This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring hypotheses; estimating physically or biologically meaningful parameters for use in further modeling; and revealing patterns in complex, multidimensional data or model outputs. An important research frontier is the injection of limnological knowledge into machine-learning models, which has shown great promise for increasing such models’ accuracy, trustworthiness, and interpretability. Here we describe a few of the most powerful machine learning tools, describe best practices for employing these tools and injecting knowledge guidance, and give examples of their applications to advance understanding of inland waters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of inland waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00121-3","usgsCitation":"Appling, A.P., Oliver, S.K., Read, J., Sadler, J.M., and Zwart, J.A., 2022, Machine learning for understanding inland water quantity, quality, and ecology, chap. of Encyclopedia of inland waters, v. 4, p. 585-606, https://doi.org/10.1016/B978-0-12-819166-8.00121-3.","productDescription":"22 p.","startPage":"585","endPage":"606","ipdsId":"IP-122850","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445607,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5964s","text":"External Repository"},{"id":411277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Mehner, Thomas","contributorId":272917,"corporation":false,"usgs":false,"family":"Mehner","given":"Thomas","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":860710,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Tockner, Klement","contributorId":224174,"corporation":false,"usgs":false,"family":"Tockner","given":"Klement","email":"","affiliations":[{"id":40838,"text":"FWF Austrian Science Fund","active":true,"usgs":false}],"preferred":false,"id":860711,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":860690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239174,"text":"70239174 - 2022 - Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA","interactions":[],"lastModifiedDate":"2023-01-02T19:23:03.108814","indexId":"70239174","displayToPublicDate":"2023-01-02T13:16:33","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA","docAbstract":"The 2002 M 7.9 Denali earthquake in Alaska, USA, was the largest inland earthquake in North America in nearly 150 years. The earthquake involved oblique thrusting but mostly strike-slip motion, and faults ruptured the ground surface over 330 km. Fault rupture occurred in a rugged, mountainous, subarctic environment with extensive permafrost and variable glaciation, geology, and groundwater presence, and many triggered landslides mobilized into avalanches that traversed varied physiographic settings, some moving farther than 11 km. However, only several thousand landslides were triggered, and these occurred in a narrow zone along the fault rupture. These characteristics of the event provide ample opportunities to improve understanding of controls on coseismic landsliding and avalanching mechanisms. The paucity and limited extent of landslides likely resulted from high directivity of seismic energy and relatively low levels of high-amplitude, high-frequency ground motion; glacial damping of seismic energy was likely not a factor. Landslides preferentially occurred on hillslopes steeper and higher than average. Meteorological conditions were near historical averages at the time of the event, although the region has experienced gradual warming historically that appears to have resulted in increased landslide occurrence in other parts of Alaska during recent years. Inherent susceptibility of geological formations to landsliding was not apparent with the available data, although discontinuities created dip-slope conditions for the five largest slides. Historical thinning of glaciers and consequent slope debuttressing may have been a factor in aiding occurrence of some of the earthquake-induced landslides, particularly some of the largest. Mobility of the largest avalanches was above average compared to global data, and mobility of all sizes of avalanches was apparently aided by movement over glacial ice. Avalanche deposits displayed characteristics indicative of turbulent flow on steeper slopes and laminar plug flow in flatter areas, where sliding also likely occurred.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coseismic landslides: Phenomena, long-term effects and mitigation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-981-19-6597-5_4","usgsCitation":"Schulz, W.H., 2022, Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA, chap. of Coseismic landslides: Phenomena, long-term effects and mitigation, p. 83-114, https://doi.org/10.1007/978-981-19-6597-5_4.","productDescription":"32 p.","startPage":"83","endPage":"114","ipdsId":"IP-118114","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.29368601014386,\n 59.11878225343841\n ],\n [\n -156.0264002993337,\n 58.779813559186465\n ],\n [\n -152.25996460189066,\n 61.06590743096231\n ],\n [\n -149.1643813809494,\n 62.16054388876884\n ],\n [\n -140.9851481053823,\n 61.673553940907254\n ],\n [\n -140.98590984229733,\n 63.075995036970994\n ],\n [\n -148.91306197242972,\n 64.36320333772588\n ],\n [\n -155.3934657440926,\n 62.81575979286217\n ],\n [\n -159.29368601014386,\n 59.11878225343841\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"editors":[{"text":"Towhata, Ikuo","contributorId":300539,"corporation":false,"usgs":false,"family":"Towhata","given":"Ikuo","email":"","affiliations":[],"preferred":false,"id":860706,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wang, Gonghui","contributorId":99452,"corporation":false,"usgs":true,"family":"Wang","given":"Gonghui","affiliations":[],"preferred":false,"id":860707,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Xu, Qiang","contributorId":214818,"corporation":false,"usgs":false,"family":"Xu","given":"Qiang","email":"","affiliations":[{"id":39123,"text":"Key Laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research and Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":860708,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Massey, Chris","contributorId":206127,"corporation":false,"usgs":false,"family":"Massey","given":"Chris","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":860709,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860684,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239182,"text":"70239182 - 2022 - Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature","interactions":[],"lastModifiedDate":"2023-01-02T19:15:38.169222","indexId":"70239182","displayToPublicDate":"2023-01-02T13:08:22","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature","docAbstract":"This paper proposes a new data-driven method for predicting water temperature in stream networks with reservoirs. The water flows released from reservoirs greatly affect the water temperature of downstream river segments. However, the information of released water flow is often not available for many reservoirs, which makes it difficult for data-driven models to capture the impact to downstream river segments. In this paper, we first build a state-aware graph model to represent the interactions amongst streams and reservoirs, and then propose a parallel learning structure to extract the reservoir release information and use it to improve the prediction. In particular, for reservoirs with no available release information, we mimic the water managers' release decision process through a pseudo-prospective learning method, which infers the release information from anticipated water temperature dynamics. For reservoirs with the release information, we leverage a physics-based model to simulate the water release temperature and transfer such information to guide the learning process for other reservoirs. The evaluation for the Delaware River Basin shows that the proposed method brings over 10% accuracy improvement over existing data-driven models for stream temperature prediction when the release data is not available for any reservoirs. The performance is further improved after we incorporate the release data and physical simulations for a subset of reservoirs.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2022 SIAM International Conference on Data Mining (SDM)","conferenceDate":"April 28-30, 2022","conferenceLocation":"Alexandria, Virginia, United States","language":"English","publisher":"Society for Industrial and Applied Mathematics","doi":"10.1137/1.9781611977172.11","usgsCitation":"Jia, X., Chen, S., Xie, Y., Yang, H., Appling, A.P., Oliver, S.K., and Jiang, Z., 2022, Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature, in Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), Alexandria, Virginia, United States, April 28-30, 2022, p. 91-99, https://doi.org/10.1137/1.9781611977172.11.","productDescription":"9 p.","startPage":"91","endPage":"99","ipdsId":"IP-134356","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":445610,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/2202.05714","text":"External Repository"},{"id":411275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"editors":[{"text":"Banerjee, Arindam","contributorId":300535,"corporation":false,"usgs":false,"family":"Banerjee","given":"Arindam","email":"","affiliations":[],"preferred":false,"id":860702,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Zhou, Zhi-Hua","contributorId":300536,"corporation":false,"usgs":false,"family":"Zhou","given":"Zhi-Hua","email":"","affiliations":[],"preferred":false,"id":860703,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Papalexakis, Evangelos E.","contributorId":300537,"corporation":false,"usgs":false,"family":"Papalexakis","given":"Evangelos","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":860704,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Riondato, Matteo","contributorId":300538,"corporation":false,"usgs":false,"family":"Riondato","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":860705,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":860696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":860697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yang, Haoyu","contributorId":298611,"corporation":false,"usgs":false,"family":"Yang","given":"Haoyu","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":860699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Zhe","contributorId":267317,"corporation":false,"usgs":false,"family":"Jiang","given":"Zhe","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":860701,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230419,"text":"70230419 - 2022 - Ground motion selection for nonlinear response history analyses of concrete dams","interactions":[],"lastModifiedDate":"2023-05-16T18:48:59.636551","indexId":"70230419","displayToPublicDate":"2022-12-31T13:45:28","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Ground motion selection for nonlinear response history analyses of concrete dams","docAbstract":"Evaluating the seismic performance of a 3D concrete dam using nonlinear response history analysis (NLRHA) requires three orthogonal components of ground acceleration histories, or ground motions (GMs) for brevity. Although much progress has been made for the topic of ground motion selection and modification (GMSM) in the context of multistory buildings, NLRHA of dams requires at least two additional considerations: (i) accounting for multiple modes of vibration and (ii) including three orthogonal components of GMs. To convey the key ideas in developing an ensemble of multicomponent GMs for this context, the fundamentals of GMSM are first briefly reviewed using a case study. Then, special considerations for concrete dams are highlighted. Finally, a practical method for developing target spectra and selecting multicomponent GMs is presented.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2022 USSD annual conference & exhibition","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"United States Society on Dams (USSD)","usgsCitation":"Kwong, N.S., 2022, Ground motion selection for nonlinear response history analyses of concrete dams, in 2022 USSD annual conference & exhibition, 15 p.","productDescription":"15 p.","ipdsId":"IP-135268","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":417105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398526,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ussd.conferencespot.org/2022/bio/bmt3b25ndXNnc2dvdg%3D%3D","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840399,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70246597,"text":"70246597 - 2022 - Three-decades of Rocky Intertidal Photo Series Documenting interannual variability in western Prince William Sound","interactions":[],"lastModifiedDate":"2024-02-27T17:55:08.04652","indexId":"70246597","displayToPublicDate":"2022-12-31T11:51:12","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Three-decades of Rocky Intertidal Photo Series Documenting interannual variability in western Prince William Sound","docAbstract":"During summer 2021 we re-visited and re-photographed intertidal community scenes at seven rocky intertidal sites in Western Prince William Sound, adding another year of photos to a 32-year monitoring effort. The sites include both previously-oiled and un-oiled locations that were the subject of repeated annual photos beginning in 1990, one year after the March 24, 1989 Exxon Valdez Oil Spill. Photos from summer 2021 were compared with those available from the previous 31 years, visually revealing multi-year cycles of variation in the cover of dominant intertidal community organisms, mainly rockweed (Fucus distichus) and mussels (Mytilus trossulus). The repeated photos, together with basic time series graphs of percent cover estimated from many photos, provide a visual sense of major year-to-year variations in the cover of rockweed, mussels and to some extent, barnacles. In summer 2021 the cover of rockweed at five of the seven sites was low compared to recent previous years. The entire photo-timeseries shows that during the last three decades there have been four or five episodes of growth and senescence of rockweed and mussels. This variability shows how difficult it is to define “recovery” and supports the idea that recovery is a return to the natural range of variability, not necessarily the condition that prevailed immediately before the disturbance.","largerWorkTitle":"Proceedings of the forty-forth AMOP technical seminar","language":"English","publisher":"Environment and Climate Change Canada","usgsCitation":"Mearns, A., Janka, D., Pegau, S., Campbell, R., and Robinson, B.H., 2022, Three-decades of Rocky Intertidal Photo Series Documenting interannual variability in western Prince William Sound, in Proceedings of the forty-forth AMOP technical seminar, v. 44, p. 230-242.","productDescription":"13 p.","startPage":"230","endPage":"242","ipdsId":"IP-139662","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":426034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mearns, Alan","contributorId":316283,"corporation":false,"usgs":false,"family":"Mearns","given":"Alan","email":"","affiliations":[{"id":68546,"text":"NOAA - Retired","active":true,"usgs":false}],"preferred":false,"id":877305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janka, Dave","contributorId":316284,"corporation":false,"usgs":false,"family":"Janka","given":"Dave","email":"","affiliations":[{"id":68547,"text":"Auklet Charter Services","active":true,"usgs":false}],"preferred":false,"id":877306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pegau, Scott","contributorId":316285,"corporation":false,"usgs":false,"family":"Pegau","given":"Scott","email":"","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":877307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Robert","contributorId":316286,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":877308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Brian H. 0000-0001-8588-7162 brobinson@usgs.gov","orcid":"https://orcid.org/0000-0001-8588-7162","contributorId":191406,"corporation":false,"usgs":true,"family":"Robinson","given":"Brian","email":"brobinson@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":877309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236479,"text":"70236479 - 2022 - Assessing the efficacy of oblique bubble screens for control of aquatic invasive species","interactions":[],"lastModifiedDate":"2024-02-22T17:08:42.891975","indexId":"70236479","displayToPublicDate":"2022-12-31T11:06:29","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessing the efficacy of oblique bubble screens for control of aquatic invasive species","docAbstract":"Non-physical barriers, such as bubble screens (or curtains), are promising low-impact strategies to deter the spread of Aquatic Invasive Species (AIS) in streams. Bubble screens have been successfully implemented to redirect and/or deter adult fish and to capture plastics in some rivers, but their efficacy on invasive fish at multiple life stages (eggs, larvae, and adult fish) is not yet known. Air bubbles rising from a diffuser placed at the bottom of a stream generate counterrotating eddies that interact with the mean flow. Understanding such interactions allows us to design an Oblique Bubble Screen (OBS), a system able to direct drifting particles (i.e., eggs and larvae) towards the banks of a stream for potential capture, based on the water velocity, river morphology, orientation of the OBS, diffuser material, and air flow rate. We present the results from a series of laboratory experiments at the Ecohydraulics and Ecomorphodynamics Laboratory at the University of Illinois at Urbana-Champaign, using positively buoyant (specific gravity SG=0.9, and diameter d=7.09mm) and negatively buoyant (SG=1.04, d=5.9mm) spherical particles to represent the range of size and density of developing Grass carp eggs, an invasive species in North America (Ctenopharyngodon idella). An air compressor was connected to a porous tube laid at the bottom of a recirculating flume, with a regulator and a flow meter to control air pressure and air flow rate. Acoustic Doppler Velocimeters (ADV) and Surface Particle Image Velocimetry (PIV) were used to measure the effect of the OBS on the velocity field. Our collected data showed that: (1) a single OBS is able to direct drifting particles towards the bank at the downstream end of the OBS, (2) adjusting orientation angle and air flow rate of the diffuser can increase capture efficacy under different flow conditions, reaching up to a 100% of capture for buoyant particles, and (3) the ratio between lateral velocity generated by the OBS (as a function of air flow rate) and the mean longitudinal flow velocities, can be used as an indicator to predict whether the OBS will be able to carry the particles all along the length of the diffuser in wider and deeper streams. The optimal configurations from our study will be tested with live Grass carp eggs and larvae, as well as with upstream-swimming adult carp to assess its potential as a two-way barrier, and to provide design parameters to set the air-flow rate and diffuser type needed for field deployments, according to width-to-depth ratios and stream morphology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 39th IAHR World Congress, Granada, Spain","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Association for Hydro-Environment Engineering and Research","doi":"10.3850/IAHR-39WC2521711920221833","usgsCitation":"Prasad, V., Suski, C., Jackson, P.R., George, A.E., Chapman, D., Fischer, J., and Tinoco, R.O., 2022, Assessing the efficacy of oblique bubble screens for control of aquatic invasive species, in Proceedings of the 39th IAHR World Congress, Granada, Spain, v. 39, p. 1565-1570, https://doi.org/10.3850/IAHR-39WC2521711920221833.","productDescription":"6 p.","startPage":"1565","endPage":"1570","ipdsId":"IP-135122","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":445612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3850/iahr-39wc2521711920221833","text":"Publisher Index Page"},{"id":425879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Prasad, Vindhyawasini 0000-0003-0585-7217","orcid":"https://orcid.org/0000-0003-0585-7217","contributorId":296287,"corporation":false,"usgs":false,"family":"Prasad","given":"Vindhyawasini","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":851177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suski, C. D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":851178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":851179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Amy E. 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":3950,"corporation":false,"usgs":true,"family":"George","given":"Amy","email":"ageorge@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":851180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":851181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fischer, Jesse Robert","contributorId":296288,"corporation":false,"usgs":true,"family":"Fischer","given":"Jesse Robert","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":851182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tinoco, Rafael O.","contributorId":211779,"corporation":false,"usgs":false,"family":"Tinoco","given":"Rafael","email":"","middleInitial":"O.","affiliations":[{"id":38317,"text":"Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":851183,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240326,"text":"70240326 - 2022 - Status and trends in the Lake Superior fish community, 2021","interactions":[],"lastModifiedDate":"2023-03-30T16:33:53.138792","indexId":"70240326","displayToPublicDate":"2022-12-31T10:51:30","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends in the Lake Superior fish community, 2021","docAbstract":"The Lake Superior nearshore fish community was sampled in May-June 2021 with daytime bottom trawl tows at 45 stations located in USA waters. The 45 locations sampled were long-term monitoring sites that had been annually sampled since 1978. All comparisons to 2021 results were limited to past collections from USA waters, as compared to previous years, where comparisons included USA and Canadian sites. In 2021, the number of species collected at each site ranged from 0 to 15, with a median of 5 species. Average fish biomass was 6.3 kg/ha, which was higher than the average observed over the past 10 years (4.7 kg/ha), similar to the average observed from 2001-10 (6.7 kg/ha), and less than the averages observed in 1991-2000 (14.8 kg/ha), and 1981-1990 (11.9 kg/ha), but higher than the average from 1978-1980 (5.2 kg/ha). Average biomass in 2021 was highest for Lake Whitefish (Coregonus clupeaformis, 3.2 kg/ha), Bloater (C. hoyi, 1.4 kg/ha), Rainbow Smelt (Osmerus mordax, 0.5 kg/ha), and Cisco (C. artedi, 0.3 kg/ha). Coregonus spp. year-class strength, as measured by densities of age-1 fish, was 8 fish/ha for Bloater, 11 fish/ha for Cisco, and 41 fish/ha for Lake Whitefish. The age-1 Bloater estimate was in the range observed for the 2014, 2015, and 2016 year-classes (7-9 age-1 fish/ha) and greater than that observed in other years over the past decade (<1 age-1 fish/ha). The age-1 Cisco estimate was the highest estimate since the 2009 year-class. Average Lake Whitefish age-1 density was the second highest estimate observed over the past 44-years. Cisco survival to age-1 has been low since 2009 and near zero since the 2014- and 2015-year classes. This lack of survival has yet to be adequately explained and continues to be a major concern of fishery managers due to Cisco’s importance in ecosystem dynamics and value to the commercial fishery.
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0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":302070,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Sydney B 0000-0003-0179-6533","orcid":"https://orcid.org/0000-0003-0179-6533","contributorId":302071,"corporation":false,"usgs":true,"family":"Phillips","given":"Sydney","email":"","middleInitial":"B","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863417,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240325,"text":"70240325 - 2022 - Status and trends in the Lake Superior fish community, 2020","interactions":[],"lastModifiedDate":"2023-03-30T16:34:40.032501","indexId":"70240325","displayToPublicDate":"2022-12-31T10:48:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends in the Lake Superior fish community, 2020","docAbstract":"The Lake Superior fish community within Management Unit WI-2 was sampled in July 2020 with daytime bottom trawls at 11 nearshore stations. The 11 locations sampled were long-term monitoring sites that had been annually sampled since 1974. In 2020, the number of species collected at each site ranged from 0 to 13, with a mean of 6.3 and median of six. All comparisons to 2020 results were limited to past collections from Management Unit WI-2. Mean total biomass was 10.5 kg/ha which was similar to the average observed over the past 10 years (10.3 kg/ha), less than averages over the past 20 and 30-years, 15.3 and 19.8 kg/ha respectively, and higher than the average observed from 1974-84 (4.7 kg/ha). Average biomass in 2020 was highest for Bloater (6.2 kg/ha), Lake Whitefish (2.3 kg/ha), and Cisco (0.9 kg/ha). Rainbow Smelt biomass averaged 0.3 kg/ha. Year-class strength, as measured by age-1 densities, was well below the 5, 10, and 25-year averages for Bloater, Cisco, Lake Whitefish and Rainbow Smelt. Bloater averaged 1 age-1 fish/ha, Cisco, 0.2 age-1 fish/ha, Lake Whitefish, 15 age-1 fish/ha, and Rainbow Smelt 6 age-1 fish/ha. Cisco survival to age-1 has been near non-existent since the 2014- and 2015-year classes and the last moderate sized year class was in 2009. This lack of survival has yet to be adequately explained and continues to be a major concern of fishery managers due to Cisco’s importance in ecosystem dynamics and value to the commercial fishery.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Vinson, M., Evrard, L.M., Gorman, O., and Yule, D.L., 2022, Status and trends in the Lake Superior fish community, 2020, 21 p.","productDescription":"21 p.","ipdsId":"IP-128615","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":412747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412746,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/publication-media-search.php","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863411,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863412,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70245367,"text":"70245367 - 2022 - Nuclear magnetic resonance logging of a deep test well for estimation of aquifer and confining-unit hydraulic properties, Long Island, New York","interactions":[],"lastModifiedDate":"2024-02-27T17:08:46.461733","indexId":"70245367","displayToPublicDate":"2022-12-31T10:44:22","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Nuclear magnetic resonance logging of a deep test well for estimation of aquifer and confining-unit hydraulic properties, Long Island, New York","docAbstract":"A 1,200-foot deep well in southwestern Nassau County, Long Island, N.Y. was selected to evaluate the application of a nuclear magnetic resonance (NMR) logging tool. Technological advances in NMR borehole systems have allowed for reduced probe length and diameter, and focused measurement at specific diameters beyond the disturbed zone surrounding a well. This 3-inch-diameter NMR tool was specifically developed for use in deep 4-inch-diameter polyvinyl chloride cased wells common to Long Island. Selected intervals of the Magothy and Lloyd aquifers and the Raritan confining unit were logged for the evaluation.
Unlike other petrophysical logs that respond to the rock matrix and fluid properties and are strongly dependent on mineralogy, NMR logs respond to the presence of hydrogen protons in the formation fluid to determine water fraction and pore-size distribution. NMR log analysis provided estimates of the clay-bound, capillary-bound, and mobile water fraction and hydraulic conductivity of aquifers and confining units penetrated by the well. NMR-estimated porosity and mobile water fraction for the Magothy aquifer (0.34 and 0.22 respectively), Magothy/Raritan(?) (0.35 and 0.30), Raritan confining unit (0.30 and 0.13), Raritan clay and silt (0.23 and 0.01), and the Lloyd aquifer (0.27 and 0.19) was determined from the NMR log.
Hydraulic conductivity was estimated from the NMR-log data using the Schlumberger- Doll Research and sum of squared echoes equations with empirically derived constants for unconsolidated aquifers. Average hydraulic conductivity of the Magothy aquifer was 70 ft/d, the Raritan confining unit was 9.0 ft/d overall, the clay-rich lower part 0.24 ft/d, and the Lloyd aquifer was 56 ft/d. The coarse sandy Magothy/Raritan(?) unit between the Magothy aquifer and the top of the Raritan confining unit had the highest hydraulic conductivity of 345 ft/d. The hydraulic-conductivity estimates from the NMR log analysis for the Magothy and Lloyd aquifers were consistent with published values and that estimated for the Lloyd aquifer from a specific-capacity test at the well site.
","conferenceTitle":"29th Conference on Geology of Long Island and Metropolitan New York","conferenceDate":"April 9, 2022","language":"English","publisher":"Long Island Geologists","usgsCitation":"Stumm, F., and Williams, J., 2022, Nuclear magnetic resonance logging of a deep test well for estimation of aquifer and confining-unit hydraulic properties, Long Island, New York, 29th Conference on Geology of Long Island and Metropolitan New York, v. 29, April 9, 2022, 11 p.","productDescription":"11 p.","ipdsId":"IP-138611","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":426032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426031,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.stonybrook.edu/commcms/geosciences/about/_LIG-Past-Conferences/2022Conference.php","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","county":"Nassau County","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.695,\n 40.65\n ],\n [\n -73.695,\n 40.64\n ],\n [\n -73.685,\n 40.64\n ],\n [\n -73.685,\n 40.65\n ],\n [\n -73.695,\n 40.65\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stumm, Frederick 0000-0002-5388-8811 fstumm@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-8811","contributorId":1077,"corporation":false,"usgs":true,"family":"Stumm","given":"Frederick","email":"fstumm@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John H. 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","middleInitial":"H.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70235860,"text":"70235860 - 2022 - Environmental geochemistry of an epigenetic Pb-Zn-Ag deposit at the abandoned Cecilia mine, Puno region, Peru","interactions":[],"lastModifiedDate":"2024-02-22T16:58:58.60074","indexId":"70235860","displayToPublicDate":"2022-12-31T10:32:03","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Environmental geochemistry of an epigenetic Pb-Zn-Ag deposit at the abandoned Cecilia mine, Puno region, Peru","docAbstract":"The abandoned Cecilia Pb-Zn-Ag mine is located at the headwaters of the Lake Titicaca watershed in the Altiplano of Peru. The site is characterized by three months of high precipitation and nine months of limited precipitation. The environmental geochemical characterization of the abandoned mine was done to evaluate environmental risks at the site from mine wastes and mine drainage, and their potential for downstream impacts on water quality in Lake Titicaca.
The approach included sampling of mine waste, water, and sediment. Composite mine waste samples were collected from six main piles (four tailings, two waste rock). The surface water was collected from (1) drainage from mine portals; (2) the Cecilia and Crucero rivers upstream of mine influences; (3) the impacted reach of the Cecilia River down to its confluence with the Crucero River; and (4) the Crucero River, which receives drainage from the Cecilia River. Sampling in the dry season did not identify seeps from the waste rock or tailings piles.
This study documents the capacity of the site to generate acid mine drainage from the mine waste and underground workings. Mine waste has elevated concentrations of As (up to 883 mg/kg), Cu (up to 20,106 mg/kg), Pb (up to 16,716 mg/kg), and Zn (up to 11,937 mg/kg). Results for dissolved concentrations from leaching experiments on mine waste samples showed high leachability for As (0.001 to 0.95 mg/L), Cu (0.01 to 57.34 mg/L), Cd (0.001 to 1.13 mg/L), Fe (0.42 to 785 mg/L), Zn (0.01 to 91 mg/L), and Mn (0.05 to 279 mg/L) with an acidic pH (2.5 to 6.0). Water chemistry at the site varied on the basis of water type. The Cecilia and Crucero rivers had neutral pH and low concentrations of metals upstream of mine influences. In contrast, samples collected at the mine portal were highly acidic (pH 1.4 to 3.7) with high dissolved concentrations of Fe (up to 4,720 mg/L), Al (up to 400 mg/L), sulfate (up to 19,428 mg/L), As (up to 5.92 mg/L), Cd (up to 9.84 mg/L), Cu (up to 1.56 mg/L), Pb (up to 1.95 mg/L), and Zn (up to 4,065 mg/L), causing an increase in metal concentrations in the river downstream after mixing. Carbonate rocks in the watershed produce alkaline waters that neutralize acid drainage prior to its confluence with the Crucero River. Proposed remediation methods include capping mine waste to limit contact with rainwater and passive treatment of mine portal drainage.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th international conference on acid rock drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Rock Drainage (ICARD)","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Palomino, S., Seal,, R., Garcia, F., Ochoa, M., Machaca, D., Condorhuaman, A., and Valencia, M., 2022, Environmental geochemistry of an epigenetic Pb-Zn-Ag deposit at the abandoned Cecilia mine, Puno region, Peru, in Proceedings of the 12th international conference on acid rock drainage, September 18-24, 2022, p. 126-137.","productDescription":"12 p.","startPage":"126","endPage":"137","ipdsId":"IP-140549","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":425878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":425877,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022#"}],"country":"Peru","otherGeospatial":"Cecilia mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -69.86739066896408,\n -14.47810004873395\n ],\n [\n -69.86739066896408,\n -14.518553485612628\n ],\n [\n -69.8006182214147,\n -14.518553485612628\n ],\n [\n -69.8006182214147,\n -14.47810004873395\n ],\n [\n -69.86739066896408,\n -14.47810004873395\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Palomino, S.","contributorId":295480,"corporation":false,"usgs":false,"family":"Palomino","given":"S.","email":"","affiliations":[{"id":63892,"text":"Instituto Geológico Minero y Metalúrgico (Peru)","active":true,"usgs":false}],"preferred":false,"id":849540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia, F.","contributorId":334298,"corporation":false,"usgs":false,"family":"Garcia","given":"F.","email":"","affiliations":[],"preferred":false,"id":849542,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ochoa, M.","contributorId":334299,"corporation":false,"usgs":false,"family":"Ochoa","given":"M.","email":"","affiliations":[],"preferred":false,"id":895246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Machaca, D.","contributorId":334300,"corporation":false,"usgs":false,"family":"Machaca","given":"D.","email":"","affiliations":[],"preferred":false,"id":849543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Condorhuaman, A.","contributorId":295482,"corporation":false,"usgs":false,"family":"Condorhuaman","given":"A.","email":"","affiliations":[{"id":63892,"text":"Instituto Geológico Minero y Metalúrgico (Peru)","active":true,"usgs":false}],"preferred":false,"id":849544,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Valencia, M.","contributorId":334301,"corporation":false,"usgs":false,"family":"Valencia","given":"M.","email":"","affiliations":[],"preferred":false,"id":895247,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240292,"text":"70240292 - 2022 - A review of Arctomecon californica (Papaveraceae) with a focus on the species’ potential for propagation and reintroduction and conservation needs","interactions":[],"lastModifiedDate":"2023-02-03T16:39:51.748313","indexId":"70240292","displayToPublicDate":"2022-12-31T10:22:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2785,"text":"Monographs of the Western North American Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A review of Arctomecon californica (Papaveraceae) with a focus on the species’ potential for propagation and reintroduction and conservation needs","title":"A review of Arctomecon californica (Papaveraceae) with a focus on the species’ potential for propagation and reintroduction and conservation needs","docAbstract":"Las Vegas bearpoppy (Arctomecon californica) occurrences have fluctuated during the past several decades, in part due to interannual variability in rainfall that influences recruitment and mortality events; yet, development in the Las Vegas Valley continues to threaten habitat supporting this species. Arctomecon californica was petitioned for listing under the Endangered Species Act in 2019 and is currently under review to determine whether listing is warranted (USFWS 2020). This review updates species information for A. californica and includes recent insights into the species' seed ecology, habitat requirements and suitability models, propagation and reintroduction, and pollinator biology. We include information from the past 20 years in these areas that supplement conservation and restoration actions for the species. We also identify topics with scarce information and highlight areas for future study, including the following: preservation of genetic diversity through germplasm collections, identification of mechanisms driving the species' soil endemism, maintenance of A. californica–pollinator relationships through understanding pollinator habitat, determination of the viable seed fraction and its longevity in the soil seed reserves, and prediction of population response to regional climate change based on demographic modeling.
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Bean Life Science Museum, Brigham Young University","doi":"10.3398/042.014.0101","usgsCitation":"Stosich, A., DeFalco, L., and Scoles-Sciulla, S.J., 2022, A review of Arctomecon californica (Papaveraceae) with a focus on the species’ potential for propagation and reintroduction and conservation needs: Monographs of the Western North American Naturalist, v. 14, no. 1, p. 1-22, https://doi.org/10.3398/042.014.0101.","productDescription":"22 p.","startPage":"1","endPage":"22","ipdsId":"IP-140238","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3398/042.014.0101","text":"Publisher Index Page"},{"id":412688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada","county":"Clark County, Mohave 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Alexander 0000-0002-4403-1090","orcid":"https://orcid.org/0000-0002-4403-1090","contributorId":301994,"corporation":false,"usgs":true,"family":"Stosich","given":"Alexander","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scoles-Sciulla, Sara J. 0000-0003-1693-5030 sscoles@usgs.gov","orcid":"https://orcid.org/0000-0003-1693-5030","contributorId":2614,"corporation":false,"usgs":true,"family":"Scoles-Sciulla","given":"Sara","email":"sscoles@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863262,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241106,"text":"70241106 - 2022 - Utilization of genetic data to inform native Brook Trout conservation in North Carolina","interactions":[],"lastModifiedDate":"2023-03-13T10:56:52.942477","indexId":"70241106","displayToPublicDate":"2022-12-31T09:25:06","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Utilization of genetic data to inform native Brook Trout conservation in North Carolina","docAbstract":"As North Carolina’s only native salmonid, Brook Trout Salvelinus fontinalis is a fish of considerable ecological and cultural significance in the state, but anthropogenic alterations to the landscape and introductions of nonnative salmonids have fragmented and reduced its native range. As a result, the North Carolina Wildlife Resources Commission (NCWRC) has enacted numerous efforts to help conserve the species. Annual demographic surveys of self-sustaining Brook Trout populations have been on-going since 1978, which have also included successful efforts to document previously unidentified populations. Beginning in earnest during the 1990s, allozyme testing was used to assess patterns of hatchery introgression, with over 480 collections genotyped at the creatine kinase locus. In 2010, the NCWRC began using microsatellite markers to conduct an extensive survey of Brook Trout genetic diversity and variation. To date, 541 Brook Trout collections representing 11,090 individuals have been genotyped at 12 microsatellite loci. These data have provided insights into evolutionary relationships among populations, spatial patterns of genetic diversity, and the extent of hatchery introgression within populations. Ultimately, increased understanding of genetic diversity and relatedness have been informative for determining that Brook Trout management in North Carolina is likely best enacted at the level of individual populations. Moreover, we have used these data to actively guide stream restoration and population reintroduction activities. Over the last 15 years, NCWRC and its partners have used genetic data to prioritize habitat enhancement activities and guide 17 Brook Trout population reintroduction projects. In the future, we plan to continue expanding the microsatellite genetic baseline while also exploring the utility of phylogenomic analyses to inform Brook Trout conservation activities. Genetic and genomic approaches have great potential to improve the efficacy of conservation actions for Brook Trout in North Carolina and throughout its native range.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of Wild Trout XIII","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Wild Trout XIII","conferenceDate":"September 27-30, 2022","conferenceLocation":"West Yellowstone, MT","language":"English","publisher":"Wild Trout Symposium","usgsCitation":"Rash, J., Kazyak, D., White, S.L., and Lubinski, B.A., 2022, Utilization of genetic data to inform native Brook Trout conservation in North Carolina, in Proceedings of Wild Trout XIII, West Yellowstone, MT, September 27-30, 2022, p. 158-163.","productDescription":"6 p.","startPage":"158","endPage":"163","ipdsId":"IP-143335","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":413954,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildtroutsymposium.com/proceedings.php","linkFileType":{"id":5,"text":"html"}},{"id":413955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.04921892394643,\n 35.16380575406262\n ],\n [\n -80.26699801469118,\n 36.54940722798543\n ],\n [\n -81.72273121506292,\n 36.60331819137433\n ],\n [\n -82.20159275018115,\n 36.10046486828409\n ],\n [\n -82.88139191858609,\n 35.905982228760394\n ],\n [\n -83.58707291840865,\n 35.49691451561709\n ],\n [\n -84.00314930521716,\n 35.43636411766791\n ],\n [\n -84.19291110790027,\n 35.20050466686614\n ],\n [\n -84.40371695037375,\n 34.915348088734206\n ],\n [\n -83.13188407946514,\n 34.95778267269911\n ],\n [\n -82.04921892394643,\n 35.16380575406262\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rash, Jacob","contributorId":202482,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":866100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":866101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":866102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":866103,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242769,"text":"70242769 - 2022 - Effect of repeated fire on annual brome invasion at Badlands National Park","interactions":[],"lastModifiedDate":"2024-03-05T15:12:34.730234","indexId":"70242769","displayToPublicDate":"2022-12-31T09:09:10","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Effect of repeated fire on annual brome invasion at Badlands National Park","docAbstract":"Prescribed fire is used to combat exotic plant species in mixed-grass prairie of Northern Great Plains parks. However, prescribed fires rarely occur at a frequency likely to maintain any gains against exotic species. The unusual circumstance of experimental plots being burned twice in 2 years provides a unique opportunity to investigate the effect of more frequent fire on invasive annual brome grasses. I established 40 plots on Sheep Mountain Table at Badlands National Park in 2015 to examine the relative effectiveness of prescribed fire alone or in combination with imazapic (an herbicide) application or with native seeding. Ten of the 40 plots were controls, with no experimental treatment; the remainder were burned with a prescribed fire in November 2016, and the herbicide and seeding treatments were applied soon thereafter to 10 plots each. In the 2018 growing season, annual brome abundance remained lower in the burned plots than in the controls, but monitoring by the National Park Service’s Northern Great Plains Fire Effects programs suggests that, by 5 years (or perhaps earlier) following a prescribed fire, annual brome abundance will return to its pre-fire level. Repeated fires may prevent this return if they sufficiently reduce the annual brome seedbank or produce conditions less conducive to annual brome growth (reduced litter layer or increased competition, for example). All plots in this experiment burned as part of a larger prescribed fire in fall 2018. This extension of the original study measures plant community composition (to species level) in the experimental plots (original control and burn only) after the 2018 prescribed fire; this report provides the results from the fourth growing season after that fire.
","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., 2022, Effect of repeated fire on annual brome invasion at Badlands National Park: Annual Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-152069","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415837,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573315"},{"id":426320,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.9816413781004,\n 43.81545397317089\n ],\n [\n -102.10404473861178,\n 43.820721999747335\n ],\n [\n -102.18038072914308,\n 43.900094036554435\n ],\n [\n -102.43056276472474,\n 43.93869274314153\n ],\n [\n -102.46588237645057,\n 43.87808438644481\n ],\n [\n -102.46227631796151,\n 43.81240136470154\n ],\n [\n -102.52583495138943,\n 43.76271118438757\n ],\n [\n -102.61056188331933,\n 43.745312984118215\n ],\n [\n -102.61512488487168,\n 43.697319743127245\n ],\n [\n -102.79687064513114,\n 43.69924298806647\n ],\n [\n -102.80984003809536,\n 43.66341493167664\n ],\n [\n -102.90154396748794,\n 43.662470844462945\n ],\n [\n -102.91146582849841,\n 43.47194100980886\n ],\n [\n -102.80317094893881,\n 43.47397686938032\n ],\n [\n -102.71249040143672,\n 43.53766576763433\n ],\n [\n -102.60922465539478,\n 43.48525504065212\n ],\n [\n -102.55509069073659,\n 43.49459163360207\n ],\n [\n -102.49109164390808,\n 43.49135456209459\n ],\n [\n -102.40294493885204,\n 43.47379006618429\n ],\n [\n -102.3098505724263,\n 43.465209713416414\n ],\n [\n -102.27255837742683,\n 43.48077466407841\n ],\n [\n -102.25880034575657,\n 43.582995671627835\n ],\n [\n -102.35279341761728,\n 43.577534191075756\n ],\n [\n -102.44677360300271,\n 43.541331165393316\n ],\n [\n -102.54267701175816,\n 43.56638417465828\n ],\n [\n -102.58354318324504,\n 43.60646020158184\n ],\n [\n -102.53234630194093,\n 43.63244149516539\n ],\n [\n -102.49724178055375,\n 43.716432342349705\n ],\n [\n -102.34297147119695,\n 43.748511777562356\n ],\n [\n -102.2746784068271,\n 43.781173073417534\n ],\n [\n -102.25598001505656,\n 43.80871222310375\n ],\n [\n -102.08569317423665,\n 43.7448827308326\n ],\n [\n -101.86229425624181,\n 43.732224058910504\n ],\n [\n -101.87763233485761,\n 43.800704970828534\n ],\n [\n -101.9816413781004,\n 43.81545397317089\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869742,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70244313,"text":"70244313 - 2022 - Polar bear research in a changing arctic","interactions":[],"lastModifiedDate":"2023-06-13T14:15:25.565615","indexId":"70244313","displayToPublicDate":"2022-12-31T08:48:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14467,"text":"Polar Bears International: Annual Newsmagazine","active":true,"publicationSubtype":{"id":10}},"title":"Polar bear research in a changing arctic","docAbstract":"No abstract available
","language":"English","publisher":"Polar Bears International","usgsCitation":"Atwood, T.C., 2022, Polar bear research in a changing arctic: Polar Bears International: Annual Newsmagazine, v. 2022, p. 4-16.","productDescription":"3 p.","startPage":"4","endPage":"16","ipdsId":"IP-141793","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":418056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418043,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://polarbearsinternational.org/news-media/publications-reports/"}],"otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -160.58476302858418,\n 66.63922467967527\n ],\n [\n -141.94473924754848,\n 68.25714310364108\n ],\n [\n -133.85567232370295,\n 67.8629329712283\n ],\n [\n -127.17339964748228,\n 61.081649664350834\n ],\n [\n -99.03751469497548,\n 60.56731746481029\n ],\n [\n -63.16426138052901,\n 56.72921905083541\n ],\n [\n -41.71064910424283,\n 58.42594082088394\n ],\n [\n -18.8502425803311,\n 61.41996334280503\n ],\n [\n 22.650187724616984,\n 67.73002729328053\n ],\n [\n 38.828321572308084,\n 62.41324916089022\n ],\n [\n 63.798919467657896,\n 68.12648730541824\n ],\n [\n 71.88798639150409,\n 65.64357799629823\n ],\n [\n 110.57482820120106,\n 72.49325261820758\n ],\n [\n 129.9182491060492,\n 70.48535045029931\n ],\n [\n 195.6586678012684,\n 66.07507810590701\n ],\n [\n 194.47226709362172,\n 84.95926931584484\n ],\n [\n -162.48858677855625,\n 84.99007663908839\n ],\n [\n -160.58476302858418,\n 66.63922467967527\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":875339,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239166,"text":"ofr20221118 - 2022 - Characterization of subsurface conditions and recharge at the irrigated four-plex baseball field, Fort Irwin National Training Center, California, 2018–20","interactions":[],"lastModifiedDate":"2026-02-10T21:20:37.248913","indexId":"ofr20221118","displayToPublicDate":"2022-12-30T13:25:58","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1118","displayTitle":"Characterization of Subsurface Conditions and Recharge at the Irrigated Four-Plex Baseball Field, Fort Irwin National Training Center, California, 2018-20","title":"Characterization of subsurface conditions and recharge at the irrigated four-plex baseball field, Fort Irwin National Training Center, California, 2018–20","docAbstract":"The U.S. Geological Survey performed subsurface and geophysical site characterization of the irrigated four-plex baseball field in the Langford Valley–Irwin Groundwater Subbasin, as part of a research study in cooperation with the U.S. Environmental Protection Agency, the Agricultural Research Service, and the Fort Irwin National Training Center, California. To help meet future demands, the Fort Irwin National Training Center is evaluating the efficacy of gravity-fed drywells to enhance storm-water recharge into the Langford Valley–Irwin Groundwater Subbasin by bypassing fine-grained, less permeable deposits between land surface and the water table. The amount, rate, and location of recharge beneath an irrigated baseball field in the groundwater basin at the Fort Irwin National Training Center is not well understood, so data were collected using physical and geophysical techniques to characterize subsurface materials, geologic controls, and the vertical movement of water through the unsaturated zone to the water table near the drywell at the Fort Irwin National Training Center. Based on the data collected and interpreted from these techniques, several fine-grained deposits were identified. Although these deposits appear to impede the downward movement of water through the unsaturated zone locally, they are not laterally continuous, and water appears to continue to move downward when it reaches the edges of the deposits. These data will help managers evaluate recharge at the site and determine if the use of gravity-fed drywells enhances recharge from surface runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221118","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","programNote":"U.S. Environmental Protection Agency","usgsCitation":"Densmore, J.N., Dick, M.C., Groover, K.D., Ely, C.P., and Brown, A., 2022, Characterization of subsurface conditions and recharge at the irrigated four-plex baseball field, Fort Irwin National Training Center, California, 2018–20: U.S. Geological Survey Open File Report 2022-1118, 13 p., https://doi.org/10.3133/ofr20221118","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-129107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499727,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114180.htm","linkFileType":{"id":5,"text":"html"}},{"id":411259,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.XML"},{"id":411257,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1118/images"},{"id":411255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1118/coverthb.jpg"},{"id":411256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.pdf","text":"Report","size":"3.61 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","city":"Fort Irwin","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.69261791592291,\n 35.26487666931442\n ],\n [\n -116.69251062756216,\n 35.26470146901906\n ],\n [\n -116.69238188152951,\n 35.26459634865991\n ],\n [\n -116.69212438946424,\n 35.264447427917574\n ],\n [\n -116.69163086300526,\n 35.264359827352905\n ],\n [\n -116.69129826908738,\n 35.26422842632836\n ],\n [\n -116.69092275982544,\n 35.263983143846076\n ],\n [\n -116.68835856800732,\n 35.2661468601287\n ],\n [\n -116.6903755891864,\n 35.26772362102348\n ],\n [\n -116.69260718708664,\n 35.265822744364684\n ],\n [\n -116.69281103497185,\n 35.265752665110384\n ],\n [\n -116.69268228893922,\n 35.26531466839623\n ],\n [\n -116.69261791592291,\n 35.26487666931442\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
https://www.usgs.gov/centers/ca-water/
Contact Pubs Warehouse
https://pubs.er.usgs.gov/contact
Greater sage-grouse (Centrocercus urophasianus) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush ecosystems. This updated population trend analysis provides state and federal land and wildlife managers with best-available science to help guide current management and conservation plans aimed at benefitting sage-grouse populations. This analysis relied on previously published population trend modeling methodology from Coates and others (2021) and includes the addition of three analytical updates: (1) identification of population nadirs (lowest points within cycles) at the lek (breeding ground) and neighborhood cluster (group of leks) spatial scales, (2) truncation of prior distributions on rate of change in apparent abundance values to more realistic boundaries for leks with missing data, and (3) addition of 2 years of population lek count data (2020 and 2021) to the current dataset (1953–2021). Bayesian state-space models estimated 2.9 percent average annual decline in sage-grouse populations across their geographical range, which varied among subpopulations at the largest scale of analysis, termed climate clusters (2.2–4.6). Cumulative declines were 42.5, 65.6, and 80.1 percent range-wide across short (19 years), medium (35 years), and long (55 years) temporal periods, respectively. These results indicate that range-wide populations continued to decline during 2020 and 2021, although two climate clusters (eastern area and Bi-State area) have shown growth in population abundance in recent years, indicating they have surpassed a recent population abundance nadir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1165","issn":"2771-9448","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the Bureau of Land Management","programNote":"Species Management Research Program","usgsCitation":"Coates, P.S., Prochazka, B.G., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2022, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2021: Data Report 1165, 16 p., https://doi.org/10.3133/dr1165.","productDescription":"Report: viii, 16 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-144163","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":411225,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"U.S. Geological Survey data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (1960–2021)"},{"id":411222,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1165/dr1165.pdf","text":"Report","size":"8.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1165"},{"id":411223,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1165/images"},{"id":411221,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1165/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.19101705712868,\n 48.89284566335482\n ],\n [\n -122.13131256755497,\n 48.37855671670232\n ],\n [\n -121.63700211579436,\n 47.85380781194411\n ],\n [\n -121.86067071873805,\n 47.51242609246373\n ],\n [\n -121.87668371107034,\n 47.11115078292244\n ],\n [\n -122.4532512741522,\n 46.70567448488106\n ],\n [\n -122.57397075207928,\n 46.22739431053469\n ],\n [\n -122.36606239056442,\n 45.90712886523926\n ],\n [\n -121.91588031540189,\n 45.358384504867246\n ],\n [\n -122.45322729336237,\n 44.953343420279765\n ],\n [\n -122.52983521148596,\n 44.52144457126775\n ],\n [\n -122.54530349941209,\n 44.259263341793\n ],\n [\n -122.85735468588939,\n 43.86827650155766\n ],\n [\n -123.01704364538307,\n 43.46272668287682\n ],\n [\n -123.01026119844099,\n 43.21452795313556\n ],\n [\n -123.10511846238558,\n 42.807780288627384\n ],\n [\n -122.77301525682884,\n 42.07884845828369\n ],\n [\n -122.62454526743153,\n 41.5133850817748\n ],\n [\n -122.14925905063672,\n 40.83036532174481\n ],\n [\n -121.68837858072334,\n 40.49667518946566\n ],\n [\n -121.57750448671058,\n 39.80789795232664\n ],\n [\n -121.16256808423407,\n 39.215880289775015\n ],\n [\n -120.64471039578123,\n 38.57511631320122\n ],\n [\n -119.84212022937817,\n 37.43985090599355\n ],\n [\n -118.83488568782542,\n 36.55782111752346\n ],\n [\n -118.59349323888452,\n 35.83229168807691\n ],\n [\n -117.40450808029976,\n 35.69535862053445\n ],\n [\n -116.43105077565428,\n 35.459239916109155\n ],\n [\n -114.6229823251931,\n 35.413666627683824\n ],\n [\n -96.18756245429773,\n 35.03931170375198\n ],\n [\n -94.57905716272413,\n 37.1225590274522\n ],\n [\n -94.53555587839759,\n 39.07884303955356\n ],\n [\n -95.83917624651616,\n 40.61806593890233\n ],\n [\n -96.37123578579417,\n 42.39205565405334\n ],\n [\n -96.46625839716233,\n 45.31077773932529\n ],\n [\n -97.30155203348903,\n 48.980368873698694\n ],\n [\n -122.19101705712868,\n 48.89284566335482\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
https://www.usgs.gov/centers/werc
Contact Pubs Warehouse
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The discovery of a large fossil canid jawbone in Idaho gives clues to the region’s diverse, verdant past.
The protection of all sea turtles globally is a high priority, and research projects on these imperiled species are focused on those that are likely to result in improvements in monitoring and management for population recovery. Determining distribution, seasonal movements, vital rates and habitat use for all life-stages of sea turtles has been identified by the US Fish and Wildlife Service (USFWS) and US National Marine Fisheries Service (NMFS) as important for achieving recovery. This study provides information on in-water aggregations of sea turtles in the northern Gulf of Mexico. Data collected includes individual dive profiles, movements, seasonal site fidelity, genetic population structure, and isotopic signatures.
","language":"English","publisher":"Bureau of Ocean Energy Management","usgsCitation":"Hart, K., and Lamont, M., 2022, Discerning behavioral patterns of sea turtles in the Gulf of Mexico to inform management decisions, iv, 76 p.","productDescription":"iv, 76 p.","ipdsId":"IP-133772","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":411563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411550,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://espis.boem.gov/final%20reports/BOEM_2021-088.pdf"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.65793958565853,\n 25.620964087484467\n ],\n [\n -80.65793958565853,\n 31.33180053527252\n ],\n [\n -99.2828424566061,\n 31.33180053527252\n ],\n [\n -99.2828424566061,\n 25.620964087484467\n ],\n [\n -80.65793958565853,\n 25.620964087484467\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":222407,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":861127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":861128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70245790,"text":"70245790 - 2022 - Perspectives on premetamorphic stratabound tourmalinites","interactions":[],"lastModifiedDate":"2023-06-27T12:10:06.160041","indexId":"70245790","displayToPublicDate":"2022-12-30T07:09:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":15684,"text":"Journal of Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Perspectives on premetamorphic stratabound tourmalinites","docAbstract":"Stratabound tourmalinites are metallogenically important rocks that locally show a close spatial association with diverse types of mineralization, especially volcanogenic massive sulfides (VMS) and clastic-dominated (CD) Zn-Pb deposits. These tourmalinite occurrences pan the geologic record from Eoarchean to Jurassic. Host lithologies are dominated by clastic metasedimentary rocks but in some areas include metavolcanic rocks, marble, or metaevaporites. Stratabound and stratiform (conformable) tourmalinites commonly display sedimentary structures such as graded beds, cross-beds, and rip-up clasts. In most cases, field and microtextural relationships are consistent with a synsedimentary to the early diagenetic introduction of boron as a precursor to tourmaline formation.
Whole-rock geochemical data for major, trace, and rare earth elements (REE) provide valuable insights into tourmalinite origins. Al-normalized values relative to those for least-altered host metasedimentary rocks suggest that tourmalinites in proximal settings at or near hydrothermal vent sites characterized by high fluid/rock regimes (e.g., Sullivan Pb-Zn-Ag deposit, Canada) have very different signatures than those in low fluid/rock, distal settings (e.g., Broken Hill Pb-Zn-Ag deposit, Australia). The high fluid/rock regimes at Sullivan show large mass changes of +60 % for Mg and +180 % for Mn, as well as large variations in abundances of light and middle REE. In contrast, tourmalinite formation in low fluid/rock regimes yields minimal Al-normalized changes in major elements, trace elements, and REE. Boron isotope values of tourmalinite-hosted tourmaline vary widely from -26.1 to +27.5 ‰, and are attributed mainly to boron sources (e.g., sediments, evaporites) with generally minor influence from processes such as formational temperature, fluid/rock ratio, and secular variation in seawater δ11B values.
Laterally extensive stratiform tourmalinites formed mainly by syngenetic or early diagenetic processes on or beneath the seafloor. The syngenetic process is attributed to the interaction of vented B-rich brines with aluminous minerals in sediments, whereas the diagenetic process involves the selective replacement of aluminous sediments by B-rich fluids. Modern examples of tourmalinites, as yet undiscovered, may exist in metalliferous sediments of the Red Sea and the eastern Pacific Ocean, in altered volcaniclastic sediments within active seafloor-hydrothermal systems of the South Pacific, and in hydrothermal mounds and vents associated with mafic sill complexes in extensional basins as in the North Sea and South China Sea. Stratabound tourmalinites that contain base-metal sulfides, high Mn concentrations (>1 wt. % MnO), or positive Eu anomalies can be valuable exploration guides for base-metal sulfide deposits in sedimentary and volcanic terranes.
The U.S. Geological Survey (USGS) has continuously monitored real-time water quality and suspended-sediment transport in San Francisco Bay (the Bay) since 1989 as part of a multi-agency effort (see “Acknowledgments” section) to address estuary management, water supply, and ecological concerns. The San Francisco Bay area is home to millions of people and biologically diverse marine and terrestrial flora and fauna. Freshwater mixes with saltwater in the Bay and is subject to riverine influences (floods, droughts, managed reservoir releases, and freshwater diversions) and marine influences (tides, waves, and effects of saltwater).
Water temperature, salinity, suspended-sediment concentration (SSC), and turbidity, are used by State and Federal resources managers and are monitored at eight key locations throughout the Bay (fig. 1). Water temperature and salinity affect the density of water, which controls gravity-driven circulation patterns and stratification in the water column. Salinity indicates the relative mixing of fresh and ocean waters in the Bay and is derived from specific conductance measurements. Turbidity is a measure of light scattered from suspended particles in the water that is used to estimate suspended-sediment concentration. Suspended-sediment concentrations also are directly measured through depth-integrated water sampling.
Suspended sediment affects Bay water quality in multiple ways. Suspended sediment affects phytoplankton growth by attenuating sunlight in the water column. Suspended sediment deposition on tidal marshes and intertidal mudflats helps to restore and sustain these habitats as sea level rises. Settling of suspended sediment in ports and shipping channels creates the need for more dredging. In addition, suspended sediment often carries adsorbed contaminants as it is transported in the water column, which affects the distributions and concentrations of adsorbed contaminants in the environment. Excessive concentrations of sediment-adsorbed contaminants in deposits on the bottom of the Bay can affect ecosystem health.
External factors, such as tidal currents, waves, and wind can also affect water quality in the Bay. Tidal currents in the Bay change direction four times daily, and wind direction and intensity typically fluctuate on a daily cycle. Consequently, salinity, water temperature, and suspended-sediment concentration differ spatially and temporally throughout the Bay. Therefore, high-frequency measurements at multiple locations are needed to monitor these changes. Data collected at eight stations throughout the Bay are transmitted in near real-time using cellular telemetry and posted to the USGS National Water Information System (NWIS; https://waterdata.usgs.gov/usa/nwis). The purposes of this fact sheet are to (1) provide information about the USGS San Francisco Bay water-quality monitoring network; (2) highlight various applications in which these data can be used; and (3) provide internet links to access the resulting continuous water-quality data collected by the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223087","usgsCitation":"Palm, D.L., Einhell, D.C., Davila Olivera, S.M., 2022, Continuous water-quality and suspended-sediment transport monitoring in San Francisco Bay, California, water years 2020–21: U.S. Geological Survey Fact Sheet 2022–3087, 4 p., https://doi.org/10.3133/fs20223087.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-138273","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3087/coverthb.jpg"},{"id":411163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3087/fs20223087.pdf","text":"Report","size":"2.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3087"},{"id":411164,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2022-3087"},{"id":411165,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3087/images/"},{"id":411166,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3087/fs20223087.XML"},{"id":501514,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114175.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.7032269260365,\n 38.2575437837898\n ],\n [\n -122.64478458511374,\n 38.2575437837898\n ],\n [\n -122.64478458511374,\n 37.373118003359465\n ],\n [\n -121.7032269260365,\n 37.373118003359465\n ],\n [\n -121.7032269260365,\n 38.2575437837898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
Understanding what drives changes in wildlife demography is fundamental to the conservation and management of depleted or declining populations, though making inference about the intrinsic and extrinsic factors that influence survival and reproduction remains challenging. Here we use mark–resight data from 2000 to 2018 to examine the effects of environmental variability on age-specific survival and natality for the endangered western distinct population segment (wDPS) of Steller sea lions (Eumetopias jubatus) in Alaska, USA. Though this population has been studied extensively over the last four decades, the causes of divergent abundance trends that have been observed across the wDPS range remain unknown. We developed a Bayesian multievent mark–resight model that accounts for female reproductive state uncertainty. Annual survival probabilities for male pups (0.44; 0.36–0.53), female yearlings (0.63; 0.49–0.73), and male yearlings (0.62; 0.51–0.71) born in the western portion of the wDPS range, estimated here for the first time, were lower than those in the eastern portion of the wDPS range, estimated as: male pups (0.69; 0.65–0.74), female yearlings (0.76; 0.71–0.81), and male yearlings (0.71; 0.65–0.78). There was a higher proportion of young female breeders in the western portion of the range, but overall natality was lower (0.69; 0.47–0.96) than in the eastern portion of the range (0.80; 0.74–0.84). Additionally, pup mass had a positive effect on pup survival in the eastern portion of the range and a negative effect in the western portion of the range, potentially due to earlier weaning of heavier pups. Local- and basin-scale oceanographic features such as the Aleutian Low, the Arctic Oscillation Index, the North Pacific Gyre Oscillation, chlorophyll concentration, upwelling, and wind in certain seasons were correlated with vital rates. However, drawing strong inferences from these correlations is challenging given that relationships between ocean conditions and an adaptive top predator in a dynamic ecosystem are exceedingly complex. This study provides the first demographic rate estimates for the western portion of the range where abundance estimates continue to decline. These results will advance efforts to identify factors driving regionally divergent abundance trends, with implications for population-level responses to future climate variability.