The U.S. Geological Survey (USGS) has completed processing of the historical Landsat archive to Collection-2 as of December of 2020 and has released it to the public. As part of Collection-2, several geometric changes have been implemented, including changes to the ground control points (GCPs) and elevation datasets. These datasets are used as a geometric reference for all missions. In addition, mission specific improvements were included in Collection-2, such as improvements to the precision correction algorithms and updates of the calibration parameters. This paper discusses a preliminary analysis of a comparison between the Collection-1 and Collection-2 products of the entire Landsat archive. Compared to the Level 1 products in Collection-1, the number of Tier-1 precision- and terrain-corrected (L1TP) Level 1 products in Collection-2 increased by 6.26% across all sensors. Landsat 8 products showed an increase of Tier-1 L1TP products by 5.33%; Landsat 7 products showed an increase of Tier-1 products by 6.94%; and Landsat 5 and Landsat 4 Thematic Mapper (TM) products showed an increase of Tier-1 products by 9.35%. The geometric accuracy of the Tier-1 terrain corrected products also improved by 2 meters or more.
","largerWorkTitle":"SPIE proceedings volume 11829, earth observing systems XXVI","language":"English","publisher":"SPIE","doi":"10.1117/12.2596200","usgsCitation":"Lubke, M., Rengarajan, R., and Choate, M.J., 2021, Preliminary assessment of the geometric improvements to the Landsat Collection-2 archive, in SPIE proceedings volume 11829, earth observing systems XXVI, v. 11829, 1182901, 14 p., https://doi.org/10.1117/12.2596200.","productDescription":"1182901, 14 p.","ipdsId":"IP-131181","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lubke, Mark 0000-0002-7257-2337","orcid":"https://orcid.org/0000-0002-7257-2337","contributorId":261911,"corporation":false,"usgs":false,"family":"Lubke","given":"Mark","email":"","affiliations":[{"id":53079,"text":"KBR, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":820758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengarajan, Rajagopalan 0000-0003-1860-7110","orcid":"https://orcid.org/0000-0003-1860-7110","contributorId":242014,"corporation":false,"usgs":false,"family":"Rengarajan","given":"Rajagopalan","affiliations":[{"id":48475,"text":"KBR, Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":820759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":216866,"corporation":false,"usgs":true,"family":"Choate","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70226639,"text":"70226639 - 2021 - Brown treesnake mortality after aerial application of toxic baits","interactions":[],"lastModifiedDate":"2021-12-01T13:31:25.091333","indexId":"70226639","displayToPublicDate":"2021-08-06T07:29:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Brown treesnake mortality after aerial application of toxic baits","docAbstract":"Quantitative evaluation of control tools for managing invasive species is necessary to assess overall effectiveness and individual variation in treatment susceptibility. Invasive brown treesnakes (Boiga irregularis) on Guam have caused severe ecological and economic effects, pose a risk of accidental introduction to other islands, and are the greatest impediment to the reestablishment of extirpated native fauna. An aerial delivery system for rodent-based toxic baits can reduce brown treesnake abundance and heterogeneity among individuals may influence bait attraction or toxicant susceptibility. Previous baiting trials have either been simulated aerial treatments or relied on slightly different bait capsule compositions and the results of aerial delivery of toxic baits under operational conditions may not be directly comparable. We monitored 30 radio-tagged adult snakes (990–1,265 mm snout-vent length) during an aerial baiting operation in a 55-ha area using transmitters equipped with accelerometers and receivers programed to display a status code indicating mortality if a snake failed to move for >24 hours. We used known-fate models to estimate mortality and evaluate a priori hypotheses explaining differences in mortality based on size, sex, and treatment effects. Eleven radio-tagged snakes died in the aerial baiting treatment period (0.37, 95% CI = 0.21–0.55) and no individuals (0.00, 95% CI = 0.00–0.04) died during the non-treatment period. Our data provide strong evidence for an additive size-based treatment effect on mortality, with smaller adults (0.59, 95% CI = 0.35–0.80) exhibiting higher mortality than larger snakes (0.14, 95% CI = 0.02–0.37) but did not support a sex effect on mortality. The high mortality of snakes during the treatment period indicates that aerial baiting can reduce brown treesnake abundance, but further refinement or use in combination with other removal tools may be necessary to overcome size-based differences in susceptibility and achieve eradication.
Stormwater discharges from municipalities are regulated by provisions in the Clean Water Act of 1972 to protect the Nation’s water resources from harmful pollutants. In 2014, the Kansas Department of Health and Environment issued new stormwater discharge permits for 17 municipalities in Johnson County, Kansas, in the northeastern part of the State. The county is largely suburban and has 20 municipalities within 22 watersheds. Municipalities in Johnson County are required to implement stormwater management programs that reduce discharges of pollutants, protect water quality, and satisfy applicable water-quality regulations.
In 2015, the U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a 4-year monitoring program designed to meet new stormwater monitoring requirements for some municipalities in Johnson County. Additional data were collected to evaluate the usefulness of continuous water-quality monitoring and different sampling methods in assessing changes in water quality. Twelve of the 22 watersheds in the county were within the sampling network for this project.
Discrete water-quality samples were collected at 25 stream sites and 2 lake sites using passive, grab, and equal-width increment sampling methods. Samples at all sites were analyzed for nutrients, Escherichia coli bacteria, total suspended solids, and suspended-sediment concentration. Ninety-nine percent of storm-event samples and 98 percent of low-flow samples were less than the Kansas Surface Water Quality Standard for nitrate plus nitrite. Eight percent of storm-event samples and 100 percent of low-flow samples were less than the total suspended solids screening value of 50 milligrams per liter. Passive samples generally had higher concentrations when compared to equal-width increment and grab samples, and grab samples and equal-width increment samples generally had similar concentrations.
Continuous water-quality data were collected at one site. Ordinary least squares regression analysis was used to relate continuous (15-minute) water-quality sensor measurements to discretely sampled constituent concentrations at one site.
Numerous factors affect water quality in urban runoff. Urban areas have many possible contaminant sources, including municipal and industrial wastewater discharges, stormwater runoff from impervious surfaces, and failing infrastructure. A better understanding of these factors can inform future monitoring efforts, leading to datasets that are representative of storm runoff and can be used to detect differences between sites and over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215041","collaboration":"Prepared in cooperation with the Johnson County Stormwater Management Program","usgsCitation":"Leiker, B.M., Rasmussen, T.J., Eslick-Huff, P.J., and Painter, C.C., 2021, Assessment of water-quality constituents monitored for total maximum daily loads in Johnson County, Kansas, January 2015 through December 2018: U.S. Geological Survey Scientific Investigations Report 2021–5041, 45 p., https://doi.org/10.3133/sir20215041.","productDescription":"Report: viii, 45 p.; Appendixes: 62 p.; Data Release","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-119343","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":387659,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91397BC","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality and preceding precipitation data for low-flow and storm-event samples collected in Johnson County, Kansas, from January 2015 through November 2018"},{"id":387657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5041/sir20215041.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5041"},{"id":387656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5041/coverthb.jpg"},{"id":387658,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5041/sir20215041_appendixes_2to6.pdf","text":"Appendixes 2–6","size":"2.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5041 Appendixes"}],"country":"United States","state":"Kansas","county":"Johnson County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.6075,39.0437],[-94.6075,39.0399],[-94.6082,38.8463],[-94.6084,38.8341],[-94.6102,38.7376],[-95.0572,38.7395],[-95.0558,38.9816],[-95.0477,38.9778],[-95.0383,38.9771],[-95.0312,38.9773],[-95.0292,38.9813],[-95.0271,38.9881],[-95.0249,38.9962],[-95.0189,38.9987],[-95.0135,38.9991],[-95.0077,38.998],[-94.9946,38.9976],[-94.9899,38.997],[-94.9841,38.995],[-94.9789,38.9926],[-94.9755,38.9885],[-94.9704,38.9851],[-94.9645,38.9832],[-94.9575,38.982],[-94.9527,38.9828],[-94.9479,38.9845],[-94.9448,38.9871],[-94.9423,38.9898],[-94.9386,38.9933],[-94.9367,38.9964],[-94.9335,38.9995],[-94.9264,38.9998],[-94.9217,38.9996],[-94.9176,38.9977],[-94.9209,38.9919],[-94.923,38.9856],[-94.9207,38.9837],[-94.9164,38.9859],[-94.9115,38.9889],[-94.9078,38.9924],[-94.9014,39.0022],[-94.8989,39.0053],[-94.8945,39.0102],[-94.8919,39.0155],[-94.891,39.021],[-94.8875,39.0313],[-94.8824,39.0379],[-94.8768,39.0441],[-94.8681,39.052],[-94.8631,39.0564],[-94.8488,39.0578],[-94.8318,39.0546],[-94.8131,39.0486],[-94.8038,39.0456],[-94.7197,39.0435],[-94.6693,39.0433],[-94.6075,39.0437]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"KS\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
Private lands provide key habitat for imperiled species and are core components of function protected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social-ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13673","usgsCitation":"Williamson, M., Dickson, B., Hooten, M., Graves, R., Lubell, M., and Schwartz, M., 2021, Improving inferences about private land conservation by accounting for incomplete reporting: Conservation Biology, v. 35, no. 4, p. 1174-1185, https://doi.org/10.1111/cobi.13673.","productDescription":"12 p.","startPage":"1174","endPage":"1185","ipdsId":"IP-113790","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.044156,43.020052],[-111.046689,42.001567],[-112.173352,41.996568],[-112.192976,42.001167],[-112.709375,42.000309],[-113.893261,41.988057],[-114.041723,41.99372],[-114.598267,41.994511],[-114.831077,42.002207],[-115.031783,41.996008],[-117.026222,42.000252],[-117.02678,43.829841],[-117.01077,43.862269],[-116.98294,43.86771],[-116.977332,43.905812],[-116.96247,43.928336],[-116.963666,43.952644],[-116.971835,43.962806],[-116.942944,43.987512],[-116.934485,44.021249],[-116.943361,44.035645],[-116.972504,44.048771],[-116.977351,44.085364],[-116.933704,44.100039],[-116.894309,44.158114],[-116.900103,44.176851],[-116.925392,44.191544],[-116.971675,44.197256],[-116.975905,44.242844],[-117.031862,44.248635],[-117.042283,44.242775],[-117.050057,44.22883],[-117.089503,44.258234],[-117.098531,44.275533],[-117.107673,44.280763],[-117.118018,44.278945],[-117.143394,44.258262],[-117.170342,44.25889],[-117.198147,44.273828],[-117.222647,44.297578],[-117.217843,44.30718],[-117.2055,44.311789],[-117.189842,44.335007],[-117.196149,44.346362],[-117.235117,44.373853],[-117.242675,44.396548],[-117.22698,44.405583],[-117.215072,44.427162],[-117.215573,44.453746],[-117.225076,44.482346],[-117.200237,44.492027],[-117.181583,44.52296],[-117.161033,44.525166],[-117.149242,44.536151],[-117.14293,44.557236],[-117.147934,44.562143],[-117.146032,44.568603],[-117.126009,44.581553],[-117.120522,44.614658],[-117.098221,44.640689],[-117.095868,44.664737],[-117.07912,44.692175],[-117.061799,44.706654],[-117.062273,44.727143],[-117.03827,44.748179],[-117.013802,44.756841],[-116.998903,44.756382],[-116.972902,44.772581],[-116.9368,44.782881],[-116.9308,44.790981],[-116.931099,44.804781],[-116.896249,44.84833],[-116.865338,44.870599],[-116.852427,44.887577],[-116.83199,44.933007],[-116.850737,44.958113],[-116.858313,44.978761],[-116.846103,44.999878],[-116.848037,45.021728],[-116.797329,45.060267],[-116.78371,45.076972],[-116.783537,45.093605],[-116.774847,45.105536],[-116.754643,45.113972],[-116.731216,45.139934],[-116.724205,45.171501],[-116.709536,45.203015],[-116.703607,45.239757],[-116.691388,45.263739],[-116.675587,45.274867],[-116.672733,45.283183],[-116.673793,45.321511],[-116.619057,45.39821],[-116.597447,45.41277],[-116.588195,45.44292],[-116.554829,45.46293],[-116.558803,45.480076],[-116.548676,45.510385],[-116.523638,45.54661],[-116.502756,45.566608],[-116.48297,45.577008],[-116.463635,45.602785],[-116.463504,45.615785],[-116.487894,45.649769],[-116.535396,45.691734],[-116.535698,45.734231],[-116.546643,45.750972],[-116.593004,45.778541],[-116.632032,45.784979],[-116.646342,45.779815],[-116.665344,45.781998],[-116.680139,45.79359],[-116.697192,45.820135],[-116.711822,45.826267],[-116.736268,45.826179],[-116.759787,45.816167],[-116.782676,45.825376],[-116.788329,45.831928],[-116.790151,45.849851],[-116.814142,45.877551],[-116.84355,45.892273],[-116.859795,45.907264],[-116.892935,45.974396],[-116.91868,45.999875],[-116.942656,46.061],[-116.957372,46.075449],[-116.978938,46.080007],[-116.981962,46.084915],[-116.978823,46.095731],[-116.955263,46.102237],[-116.950276,46.123464],[-116.922648,46.160744],[-116.923958,46.17092],[-116.965841,46.203417],[-116.955264,46.23088],[-116.966742,46.256923],[-116.991134,46.276342],[-116.986688,46.296662],[-117.020663,46.314793],[-117.027744,46.338751],[-117.051735,46.343833],[-117.06263,46.352522],[-117.062785,46.365287],[-117.046915,46.379577],[-117.034696,46.418318],[-117.039813,46.425425],[-117.042657,47.760857],[-117.032351,48.999188],[-104.048736,48.999877],[-104.041662,47.862282],[-104.046822,46.000199],[-104.040128,44.999987],[-105.913382,45.000941],[-105.928184,44.993647],[-106.263586,44.993788],[-107.351441,45.001407],[-109.08301,44.99961],[-109.103445,45.005904],[-110.110103,45.003905],[-110.199503,44.996188],[-110.362698,45.000593],[-110.402927,44.99381],[-110.552433,44.992237],[-110.705272,44.992324],[-110.785008,45.002952],[-111.055199,45.001321],[-111.044156,43.020052]]]},\"properties\":{\"name\":\"Idaho\",\"nation\":\"USA \"}}]}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Williamson, Matthew A.","contributorId":351796,"corporation":false,"usgs":false,"family":"Williamson","given":"Matthew A.","affiliations":[{"id":84047,"text":"bsu","active":true,"usgs":false}],"preferred":false,"id":929510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickson, Brett G.","contributorId":351797,"corporation":false,"usgs":false,"family":"Dickson","given":"Brett G.","affiliations":[{"id":62994,"text":"CSP","active":true,"usgs":false}],"preferred":false,"id":929511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin","contributorId":18254,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","affiliations":[],"preferred":false,"id":929695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Rose A.","contributorId":351798,"corporation":false,"usgs":false,"family":"Graves","given":"Rose A.","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":929512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lubell, Mark N.","contributorId":351799,"corporation":false,"usgs":false,"family":"Lubell","given":"Mark N.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Mark W.","contributorId":351800,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark W.","affiliations":[{"id":54468,"text":"uc","active":true,"usgs":false}],"preferred":false,"id":929514,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222458,"text":"ofr20211073 - 2021 - Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","interactions":[],"lastModifiedDate":"2021-08-06T21:38:29.620031","indexId":"ofr20211073","displayToPublicDate":"2021-08-05T15:00:00","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":"2021-1073","displayTitle":"Reconnaissance Study of the Major and Trace Element Content of Bauxite Deposits in the Arkansas Bauxite Region, Saline and Pulaski Counties, Central Arkansas","title":"Reconnaissance study of the major and trace element content of bauxite deposits in the Arkansas bauxite region, Saline and Pulaski Counties, central Arkansas","docAbstract":"The Arkansas bauxite district, which comprises about 275 square miles (710 square kilometers) of central Arkansas, produced an order of magnitude more bauxite and alumina than the other bauxite districts in the United States combined. Bauxite was mined in the region continuously from 1898 to 1982. These bauxites are laterite deposits, formed from intensive in-place weathering of the exposed surface of the Granite Mountain pluton, a Late Cretaceous batholith composed mainly of nepheline syenite and lesser amounts of syenite. Nepheline syenite was the aluminum source for the bauxite and clay deposits that blanket the pluton. The early Eocene continental sedimentary rocks that contain and overlie the bauxite deposits indicate that central Arkansas had a warm tropical environment during bauxite formation.
Bauxite ores are the principal sources of aluminum. Some of the global bauxite deposits have been found to contain co-occurring metals that have essential applications in modern technologies. For example, bauxite is the largest global source of gallium (Ga), used in semiconductors, which is recovered as a byproduct of processing bauxite to recover alumina. Other critical metal commodities within some bauxites that reportedly have potential for byproduct recovery include niobium (Nb), scandium (Sc), and rare earth elements (REEs). Currently (2021), the United States is wholly dependent on imports for its supplies of bauxite for processing to produce alumina. The United States is also dependent on foreign sources of gallium, niobium, and scandium, as well for most of its domestic requirements of REEs.
For these reasons, samples were collected from Arkansas bauxite deposits, associated clays, mill residue wastes (respectively referred to as red muds and black sands), and the parent nepheline syenite to determine their elemental content, with a particular focus on gallium, niobium, scandium, and REEs. Each sample was analyzed for 60 elements; these data and the methods used are published as a U.S. Geological Survey data release.
The results indicate that, of the critical metals in bauxites, gallium is a potential byproduct from the central Arkansas bauxite deposits. The highest gallium concentrations occur in the raw bauxite ore, with an average concentration of 76 parts per million (ppm). Gallium partitions with alumina (the product) rather than into mine waste residues. Results indicate an average niobium content of 662 ppm in the Arkansas bauxite ores. Niobium progressively increases in concentration from parent syenite (247 ppm) to clays (315 ppm) and further from bauxite (662 ppm) to processed residues (1,075 ppm). Low concentrations of scandium were found in all samples, averaging 10 ppm or less in the parent rock (syenite), bauxite, clays, and processing residues. Modest concentrations of the light and heavy REEs were found in samples of bauxite ores, bauxitic clays and interbedded clays, syenite, and the residues of ore. The highest REE values were found in processed residues, with average concentrations of 613 ppm total light REEs and 130 ppm total heavy REEs. These concentrations suggest that additional processing to recover REEs is unlikely to be economic in the foreseeable future.
Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
The Eastern Nebraska Water Resources Assessment (ENWRA) project was initiated in 2006 to assist water managers by developing a hydrogeologic framework and water budget for the glaciated portion of eastern Nebraska. Within the ENWRA area, the primary groundwater sources for municipal, domestic, and irrigation water needs are provided by withdrawals from alluvial, buried paleovalley, and the High Plains aquifer (where present). Generally, other bedrock aquifers are considered a secondary water source. However, in some areas, such as parts of Sarpy and Nemaha Counties, these secondary bedrock aquifers are the only source of water within glaciated upland areas. To improve the understanding of the quality, geochemistry, and age of groundwater from bedrock aquifers, the U.S. Geological Survey (USGS), in cooperation with the ENWRA group, which includes the Lewis and Clark, Lower Elkhorn, Lower Platte North, Lower Platte South, Nemaha, and Papio-Missouri River Natural Resources Districts, designed a study to sample 31 wells completed in the secondary bedrock aquifers and analyze samples for major ions, physical properties, nutrients, stable isotopes, and selected age tracers. Of the 31 samples collected for this report, 22 samples were collected from the Dakota aquifer contained in the Dakota Sandstone, 3 from the Niobrara aquifer contained in the Niobrara Formation of Colorado Group, and 6 from Paleozoic aquifers contained in undifferentiated Paleozoic-age units.
The results of this study indicate that major ion data collected from the Dakota aquifer can be used for assessing the quality, recharge source, and age of groundwater. Calcium bicarbonate dominant samples were characterized as modern or mixed, indicating that, in these areas, groundwater is unconfined and is recharged by precipitation and (or) surface water. If groundwater extraction rates exceed recharge rates, total dissolved solid concentrations may increase as a result of upwelling of groundwater from deeper units or formations, which can adversely affect groundwater quality. Sampling results presented in this report indicate water quality is good, but that groundwater in the Dakota aquifer with calcium bicarbonate water type may be vulnerable to surface contamination. In contrast, groundwater sampled from the Dakota aquifer, having a dominant water type other than calcium bicarbonate, generally has low dissolved oxygen and nitrate concentrations, and higher concentrations of total dissolved solids and trace elements, including iron and strontium. The geochemical characteristics of noncalcium bicarbonate samples from the Dakota aquifer indicated confining conditions and limited groundwater recharge from local precipitation. Apparent groundwater ages estimated from radiocarbon (carbon-14) sampling of noncalcium bicarbonate samples from the Dakota aquifer indicated that the time of groundwater recharge to the Dakota aquifer occurred during Pleistocene time. Depleted stable isotopes results indicate recharge during a colder climate. Groundwater under confined conditions is not easily recharged from precipitation or surface water. Future groundwater-level monitoring in locations where the Dakota aquifer appears to be confined could provide information to evaluate whether groundwater supplies remain sufficient to meet future municipal, domestic, and irrigation needs.
For the Niobrara aquifer and Paleozoic aquifers, the dominant water type was not a diagnostic indicator of recharge source, age, and groundwater quality as with the Dakota aquifer. Most likely this is because the host formation was dominated by calcium-carbonate-rich rocks; however, few samples were collected from these aquifers to be able to confirm this interpretation. Samples collected from wells completed in the Niobrara aquifer and Paleozoic aquifers and characterized as calcium sulfate water type have statistically significantly higher concentrations of total dissolved solids compared to other samples from the Niobrara aquifer and Paleozoic aquifers characterized as calcium bicarbonate. Given that six of the nine of samples collected from the Niobrara and Paleozoic aquifers indicated modern recharge, these secondary bedrock aquifers are reliant on precipitation to sustain groundwater levels and may be vulnerable to a multiyear drought. Well yields of the Niobrara and Paleozoic aquifers are dependent on the presence of secondary porosity and these units offer little storage. Samples collected from wells completed in Paleozoic aquifers were the most isotopically enriched and similar to modern precipitation and had the highest concentrations of nitrate, indicating that groundwater is affected by agricultural activities. Future groundwater sampling would be beneficial to characterize groundwater-quality changes within the Niobrara and Paleozoic aquifers over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215055","collaboration":"Prepared in cooperation with the Eastern Nebraska Water Resources Assessment","usgsCitation":"Hobza, C.M., and Flynn, A.T., 2021, Groundwater quality and age of secondary bedrock aquifers in the glaciated portion of eastern Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5055, 42 p., https://doi.org/10.3133/sir20215055.","productDescription":"Report: viii, 42 p.; Dataset","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-122775","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":387641,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":387643,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5055/sir20215055.XML","linkFileType":{"id":8,"text":"xml"}},{"id":387642,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5055/images"},{"id":387640,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5055/sir20215055.pdf","text":"Report","size":"2.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5055"},{"id":387639,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5055/coverthb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.9541015625,\n 42.779275360241904\n ],\n [\n -97.7783203125,\n 42.261049162113856\n ],\n [\n -97.58056640625,\n 41.52502957323801\n ],\n [\n -97.05322265625,\n 41.07935114946899\n ],\n [\n -96.87744140625,\n 40.64730356252251\n ],\n [\n -96.591796875,\n 39.99395569397331\n ],\n [\n -95.2734375,\n 39.977120098439634\n ],\n [\n -95.49316406249999,\n 40.3130432088809\n ],\n [\n -95.80078125,\n 40.713955826286046\n ],\n [\n -95.91064453125,\n 41.31082388091818\n ],\n [\n -96.13037109375,\n 42.00032514831621\n ],\n [\n -96.5478515625,\n 42.65012181368022\n ],\n [\n -97.0751953125,\n 42.87596410238256\n ],\n [\n -97.822265625,\n 42.89206418807337\n ],\n [\n -97.9541015625,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
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5231 South 19th Street
Lincoln, NE 68512
Temporal variations of de facto wastewater reuse are relevant to public drinking water systems (PWSs) that obtain water from surface sources. Variations in wastewater discharge flows, streamflow, de facto reuse, and disinfection by-products (DBPs – trihalomethane-4 [THM4] and haloacetic acid-5 [HAA5]) over an 18-year period were examined at 11 PWSs in the Shenandoah River watershed, using more than 25,000 data records, in gaged and ungaged reaches. The relationship of de facto reuse with DBPs by year and quarter at the PWSs was examined. A linear relationship was found between THM4 and de facto reuse on an annual average basis (p = 0.050), as well as in quarters 3 (July – September) (p = 0.032) and 4 (October – December) (p = 0.031). Using a t-test (p < 0.05), the study also showed that there were significant differences in DBP levels for PWSs relative to 1% de facto reuse. This was found for THM4 based on annual average and quarter 1 (January – March) data, and for HAA5 based on quarter 3 data during the period of record.
The Green Mountain State of Vermont is known for its vast swaths of deciduous forest, patches of evergreen, and the Green Mountains that run through its center.
Valuable insight into the forests and landscape features of Vermont can be gleaned from the 50-year historical record of Landsat satellite imagery. The archive is accessible at no cost to researchers, land managers, and the public thanks to the open data policy of the U.S. Geological Survey’s National Land Imaging Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213038","usgsCitation":"U.S. Geological Survey, 2021, Vermont and Landsat (ver. 1.1, February 2023): U.S. Geological Survey Fact Sheet 2021–3038, 2 p., https://doi.org/10.3133/fs20213038.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-129952","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":413179,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20213038/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":413174,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3038/fs20213038.pdf","text":"Report","size":"2.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021–3038"},{"id":413175,"rank":3,"type":{"id":25,"text":"Version 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\"}}]}","edition":"Version 1.0: August 3, 2021; Version 1.1: February 17, 2023","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Eastern Bangladesh sits on the seismically active Chittagong-Myanmar fold and thrust belt (CMFB), a north-trending accretionary wedge on the eastern side of the India-Eurasia collision. Earthquakes on the basal décollement and associated thrusts within the CMFB present a hazard to this densely populated region. In this study, we interpret 28 seismic reflection profiles from both published and unpublished sources to constrain the depth of the basal décollement. To convert profiles from the time domain to the depth domain, we integrate sonic log and seismic stacking velocity data to generate time-velocity relationships for different parts of the CMFB. Our analysis reveals that the décollement is ∼9 km deep in northeast and southeast Bangladesh, but shallows to ∼5 km in east-central Bangladesh. The décollement has an area of 7.25 × 104 km2 (∼150 × 450 km), making it capable of an Mw 8.5 earthquake. However, the warped geometry of this fault might act as a rupture barrier were a large earthquake to occur on the décollement. Our combined velocity and fault model lay the groundwork for future studies to address seismic segmentation, ground shaking, and rupture modeling in the CMFB. Finally, we use our compiled data set to analyze the evolution of fold kinematics in the CMFB. We observe that folding style and failure mode varies, from mainly ductile deformation in the foreland to mainly brittle in the hinterland. The dual-failure modes within the CMFB support the hypothesis that a region with ductile deformation may still be capable of seismic behavior.
Historically, the Mississippi Alluvial Valley (MAV) (Partners in Flight Bird Conservation Region #26) was predominantly bottomland hardwood forest, but natural vegetation has been cleared from about 80 percent of this ecoregion and converted primarily to agriculture. Because most bird species that are of conservation concern in this region are dependent on forested wetlands, bottomland hardwood forest is the habitat of greatest conservation concern in the MAV. Past conservation planning for forest-dwelling birds in this region has focused on habitat objectives with presumptions regarding bird population goals being met through habitat provision. To better define population objectives, we estimated current populations of silvicolous birds on the basis of detections during 10 years of North American Breeding Bird Surveys (BBS). For each species, we used their estimated population and historical (1966–2015) change in their relative abundance, as assessed from BBS data, to establish regional population goals. We used the variance associated with historical BBS trends to estimate the minimum forest area required to sustain greater than or equal to (≥) 25 breeding pairs, which we combined with predicted probability of occupancy to identify sustainable forested habitat. For 54 species, we used published empirical density estimates, as affected by forest management, to estimate the proportion of the population objective that could be provisioned within sustainable forest patches. The area of presumed population-sustaining habitat, under existing forest management, was sufficient to support the species’ population objective for 23 species. We estimated that the target populations of seven additional species (Black-and-white Warbler, Brown Thrasher, Cerulean Warbler, Eastern Towhee, Indigo Bunting, Wood Thrush, and Yellow-breasted Chat) could be supported by current forest area through widespread changes in forest management. Target populations of seven other species (American Robin, Barred Owl, Boat-tailed Grackle, Chipping Sparrow, Eastern Phoebe, Mississippi Kite, and Red-headed Woodpecker) were accommodated within the MAV when populations in both forest and nonforest habitats are considered. For the remaining 20 species, we estimated the population increase needed to achieve their population goals. For these species, we estimated the additional area of forest restoration required to achieve their population goal within sustainable forest patches or, alternatively, the additional area of occupied habitat required to support their population goal within both forest and nonforest habitat. An additional 700,000 hectares of sustainable forest habitat may be enough to attain the forest-dependent population goals for most bird species within the MAV.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201097","collaboration":"Prepared in cooperation with the Lower Mississippi Valley Joint Venture","usgsCitation":"Twedt, D.J., and Mini, A., 2021, Forest area to support landbird population goals for the Mississippi Alluvial Valley (ver. 1.1, August 2021): U.S. Geological Survey Open-File Report 2020–1097, 84 p., https://doi.org/10.3133/ofr20201097.","productDescription":"Report: vi, 75 p.; 2 Appendixes; Version History","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-112336","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":436253,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YMSM8I","text":"USGS data release","linkHelpText":"Eastern Ecological Science CenterxLegacy Data ReleasesPatuxent Wildlife Research CenterPredicted Avian Species Occupancy, Area of Sustainable Forest Habitat, and Area of Occupied Habitat within the Mississippi Alluvial Valley Bird Conservation Region Predicted Avian Species Occupancy, Area of Sustainable Forest Habitat, and Area of Occupied Habitat within the Mississippi Alluvial Valley Bird Conservation Region"},{"id":436252,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AFKXXK","text":"USGS data release","linkHelpText":"Stop locations along Breeding Bird Survey routes in the Gulf Coastal Plains &amp;amp; Ozarks region"},{"id":381438,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1097/ofr20201097.pdf","text":"Report","size":"2.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1097"},{"id":387552,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1097/versionHist.txt","size":"519 B","linkFileType":{"id":2,"text":"txt"}},{"id":381541,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://doi.org/10.5066/P9YMSM8I","text":"Appendixes 7, 8, and 9","linkHelpText":"- Predicted avian species occupancy"},{"id":381539,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://doi.org/10.5066/P9AFKXXK","text":"Appendixes 2 and 3","linkHelpText":"- Bird detections during North American Breeding Bird Surveys"},{"id":381437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1097/coverthb3.jpg"}],"country":"United States","state":"Arkansas, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Mississippi Alluvial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.76953125,\n 36.932330061503144\n ],\n [\n -89.80224609374999,\n 37.142803443716836\n ],\n [\n -90.06591796875,\n 37.055177106660814\n ],\n [\n -92.04345703125,\n 34.63320791137959\n ],\n [\n -91.91162109375,\n 32.47269502206151\n ],\n [\n -92.197265625,\n 30.41078179084589\n ],\n [\n -90.06591796875,\n 29.22889003019423\n ],\n [\n -89.4287109375,\n 30.012030680358613\n ],\n [\n -91.1865234375,\n 31.372399104880525\n ],\n [\n -90.63720703125,\n 32.565333160841035\n ],\n [\n -89.7802734375,\n 33.46810795527896\n ],\n [\n -89.7802734375,\n 34.615126683462194\n ],\n [\n -88.76953125,\n 36.932330061503144\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021; Version 1.0: February 2021","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD 20708
Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) is a long-lived, anadromous species that is broadly distributed along the Atlantic coast of North America. Historic overharvest and habitat degradation resulted in significant declines to Atlantic sturgeon populations and, following decades of limited recovery, the species was listed under the Endangered Species Act of the United States in 2012. Given continued threats to recovery and limited information about population demography, there is a need for new tools to assist in Atlantic sturgeon conservation. Here, we present a range-wide microsatellite genetic baseline for North American Atlantic sturgeon that is comprised of 2510 individuals from 18 genetically distinct groups collected in 13 rivers and one estuary. Analysis of this baseline suggested that populations from the northern range of Atlantic sturgeon were more highly differentiated than those from the southern extent, where patterns of differentiation were complicated by rivers with genetically distinct spring and fall spawning runs and less geographic distance separating populations. Despite significant demographic bottleneck events, all populations showed at least moderate levels of genetic diversity across a suite of metrics. Additionally, individual-based assignment tests had over 80% accuracy for assigning individuals to their river of origin, highlighting the utility of this baseline for characterizing the composition of mixed-stock aggregations and understanding stock-specific vulnerability and recovery. The expanded spatial coverage of this baseline dataset enabled novel inferences about patterns of genetic differentiation and spawning phenology in Atlantic sturgeon which can be used to support conservation and management efforts.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-021-01390-x","usgsCitation":"White, S.L., Kazyak, D., Darden, T.L., Farrae, D.J., Lubinski, B.A., Johnson, R.L., Eackles, M.S., Balazik, M., Brundage, H., Fox, A.G., Fox, D.A., Hager, C.H., Kahn, J.E., and Wirgin, I.I., 2021, Establishment of a microsatellite genetic baseline for North American Atlantic sturgeon (Acipenser o. oxyrhinchus) and range-wide analysis of population genetics: Conservation Genetics, v. 22, p. 977-992, https://doi.org/10.1007/s10592-021-01390-x.","productDescription":"16 p.","startPage":"977","endPage":"992","ipdsId":"IP-124759","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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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":820833,"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":820834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Darden, Tanya L.","contributorId":263425,"corporation":false,"usgs":false,"family":"Darden","given":"Tanya","email":"","middleInitial":"L.","affiliations":[{"id":53977,"text":"SC DNR","active":true,"usgs":false}],"preferred":false,"id":820835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farrae, Daniel J.","contributorId":263426,"corporation":false,"usgs":false,"family":"Farrae","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":53977,"text":"SC DNR","active":true,"usgs":false}],"preferred":false,"id":820836,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":820837,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Robin L. 0000-0003-4314-3792 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Resources, Delaware State University","active":true,"usgs":false}],"preferred":false,"id":820843,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hager, Chris H","contributorId":263429,"corporation":false,"usgs":false,"family":"Hager","given":"Chris","email":"","middleInitial":"H","affiliations":[{"id":53979,"text":"Chesapeake Scientific","active":true,"usgs":false}],"preferred":false,"id":820844,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kahn, Jason E","contributorId":263430,"corporation":false,"usgs":false,"family":"Kahn","given":"Jason","email":"","middleInitial":"E","affiliations":[{"id":53980,"text":"NMFS","active":true,"usgs":false}],"preferred":false,"id":820845,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wirgin, Isaac 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geophysical maps of the Santa Maria and part of the Point Conception 30'×60' quadrangles, California"},"id":1},{"subject":{"id":21108,"text":"ofr9525 - 1995 - Preliminary digital geologic map of the Santa Maria 30' x 60' Quadrangle, California, in ARC/INFO, with exploration well locations and subsurface formation depths","indexId":"ofr9525","publicationYear":"1995","noYear":false,"title":"Preliminary digital geologic map of the Santa Maria 30' x 60' Quadrangle, California, in ARC/INFO, with exploration well locations and subsurface formation depths"},"predicate":"SUPERSEDED_BY","object":{"id":70222414,"text":"sim3472 - 2021 - Geologic and geophysical maps of the Santa Maria and part of the Point Conception 30'×60' quadrangles, California","indexId":"sim3472","publicationYear":"2021","noYear":false,"title":"Geologic and geophysical maps of the Santa Maria and part of the Point Conception 30'×60' quadrangles, California"},"id":2}],"lastModifiedDate":"2021-08-03T11:47:53.611967","indexId":"sim3472","displayToPublicDate":"2021-08-02T09:30:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3472","displayTitle":"Geologic and Geophysical Maps of the Santa Maria and Part of the Point Conception 30'×60' Quadrangles, California","title":"Geologic and geophysical maps of the Santa Maria and part of the Point Conception 30'×60' quadrangles, California","docAbstract":"This report presents digital geologic, gravity, and aeromagnetic maps for the onshore parts of the Santa Maria and Point Conception 30'x60' quadrangles at a compilation scale of 1:100,000. The map depicts the distribution of bedrock units, surficial deposits, paleontological data, geophysical data and structural features in the Santa Maria basin and the Santa Ynez Mountains to the south, an area corresponding to 26 contiguous 7.5-minute quadrangles. The map also includes offshore faults from the Hosgri fault, a major structural feature, east to the shoreline. This new map revises and supersedes two earlier versions of the 30'x60' Santa Maria quadrangle that were produced as part of the U.S. Geological Survey’s investigations of onshore oil and gas resources of the Santa Maria province (Keller, 1995). The first map was released as a scanned black-and-white image of hand-drawn compilation (Tennyson, 1992); the second map was a digital release that is no longer available (Tennyson and others, 1995). This new map also includes the geology of the onshore part of the adjacent Point Conception 30'x60' quadrangle that encompasses the Santa Ynez Mountains of the western Transverse Ranges. The digital database also contains magnetic and gravity data for the entire region, paleontological data, and interpretation of major offshore structural features that bear on the continuity and connection of the mapped onshore structures.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3472","usgsCitation":"Sweetkind, D.S., Langenheim, V.E., McDougall-Reid, K., Sorlien, C.C., Demas, S.C., Tennyson, M.E., and Johnson, S.Y., 2021, Geologic and geophysical maps of the Santa Maria and part of the Point Conception 30'×60' quadrangles, California: U.S. Geological Survey Scientific Investigations Map 3472, 1 sheet, scale 1:100,000, 58-p. pamphlet, https://doi.org/10.3133/sim3472. [Supersedes USGS Open-File Reports 95–25 and 92–189.]","productDescription":"Report: vi, 58 p.; 9 Sheets: 57.14 x 35.04 inches or smaller; Data Release; ReadMe; Related Works","onlineOnly":"Y","ipdsId":"IP-054681","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":387551,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181024","linkHelpText":"California State Waters Map Series — Offshore of Point Conception, California"},{"id":387550,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3319","linkHelpText":"California State Waters Map Series: offshore of Refugio Beach, 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MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3472 Multilayered, interactive, geospatial PDF","linkHelpText":"Download file and view it in Adobe Acrobat DC or Adobe Reader DC to access interactive layers."}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.16271972656249,\n 34.266296360583546\n ],\n [\n -119.8443603515625,\n 34.266296360583546\n ],\n [\n -119.8443603515625,\n 34.93548199355901\n ],\n [\n -121.16271972656249,\n 34.93548199355901\n ],\n [\n -121.16271972656249,\n 34.266296360583546\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Beginning in 2015, the United States Environmental Protection Agency’s (EPA’s) National Estuary Program (NEP) started a collaboration with partners in seven estuaries along the East Coast (Barnegat Bay; Casco Bay), West Coast (Santa Monica Bay; San Francisco Bay; Tillamook Bay), and the Gulf of Mexico (GOM) Coast (Tampa Bay; Mission-Aransas Estuary) of the United States to expand the use of autonomous monitoring of partial pressure of carbon dioxide (pCO2) and pH. Analysis of high-frequency (hourly to sub-hourly) coastal acidification data including pCO2, pH, temperature, salinity, and dissolved oxygen (DO) indicate that the sensors effectively captured key parameter measurements under challenging environmental conditions, allowing for an initial characterization of daily to seasonal trends in carbonate chemistry across a range of estuarine settings. Multi-year monitoring showed that across all water bodies temperature and pCO2 covaried, suggesting that pCO2 variability was governed, in part, by seasonal temperature changes with average pCO2 being lower in cooler, winter months and higher in warmer, summer months. Furthermore, the timing of seasonal shifts towards increasing (or decreasing) pCO2 varied by location and appears to be related to regional climate conditions. Specifically, pCO2 increases began earlier in the year in warmer water, lower latitude water bodies in the GOM (Tampa Bay; Mission-Aransas Estuary) as compared with cooler water, higher latitude water bodies in the northeast (Barnegat Bay; Casco Bay), and upwelling-influenced West Coast water bodies (Tillamook Bay; Santa Monica Bay; San Francisco Bay). Results suggest that both thermal and non-thermal influences are important drivers of pCO2 in Tampa Bay and Mission-Aransas Estuary. Conversely, non-thermal processes, most notably the biogeochemical structure of coastal upwelling, appear to be largely responsible for the observed pCO2 values in West Coast water bodies. The co-occurrence of high salinity, high pCO2, low DO, and low temperature water in Santa Monica Bay and San Francisco Bay characterize the coastal upwelling paradigm that is also evident in Tillamook Bay when upwelling dominates freshwater runoff and local processes. These data demonstrate that high-quality carbonate chemistry observations can be recorded from estuarine environments using autonomous sensors originally designed for open-ocean settings.
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Largier, Nielsen, K., Hu, X., McCutcheon, M., Vasslides, J., Poach, M., Ford, T., Johnston, K., and Steele, A., 2021, Integrating high-resolution coastal acidification monitoring data across seven United States estuaries: Frontiers in Marine Science, v. 8, 679913, 21 p., https://doi.org/10.3389/fmars.2021.679913.","productDescription":"679913, 21 p.","ipdsId":"IP-122630","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.679913","text":"Publisher Index Page"},{"id":408298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Florida, Maine, New Jersey, Oregon, Texas,","otherGeospatial":"Aransas Estuary, Barnegat Bay, Casco Bay Estuary, Coastal Bend Bay, San Francisco Bay Estuary, Santa Monica Bay, Tampa Bay 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This annual report focuses on changes in population abundance and habitat use by natural- and hatchery-origin spawners. Typically, we also report on population attributes of natural-origin juveniles, but data on juveniles were not collected in 2020 due to Covid-19. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching the point that no more redds can be supported. Timing of spawning and fry emergence have been relatively stable, but effects of density dependence are evident in juvenile life stages. Apparent abundance of juvenile fall Chinook salmon has increased and we noted the following changes: parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier; growth rate (g/d) and dispersal size of parr has declined; and passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate has increased. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir resulting from the expansion of the recovery program. The long-term goal is to use this information in a comprehensive modeling effort to conduct action-effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management Research, Monitoring, and Evaluation (RM&E) programs.
In 2020, the U.S. Geological Survey (USGS) focused survey efforts in the Snake River on deepwater redd searches and fish collection for parentage-based tagging (PBT) analyses. We use a boat-mounted underwater video camera to count 170 deepwater redds at 19 of the 28 sites surveyed. Redd depths averaged 4.2 m. We collected genetic samples from 297 live fall Chinook salmon and 16 carcasses at 44 unique geographic locations that spanned 89 river kilometers. Seventy-two fish were recovered at Eureka Bar (rkm 307.1) and Corral Creek (rkm 349.7), which accounted for 23% of all collected fish in 2020. Most (238 fish) post-spawned salmon were collected from early to mid-November just after peak spawning. A summary of 2019 PBT results can be found in Appendix A.1.
In 2020, we PIT tagged subyearling fall Chinook salmon in the Clearwater River to obtain population and growth data. In the Clearwater River, we tagged 2,192 subyearlings and recaptured 79 (3.6%) fish in the river and 187 fish (78 tagged by the U.S. Geological Survey, 109 tagged by the Nez Perce Tribe) at Lower Granite Dam during October which provided information for growth estimation. Within riverine habitats, growth in both length and mass were higher for fish tagged with 8-mm tags than with 9- and 12-mm tags. Estimated growth in length and mass of subyearlings was generally lower in Lower Granite Reservoir than in riverine habitats.
Information on prey resources and juvenile fall Chinook salmon prey consumption was collected to better understand the growth opportunity of late-migrating fish in Lower Granite Reservoir. Zooplankton and surface drifting prey were collected from three reservoir locations from July through October during 2019 and 2020. Fall Chinook salmon diet data were collected from angled fish using gastric lavage. Cladocera and Copepoda were the most abundant zooplankton taxa collected while Diptera was the most common invertebrate taxon collected in surface drift samples. Totals of 49 and 94 juvenile fall Chinook salmon were captured in 2019 and 2020, respectively, and most fish were caught in the lower reach of the reservoir in October of each year. Juvenile fall Chinook salmon consumed mainly dipterans in July and October 2019 and mainly Daphnia during August–October in 2020. Fish showed selection mainly for dipterans in 2019 but strong selection for Daphnia during October 2020. Stomach fullness values were relatively low (<1.1%) during both years. Results show that prey resources are adequate in Lower Granite Reservoir to support positive fish growth during late summer and early autumn.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K., Barry, P.H., Hance, D., Plumb, J., Bickford, B., Rhodes, T., King, K.G., Lebeda, D.D., Hemingway, R.J., and Hargrove, J., 2021, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River Fall Chinook salmon ESU, 89 p.","productDescription":"89 p.","ipdsId":"IP-132164","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":426905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396070,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Project.mvc/Display/1991-029-00"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": 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John","contributorId":181828,"corporation":false,"usgs":false,"family":"Hargrove","given":"John","affiliations":[],"preferred":false,"id":897113,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237364,"text":"70237364 - 2021 - Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles","interactions":[],"lastModifiedDate":"2022-10-11T16:38:54.583308","indexId":"70237364","displayToPublicDate":"2021-08-01T11:32:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12633,"text":"ACM/IMS Transactions on Data Science","active":true,"publicationSubtype":{"id":10}},"title":"Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles","docAbstract":"Physics-based models are often used to study engineering and environmental systems. The ability to model these systems is the key to achieving our future environmental sustainability and improving the quality of human life. This article focuses on simulating lake water temperature, which is critical for understanding the impact of changing climate on aquatic ecosystems and assisting in aquatic resource management decisions. General Lake Model (GLM) is a state-of-the-art physics-based model used for addressing such problems. However, like other physics-based models used for studying scientific and engineering systems, it has several well-known limitations due to simplified representations of the physical processes being modeled or challenges in selecting appropriate parameters. While state-of-the-art machine learning models can sometimes outperform physics-based models given ample amount of training data, they can produce results that are physically inconsistent. This article proposes a physics-guided recurrent neural network model (PGRNN) that combines RNNs and physics-based models to leverage their complementary strengths and improves the modeling of physical processes. Specifically, we show that a PGRNN can improve prediction accuracy over that of physics-based models (by over 20% even with very little training data), while generating outputs consistent with physical laws. An important aspect of our PGRNN approach lies in its ability to incorporate the knowledge encoded in physics-based models. This allows training the PGRNN model using very few true observed data while also ensuring high prediction accuracy. Although we present and evaluate this methodology in the context of modeling the dynamics of temperature in lakes, it is applicable more widely to a range of scientific and engineering disciplines where physics-based (also known as mechanistic) models are used.","language":"English","publisher":"ACM","doi":"10.1145/3447814","usgsCitation":"Jia, X., Willard, J., Karpatne, A., Read, J., Zwart, J.A., Steinbach, M., and Kumar, V., 2021, Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles: ACM/IMS Transactions on Data Science, v. 2, no. 3, 20, 26 p., https://doi.org/10.1145/3447814.","productDescription":"20, 26 p.","ipdsId":"IP-114876","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":451310,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1145/3447814","text":"Publisher Index Page"},{"id":408166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karpatne, Anuj","contributorId":237810,"corporation":false,"usgs":false,"family":"Karpatne","given":"Anuj","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":854276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":854277,"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":854278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steinbach, Michael","contributorId":237811,"corporation":false,"usgs":false,"family":"Steinbach","given":"Michael","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854280,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228321,"text":"70228321 - 2021 - Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States","interactions":[],"lastModifiedDate":"2022-02-08T16:51:22.708275","indexId":"70228321","displayToPublicDate":"2021-08-01T10:43:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5709,"text":"OCS Study","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"BOEM 2021-014","title":"Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States","docAbstract":"This report describes the at-sea spatial distributions of marine birds in Pacific OCS waters off the contiguous U.S. (Figure 1.1) to inform marine spatial planning in the region. The goal was to estimate long-term average spatial distributions for marine bird species using all available science-quality transect survey data and numerous bathymetric, oceanographic, and atmospheric predictor variables. We developed seasonal habitat-based spatial models of the at-sea distribution for 33 individual species and 13 taxonomic groups of marine birds throughout the study region. A statistical modeling framework was used to estimate numerical relationships between bird sighting data (i.e., standardized counts) and a range of temporal (e.g., Pacific Decadal Oscillation [PDO] index), spatially static (e.g., depth), and spatially dynamic (e.g., sea surface chlorophyll-a concentration) environmental variables. The estimated relationships were then used to predict spatially explicit long-term average density (individuals per km2) throughout the study area for each species/group in each of four seasons. Bird sighting data came from multiple scientific survey programs and consisted of at-sea counts of birds collected between 1980 and 2017 using boat-based and fixed-wing aerial transect survey methods. Spatial environmental variables were derived from remote sensing satellite data and an ocean dynamics model.
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9: Ready for Launch","docAbstract":"Landsat 9 is in its final preparations for launch from Vandenberg Space Force Base on 16 September 2021. It has completed its environmental testing at Northrop Grumman Space (NGSP) in Gilbert, Arizona and has been transported to its California launch site. It will be launched into a 705 km orbit replacing Landsat 7 to provide 8-day Earth land mass coverage in concert with Landsat 8. Landsat 8 carries the first Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS); Landsat 9 carries the second of each: OLI-2 and TIRS-2. Once launched it will undergo a 90-day activation, checkout, characterization and calibration, a.k.a. commissioning phase before transitioning to operations. For a several-day period during this commissioning phase, Landsat 9 will under-fly Landsat 8, allowing near simultaneous data collection by both sensors of common Earth targets. These data will be used to compare the radiometric calibrations of the instruments and allow for adjustments of processing parameters to provide more consistent data products.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SPIE: Earth observing systems XXVI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPIE Optics + Photonics 2021","conferenceDate":"Aug 1-5, 2021","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.2595885","usgsCitation":"Markham, B., Anderson, C., Choate, M., Crawford, C., Jenstrom, D., Masek, J., Pedelty, J., Sauer, B., and Thome, K., 2021, Landsat 9: Ready for Launch, in Proceedings of SPIE: Earth observing systems XXVI, v. 11829, San Diego, CA, Aug 1-5, 2021, 118290J, https://doi.org/10.1117/12.2595885.","productDescription":"118290J","ipdsId":"IP-131273","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":391324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11829","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Markham, Brian","contributorId":268247,"corporation":false,"usgs":false,"family":"Markham","given":"Brian","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":826269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":826270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Michael J. 0000-0002-8101-4994","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":268248,"corporation":false,"usgs":true,"family":"Choate","given":"Michael J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":826271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":826272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jenstrom, Del","contributorId":268250,"corporation":false,"usgs":false,"family":"Jenstrom","given":"Del","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":826273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masek, Jeff","contributorId":268252,"corporation":false,"usgs":false,"family":"Masek","given":"Jeff","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":826274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pedelty, Jeffery","contributorId":268253,"corporation":false,"usgs":false,"family":"Pedelty","given":"Jeffery","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":826275,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sauer, Brian 0000-0003-2205-1442 bsauer@usgs.gov","orcid":"https://orcid.org/0000-0003-2205-1442","contributorId":3534,"corporation":false,"usgs":true,"family":"Sauer","given":"Brian","email":"bsauer@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":826276,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thome, Kurtis","contributorId":268256,"corporation":false,"usgs":false,"family":"Thome","given":"Kurtis","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":826277,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227960,"text":"70227960 - 2021 - Using growth rates to estimate the minimum age and size at sexual maturity in a captive population of the critically endangered Central American river turtle Dermatemys mawii","interactions":[],"lastModifiedDate":"2022-02-02T15:03:31.212647","indexId":"70227960","displayToPublicDate":"2021-07-31T08:42:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10077,"text":"Journal of Zoo and Aquarium Research","onlineIssn":"2214-7594","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using growth rates to estimate the minimum age and size at sexual maturity in a captive population of the critically endangered Central American river turtle Dermatemys mawii","title":"Using growth rates to estimate the minimum age and size at sexual maturity in a captive population of the critically endangered Central American river turtle Dermatemys mawii","docAbstract":"The Central American river turtle Dermatemys mawii is a critically endangered species that has incurred substantial losses over the last several decades due to overhunting. This species is now being considered for head-starting programs (i.e. captive breeding of turtles for wild release). However, relatively little is known about their life history characteristics, especially with respect to growth and sexual maturation. A robust knowledge of D. mawii life history traits is important in developing conservation management plans. Our research is the first known study to maintain hatchlings, juveniles, and adults in captivity with regular morphometric data collection. We quantified growth rates (cm yr-1) and calculated growth parameters (e.g. growth coefficients) to estimate body size and age at onset of sexual maturity in a group of wild-caught but captive-held and captive-bred D. mawii in Belize. Sizes at the onset of sexual maturity were inferred by segmented linear regressions that identified changes in growth rate by body size. Asymptotic sizes and growth coefficients were calculated using the Fabens method and the Wang method. Parameters from these models were then applied to a modified von Bertalanffy growth equation to estimate age at the onset of sexual maturity. Male and female D. mawii begin sexual maturation at ca. 38.0 cm and 40.0 cm straight-line carapace length, respectively. We estimated ages associated with these sizes at 13.5-16.9 yrs (males) and 13.6-17.3 yrs (females). No previous literature on growth rates or age at maturation for wild or captive D. mawii has been reported, so our results serve as a starting point in conservation management. Given the life history trait of delayed sexual maturity (>10 years), D. mawii may be more sensitive to losses of the adult population. Therefore, the importance of captive breeding and head-starting programs may be concomitant with protecting wild, adult populations.
","language":"English","publisher":"European Association of Zoos and Aquaria","doi":"10.19227/jzar.v9i3.432","usgsCitation":"Bishop, N.D., Hudson, R., Marlin, J., Pop, T., Rainwater, T.R., Boylan, S.M., Atkinson, B.K., and Carthy, R., 2021, Using growth rates to estimate the minimum age and size at sexual maturity in a captive population of the critically endangered Central American river turtle Dermatemys mawii: Journal of Zoo and Aquarium Research, v. 9, no. 3, p. 150-156, https://doi.org/10.19227/jzar.v9i3.432.","productDescription":"7 p.","startPage":"150","endPage":"156","ipdsId":"IP-094451","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","county":"Toledo","otherGeospatial":"Belize Foundation for Research and Environmental Education, Hicatee Conservation Research Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.74309539794922,\n 16.444975888014174\n ],\n [\n -88.57486724853516,\n 16.444975888014174\n ],\n [\n -88.57486724853516,\n 16.59506848241128\n ],\n [\n -88.74309539794922,\n 16.59506848241128\n ],\n [\n -88.74309539794922,\n 16.444975888014174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bishop, Nichole D.","contributorId":273246,"corporation":false,"usgs":false,"family":"Bishop","given":"Nichole","email":"","middleInitial":"D.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":832713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Rick","contributorId":212739,"corporation":false,"usgs":false,"family":"Hudson","given":"Rick","affiliations":[],"preferred":false,"id":832714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marlin, Jacob","contributorId":273247,"corporation":false,"usgs":false,"family":"Marlin","given":"Jacob","email":"","affiliations":[{"id":56441,"text":"Belize Foundation for Research and Environmental Education","active":true,"usgs":false}],"preferred":false,"id":832715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pop, Thomas","contributorId":273248,"corporation":false,"usgs":false,"family":"Pop","given":"Thomas","email":"","affiliations":[{"id":56441,"text":"Belize Foundation for Research and Environmental Education","active":true,"usgs":false}],"preferred":false,"id":832716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rainwater, Thomas R.","contributorId":93791,"corporation":false,"usgs":true,"family":"Rainwater","given":"Thomas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boylan, Shane M.","contributorId":220012,"corporation":false,"usgs":false,"family":"Boylan","given":"Shane","email":"","middleInitial":"M.","affiliations":[{"id":40118,"text":"Clearwater Marine Aquarium, Clearwater, FL, USA","active":true,"usgs":false}],"preferred":false,"id":832718,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Atkinson, Benjamin K.","contributorId":273250,"corporation":false,"usgs":false,"family":"Atkinson","given":"Benjamin","email":"","middleInitial":"K.","affiliations":[{"id":56443,"text":"Flagler College","active":true,"usgs":false}],"preferred":false,"id":832719,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carthy, Raymond 0000-0001-8978-5083","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":219303,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832720,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70230579,"text":"70230579 - 2021 - Establishing conservation units to promote recovery of two threatened freshwater mussel species (Bivalvia: Unionida: Potamilus)","interactions":[],"lastModifiedDate":"2022-04-18T11:51:52.930376","indexId":"70230579","displayToPublicDate":"2021-07-31T06:50:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Establishing conservation units to promote recovery of two threatened freshwater mussel species (Bivalvia: Unionida: Potamilus)","docAbstract":"Population genomics has significantly increased our ability to make inferences about microevolutionary processes and demographic histories, which have the potential to improve protection and recovery of imperiled species. Freshwater mussels (Bivalvia: Unionida) represent one of the most imperiled groups of organisms globally. Despite systemic decline of mussel abundance and diversity, studies evaluating spatiotemporal changes in distribution, demographic histories, and ecological factors that threaten long-term persistence of imperiled species remain lacking. In this study, we use genotype-by-sequencing (GBS) and mitochondrial sequence data (mtDNA) to define conservation units (CUs) for two highly imperiled freshwater mussel species, Potamilus amphichaenus and Potamilus streckersoni. We then synthesize our molecular findings with details from field collections spanning from 1901 to 2019 to further elucidate distributional trends, contemporary status, and other factors that may be contributing to population declines for our focal species. We collected GBS and mtDNA data for individuals of P. amphichaenus and P. streckersoni from freshwater mussel collections in the Brazos, Neches, Sabine, and Trinity drainages ranging from 2012 to 2019. Molecular analyses resolved disputing number of genetic clusters within P. amphichaenus and P. streckersoni; however, we find defensible support for four CUs, each corresponding to an independent river basin. Evaluations of historical and recent occurrence data illuminated a generally increasing trend of occurrence in each of the four CUs, which were correlated with recent increases in sampling effort. Taken together, these findings suggest that P. amphichaenus and P. streckersoni are likely rare throughout their respective ranges. Because of this, the establishment of CUs will facilitate evidence-based recovery planning and ensure potential captive propagation and translocation efforts are beneficial. Our synthesis represents a case study for conservation genomic assessments in freshwater mussels and provides a model for future studies aimed at recovery planning for these highly imperiled organisms.
In research, sometimes sheer happenstance and serendipity make for an unexpected discovery. Once revealed and if interesting enough, such a finding and its follow-up investigations can lead to advances by others that leave its originators ‘scooped’ and mulling about what next to do with their unpublished data, specifically what journals could it still be published in and be perceived as original. This is what occurred with us nearly 40 years ago with regard to our follow-up observations of acetylene fermentation and led us to concoct a ‘cock-and-bull’ story. We hypothesized about a plausible role for acetylene metabolism in the primordial biogeochemistry of Earth and the possibility of acetylene serving as a key life-sustaining substrate for alien microbes dwelling in the orbs of the outer solar system. With the passage of time, advances were made in whole-genome sequencing coupled with major in silico progress in bioinformatics. In parallel came the results of explorations of the outer solar system (i.e. the Cassini mission to Saturn and its moons). It now appears that these somewhat harebrained ideas of ours, arisen at first out of a sense of desperation, actually ring true in fact, and particularly well in song:
‘Tell a tale of cock and bull,
Of convincing detail full
Tale tremendous,
Heav'n defend us!
What a tale of cock and bull!'
From ‘The Yeoman of the Guard’ by Gilbert & Sullivan.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/femsmc/xtab009","usgsCitation":"Oremland, R., 2021, Got acetylene: A personal research retrospective: FEMS Microbes, v. 2, xtab009, 11 p., https://doi.org/10.1093/femsmc/xtab009.","productDescription":"xtab009, 11 p.","ipdsId":"IP-129240","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":451330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/femsmc/xtab009","text":"Publisher Index Page"},{"id":404553,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","noUsgsAuthors":false,"publicationDate":"2021-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Oremland, Ronald S. 0000-0001-7382-0147","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":257598,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":847775,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70222432,"text":"sim3473 - 2021 - Colored shaded-relief bathymetry, acoustic backscatter, and selected perspective views of the northern part of the California Continental Borderland, southern California","interactions":[],"lastModifiedDate":"2021-08-02T11:31:35.361279","indexId":"sim3473","displayToPublicDate":"2021-07-30T10:12:21","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3473","displayTitle":"Colored Shaded-Relief Bathymetry, Acoustic Backscatter, and Selected Perspective Views of the Northern Part of the California Continental Borderland, Southern California","title":"Colored shaded-relief bathymetry, acoustic backscatter, and selected perspective views of the northern part of the California Continental Borderland, southern California","docAbstract":"The California Continental Borderland is the complex continental margin in southern California that extends from Point Conception southward into northern Baja California (Fisher and others, 2009). This colored shaded-relief bathymetry map of the northern continental borderland in southern California was generated primarily from multibeam-echosounder data collected by the University of Washington in 2016, the Ocean Exploration Trust-Nautilus Exploration Program in 2015–17, and the National Oceanic and Atmospheric Administration in 2017. These datasets were processed in part by the U.S. Geological Survey. Additional smaller amounts of publicly available multibeam-bathymetry data collected by other federal and local agencies, academic institutions, and private firms were also incorporated into this map. Since the production of this map, other multibeam-bathymetry data have been collected in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3473","collaboration":"Prepared in cooperation with the University of Washington, Ocean Exploration Trust's Nautilus Exploration Program, and National Oceanographic and Atmospheric Administration","usgsCitation":"Dartnell, P., Roland, E.C., Raineault, N.A., Castillo, C.M., Conrad, J.E., Kane, R., Brothers, D.S., Kluesner, J., and Walton, M.A.L., 2021, Colored shaded-relief bathymetry, acoustic backscatter, and selected perspective views of the northern part of the California Continental Borderland, southern California: U.S. Geological Survey Scientific Investigations Map 3473, 3 sheets, scale 1:250,000, https://doi.org/10.3133/sim3473.","productDescription":"3 Sheets: 30.89 x 31.00 inches or smaller","additionalOnlineFiles":"Y","ipdsId":"IP-088853","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436255,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FU7SJL","text":"USGS data release","linkHelpText":"Data release of geologic and geophysical maps of the Santa Maria and northern part of the Point Conception 30' x 60' quadrangles, California"},{"id":387521,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3473/covrthb.jpg"},{"id":387522,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3473/sim3473_sheet1.pdf","text":"Sheet 1","size":"32 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387523,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3473/sim3473_sheet2.pdf","text":"Sheet 2","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387524,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3473/sim3473_sheet3.pdf","text":"Sheet 3","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.47607421874999,\n 32.81959486923976\n ],\n [\n -117.33947753906249,\n 32.81959486923976\n ],\n [\n -117.33947753906249,\n 34.093610452768715\n ],\n [\n -120.47607421874999,\n 34.093610452768715\n ],\n [\n -120.47607421874999,\n 32.81959486923976\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
Oil spills represent a continued threat to marine wildlife. Although the public expects, and the State of California, US requires, oiled animals to be rescued for rehabilitation and release, scientists have questioned the welfare and conservation value of capture and rehabilitation of oiled wildlife, based on poor postrelease survival documented in the few available studies. In May 2015, Plains Pipeline 901 spilled >100,000 gallons of oil near Refugio State Beach, California. Many California Brown Pelicans (Pelecanus occidentalis californicus) were oiled; capture and rehabilitation efforts began within 1 d. Ultimately, 65 live birds were captured, including 50 pelicans. Forty-six pelicans survived and were released. Of these, 12 adults (six male, six female) were fitted with solar-powered GPS satellite Platform Terminal Transmitters (PTT) and released in June 2015. In early July, we captured eight adult (three male, four female, one unknown), unoiled pelicans from the Ventura, California area. These control birds were similarly instrumented and released immediately. At 6 mo after release, PTTs from nine of 12 oiled pelicans and six of eight control pelicans were still transmitting; at 1 yr, those numbers decreased to two of 12 and two of eight, respectively. Survival analysis revealed no difference in survival between oiled and control birds. Although our sample size is limited, these data demonstrate that most oiled and rehabilitated pelicans can survive for 6 mo following release, and some individuals can survive over 1 yr.
","language":"English","doi":"10.7589/JWD-D-20-00171","usgsCitation":"Fiorello, C., Jodice, P.G., Lamb, J., Satgé, Y., Mills, K., and Ziccardi, M., 2021, Post-release survival of California brown pelicans (Pelecanus Occidentalis Californicus) following oiling and rehabilitation after the Refugio oil spill: Journal of Wildlife Diseases, v. 57, no. 3, p. 590-600, https://doi.org/10.7589/JWD-D-20-00171.","productDescription":"11 p.","startPage":"590","endPage":"600","ipdsId":"IP-119138","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451346,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/jwd-d-20-00171","text":"Publisher Index Page"},{"id":396455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Gaviota Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.37033081054688,\n 34.38197934098774\n ],\n [\n -120.1667,\n 34.38197934098774\n ],\n [\n -120.1667,\n 34.55011476000879\n ],\n [\n -120.37033081054688,\n 34.55011476000879\n ],\n [\n -120.37033081054688,\n 34.38197934098774\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fiorello, C. V.","contributorId":212006,"corporation":false,"usgs":false,"family":"Fiorello","given":"C. V.","affiliations":[],"preferred":false,"id":835899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":835900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, J. S.","contributorId":270975,"corporation":false,"usgs":false,"family":"Lamb","given":"J. S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":835901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satgé, Y. G.","contributorId":265430,"corporation":false,"usgs":false,"family":"Satgé","given":"Y. G.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":835902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, K.","contributorId":280025,"corporation":false,"usgs":false,"family":"Mills","given":"K.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":835903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ziccardi, M.","contributorId":212007,"corporation":false,"usgs":false,"family":"Ziccardi","given":"M.","affiliations":[],"preferred":false,"id":835904,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}