Toxic cyanobacterial blooms, often containing multiple toxins, are a serious public health issue. However, there are no known models that predict a cyanotoxin mixture (anatoxin-a, microcystin, saxitoxin). This paper presents two cyanotoxin mixture models (MIX) and compares them to two microcystin (MC) models from data collected in 2016–2017 from three recurring cyanobacterial bloom locations in Kabetogama Lake, Voyageurs National Park (Minnesota, USA). Models include those using near-real-time environmental variables (readily available) and those using additional comprehensive variables (based on laboratory analyses). Comprehensive models (R2 = 0.87 MC; R2 = 0.86 MIX) explained more variability than the environmental models (R2 = 0.58 MC; R2 = 0.57 MIX). Although neither MIX model was a better fit than the MC models, the MIX models produced no false negatives in the calibration dataset, indicating that all observations above regulatory guidelines were simulated by the MIX models. This is the first known use of Virtual Beach software for a cyanotoxin mixture model, and the methods used in this paper may be applicable to other lakes or beaches.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2021.125560","usgsCitation":"Christensen, V., Stelzer, E., Eikenberry, B., Olds, H., LeDuc, J.F., Maki, R., Norland, J.E., and Khan, E., 2021, Cyanotoxin mixture models: Relating environmental variables and toxin co-occurrence to human exposure risk: Journal of Hazardous Materials, v. 415, 125560, 13 p., https://doi.org/10.1016/j.jhazmat.2021.125560.","productDescription":"125560, 13 p.","ipdsId":"IP-123013","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":436472,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X7EO1K","text":"USGS data release","linkHelpText":"Data and model archive for multiple linear regression models for prediction of weighted cyanotoxin mixture concentrations and microcystin concentrations at three recurring bloom sites in Kabetogama Lake in Minnesota"},{"id":384883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.3453369140625,\n 48.21735290928554\n ],\n [\n -92.48291015625,\n 48.21735290928554\n ],\n [\n -92.48291015625,\n 48.622016428468385\n ],\n [\n -93.3453369140625,\n 48.622016428468385\n ],\n [\n -93.3453369140625,\n 48.21735290928554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"415","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eikenberry, Barbara C. Scudder 0000-0001-8058-1201 beikenberry@usgs.gov","orcid":"https://orcid.org/0000-0001-8058-1201","contributorId":172148,"corporation":false,"usgs":true,"family":"Eikenberry","given":"Barbara C. Scudder","email":"beikenberry@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":813550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olds, Hayley T. 0000-0002-6701-6459 htemplar@usgs.gov","orcid":"https://orcid.org/0000-0002-6701-6459","contributorId":5002,"corporation":false,"usgs":true,"family":"Olds","given":"Hayley T.","email":"htemplar@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":false,"id":813551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeDuc, Jaime F.","contributorId":190132,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":813552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maki, Ryan P.","contributorId":190131,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":813553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Norland, Jack E.","contributorId":214257,"corporation":false,"usgs":false,"family":"Norland","given":"Jack","email":"","middleInitial":"E.","affiliations":[{"id":39001,"text":"School of Natural Resources Sciences, North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":813554,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khan, Eakalak","contributorId":220550,"corporation":false,"usgs":false,"family":"Khan","given":"Eakalak","email":"","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":813555,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70221894,"text":"70221894 - 2021 - Simulation of dissolved organic carbon flux in the Penobscot Watershed, Maine","interactions":[],"lastModifiedDate":"2021-07-13T18:35:29.258188","indexId":"70221894","displayToPublicDate":"2021-03-05T13:30:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3892,"text":"Ecohydrology & Hydrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Simulation of dissolved organic carbon flux in the Penobscot Watershed, Maine","docAbstract":"Dissolved organic carbon (DOC) is an important component of the carbon cycle as a measure of the hydrological transport of carbon between terrestrial carbon pools into soil pools and eventually into streams. As a result, changes in DOC in rivers and streams may indicate alterations in the storage of terrestrial carbon. Exploring the complex interactions between biogeochemical cycling and hydrologic processes, as well as the micro-climate variabilities that impact the rate of DOC fluxes, are challenging because the information is not readily available from in-situ measurements or from empirical models alone. This is particularly true of large-scale watersheds. The Penobscot Watershed is the largest watershed of the Gulf of Maine and the second largest in New England. Its typical soils, with high organic matter and a large forested and wetland landscape, result in higher DOC fluxes than what has been observed previously for most rivers in the northern temperate or boreal zones (Hope et al., 1994; Mulholland, 1997; Aitkenhead and McDowell, 2000).
In this study, we emphasized the simulation of streamflow and DOC fluxes from the Penobscot Watershed (and several tributaries within the Penobscot Watershed) using the spatially distributed process-based Regional Hydro-Ecological Simulation System (RHESSys) model. Simulated results were evaluated using field measurements (streamflow, DOC fluxes) and remotely sensed products (Net Primary Production (NPP) and Leaf Area Index (LAI) from Moderate Resolution Imaging Spectroradiometer (MODIS). The average DOC flux for the Penobscot Watershed during 2004-2012 using the RHESSys model was 69 kg C/ha/year. The RHESSys simulated DOC flux is shown to correlate well with observed values, as well as with results previously reported from the empirical Load Estimator (LOADEST) model (71 kg C/ha/year) for 2004-2007 (Huntington and Aiken, 2013).
Our simulated results also show a temporal variation in the amount of DOC flux, indicating that the antecedent DOC concentration from one year can impact the DOC export in following years. Thus, DOC concentration is positively correlated with streamflow and antecedent precipitation, in agreement with previous studies (Ågren et al., 2010; Huntington and Aiken, 2013; Tian et al., 2013). The successful application of the rigorous RHESSys model in the Penobscot Watershed makes it a reasonable platform to test future scenarios impacting the hydrology and biogeochemistry within similar large complex watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecohyd.2021.02.005","usgsCitation":"Rouhani, S., Schaaf, C.B., Huntington, T., and Choate, J., 2021, Simulation of dissolved organic carbon flux in the Penobscot Watershed, Maine: Ecohydrology & Hydrobiology, v. 21, no. 23-24, p. 256-270, https://doi.org/10.1016/j.ecohyd.2021.02.005.","productDescription":"15 p.","startPage":"256","endPage":"270","ipdsId":"IP-106391","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":453173,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecohyd.2021.02.005","text":"Publisher Index Page"},{"id":387156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.73046875,\n 44.48866833139464\n ],\n [\n -67.576904296875,\n 45.57560020947802\n ],\n [\n -68.5986328125,\n 46.255846818480315\n ],\n [\n -70.15869140625,\n 46.430285240839964\n ],\n [\n -70.37841796875,\n 45.78284835197676\n ],\n [\n -69.43359375,\n 45.874712248904764\n ],\n [\n -69.60937499999999,\n 45.36758436884978\n ],\n [\n -70.11474609375,\n 45.213003555993964\n ],\n [\n -69.345703125,\n 44.6061127451739\n ],\n [\n -68.73046875,\n 44.48866833139464\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"23-24","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rouhani, Shabnam","contributorId":260994,"corporation":false,"usgs":false,"family":"Rouhani","given":"Shabnam","email":"","affiliations":[{"id":52735,"text":"University of Massachusetts, Boston, MA","active":true,"usgs":false}],"preferred":false,"id":819233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaaf, Crystal B.","contributorId":149538,"corporation":false,"usgs":false,"family":"Schaaf","given":"Crystal","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":819234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntington, Thomas G. 0000-0002-9427-3530","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":218737,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas G.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Choate, Janet","contributorId":260995,"corporation":false,"usgs":false,"family":"Choate","given":"Janet","email":"","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":819236,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218813,"text":"70218813 - 2021 - The making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)","interactions":[],"lastModifiedDate":"2021-03-15T13:59:10.529639","indexId":"70218813","displayToPublicDate":"2021-03-05T07:53:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"The making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)","docAbstract":"The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.
Periods of very shallow water (water depth in the order of 10 cm) occur daily on tidal flats because of the propagation of tides over very gently sloping beds, leading to distinct morphodynamical phenomena. To improve the understanding of the characteristics of velocity and suspended sediment concentration (SSC) surges and their contribution to sediment transport and local bed changes during periods of very shallow water, measurements of near-bed flow, and SSC were carried out at two cross-shore locations on an intertidal flat along the Jiangsu coast, China. Furthermore, the role of surges in local resuspension and morphological change was explored. Results indicate that flow and SSC surges occurred at both stations during very shallow water periods. On the lower intertidal flat, flood surges were erosive, while weaker surges on the middle intertidal flat were not. Surges on lower intertidal flats resulted in local resuspension and strong turbidity, contributing up to 25% of the onshore-suspended sediment flux during flood tides, even though they last only 10% of the flood duration. When surges travel across the flats, conditions change from erosional to depositional. Velocity surges on the middle intertidal flat were too weak to resuspend bed sediment, and the associated SSC surges were produced by advection.
Water supplies for millions of U.S. individuals exceed maximum contaminant levels for per- and polyfluoroalkyl substances (PFAS). Contemporary and legacy use of aqueous film forming foams (AFFF) is a major contamination source. However, diverse PFAS sources are present within watersheds, making it difficult to isolate their predominant origins. Here we examine PFAS source signatures among six adjacent coastal watersheds on Cape Cod, MA, U.S.A. using multivariate clustering techniques. A distinct signature of AFFF contamination enriched in precursors with six perfluorinated carbons (C6) was identified in watersheds with an AFFF source, while others were enriched in C4 precursors. Principal component analysis of PFAS composition in impacted watersheds showed a decline in precursor composition relative to AFFF stocks and a corresponding increase in terminal perfluoroalkyl sulfonates with < C6 but not those with ≥ C6. Prior work shows that in AFFF stocks, all extractable organofluorine (EOF) can be explained by targeted PFAS and precursors inferred using Bayesian inference on the total oxidizable precursor assay. Using the same techniques for the first time in impacted watersheds, we find that only 24%–63% of the EOF can be explained by targeted PFAS and oxidizable precursors. Our work thus indicates the presence of large non-AFFF organofluorine sources in these coastal watersheds.
Incorporating the influence of soil layering and local variability into the parameterizations of physics-based numerical models for distributed landslide susceptibility assessments remains a challenge. Typical applications employ substantial simplifications including homogeneous soil units and soil-hydraulic properties assigned based only on average textural classifications; the potential impact of these assumptions is usually disregarded. We present a multi-scale approach for parameterizing the distributed Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model that accounts for site-specific spatial variations in both soil thickness and complex layering properties by defining homogeneous soil properties that vary spatially for each model grid cell. These effective properties allow TRIGRS to accurately simulate the timing and distribution of slope failures without any modification of the model structure. We implemented this approach for the carbonate ridge of Sarno Mountains (southern Italy) whose slopes are mantled by complex layered soils of pyroclastic origin. The urbanized foot slopes enveloping these mountains are among the most landslide-prone areas of Italy and have been subjected to repeated occurrences of damaging and deadly rainfall-induced flow-type shallow landslides. At this scope, a primary local-scale application of TRIGRS was calibrated on physics-based rainfall thresholds, previously determined by a coupled VS2D (version 1.3) hydrological modeling and slope stability analysis. Subsequently, by taking into account the spatial distribution of soil thickness and vertical heterogeneity of soil hydrological and mechanical properties, a distributed assessment of landslide hazard was carried out by means of TRIGRS. The combination of these approaches led to the spatial assessment of landslide hazard under different hypothetical rainfall intensities and antecedent hydrological conditions. This approach to parameterizing TRIGRS can be adapted to other spatially variable soil layering and thickness to improve hazard assessments.
","language":"English","publisher":"MDPI","doi":"10.3390/w13050713","usgsCitation":"Fusco, F., Mirus, B.B., Baum, R.L., Calcaterra, D., and De Vita, P., 2021, Incorporating the effects of complex soil layering and thickness local variability into distributed landslide susceptibility assessments: Water, v. 13, no. 5, 27 p., https://doi.org/10.3390/w13050713.","productDescription":"27 p.","ipdsId":"IP-120315","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":453185,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13050713","text":"Publisher Index Page"},{"id":384490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Mount Vesuvius","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 14.327545166015625,\n 40.75974059207392\n ],\n [\n 14.53765869140625,\n 40.75974059207392\n ],\n [\n 14.53765869140625,\n 40.90832339902113\n ],\n [\n 14.327545166015625,\n 40.90832339902113\n ],\n [\n 14.327545166015625,\n 40.75974059207392\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fusco, F. 0000-0002-6271-2228","orcid":"https://orcid.org/0000-0002-6271-2228","contributorId":219005,"corporation":false,"usgs":false,"family":"Fusco","given":"F.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":812515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":812516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":812517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calcaterra, D. 0000-0002-3480-3667","orcid":"https://orcid.org/0000-0002-3480-3667","contributorId":219008,"corporation":false,"usgs":false,"family":"Calcaterra","given":"D.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":812518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Vita, P.","contributorId":219006,"corporation":false,"usgs":false,"family":"De Vita","given":"P.","email":"","affiliations":[{"id":39950,"text":"University of Napoli Federico II, Italy","active":true,"usgs":false}],"preferred":false,"id":812519,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218517,"text":"ofr20201145 - 2021 - Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018","interactions":[],"lastModifiedDate":"2021-03-05T12:53:46.034292","indexId":"ofr20201145","displayToPublicDate":"2021-03-04T15:39:22","publicationYear":"2021","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":"2020-1145","displayTitle":"Estimated Total Phosphorus Loads for Selected Sites on Great Lakes Tributaries, Water Years 2014–2018","title":"Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018","docAbstract":"Monthly and annual total phosphorus loads were estimated for water years 2014 through 2018 for 23 streamgaged (gaged) sites on tributaries to the Great Lakes. Processing and regression methods described by Robertson and others (2018) were used with discrete and continuous data collected during water years 2011 and 2018 to update regression models for estimating instantaneous flux with the same form of equations as published by Robertson and others (2018). Monthly and water year average fluxes for all but two of the 23 gage sites were estimated using a weighted combination of results from surrogate models (which have streamflow, turbidity, and seasonal indicators as explanatory variables) and unit-value (UV)-flow models which have only UV streamflow and seasonal indicators as explanatory variables. Two of the gage sites had extensive periods of missing turbidity records, so average flux estimates for those stations were based solely on results from UV-flow models.
For most sites, estimated loads of total phosphorus were computed and summed for water years 2014–2018. The cumulative loads were used to compute yields and flow-weighted mean concentrations for water years 2014–2018. The estimated cumulative total phosphorus loads for water years 2014–2018 ranged from 112 to 11,500 metric tons. The Maumee River site (U.S. Geological Survey gage number 04193500) had the largest estimated cumulative load for water years 2014–2018 and the third largest estimated flow-weighted mean concentration. In fact, the estimated cumulative load at the Maumee River site was more than three times larger than the second largest estimated cumulative load.
Estimated average annual total phosphorus yields and flow-weighted mean concentrations for water years 2014–2018 ranged from 0.016 metric tons per square kilometer to 0.771 metric tons per square kilometer and 0.033 milligram per liter to 0.466 milligram per liter, respectively. The Cattaraugus Creek gage site (U.S. Geological Survey gage number 04213500) had the highest estimated average annual total phosphorus yield and flow-weighted mean concentration. The average annual total phosphorus yield at the Cattaraugus Creek gage site was almost twice as large as the second largest estimated yield.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201145","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Koltun, G.F., 2021, Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018: U.S. Geological Survey Open-File Report 2020–1145, 13 p., https://doi.org/10.3133/ofr20201145.","productDescription":"Report: v, 13 p.; 2 Appendixes; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-122090","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":383717,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145//ofr20201145_appendix_2.csv","text":"Appendix 2","size":"64.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2020–1145 Appendix 2","linkHelpText":"— Estimated monthly total phosphorus loads at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1145/coverthb.jpg"},{"id":383713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1145"},{"id":383714,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_1.xlsx","text":"Appendix 1","size":"16.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2020–1145 Appendix 1","linkHelpText":"— Estimated annual total phosphorus loads and flow-weighted mean concentrations at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383715,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_1.csv","text":"Appendix 1","size":"8.45 kB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2020–1145 Appendix 1","linkHelpText":"— Estimated annual total phosphorus loads and flow-weighted mean concentrations at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383716,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1145/ofr20201145_appendix_2.xlsx","text":"Appendix 2","size":"66.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2020–1145 Appendix 2","linkHelpText":"— Estimated monthly total phosphorus loads at selected U.S. Geological Survey gage sites on Great Lakes tributaries"},{"id":383718,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEW32M","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Model archive—Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018"}],"country":"United States","state":"Illinois, Indiana, Michigan, 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6460 Busch Boulevard Ste 100
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The lake charr Salvelinus namaycush is restricted in its native distribution to oligotrophic fresh waters of northern North America largely within the extent of the Pleistocene glaciations. It is the only freshwater species in northwest North America that does not occur in Siberia. A GIS-based native occurrence map linked to the HydroLAKES database does not extend the lake charr range but provides more comprehensive occurrence data than previous maps. The total waterbody area of lakes occupied by lake charr (451,304 km2) is 40% of the total waterbody area across the range. Lake charr occur from 42.020901 latitude in the south to 74.420800 in the north and from −62.700000 longitude in the east to −161.173090 in the west. Lake charr lakes range in surface area from 3.4 to 8,210,000 ha (mean = 9715 ha; median = 191 ha), maximum depth from 2.7 to 614 m, and elevation from sea level to 2035 m ASL (mean = 381 m; median = 366 m). Glaciation, water temperature, dissolved oxygen, depth, and nutrient content are the main variables associated with lake charr native distribution in lakes. Life history variation, physiology, and ecological opportunity are the most likely drivers of lake charr dispersal and colonization.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-62259-6_2","usgsCitation":"Muir, A.M., Bennion, D., Hansen, M.J., Riley, S., and Gunn, J., 2021, Distribution, chap. 2 of The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management, v. 39, p. 13-40, https://doi.org/10.1007/978-3-030-62259-6_2.","productDescription":"28 p.","startPage":"13","endPage":"40","ipdsId":"IP-116034","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":386348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationDate":"2021-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Muir, Andrew M.","contributorId":176177,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":817246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":817247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Michael J","contributorId":260100,"corporation":false,"usgs":false,"family":"Hansen","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":817248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Stephen 0000-0002-8968-8416","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":236841,"corporation":false,"usgs":false,"family":"Riley","given":"Stephen","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":817249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gunn, John","contributorId":197606,"corporation":false,"usgs":false,"family":"Gunn","given":"John","affiliations":[],"preferred":false,"id":817250,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227101,"text":"70227101 - 2021 - Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model","interactions":[],"lastModifiedDate":"2021-12-29T14:14:01.03095","indexId":"70227101","displayToPublicDate":"2021-03-04T08:10:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2043,"text":"International Journal of Forestry Research","active":true,"publicationSubtype":{"id":10}},"title":"Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model","docAbstract":"Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.
","language":"English","publisher":"Hindawi","doi":"10.1155/2021/6650821","usgsCitation":"Odom, R.H., and Ford, W., 2021, Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model: International Journal of Forestry Research, v. 2021, 6650821, 16 p., https://doi.org/10.1155/2021/6650821.","productDescription":"6650821, 16 p.","ipdsId":"IP-111053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1155/2021/6650821","text":"Publisher Index Page"},{"id":393572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0089111328125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 43.95921358836687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, Richard H.","contributorId":171659,"corporation":false,"usgs":false,"family":"Odom","given":"Richard","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":829633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829632,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218590,"text":"ofr20201146 - 2021 - Practical field survey operations for flood insurance rate maps","interactions":[],"lastModifiedDate":"2021-03-05T12:41:18.272992","indexId":"ofr20201146","displayToPublicDate":"2021-03-04T08:00:00","publicationYear":"2021","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":"2020-1146","displayTitle":"Practical Field Survey Operations for Flood Insurance Rate Maps","title":"Practical field survey operations for flood insurance rate maps","docAbstract":"The U.S. Geological Survey assists the Federal Emergency Management Agency in its mission to identify flood hazards and zones for risk premiums for communities nationwide, by creating flood insurance rate maps through updating hydraulic models that use river geometry data. The data collected consist of elevations of river channels, banks, and structures, such as bridges, dams, and weirs that can affect flow. To account for the model complexity of river structure hydraulics and the fidelity between river channel and structure geometry, two distinct standards for collecting geometry data are presented, both using global navigation satellite system real-time network surveying. This method is adapted from U.S. Geological Survey manuals and is foundational in hydraulic surveying for flood insurance rate maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201146","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Taylor, N.J., and Simeone, C.E., 2021, Practical field survey operations for flood insurance rate maps: U.S. Geological Survey Open-File Report 2020–1146, 8 p., https://doi.org/10.3133/ofr20201146.","productDescription":"iv, 8 p.","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114316","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":383741,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm11D1","text":"Techniques and Methods 11-D1","linkHelpText":"- Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey"},{"id":383723,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1146/coverthb.jpg"},{"id":383724,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1146/ofr20201146.pdf","text":"Report","size":"662 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1146"},{"id":383725,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm11D3","text":"Techniques and Methods 11-D3","linkHelpText":"- Procedures and Best Practices for Trigonometric Leveling in the U.S. Geological Survey"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack of pronounced groundwater (atmospheric) signatures. Approximately 40% of non-dam stream sites have substantial groundwater contributions as indicated by characteristic paired air and stream temperature signal metrics. Streams with shallow groundwater signatures account for half of all groundwater signature sites and show reduced baseflow and a higher proportion of warming trends compared to sites with deep groundwater signatures. These findings align with theory that shallow groundwater is more vulnerable to temperature increase and depletion. Streams with atmospheric signatures tend to drain watersheds with low slope and greater human disturbance, indicating reduced stream-groundwater connectivity in populated valley settings.
Surface deformation in California's Central Valley (CV) has long been linked to changes in groundwater storage. Recent advances in remote sensing have enabled the mapping of CV deformation and associated changes in groundwater resources at increasingly higher spatiotemporal resolution. Here, we use interferometric synthetic aperture radar (InSAR) from the Sentinel‐1 missions, augmented by continuous Global Positioning System (cGPS) positioning, to characterize the surface deformation of the San Joaquin Valley (SJV, southern two‐thirds of the CV) for consecutive dry (2016) and wet (2017) water years. We separate trends and seasonal oscillations in deformation time series and interpret them in the context of surface and groundwater hydrology. We find that subsidence rates in 2016 (mean −42.0 mm/yr; peak −345 mm/yr) are twice that in 2017 (mean −20.4 mm/yr; peak −177 mm/yr), consistent with increased groundwater pumping in 2016 to offset the loss of surface‐water deliveries. Locations of greatest subsidence migrated outwards from the valley axis in the wetter 2017 water year, possibly reflecting a surplus of surface‐water supplies in the lowest portions of the SJV. Patterns in the amplitude of seasonal deformation and the timing of peak seasonal uplift reveal entry points and potential pathways for groundwater recharge into the SJV and subsequent groundwater flow within the aquifer. This study provides novel insight into the SJV aquifer system that can be used to constrain groundwater flow and subsidence models, which has relevance to groundwater management in the context of California's 2014 Sustainable Groundwater Management Act (SGMA).
Reservoirs in arid regions often provide critical water storage but little is known about their greenhouse gas (GHG) footprint. While there is growing appreciation of the role reservoirs play as GHG sources, there is a lack of understanding of GHG emission dynamics from reservoirs in arid regions and implications for environmental policy. Here we present initial GHG emission measurements from Lake Powell, a large water storage reservoir in the desert southwest United States. We report CO2-eq emissions from the shallow (< 15 m) littoral regions of the reservoir that are higher than the global average areal emissions from reservoirs (9.4 vs. 5.8 g CO2-eq m−2 d−1) whereas fluxes from the main reservoir were two orders of magnitude lower (0.09 g CO2-eq m−2 d−1). We then compared our measurements to modeled CO2 + CH4 emissions from the reservoir using four global scale models. Factoring these emissions into hydropower production at Lake Powell yielded low GHG emissions per MWh−1 as compared to fossil-fuel based energy sources. With the exception of one model, the estimated hydropower emissions for Lake Powell ranged from 10−32 kg CO2-eq MWh−1, compared to ∼400−1000 kg CO2-eq MWh−1 for natural gas, oil, and coal. We also estimate that reduced littoral habitat under low water levels leads to ∼50% reduction in the CO2 equivalent emissions per MWh. The sensitivity of GHG emissions to reservoir water levels suggests that the interaction will be an important policy consideration in the design and operation of arid region systems.
The contamination of coastal ecosystems from a variety of toxins of marine algal origin is a common and well-documented situation along the coasts of the United States and globally. The occurrence of toxins originating from cyanobacteria along marine coastlines is much less studied, and little information exists on whether toxins from marine and freshwater sources co-occur regularly. The current study focused on the discharge of cyanotoxins from a coastal lagoon (Santa Clara River Estuary) as a consequence of an extreme tide event (King Tides; December 3–5, 2017) resulting in a breach of the berm separating the lagoon from the ocean. Monthly monitoring in the lagoon throughout 2017 documented more than a dozen co-occurring cyanobacterial genera, as well as multiple algal and cyanobacterial toxins. Biotoxin monitoring before and following the King Tide event using Solid Phase Adsorption Toxin Tracking (SPATT) in the lagoon and along the coast revealed the co-occurrence of microcystins, anatoxin, domoic acid, and other toxins on multiple dates and locations. Domoic acid was ubiquitously present in SPATT deployed in the lagoon and along the coast. Microcystins were also commonly detected in both locations, although the beach berm retained the lagoonal water for much of the year. Mussels collected along the coast contained microcystins in approximately half the samples, particularly following the King Tide event. Anatoxin was observed in SPATT only in late December, following the breach of the berm. Our findings indicate both episodic and persistent occurrence of both cyanotoxins and marine toxins may commonly contaminate coastlines in proximity to cyanobacteria-laden creeks and lagoons.
Migratory marine species cross political borders and enter the high seas, where the lack of an effective global management framework for biodiversity leaves them vulnerable to threats. Here, we combine 10,108 tracks from 5775 individual birds at 87 sites with data on breeding population sizes to estimate the relative year-round importance of national jurisdictions and high seas areas for 39 species of albatrosses and large petrels. Populations from every country made extensive use of the high seas, indicating the stake each country has in the management of biodiversity in international waters. We quantified the links among national populations of these threatened seabirds and the regional fisheries management organizations (RFMOs) which regulate fishing in the high seas. This work makes explicit the relative responsibilities that each country and RFMO has for the management of shared biodiversity, providing invaluable information for the conservation and management of migratory species in the marine realm.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.abd7225","usgsCitation":"Beal, M., Dias, M.P., Phillips, R.A., Oppel, S., Hazin, C., Pearmin, E.J., Adams, J., Anderson, D.J., Antolos, M., Arata, J.A., Arcos, J.M., Arnould, J.P., Awkerman, J., Bell, E., Bell, M., Carey, M., Carle, R., Clay, T.A., Cleeland, J., Colodro, V., Conners, M.G., Cruz-Flores, M., Cuthbert, R., Delord, K., Deppe, L., Dilley, B., Dinis, H.A., Elliot, G., de Felipe, F., Felis, J.J., Forero, M.G., Freeman, A., Fukuda, A., Gonzalez-Solis, J., Granadeiro, J.P., Hedd, A., Hodum, P., Igual, J.M., Jaeger, A., Landers, T.J., Matthieu, L., Makhado, A., Metzger, B., Militao, T., Montevecchi, W.A., Morera-Pujol, V., Navarro-Herrero, L., Nel, D., Nicholls, D., Oro, D., Ouni, R., Ozaki, K., Quintana, F., Ramos, R., Reid, T., Reyes-Gonzalez, J.M., Robertson, C., Robertson, G., Romdhane, M.S., Ryan, P.G., Sagar, P., Sato, F., Schoombie, S., Scofield, R.P., Shaffer, S.A., Shah, N.J., Stevens, K.L., Surman, C., Suryan, R.M., Takahashi, A., Tatayah, V., Taylor, G., Thompson, D.R., Torres, L., Walker, K., Wanless, R.M., Waugh, S.M., Weimerskirch, H., Yamamoto, T., Zajkova, Z., Zango, L., and Catry, P., 2021, Global political responsibility for the conservation of albatrosses and large petrels: Science Advances, v. 7, no. 10, 13 p., https://doi.org/10.1126/sciadv.abd7225.","productDescription":"13 p.","ipdsId":"IP-120301","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.abd7225","text":"Publisher Index Page"},{"id":384342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beal, Martin 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2021 - Groundwater management process simulations using an updated version of the three-dimensional numerical model of groundwater flow in northern Utah Valley, Utah County, Utah","interactions":[],"lastModifiedDate":"2021-04-08T21:43:33.834314","indexId":"sir20215010","displayToPublicDate":"2021-03-02T20:39:28","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5010","displayTitle":"Groundwater Management Process Simulations Using an Updated Version of the Three-Dimensional Numerical Model of Groundwater Flow in Northern Utah Valley, Utah County, Utah","title":"Groundwater management process simulations using an updated version of the three-dimensional numerical model of groundwater flow in northern Utah Valley, Utah County, Utah","docAbstract":"Groundwater is a primary source of drinking water in northern Utah County. The groundwater system is recharged mainly from precipitation in the adjacent Wasatch Mountains and infiltration of streamflow. In 2004, groundwater withdrawals were estimated to be roughly 44,500 acre-feet per year. In 2016, groundwater withdrawals were estimated to be greater than 63,400 acre-feet per year. To prepare for anticipated future increases in groundwater withdrawals, local cities identified 16 locations as feasible for managed aquifer recharge. Using an updated version of an existing U.S. Geological Survey groundwater flow model of northern Utah County, the Groundwater-Management Process for MODFLOW-2005 was used to investigate optimal managed aquifer recharge scenarios with the objective of maintaining acceptable reductions in simulated discharge at 12 groundwater discharge areas and flowing wells along Utah Lake.
The Groundwater-Management Process is applied to a 50-year (2017–66) projection of groundwater conditions using average recharge conditions and a linear increase of approximately 750 acre-feet per year of municipal groundwater withdrawals. Two sets of discharge constraints were applied. The first scenario constrains discharge to greater than or equal to 80 percent of the 2016 simulated groundwater discharge along Utah Lake. The constraint was met with a total managed aquifer recharge rate of roughly 7,300 acre-feet per year during 2042–56, and 15,600 acre-feet per year during 2057–66. A second scenario constrains discharge to greater than or equal to 90 percent of the 2016 simulated discharge. This constraint can only be met at 8 of the 12 discharge areas along Utah Lake. This required a managed aquifer recharge rate of roughly 10,000 acre-feet per year during 2042–56 and 15,400 acre-feet per year during 2057–66. For both scenarios, the Groundwater-Management Process indicated that all managed aquifer recharge sites need to be used to meet discharges constraints. The discharge constraints were informally defined on the basis of the water rights hierarchy associated with Utah Lake.
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Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
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The mobilization and transport of organic carbon (OC) in rivers and delivery to the near-coastal ocean are important processes in the carbon cycle that are affected by both climate and anthropogenic activities. Riverine OC transport can affect carbon sequestration, contaminant transport, ocean acidification, the formation of toxic disinfection by-products, ocean temperature and phytoplankton productivity. There have been many studies reporting temporal trends in OC concentrations in comparatively small streams with minimal anthropogenic influences but there have been fewer studies on larger rivers and fewer still that have investigated changes in OC concentration-discharge (C-Q) relations. This study examined changes in C-Q relations for total organic carbon (TOC) from 1973 to 2019 in 8 rivers in New England, USA. TOC concentrations declined in all rivers, and in most rivers, and in most seasons, the slope of the C-Q relation increased between 1973 to 1995 and 1996 to 2019. The increase in C-Q slope between periods may be related to changes in the magnitude of TOC sources. The most likely sources to have changed are wastewater inputs, urban runoff, production through photosynthesis in aquatic systems, and runoff from agricultural and forestry practices. Changes in wetland abundance and changes in sulfate concentrations can be ruled out as drivers of the observed changes in C-Q.
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Measurement of pH","docAbstract":"The “National Field Manual for the Collection of Water-Quality Data” (NFM) provides guidelines and procedures for U.S. Geological Survey (USGS) personnel who collect data used to assess the quality of the Nation’s surface-water and groundwater resources. This chapter, NFM A6.4, provides guidance and protocols for the measurement of pH of a water sample, which include the scientific basis of the measurement, selection and maintenance of equipment, calibration, procedures for measurement and reporting, and troubleshooting. It updates and supersedes USGS Techniques of Water-Resources Investigations, book 9, chapter A6.4, version 2.0, by G.F. Ritz and J.A. Collins. The pH of natural waters is routinely measured when water samples are collected, is often measured continually at USGS streamgages, and is a parameter regularly measured during laboratory and field experiments. The field methods for measuring pH described in this chapter are applicable to most natural waters.
Before 2017, the NFM chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.er.usgs.gov/. Comments, questions, and suggestions related to the NFM can be addressed to nfm@usgs.gov.
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Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 432
Reston, VA 20192
Repeat microgravity surveys carried out using relative- and absolute-gravity meters are useful for identifying changes in subsurface mass, such as the volume of water stored in an aquifer. These surveys require careful field procedures to achieve the part-per-billion accuracy required to measure the small changes in gravity relevant for hydrologic studies. This chapter describes techniques and methods for carrying out gravity surveys, requirements for assuring high-quality survey results, and data processing and archival procedures. The focus is on acquiring and documenting repeat gravity surveys for monitoring changes in groundwater storage. Similar gravity surveys may be completed to evaluate other causes of mass change, such as those caused by magma movement below volcanoes. The methods are also useful for one-time surveys that map spatial gravity variations associated with geologic structures such as faults or sedimentary basins.
Repeat microgravity surveys can be carried out using relative-gravity meters, absolute-gravity meters, or both. Specific locations, known as gravity stations, are visited during each survey. Most commonly, absolute- and relative-gravity are combined using the least-squares method of network adjustment, much like benchmark elevations and relative-height differences in a leveling network. This chapter primarily describes the use of the A-10 absolute-gravity meter manufactured by Micro-g LaCoste, Inc., and relative-gravity meters made by LaCoste & Romberg (no longer in production) and ZLS Corporation, Inc. Field and office procedures are similar for other instruments such as the FG-5 absolute-gravity meter and Scintrex relative-gravity meters, but some adaptation may be required. Quality control for absolute-gravity data focuses primarily on proper field procedures and maintaining the time and distance calibration of the instrument. Quality control for relative-gravity surveys requires careful field procedures, an understanding of how the meter is behaving while in the field, and appropriate postprocessing.
The techniques and methods described in this chapter were developed over 30 years at the USGS Arizona Water Science Center and the Southwest Gravity Program and are the basis for many studies on groundwater-storage change and geologic structure. A description of the Program and complete bibliography is available at https://www.usgs.gov/centers/az-water/science/azwsc-capabilities-hydrologic-gravity-monitoring.
Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Forest soils are among the world’s largest repositories for long-term accumulation of atmospherically deposited mercury (Hg), and understanding the potential for remobilization through gaseous emissions, aqueous dissolution and runoff, or erosive particulate transport to down-gradient aquatic ecosystems is critically important for projecting ecosystem recovery. Forestry operations, especially clear-cut logging where most of the vegetaiton is removed, can influence Hg mobility/fluxes, foodweb dynamics, and bioaccumulation processes. This paper measured surface-air Hg fluxes from catchments in the Pacific Northwest, USA, to determine if there is a difference between forested and logged catchments. These measurements were conducted as part of a larger project on the impact of forestry operations on Hg cycling which include measurements of water fluxes as well as impacts on biota. Surface-air Hg fluxes were measured using a commonly applied dynamic flux chamber (DFC) method that incorporated diel and seasonal variability in elemental Hg (Hg0) fluxes at multiple forested and harvested catchments. The results showed that the forested ecosystem had depositional Hg0 fluxes throughout most of the year (annual mean: −0.26 ng/m2/h). In contrast, the harvested catchments showed mostly emission of Hg0 (annual mean: 0.63 ng/m2/h). Differences in solar radiation reaching the soil was the primary driver resulting in a shift from net deposition to emission in harvested catchments. The surface-air Hg fluxes were larger than the fluxes to water as runoff and accounted for 97% of the differences in Hg sequestered in forested versus harvested catchments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2021.116869","usgsCitation":"Eckley, C.S., Eagles-Smith, C., Tate, M., and Krabbenhoft, D.P., 2021, Surface-air mercury fluxes and a watershed mass balance in forested and harvested catchments: Environmental Pollution, v. 277, 116869, 9 p., https://doi.org/10.1016/j.envpol.2021.116869.","productDescription":"116869, 9 p.","ipdsId":"IP-125013","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":453264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9175152","text":"Publisher Index Page"},{"id":385074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Gus Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.92028808593749,\n 45.606352077118316\n ],\n [\n -123.1842041015625,\n 45.606352077118316\n ],\n [\n -123.1842041015625,\n 46.069419674968515\n ],\n [\n -123.92028808593749,\n 46.069419674968515\n ],\n [\n -123.92028808593749,\n 45.606352077118316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"277","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eckley, Chris S. 0000-0002-6986-4451","orcid":"https://orcid.org/0000-0002-6986-4451","contributorId":246031,"corporation":false,"usgs":false,"family":"Eckley","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":39312,"text":"U.S. EPA","active":true,"usgs":false}],"preferred":false,"id":814230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":814231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814233,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218482,"text":"sir20215001 - 2021 - Review of the invasive Asian clam Corbicula spp. (Bivalvia: Cyrenidae) distribution in North America, 1924–2019","interactions":[],"lastModifiedDate":"2021-03-02T12:49:30.337586","indexId":"sir20215001","displayToPublicDate":"2021-03-01T17:11:50","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5001","displayTitle":"Review of the Invasive Asian Clam Corbicula spp. (Bivalvia: Cyrenidae) Distribution in North America, 1924–2019","title":"Review of the invasive Asian clam Corbicula spp. (Bivalvia: Cyrenidae) distribution in North America, 1924–2019","docAbstract":"The bivalve Corbicula is one of the most successful aquatic mollusk invaders in the world. Since being introduced to North America from its native range in Asia, it has dispersed widely over a large portion of the continent from southern Canada to Panama. The first evidence of its introduction in the Western Hemisphere was discovered in 1924 in British Columbia, Canada. A review of distribution records from natural history museums, scientific literature, Federal and State agencies, universities, and oral and written communications with scientists has shown the continued dispersal of Corbicula in North America. Since the most recent comprehensive review of its distribution information through the mid-1980s, Corbicula has been found in an additional 2 Canadian Provinces, 10 U.S. States and Puerto Rico, 9 Mexican States, Cuba, and Panama. The known distribution in North America now includes 47 U.S. States, District of Columbia, Puerto Rico, 3 Canadian Provinces, 16 Mexican States, Cuba, and Panama. Corbicula has been found in three of the Laurentian Great Lakes (Erie, Michigan, Superior) primarily associated with industrial warmwater effluent refugia. Problems associated with Corbicula populations were widely realized not long after its arrival and included negative impacts to power generation, industrial water supply operations, and agricultural water conveyance. In natural settings, impacts on native mussels such as altering nutrient cycling, food webs, and sediment distribution dynamics have occurred. In past decades, control of established open water populations had not been a management priority. With a relatively recent interest in eradication of small, newly established populations, several attempts were made in the United States but were unsuccessful. Recent molecular genetic analyses provide evidence of multiple species and (or) genetically and morphologically distinguishable “forms” in North America. However, the number and identification of Corbicula species in North America remain unresolved. It appears likely that more than one species of Corbicula has been introduced into U.S. waters.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215001","usgsCitation":"Benson, A.J., and Williams, J.D., 2021, Review of the invasive Asian clam Corbicula spp. (Bivalvia: Cyrenidae) distribution in North America, 1924–2019: U.S. Geological Survey Scientific Investigations Report 2021–5001, 66 p., https://doi.org/10.3133/sir20215001.","productDescription":"Report: ix, 66 p.; Data Release","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-119326","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":383682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5001/coverthb.jpg"},{"id":383683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5001/sir20215001.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
7920 NW 71st St.
Gainesville, FL 32653
Aerial surveys integrating probability-based sample designs have been implemented successfully to estimate relative abundance of wintering ducks in Arkansas, Louisiana, Mississippi, and Missouri, but these approaches have not been evaluated in the Atlantic Flyway except for American black ducks (Anas rubripes) along the Atlantic coast. Furthermore, these surveys have not been used to index abundance of other nonbreeding waterbirds. Given elimination or reduction of resources allocated to the Midwinter Waterfowl Survey in the Atlantic Flyway and elsewhere, the South Carolina Department of Natural Resources (SCDNR) expressed a need for reliable surveys to monitor waterfowl and other waterbirds during autumn through winter. We designed stratified aerial strip-transect surveys to estimate population indices for migrating and wintering dabbling ducks (Anatini), diving ducks (Aythini, Mergini, Oxyurini), pelagic and piscivorous waterbirds (Anhingidae, Laridae, Pelicanidae, Phalacrocoracidae), and wading birds (Ardeidae, Ciconiidae, Threskiornithidae) in coastal and inland regions of South Carolina during autumn-winter 2017–2019. We used unequal probability random sampling to estimate population indices with deemed adequate precision (i.e., coefficient of variation [CV] ≤ 20%) and estimated theoretical survey efforts needed to achieve desired precision for future aerial surveys. Indices met our goal for precision in September and January 2018 for wading birds, in February and November 2018 for pelagic waterbirds, and in February 2018 for diving ducks, but never for other ducks during South Carolina waterfowl hunting season. We detected peak abundance of dabbling and diving ducks in January and wading birds and wood storks (Mycteria americana) in September. We estimated ~2.5 times greater survey effort was needed across waterbird taxa than was expended to achieve a CV=20%. We also used survey data to depict spatiotemporal variation in waterbird distributions across the study area. Our surveys are applicable for the SCDNR and other agencies seeking to monitor autumn-winter waterbird populations. Although survey refinements are necessary to increase precision in South Carolina, our waterbird indices are useful to assess population trends through time, guide habitat management and restoration efforts, refine local harvest regulations, inform law enforcement to detected illicit activities (e.g., baiting), and monitor possible shifting waterbird distributions in response to land-use and climate change.
","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Ross, B., Wilkerson, G., Kneece, M., Masto, N., Gerard, P., and Kaminski, R., 2021, Aerial strip-transect surveys: Indexing autumn–winter waterbird abundance and distribution in South Carolina: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 8, p. 89-100.","productDescription":"12 p.","startPage":"89","endPage":"100","ipdsId":"IP-119300","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":480972,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://seafwa.org/journal/2021/aerial-strip-transect-surveys-indexing-autumn-winter-waterbird-abundance-and"},{"id":481109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South 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Kennedy Waterfowl & Wetlands Conservation Center","active":true,"usgs":false}],"preferred":false,"id":924830,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70218461,"text":"ds1133 - 2021 - Compilation of information on occurrence and conservation status for the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma","interactions":[],"lastModifiedDate":"2022-07-12T12:14:55.286929","indexId":"ds1133","displayToPublicDate":"2021-03-01T13:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1133","displayTitle":"Compilation of Information on Occurrence and Conservation Status for the Freshwater Mussel Fauna of Nebraska, Kansas, and Oklahoma","title":"Compilation of information on occurrence and conservation status for the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma","docAbstract":"The purpose of this data series is to compile information on the occurrence and conservation status of the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma and to map the distribution of a freshwater mussel assemblage for the U.S. Department of the Interior, Bureau of Land Management Rapid Ecoregional Assessment (REA) program. The six focal species in the freshwater mussel assemblage are Amblema plicata (threeridge), Fusconaia flava (Wabash pigtoe), Lampsilis cardium (plain pocketbook), Lampsilis teres (yellow sandshell), Pyganodon grandis (giant floater), and Uniomerus tetralasmus (pondhorn). The focal species were selected using the following criteria: (1) the species are regionally significant, (2) occurrence records are sufficient to map the distribution of the species by hydrologic subbasins, (3) the assemblage includes species representing a range of State-level conservation priorities, and (4) the species are not listed as federally endangered or threatened. In addition, the species represent a broad array of life history strategies and habitat associations.
A total of 61 native species of freshwater mussels have documented occurrences within at least 1 of the 3 States, including 6 species that appear to have been extirpated from all the States and 6 species that may have been extirpated from at least 1 State. Of the 61 species, 8 species (including 3 potentially extirpated species) are listed as federally threatened or endangered and an additional 5 species are ranked as imperiled or vulnerable across their range. Approximately 80 percent of the native species known to have occurred within the three-State area have a secure conservation status, in comparison to only 40 percent of all freshwater mussel species or subspecies occurring within the United States. The compiled records for the contemporary period (1970–2017) documented the occurrence of 24 extant species in Nebraska, 42 in Kansas, and 48 in Oklahoma.
The contemporary distributions of the six focal species were mapped by subbasins and the larger hydrologic subregions. Historical records (prior to 1962) were also mapped but were limited. Amblema plicata, Fusconaia flava, and Lampsilis cardium were present in approximately one-third of all subbasins and slightly more than half of the subregions, primarily along the eastern portion of the three-State area. Lampsilis teres and Uniomerus tetralasmus were more widespread, occurring in close to half of the subbasins and about three-quarters of the subregions. Pyganodon grandis was the most widespread, occurring in about three-quarters of the subbasins and almost all subregions. There were very few subbasins with historical occurrences that lacked contemporary occurrences. The broad-scale distribution maps for the freshwater mussel assemblage presented with this report are intended to contribute baseline information for regional assessments, such as the Southern Great Plains Rapid Ecoregional Assessment. Despite the limitations of the available data, such baseline information can be useful for identifying data gaps, monitoring future trends, identifying conservation priorities, and providing the larger context for more detailed watershed- or catchment-level studies. ScienceBase data release files associated with this data series are available at https://doi.org/10.5066/P9SBFZJU (Fancher and Carr, 2021).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1133","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Carr, N.B., and Fancher, T.S., 2021, Compilation of information on occurrence and conservation status for the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma: U.S. Geological Survey Data Series 1133, 22 p., https://doi.org/10.3133/ds1133.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-119647","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":383657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1133/ds1133.pdf","text":"Report","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1133"},{"id":383666,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SBFZJU","text":"USGS data 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\"}}]}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118