset","given":"Julianne","email":"","affiliations":[],"preferred":false,"id":836324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gahagan, Benjamin I.","contributorId":200168,"corporation":false,"usgs":false,"family":"Gahagan","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":836325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Armstrong, Michael P.","contributorId":286850,"corporation":false,"usgs":false,"family":"Armstrong","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":40132,"text":"Massachusetts Division of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":836326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whiteley, Andrew R.","contributorId":286853,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew R.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":836327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordaan, Adrian","contributorId":210892,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":836328,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216363,"text":"70216363 - 2021 - A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","interactions":[],"lastModifiedDate":"2021-06-01T17:01:46.95513","indexId":"70216363","displayToPublicDate":"2020-11-11T09:23:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A lagrangian-to-eulerian metric to identify estuarine pelagic habitats","docAbstract":"

Estuaries are among the world’s most productive ecosystems, but recent natural and anthropogenic changes have stressed these ecosystems. Tools to assess estuarine pelagic habitats are important to support and maintain healthy ecosystem function. In this work, we demonstrate that estuarine pelagic habitats can be identified by a simple ratio, termed the LE ratio, that takes into account the tidal excursion along a channel (a Lagrangian length scale) and the distance along that channel (an Eulerian length scale). To develop and assess this concept, numerical simulations of the 1D advection–dispersion equation of a conservative tracer and tidal excursion estimates based on data were used to formulize a conceptual model and to define exchange zones within a tidal channel. This conceptual model was then used to predict the extent of pelagic habitats in a terminal channel network in the Sacramento–San Joaquin Delta. Exchange zones mapped onto these channels were found to be in good agreement with independent estimates of residence time. Sensitivity analyses of the numerical model suggest that productive pelagic habitats can be expanded by a factor of 2 by either increasing dispersion or increasing spring–neap variability in mean tidal velocity. Such changes can also enhance flushing in upper channel reaches. These findings are relevant for tidal marsh restoration projects that aim to expand beneficial aquatic habitats by varying exchange or residence time over the spring–neap cycle, because this variability may interact synergistically with varying rates of phytoplankton growth due to spatiotemporal changes in environmental conditions.

","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00861-7","usgsCitation":"Stumpner, P., Burau, J.R., and Forrest, A.L., 2021, A lagrangian-to-eulerian metric to identify estuarine pelagic habitats: Estuaries and Coasts, v. 44, p. 1231-1249, https://doi.org/10.1007/s12237-020-00861-7.","productDescription":"19 p.","startPage":"1231","endPage":"1249","ipdsId":"IP-113036","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":436645,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VR4EHS","text":"USGS data release","linkHelpText":"Numerical Simulation of 1D Advection-Dispersion Equation of Conservative Tracer with Oscillating Tidal Flows"},{"id":380509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","noUsgsAuthors":false,"publicationDate":"2020-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forrest, Alexander L. 0000-0002-7853-9765","orcid":"https://orcid.org/0000-0002-7853-9765","contributorId":244855,"corporation":false,"usgs":false,"family":"Forrest","given":"Alexander","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":804811,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216403,"text":"70216403 - 2021 - A 450-year record of environmental change from Castle Lake, California (USA), inferred from diatoms and organic geochemistry","interactions":[],"lastModifiedDate":"2021-01-19T16:09:45.802233","indexId":"70216403","displayToPublicDate":"2020-11-11T08:45:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"A 450-year record of environmental change from Castle Lake, California (USA), inferred from diatoms and organic geochemistry","docAbstract":"

A 39-cm sediment core from Castle Lake, California (USA) spans the last ~ 450 years and was analyzed for diatoms and organic geochemistry (δ15N, δ13C, and C:N), with the goal of determining sensitivity to natural climate variation and twentieth century anthropogenic effects. Castle Lake is a subalpine, nitrogen-limited lake with ~ 5 months of annual ice cover. Human impacts include light recreational use, past fish stocking, and experimental use by the Castle Lake Research Station. The base of the core (below 32 cm; pre mid-1700s) represents the period of maximum ice cover. In contrast, the end of the Little Ice Age (mid 1700s–early 1800s) is dominated by cyclotelloids (mostly Discostella stelligera), indicating significant open-water periods, a condition that persisted into the early 1900s. Cyclotelloids began to decline in the 1960s and were replaced by the Fragilaria tenera grp. (peak in 1970s), succeeded by Asterionella formosa (peak ~ 2010), and accompanied by a reduction in δ15N values and a decrease in C:N that may represent increased atmospheric nitrogen deposition. Another anthropogenic signal was discerned in the core and was interpreted to be the result of an ammonium nitrate fertilization experiment of the epilimnion that was conducted in 1980 and 1981. This signal was manifested in the core largely by a negative excursion in δ15N, possibly caused by fractionation during denitrification in surface sediment. A phytoplankton monitoring dataset collected by the Castle Lake Research Station from 1967 to 1984 corroborates the timing of increased araphid euplanktonic species in the 1970s, and increases in two benthic diatoms (Staurosirella pinnata and Tabellaria fenestrata), entrained in the phytoplankton tows during the experimentation years. Both ice cover and nitrogen addition appear to be strong drivers that affected the lake diatoms, although additional drivers, such as fish stocking and associated cascade effects need further exploration. These data will be helpful for interpreting longer core records from Castle Lake, should the opportunity arise, as well as cores from similar systems in the region.


","language":"English","publisher":"Springer","doi":"10.1007/s10933-020-00160-y","usgsCitation":"Noble, P., McGaughey, G.A., Rosen, M.R., Fuller, C.C., Aquino-Lopez, M.A., and Chandra, S., 2021, A 450-year record of environmental change from Castle Lake, California (USA), inferred from diatoms and organic geochemistry: Journal of Paleolimnology, v. 65, p. 201-217, https://doi.org/10.1007/s10933-020-00160-y.","productDescription":"17 p.","startPage":"201","endPage":"217","ipdsId":"IP-114393","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":380531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Castle Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38915443420409,\n 41.22153522014608\n ],\n [\n -122.37808227539061,\n 41.22153522014608\n ],\n [\n -122.37808227539061,\n 41.23276752756589\n ],\n [\n -122.38915443420409,\n 41.23276752756589\n ],\n [\n -122.38915443420409,\n 41.22153522014608\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","noUsgsAuthors":false,"publicationDate":"2020-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Noble, Paula","contributorId":198953,"corporation":false,"usgs":false,"family":"Noble","given":"Paula","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":804913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGaughey, Gary A.","contributorId":244908,"corporation":false,"usgs":false,"family":"McGaughey","given":"Gary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":804919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804920,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":804921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aquino-Lopez, Marco A.","contributorId":244909,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":804922,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":804923,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228623,"text":"70228623 - 2021 - Testing a continuous measure of recreation specialization among birdwatchers","interactions":[],"lastModifiedDate":"2022-02-15T13:08:47.516719","indexId":"70228623","displayToPublicDate":"2020-11-11T07:04:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1909,"text":"Human Dimensions of Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Testing a continuous measure of recreation specialization among birdwatchers","docAbstract":"

Recreation specialization is a framework that can be used to explain the variation among outdoor recreationists’ preferences, attitudes, and behaviors. Recreation specialization has been operationalized using several approaches, including summative indices, cluster analysis, and self-classification categorical measures. Although these approaches measure the multiple dimensions of the framework, they may not reflect the relative contribution of the dimensions to individuals’ degree of engagement. We illustrate an approach that uses second-order confirmatory factor analysis (CFA) factor scores as weights to determine a person’s degree of recreation specialization and compares the CFA-based results to those derived from cluster analysis. This approach permits the use of a broader set of statistical tests when compared to categorical specialization measures and provides information about the distribution of responses. Data were collected from an online survey of eBird registrants from the United States.

","language":"English","publisher":"Taylor and Francis","doi":"10.1080/10871209.2020.1843741","usgsCitation":"Harshaw, H., Cole, N.W., Dayer, A., Rutter, J., Fulton, D.C., Raedeke, A., Schuster, R., and Duberstein, J., 2021, Testing a continuous measure of recreation specialization among birdwatchers: Human Dimensions of Wildlife, v. 26, no. 5, p. 472-480, https://doi.org/10.1080/10871209.2020.1843741.","productDescription":"9 p.","startPage":"472","endPage":"480","ipdsId":"IP-118798","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454279,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/102424","text":"External Repository"},{"id":395970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Harshaw, H.W.","contributorId":278635,"corporation":false,"usgs":false,"family":"Harshaw","given":"H.W.","email":"","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":834860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Nicholas W. 0000-0003-1204-971X","orcid":"https://orcid.org/0000-0003-1204-971X","contributorId":278636,"corporation":false,"usgs":true,"family":"Cole","given":"Nicholas","email":"","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":834861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dayer, Ashley A.","contributorId":278637,"corporation":false,"usgs":false,"family":"Dayer","given":"Ashley A.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rutter, Jonathan D.","contributorId":278638,"corporation":false,"usgs":false,"family":"Rutter","given":"Jonathan D.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raedeke, Andrew H.","contributorId":278640,"corporation":false,"usgs":false,"family":"Raedeke","given":"Andrew H.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schuster, Rudy 0000-0003-2353-8500 schusterr@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-8500","contributorId":3119,"corporation":false,"usgs":true,"family":"Schuster","given":"Rudy","email":"schusterr@usgs.gov","affiliations":[],"preferred":true,"id":834865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duberstein, Jennifer N.","contributorId":278642,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jennifer N.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":834866,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228599,"text":"70228599 - 2021 - Perceived constraints and negotiations to trout fishing in Georgia based on angler specialization level","interactions":[],"lastModifiedDate":"2022-02-14T17:53:49.304628","indexId":"70228599","displayToPublicDate":"2020-11-10T11:45:21","publicationYear":"2021","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":"Perceived constraints and negotiations to trout fishing in Georgia based on angler specialization level","docAbstract":"

Anglers face constraints that influence participation and dropout rates. Some recreational anglers may be able to negotiate constraints by altering the timing or frequency of participation, acquiring new skills, or modifying nonrecreational aspects such as family or work responsibilities. We consider data collected via a mail survey from Georgia-resident trout license holders to identify both perceived constraints and strategies used to negotiate them. To capture variation among anglers, survey responses were grouped by level of angler specialization using K-means cluster analysis, which resulted in a three-cluster solution of most, moderately, and least specialized anglers. Analyses of variance were used to detect potential differences among the three specialization clusters. Tests revealed that the least specialized anglers experienced constraints more intensely than the most or moderately specialized anglers. Likewise, least specialized anglers were less able to negotiate constraints when compared to the most or moderately specialized anglers. However, the least specialized anglers used negotiation strategies involving overcoming perceived lack of skill more intensely than their counterparts. The most intensely experienced constraints overall were lack of time due to work or family obligations and distance to Georgia’s trout waters from home. The most intensely used negotiation strategies overall were “learn to enjoy being outside and stress less about catching fish” and “encourage family or friends to go fishing with me.” This research benefits fishery managers by providing a method of identifying angling groups that perceive more constraints and are less likely to overcome these constraints through constraint negotiation strategies. With this information, managers may choose to tailor efforts towards reducing constraints for angling groups that have low participation and may drop out of the activity all together.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10540","usgsCitation":"TenHarmsel, H., Boley, B., Irwin, B.J., and Jennings, C.A., 2021, Perceived constraints and negotiations to trout fishing in Georgia based on angler specialization level: North American Journal of Fisheries Management, v. 41, no. 1, p. 115-129, https://doi.org/10.1002/nafm.10540.","productDescription":"15 p.","startPage":"115","endPage":"129","ipdsId":"IP-118672","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454282,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10540","text":"Publisher Index Page"},{"id":395901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"TenHarmsel, H. J.","contributorId":276309,"corporation":false,"usgs":false,"family":"TenHarmsel","given":"H. J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boley, B. B.","contributorId":276310,"corporation":false,"usgs":false,"family":"Boley","given":"B. B.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":834732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennings, Cecil A. 0000-0002-6159-6026 jennings@usgs.gov","orcid":"https://orcid.org/0000-0002-6159-6026","contributorId":874,"corporation":false,"usgs":true,"family":"Jennings","given":"Cecil","email":"jennings@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834734,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228597,"text":"70228597 - 2021 - Clothianidin decomposition in Missouri wetland soils","interactions":[],"lastModifiedDate":"2022-02-14T17:58:00.120595","indexId":"70228597","displayToPublicDate":"2020-11-09T11:55:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Clothianidin decomposition in Missouri wetland soils","docAbstract":"

Neonicotinoid pesticides can persist in soils for extended time periods; however, they also have a high potential to contaminate ground and surface waters. Studies have reported negative effects associated with neonicotinoids and nontarget taxa, including aquatic invertebrates, pollinating insect species, and insectivorous birds. This study evaluated factors associated with clothianidin (CTN) degradation and sorption in Missouri wetland soils to assess the potential for wetland soils to mitigate potential environmental risks associated with neonicotinoids. Solid-to-solution partition coefficients (Kd) for CTN sorption to eight wetland soils were determined via single-point sorption experiments, and sorption isotherm experiments were conducted using the two most contrasting soils. Clothianidin degradation was determined under oxic and anoxic conditions over 60 d. Degradation data were fit to zero- and first-order kinetic decay models to determine CTN half-life (t0.5). Sorption results indicated CTN sorption to wetland soil was relatively weak (average Kd, 3.58 L kg–1); thus, CTN has the potential to be mobile and bioavailable within wetland soils. However, incubation results showed anoxic conditions significantly increased CTN degradation rates in wetland soils (anoxic average t0.5, 27.2 d; oxic average t0.5, 149.1 d). A significant negative correlation was observed between anoxic half-life values and soil organic C content (r2 = .782; p = .046). Greater CTN degradation rates in wetland soils under anoxic conditions suggest that managing wetlands to facilitate anoxic conditions could mitigate CTN presence in the environment and reduce exposure to nontarget organisms.

","language":"English","publisher":"ACSESS","doi":"10.1002/jeq2.20175","usgsCitation":"Beringer, C.J., Goyne, K., Lerch, R.N., Webb, E.B., and Mengel, D., 2021, Clothianidin decomposition in Missouri wetland soils: Journal of Environmental Quality, v. 50, no. 1, p. 241-251, https://doi.org/10.1002/jeq2.20175.","productDescription":"11 p.","startPage":"241","endPage":"251","ipdsId":"IP-118570","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454287,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jeq2.20175","text":"External Repository"},{"id":395903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Beringer, C. J.","contributorId":276297,"corporation":false,"usgs":false,"family":"Beringer","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":834719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goyne, K. W.","contributorId":273205,"corporation":false,"usgs":false,"family":"Goyne","given":"K. W.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":834720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lerch, R. N.","contributorId":276298,"corporation":false,"usgs":false,"family":"Lerch","given":"R.","email":"","middleInitial":"N.","affiliations":[{"id":56949,"text":"USDA-Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":834721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mengel, D.","contributorId":244519,"corporation":false,"usgs":false,"family":"Mengel","given":"D.","email":"","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":834723,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216472,"text":"70216472 - 2021 - Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","interactions":[],"lastModifiedDate":"2021-10-04T16:46:47.880285","indexId":"70216472","displayToPublicDate":"2020-11-09T07:45:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale","docAbstract":"
  1. Stress gradients influence many ecosystem processes and properties, including ecosystem recovery from and resistance to disturbance. While recent analytical approaches have advanced multivariate metrics of ecosystem resilience that allow quantification of conceptual resilience models and identification of thresholds of state change, these approaches are not often translated to landscape scales.
  2. Using natural and restored salt marshes in Louisiana, USA, we quantified plant community recovery and resistance metrics along flooding stress gradients. n‐dimensional hypervolumes of plant community biomass and structure were simulated using field data collected from disturbance‐recovery experiments. The relationships between multivariate resilience metrics and flooding stress gradients were then mapped at community‐ and landscape‐relevant scales by scaling with airborne‐derived data across the region.
  3. Greater pre‐disturbance abiotic stress decreased live belowground, but not aboveground, biomass, and ultimately led to lower post‐disturbance total recovery, recovery rates, and resistance of plant communities. Vegetated plots flooded >52% of the time transitioned to an alternative, unvegetated state after disturbance. Mapping revealed differences in spatial patterns of resilience‐ highlighting low, interior marsh edges as especially vulnerable to the combination of chronic flooding stress and acute disturbance. At the landscape scale, approximately half of the area (48%) is vulnerable to state change after pulse disturbances.


Synthesis. Ultimately, we quantify the ball‐and‐cup conceptual model for a salt marsh ecosystem and its alternative state, mudflat. We find that increasing abiotic stress due to climate change diminishes ecosystem resilience, but the interaction with common episodic disturbances is necessary to reveal transitions to alternative states and quantify state change thresholds. Quantifying and mapping resilience and where alternative states may exist in this fashion improves ecologists’ ability to investigate the mechanisms of stress gradient control on emergent ecosystem properties, while providing spatially explicit resources for managing ecosystems according to their projected resilience.

","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13552","usgsCitation":"Jones, S., Stagg, C., Yando, E.S., James, W.R., Buffington, K., and Hester, M.W., 2021, Stress gradients interact with disturbance to reveal alternative states in salt marsh: Multivariate resilience at the landscape scale: Journal of Ecology, v. 109, no. 9, p. 3211-3223, https://doi.org/10.1111/1365-2745.13552.","productDescription":"13 p.","startPage":"3211","endPage":"3223","ipdsId":"IP-121938","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":436646,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FNH7F6","text":"USGS data release","linkHelpText":"Field and simulated data to construct hypervolumes of coastal wetland plant states for resilience quantification, Louisiana, USA 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\"}}]}","volume":"109","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":222380,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":805230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yando, Erik S.","contributorId":127788,"corporation":false,"usgs":false,"family":"Yando","given":"Erik","email":"","middleInitial":"S.","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":805231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"James, W. Ryan","contributorId":245037,"corporation":false,"usgs":false,"family":"James","given":"W.","email":"","middleInitial":"Ryan","affiliations":[{"id":13722,"text":"University of Louisiana-Lafayette","active":true,"usgs":false}],"preferred":false,"id":805232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hester, Mark W.","contributorId":195572,"corporation":false,"usgs":false,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":34316,"text":"University of Louisiana at Lafayette, Lafayette, LA, USA","active":true,"usgs":false}],"preferred":false,"id":805234,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216485,"text":"70216485 - 2021 - Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast","interactions":[],"lastModifiedDate":"2021-01-19T16:23:52.964451","indexId":"70216485","displayToPublicDate":"2020-11-07T08:25:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast","docAbstract":"

Context

Coastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely.

Objectives

To examine the role of land cover diversity and composition in landscape response to SLR across the northeastern United States.

Methods

Using an existing probabilistic framework, we quantify the probability of inundation, a measure of vulnerability, under different SLR scenarios on the coastal landscape. Resistant areas—wherein a dynamic response is anticipated—are defined as unlikely (p < 0.33) to inundate. Results are assessed regionally for different land cover types and at 26 sites representing varying levels of land cover diversity.

Results

Modeling results suggest that by the 2050s, 44% of low-lying, habitable land in the region is unlikely to inundate, further declining to 36% by the 2080s. In addition to a decrease in SLR resistance with time, these results show an increasing uncertainty that the coastal landscape will continue to evolve in response to SLR as it has in the past. We also find that resistance to SLR is correlated with land cover composition, wherein sites containing land cover types adaptable to SLR impacts show greater potential to undergo biogeomorphic state shifts rather than inundating with time.

Conclusions

Our findings support other studies that have highlighted the importance of ecological composition and diversity in stabilizing the physical landscape and suggest that flexible planning strategies, such as adaptive management, are particularly well suited for SLR preparation in diverse coastal settings.

","language":"English","publisher":"Springer","doi":"10.1007/s10980-020-01136-z","usgsCitation":"Lentz, E.E., Zeigler, S.L., Thieler, E.R., and Plant, N.G., 2021, Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast: Landscape Ecology, v. 36, p. 223-241, https://doi.org/10.1007/s10980-020-01136-z.","productDescription":"9 p.","startPage":"223","endPage":"241","ipdsId":"IP-101344","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":454290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-020-01136-z","text":"Publisher Index Page"},{"id":380684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.169921875,\n 44.10336537791152\n ],\n [\n -70.751953125,\n 44.26093725039923\n ],\n [\n -73.05908203125,\n 42.261049162113856\n ],\n [\n -76.7724609375,\n 39.639537564366684\n ],\n [\n -78.37646484375,\n 37.666429212090605\n ],\n [\n -77.71728515624999,\n 36.58024660149866\n ],\n [\n -75.34423828125,\n 36.43896124085945\n ],\n [\n -75.73974609375,\n 37.3002752813443\n ],\n [\n -74.0478515625,\n 39.977120098439634\n ],\n [\n -71.9384765625,\n 40.81380923056958\n ],\n [\n -69.80712890625,\n 41.178653972331674\n ],\n [\n -69.89501953125,\n 42.049292638686836\n ],\n [\n -70.64208984375,\n 42.8115217450979\n ],\n [\n -69.169921875,\n 44.10336537791152\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationDate":"2020-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeigler, Sara L. 0000-0002-5472-769X szeigler@usgs.gov","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":169601,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","email":"szeigler@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":805386,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216287,"text":"70216287 - 2021 - Hydrogeochemistry in the Yukon-Tanana Upland region of east-central Alaska: Possible exploration tool for porphyry-style deposits","interactions":[],"lastModifiedDate":"2021-01-19T16:03:38.070106","indexId":"70216287","displayToPublicDate":"2020-11-05T07:28:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeochemistry in the Yukon-Tanana Upland region of east-central Alaska: Possible exploration tool for porphyry-style deposits","docAbstract":"

A hydrogeochemical study using high resolution ICP-MS was undertaken at the Taurus and other porphyry Cu-Mo(-Au) occurrences and Ag-Au-Cu (+/- Pb, Zn) occurrences with epithermal-style characteristics in the Yukon-Tanana upland region of eastern Alaska. Surface water samples were collected from 30 sites on creeks that drain known deposits and occurrences and surrounding presumably unmineralized areas. Water samples for the entire ∼9 km length of McCord Creek, which drains the Taurus deposit, and those from streams draining the areas at and near the Bluff and Dennison porphyry occurrences have high conductivity values (492 to 1250 μS/cm) and consistently high concentrations of B (3-250 μg/L), Co (2.3 to 42 μg/L), Mn (339 to 4750 μg/L), Re (0.012 to 0.1 μg/L), and SO42- (>200 mg/L), all of which are well above the median value for this data set and significantly greater than concentrations in water samples from the unmineralized areas. These are the best pathfinder elements specifically for porphyry style deposits because most of them are not anomalous in waters near epithermal occurrences. Copper concentrations are high (up to 115 μg/L) in some low-pH water samples from McCord Creek and drainages around Bluff, and a few near neutral pH waters have high molybdenum (>1 μg/L), but neither element is consistently anomalous in close vicinity to the porphyry occurrences, possibly due to a metal-poor, sulfide-poor leached cap (average of ∼50 m) that overlies supergene and hypogene mineralized zones and is the dominant rock at surface. High concentrations of Bi and/or As occur in many waters associated with mineralized areas, particularly the Bluff and Dennison occurrences. In general, the element associations related to porphyry deposits reflect the deposit mineralogy, as well as size of the footprint related to alteration and mineralization.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2020.104821","usgsCitation":"Kelley, K.D., and Graham, G.E., 2021, Hydrogeochemistry in the Yukon-Tanana Upland region of east-central Alaska: Possible exploration tool for porphyry-style deposits: Applied Geochemistry, v. 124, 104821, 15 p., https://doi.org/10.1016/j.apgeochem.2020.104821.","productDescription":"104821, 15 p.","ipdsId":"IP-118637","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2020.104821","text":"Publisher Index Page"},{"id":380401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon-Tanana Upland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -143.3056640625,\n 62.02152819100765\n ],\n [\n -140.9326171875,\n 62.02152819100765\n ],\n [\n -140.9326171875,\n 65.71255746172102\n ],\n [\n -143.3056640625,\n 65.71255746172102\n ],\n [\n -143.3056640625,\n 62.02152819100765\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":804581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":804582,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216442,"text":"70216442 - 2021 - A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","interactions":[],"lastModifiedDate":"2021-03-05T21:58:59.699233","indexId":"70216442","displayToPublicDate":"2020-11-03T06:58:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity","docAbstract":"

Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2249","usgsCitation":"Sollmann, R., Eaton, M.J., Link, W., Mulundo, P., Ayebare, S., Prinsloo, S., Plumptre, A.J., and Johnson, D., 2021, A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity: Ecological Applications, v. 31, no. 2, e2249, https://doi.org/10.1002/eap.2249.","productDescription":"e2249","ipdsId":"IP-090810","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":454310,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2249","text":"External Repository"},{"id":380583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Sollmann, Rahel 0000-0002-1607-2039","orcid":"https://orcid.org/0000-0002-1607-2039","contributorId":244998,"corporation":false,"usgs":false,"family":"Sollmann","given":"Rahel","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":805121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":805123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulundo, Paul","contributorId":245000,"corporation":false,"usgs":false,"family":"Mulundo","given":"Paul","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayebare, Samuel","contributorId":245001,"corporation":false,"usgs":false,"family":"Ayebare","given":"Samuel","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Prinsloo, Sarah","contributorId":245002,"corporation":false,"usgs":false,"family":"Prinsloo","given":"Sarah","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":805126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Plumptre, Andrew J.","contributorId":213154,"corporation":false,"usgs":false,"family":"Plumptre","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":805127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, D.S.","contributorId":245003,"corporation":false,"usgs":false,"family":"Johnson","given":"D.S.","affiliations":[{"id":17856,"text":"National Marine Fisheries Service, NOAA","active":true,"usgs":false}],"preferred":false,"id":805128,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216402,"text":"70216402 - 2021 - Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","interactions":[],"lastModifiedDate":"2021-02-03T23:53:16.73024","indexId":"70216402","displayToPublicDate":"2020-10-31T08:26:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics","docAbstract":"

The increasing availability of high‐frequency freshwater ecosystem metabolism data provides an opportunity to identify links between metabolic regimes, as gross primary production and ecosystem respiration patterns, and consumer energetics with the potential to improve our current understanding of consumer dynamics (e.g., population dynamics, community structure, trophic interactions). We describe a conceptual framework linking metabolic regimes of flowing waters with consumer community dynamics. We use this framework to identify three emerging research needs: (1) quantifying the linkage of metabolism and consumer production data via food web theory and carbon use efficiencies, (2) evaluating the roles of metabolic dynamics and other environmental regimes (e.g., hydrology, light) in consumer dynamics, and (3) determining the degree to which metabolic regimes influence the evolution of consumer traits and phenology. Addressing these needs will improve the understanding of consumer biomass and production patterns as metabolic regimes can be viewed as an emergent property of food webs.

","language":"English","publisher":"Wiley","doi":"10.1002/lol2.10172","usgsCitation":"Ruegg, J., Conn, C.C., Anderson, E., Battin, T., Bernhardt, E., Canadell, M.B., Bonjour, S.M., Hosen, J.D., Marzolf, N.S., and Yackulic, C., 2021, Thinking like a consumer: Linking aquatic basal metabolism and consumer dynamics: Limnology and Oceanography Letters, v. 6, no. 1, p. 1-17, https://doi.org/10.1002/lol2.10172.","productDescription":"17 p.","startPage":"1","endPage":"17","ipdsId":"IP-111583","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10172","text":"Publisher Index Page"},{"id":380529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruegg, Janine","contributorId":244901,"corporation":false,"usgs":false,"family":"Ruegg","given":"Janine","email":"","affiliations":[{"id":49013,"text":"Stream Biofilm and Ecosystem Research, École Fédérale Polytechnique de Lausanne, Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":804903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Caitlin C","contributorId":219914,"corporation":false,"usgs":false,"family":"Conn","given":"Caitlin","email":"","middleInitial":"C","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":804904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Elizabeth P","contributorId":244902,"corporation":false,"usgs":false,"family":"Anderson","given":"Elizabeth P","affiliations":[{"id":49014,"text":"Department of Earth and Environment and Institute of Environment, Florida International University, Miami, FL, USA","active":true,"usgs":false}],"preferred":false,"id":804905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Battin, Tom J","contributorId":244903,"corporation":false,"usgs":false,"family":"Battin","given":"Tom J","affiliations":[{"id":49013,"text":"Stream Biofilm and Ecosystem Research, École Fédérale Polytechnique de Lausanne, Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":804906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernhardt, Emily S.","contributorId":92143,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily S.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false}],"preferred":false,"id":804907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Canadell, Marta Boix","contributorId":244904,"corporation":false,"usgs":false,"family":"Canadell","given":"Marta","email":"","middleInitial":"Boix","affiliations":[{"id":49013,"text":"Stream Biofilm and Ecosystem Research, École Fédérale Polytechnique de Lausanne, Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":804908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonjour, Sophia M","contributorId":244905,"corporation":false,"usgs":false,"family":"Bonjour","given":"Sophia","email":"","middleInitial":"M","affiliations":[{"id":49015,"text":"School of Life Sciences, Arizona State University, Tempe, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":804909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hosen, Jacob D.","contributorId":149188,"corporation":false,"usgs":false,"family":"Hosen","given":"Jacob","email":"","middleInitial":"D.","affiliations":[{"id":17663,"text":"Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, Maryland, United States","active":true,"usgs":false}],"preferred":false,"id":804910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Marzolf, Nicholas S","contributorId":244906,"corporation":false,"usgs":false,"family":"Marzolf","given":"Nicholas","email":"","middleInitial":"S","affiliations":[{"id":49016,"text":"Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA","active":true,"usgs":false}],"preferred":false,"id":804911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":804912,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70223195,"text":"70223195 - 2021 - A generic soil velocity model that accounts for near-surface conditions and deeper geologic structure","interactions":[],"lastModifiedDate":"2021-08-17T12:18:34.915965","indexId":"70223195","displayToPublicDate":"2020-10-30T07:16:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3418,"text":"Soil Dynamics and Earthquake Engineering","active":true,"publicationSubtype":{"id":10}},"title":"A generic soil velocity model that accounts for near-surface conditions and deeper geologic structure","docAbstract":"

Near-surface soil conditions can significantly alter the amplitude and frequency content of incoming ground motions – often with profound consequences for the built environment – and are thus important inputs to any ground-motion prediction. Previous soil-velocity models (SVM) have predicted shear-wave velocity profiles based on the time-averaged shear-wave velocity in the upper 30 m (VS30). This article presents a generic soil-velocity model that accounts both for near-surface conditions (VS30) and deeper geologic structure, as represented to the depth at which the profile reaches a velocity of 1.0 km/s (Z1.0). To demonstrate the advantages of our new SVM, we apply it to the Cascadia Region of North America, where numerous geologic basins and glaciated landscapes give rise to a wide range of VS30 and Z1.0 combinations. This soil velocity model yields good estimates of site response across all site conditions, and significantly improves upon a model calibrated using only VS30 data. In conjunction with existing models that describe the deep velocity structure of the region (e.g., (Stephenson et al., 2017) [27]; the proposed model is particularly suited for use in regional-scale predictions of site response, liquefaction, landslides, infrastructure damage, and loss. The proposed methodology is broadly applicable to the development of SVMs elsewhere, and with improved understanding of near-surface and deep velocity structures, can facilitate more accurate ground-motion predictions globally.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.soildyn.2020.106461","usgsCitation":"Marafi, N.A., Grant, A.R., Maurer, B.W., Rateria, G., Eberhard, M.O., and Berman, J.W., 2021, A generic soil velocity model that accounts for near-surface conditions and deeper geologic structure: Soil Dynamics and Earthquake Engineering, v. 140, 106461, 11 p., https://doi.org/10.1016/j.soildyn.2020.106461.","productDescription":"106461, 11 p.","ipdsId":"IP-117816","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":454323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.soildyn.2020.106461","text":"Publisher Index Page"},{"id":387978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.4423828125,\n 48.22467264956519\n ],\n [\n -121.4208984375,\n 48.22467264956519\n ],\n [\n -121.4208984375,\n 49.095452162534826\n ],\n [\n -123.4423828125,\n 49.095452162534826\n ],\n [\n -123.4423828125,\n 48.22467264956519\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marafi, Nasser A.","contributorId":197874,"corporation":false,"usgs":false,"family":"Marafi","given":"Nasser","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":821341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":821342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maurer, Brett W.","contributorId":139387,"corporation":false,"usgs":false,"family":"Maurer","given":"Brett","email":"","middleInitial":"W.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":821343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rateria, Gunjan","contributorId":264324,"corporation":false,"usgs":false,"family":"Rateria","given":"Gunjan","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":821344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eberhard, Marc O 0000-0001-6752-3736","orcid":"https://orcid.org/0000-0001-6752-3736","contributorId":264325,"corporation":false,"usgs":false,"family":"Eberhard","given":"Marc","email":"","middleInitial":"O","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":821345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berman, Jeff W","contributorId":264326,"corporation":false,"usgs":false,"family":"Berman","given":"Jeff","email":"","middleInitial":"W","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":821346,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}