{"pageNumber":"307","pageRowStart":"7650","pageSize":"25","recordCount":41074,"records":[{"id":70207371,"text":"70207371 - 2020 - History and sources of co-occurring pesticides in an abstraction well unravelled by age distributions of depth specific groundwater samples","interactions":[],"lastModifiedDate":"2020-01-08T14:42:44","indexId":"70207371","displayToPublicDate":"2019-11-24T19:42:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"History and sources of co-occurring pesticides in an abstraction well unravelled by age distributions of depth specific groundwater samples","docAbstract":"When groundwater-based drinking water supply becomes contaminated, the timing and source of contamination are obvious questions. However, contaminants often have diffuse sources and different contaminants may have different sources even in a single groundwater well, making these questions complicated to answer. Age dating of groundwater has been used to reconstruct contaminant travel times to wells; however, critics have highlighted that groundwater flow is often complex with mixing of groundwater of different ages. In drinking water wells, where water is typically abstracted from a large depth interval, such mixing is even more problematic. We present a way to overcome some of the obstacles in identifying the source and age of\n contaminants in drinking water wells by combining depth-specific sampling with age tracer modeling, particle tracking simulations, geological characterization, and contaminant properties. This multitool approach was applied to a drinking water well, where bentazon and dichlorprop contamination was found to have different pollutant sources and release histories, even though both pesticides can be associated with the same land use. Bentazon was derived from recent\napplication to a golf course, while dichlorprop was derived from agricultural use more than 30 years ago. The advantages, limitations, and pitfalls of the proposed course of action are then further discussed.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b03996","usgsCitation":"Jakobsen, R., Hinsby, K., Aamand, J., van der Keur, P., Kidmose, J., Purtschert, R., Jurgens, B., Sultenfuss, J., and Albers, C.N., 2020, History and sources of co-occurring pesticides in an abstraction well unravelled by age distributions of depth specific groundwater samples: Environmental Science & Technology, v. 54, no. 1, p. 158-165, https://doi.org/10.1021/acs.est.9b03996.","productDescription":"8 p.","startPage":"158","endPage":"165","ipdsId":"IP-110509","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":370438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Jakobsen, Rasmus 0000-0003-1882-2961","orcid":"https://orcid.org/0000-0003-1882-2961","contributorId":221322,"corporation":false,"usgs":false,"family":"Jakobsen","given":"Rasmus","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinsby, Klaus 0000-0003-1190-4550","orcid":"https://orcid.org/0000-0003-1190-4550","contributorId":221323,"corporation":false,"usgs":false,"family":"Hinsby","given":"Klaus","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aamand, Jens 0000-0002-4641-639X","orcid":"https://orcid.org/0000-0002-4641-639X","contributorId":221324,"corporation":false,"usgs":false,"family":"Aamand","given":"Jens","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Keur, Peter 0000-0001-6988-6266","orcid":"https://orcid.org/0000-0001-6988-6266","contributorId":221325,"corporation":false,"usgs":false,"family":"van der Keur","given":"Peter","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kidmose, Jacob 0000-0001-8577-2197","orcid":"https://orcid.org/0000-0001-8577-2197","contributorId":221326,"corporation":false,"usgs":false,"family":"Kidmose","given":"Jacob","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777848,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Purtschert, Roland 0000-0002-4734-7664","orcid":"https://orcid.org/0000-0002-4734-7664","contributorId":221327,"corporation":false,"usgs":false,"family":"Purtschert","given":"Roland","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":777849,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":777843,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sultenfuss, Jurgen","contributorId":221328,"corporation":false,"usgs":false,"family":"Sultenfuss","given":"Jurgen","email":"","affiliations":[{"id":40351,"text":"University of Bremen, Germany","active":true,"usgs":false}],"preferred":true,"id":777850,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Albers, Christian N. 0000-0001-7253-3509","orcid":"https://orcid.org/0000-0001-7253-3509","contributorId":221329,"corporation":false,"usgs":false,"family":"Albers","given":"Christian","email":"","middleInitial":"N.","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":777851,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70211498,"text":"70211498 - 2020 - Interactive range‐limit theory (iRLT): An extension for predicting range shifts","interactions":[],"lastModifiedDate":"2020-07-29T13:41:27.897824","indexId":"70211498","displayToPublicDate":"2019-11-23T19:08:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Interactive range‐limit theory (iRLT): An extension for predicting range shifts","docAbstract":"
  1. A central theme of range‐limit theory (RLT) posits that abiotic factors form high‐latitude/altitude limits, whereas biotic interactions create lower limits. This hypothesis, often credited to Charles Darwin, is a pattern widely assumed to occur in nature. However, abiotic factors can impose constraints on both limits and there is scant evidence to support the latter prediction. Deviations from these predictions may arise from correlations between abiotic factors and biotic interactions, as a lack of data to evaluate the hypothesis, or be an artifact of scale. Combining two tenets of ecology—niche theory and predator–prey theory—provides an opportunity to understand how biotic interactions influence range limits and how this varies by trophic level.
  2. We propose an expansion of RLT, interactive RLT (iRLT), to understand the causes of range limits and predict range shifts. Incorporating the main predictions of Darwin's hypothesis, iRLT hypothesizes that abiotic and biotic factors can interact to impact both limits of a species’ range. We summarize current thinking on range limits and perform an integrative review to evaluate support for iRLT and trophic differences along range margins, surveying the mammal community along the boreal‐temperate and forest‐tundra ecotones of North America.
  3. Our review suggests that range‐limit dynamics are more nuanced and interactive than classically predicted by RLT. Many (57 of 70) studies indicate that biotic factors can ameliorate harsh climatic conditions along high‐latitude/altitude limits. Conversely, abiotic factors can also mediate biotic interactions along low‐latitude/altitude limits (44 of 68 studies). Both scenarios facilitate range expansion, contraction or stability depending on the strength and the direction of the abiotic or biotic factors. As predicted, biotic interactions most often occurred along lower limits, yet there were trophic differences. Carnivores were only limited by competitive interactions (n  = 25), whereas herbivores were more influenced by predation and parasitism (77%; 55 of 71 studies). We highlight how these differences may create divergent range patterns along lower limits.
  4. We conclude by (a) summarizing iRLT; (b) contrasting how our model system and others fit this hypothesis and (c) suggesting future directions for evaluating iRLT.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.13150","usgsCitation":"Siren, A., and Morelli, T.L., 2020, Interactive range‐limit theory (iRLT): An extension for predicting range shifts: Journal of Animal Ecology, v. 89, no. 4, p. 940-954, https://doi.org/10.1111/1365-2656.13150.","productDescription":"15 p.","startPage":"940","endPage":"954","ipdsId":"IP-112467","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":458458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13150","text":"Publisher Index Page"},{"id":376817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Siren, Alexej P. K.","contributorId":236810,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej P. K.","affiliations":[],"preferred":false,"id":794352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":794353,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218479,"text":"70218479 - 2020 - Deposition potential and flow-response dynamics of emergent sandbars in a braided river","interactions":[],"lastModifiedDate":"2021-03-02T13:01:45.819116","indexId":"70218479","displayToPublicDate":"2019-11-23T08:35:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Deposition potential and flow-response dynamics of emergent sandbars in a braided river","docAbstract":"

Sandbars are ubiquitous in sandy‐braided rivers throughout the world. In the Great Plains of the United States, recovery and expansion of emergent sandbar habitat (ESH) has been a priority in lowland rivers where the natural extent of sandbars has been degraded. Recovery efforts are aimed at protection of populations of the interior least tern (Sterna antillarum) and piping plover (Charadrius melodus). But quantitative observations of deposition and erosion dynamics of populations of sandbars across long segments of rivers are rare. We present a three‐part case study which used Bayesian regression models to examine relations between hydrology, channel morphology, and ESH responses in the Platte River, eastern Nebraska. Logistic regression indicates presence of ESH is positively related to the Parker, (1976) stability criterion and a gradient in sediment transport mode, and negatively related to presence of vegetation. Hierarchical linear regression modeling shows direct coupling between sandbar top‐surface height and formative flood magnitude, but the gap between formative flood stage and sandbar top‐surface increases with increasing discharge. Finally, linear regression modeling of sandbar erosion demonstrates rates of ESH erosion are on the order of 10−1 ha/day during high‐flow periods and 10−2 during low‐flow periods, but sandbar persistence is largely a function of sandbar starting size. The collective observations highlight the importance of large floods (>3‐year recurrence) in creating very large sandbars that persist as high‐quality ESH over periods of years whereas lower‐magnitude, more‐frequent flood events create lower‐quality ESH that typically does not persist into the following nesting season.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR024107","usgsCitation":"Alexander, J., McElroy, B., Huzurbazar, S., Elliott, C.M., and Murr, M.L., 2020, Deposition potential and flow-response dynamics of emergent sandbars in a braided river: Water Resources Research, v. 56, no. 1, e2018WR024107, 23 p., https://doi.org/10.1029/2018WR024107.","productDescription":"e2018WR024107, 23 p.","ipdsId":"IP-098093","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":383680,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.11865234374999,\n 40.66397287638688\n ],\n [\n -95.8502197265625,\n 40.66397287638688\n ],\n [\n -95.8502197265625,\n 42.11859868281563\n ],\n [\n -99.11865234374999,\n 42.11859868281563\n ],\n [\n -99.11865234374999,\n 40.66397287638688\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Alexander, Jason S. 0000-0002-1602-482X","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":204220,"corporation":false,"usgs":false,"family":"Alexander","given":"Jason S.","affiliations":[{"id":36881,"text":"Department of Geology and Geophysics, University of Wyoming","active":true,"usgs":false},{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":811168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McElroy, Brandon","contributorId":198820,"corporation":false,"usgs":false,"family":"McElroy","given":"Brandon","affiliations":[],"preferred":false,"id":811169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huzurbazar, Snehalata","contributorId":85903,"corporation":false,"usgs":false,"family":"Huzurbazar","given":"Snehalata","email":"","affiliations":[],"preferred":false,"id":811171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elliott, Caroline M. 0000-0002-9190-7462 celliott@usgs.gov","orcid":"https://orcid.org/0000-0002-9190-7462","contributorId":2380,"corporation":false,"usgs":true,"family":"Elliott","given":"Caroline","email":"celliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":811172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murr, Marissa L.","contributorId":252938,"corporation":false,"usgs":false,"family":"Murr","given":"Marissa","email":"","middleInitial":"L.","affiliations":[{"id":50476,"text":"Department of Geology and Geophysics, University of Wyoming, Laramie, Wyoming","active":true,"usgs":false}],"preferred":false,"id":811170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217731,"text":"70217731 - 2020 - Nitrogen budgets of the Long Island Sound estuary","interactions":[],"lastModifiedDate":"2021-02-01T14:33:51.98955","indexId":"70217731","displayToPublicDate":"2019-11-22T10:02:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen budgets of the Long Island Sound estuary","docAbstract":"

Nitrogen (N) inputs to coastal ecosystems have significant impacts on coastal community structure. In N limited systems, increases in N inputs may lead to excess productivity and hypoxia. Like many temperate estuaries, Long Island Sound (LIS), a major eastern U.S. estuary, is a N limited system which has experienced seasonal hypoxia since the 1800s. This study is the first effort to constrain the total N cycle in this estuary. The approach utilizes data collected over the last two decades in the LIS time series with hydrodynamic model results to generate both monthly and annual N budgets between 1995 and 2016. Of the total N that is delivered to LIS through rivers and atmospheric inputs, 40% is exported to the adjacent continental shelf on the order of 10.8 ± 8.9 × 106 kg N/year. Of this export, 41% is dissolved organic N, 29% is particulate organic N, 32% is nitrate + nitrite, and −3% is ammonium. The remaining 60% of the N delivered to LIS is either buried in sediments or lost through denitrification. This inferred internal loss rate is equivalent to 5.4 g N/(m2year). This study serves as an example of the significant inter-annual variations that estuarine budgets undergo as efforts to understand coastal biogeochemical cycles move forward.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2019.106493","usgsCitation":"Vlahos, P., Whitney, M., Menniti, C., Mullaney, J., Morrison, J., and Jia, Y., 2020, Nitrogen budgets of the Long Island Sound estuary: Estuarine, Coastal and Shelf Science, v. 232, 106493, 9 p., https://doi.org/10.1016/j.ecss.2019.106493.","productDescription":"106493, 9 p.","ipdsId":"IP-109478","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":437196,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AVXGBB","text":"USGS data release","linkHelpText":"Nitrogen concentrations and loads and seasonal nitrogen loads in selected Long Island Sound tributaries, water years 1995-2016"},{"id":382808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, New York","otherGeospatial":"Long Island Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.8336181640625,\n 40.77638178482896\n ],\n [\n -73.63037109375,\n 40.81796653313175\n ],\n [\n -73.17993164062499,\n 40.88029480552824\n ],\n [\n -72.61962890625,\n 40.9218144123785\n ],\n [\n -72.3834228515625,\n 40.896905775860006\n ],\n [\n -71.8670654296875,\n 41.05864414643029\n ],\n [\n -71.553955078125,\n 41.15384235711447\n ],\n [\n -71.4605712890625,\n 41.413895564677304\n ],\n [\n -72.1856689453125,\n 41.31907562295139\n ],\n [\n -72.784423828125,\n 41.290189955885644\n ],\n [\n -72.9656982421875,\n 41.269549502842565\n ],\n [\n -73.3447265625,\n 41.1455697310095\n ],\n [\n -73.7677001953125,\n 40.97160353279909\n ],\n [\n -73.8720703125,\n 40.834593138080244\n ],\n [\n -73.8336181640625,\n 40.77638178482896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"232","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vlahos, Penny","contributorId":191277,"corporation":false,"usgs":false,"family":"Vlahos","given":"Penny","email":"","affiliations":[],"preferred":false,"id":809411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitney, Michael 0000-0002-2048-7755","orcid":"https://orcid.org/0000-0002-2048-7755","contributorId":248577,"corporation":false,"usgs":false,"family":"Whitney","given":"Michael","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":809412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menniti, Christina","contributorId":248578,"corporation":false,"usgs":false,"family":"Menniti","given":"Christina","email":"","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":809413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mullaney, John R. 0000-0003-4936-5046","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":203254,"corporation":false,"usgs":true,"family":"Mullaney","given":"John R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morrison, Jonathan 0000-0002-1756-4609 jmorriso@usgs.gov","orcid":"https://orcid.org/0000-0002-1756-4609","contributorId":2274,"corporation":false,"usgs":true,"family":"Morrison","given":"Jonathan","email":"jmorriso@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jia, Yan","contributorId":248579,"corporation":false,"usgs":false,"family":"Jia","given":"Yan","email":"","affiliations":[],"preferred":false,"id":809415,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206881,"text":"70206881 - 2020 - Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud","interactions":[],"lastModifiedDate":"2020-04-06T21:07:55.202827","indexId":"70206881","displayToPublicDate":"2019-11-22T06:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud","docAbstract":"The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, ten time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the 3 time-periods over 12 months (monsoon: Julian days 151-300; winter: Julian days 301-365 plus 1-60; and summer: Julian days 61-150), taking the every 8-day data from Landsat-8 and 7 for the years 2013-2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the 5 agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N=2179) in 5 AEZs. Classification was performed on GEE for each of the 5 AEZs using well-established knowledge-based and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N=1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2019.1690780","usgsCitation":"Gumma, M.K., Thenkabail, P., Pardhasaradhi Teluguntla, and Oliphant, A., 2020, Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud: GIScience and Remote Sensing, v. 57, no. 3, p. 302-322, https://doi.org/10.1080/15481603.2019.1690780.","productDescription":"21 p.","startPage":"302","endPage":"322","ipdsId":"IP-111091","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":458465,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15481603.2019.1690780","text":"Publisher Index Page"},{"id":369607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India, Pakistan, Bangladesh, Nepal, Sri Lanka, Bhutan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[77.83745,35.49401],[78.91227,34.32194],[78.81109,33.5062],[79.20889,32.99439],[79.17613,32.48378],[78.45845,32.61816],[78.73889,31.51591],[79.72137,30.88271],[81.11126,30.18348],[81.5258,30.42272],[82.32751,30.11527],[83.33712,29.46373],[83.89899,29.32023],[84.23458,28.83989],[85.01164,28.64277],[85.82332,28.20358],[86.95452,27.97426],[88.12044,27.87654],[88.73033,28.08686],[88.81425,27.29932],[89.47581,28.04276],[90.01583,28.29644],[90.73051,28.06495],[91.25885,28.04061],[91.69666,27.77174],[92.50312,27.89688],[93.41335,28.64063],[94.56599,29.27744],[95.4048,29.03172],[96.11768,29.4528],[96.58659,28.83098],[96.24883,28.41103],[97.32711,28.26158],[97.40256,27.88254],[97.05199,27.69906],[97.134,27.08377],[96.41937,27.26459],[95.12477,26.57357],[95.15515,26.00131],[94.60325,25.1625],[94.55266,24.67524],[94.10674,23.85074],[93.32519,24.07856],[93.28633,23.04366],[93.06029,22.70311],[93.16613,22.27846],[92.67272,22.04124],[92.65226,21.32405],[92.30323,21.47549],[92.36855,20.67088],[92.08289,21.1922],[92.02522,21.70157],[91.83489,22.18294],[91.41709,22.76502],[90.49601,22.80502],[90.58696,22.39279],[90.27297,21.83637],[89.84747,22.03915],[89.70205,21.85712],[89.41886,21.96618],[89.03196,22.05571],[88.88877,21.69059],[88.2085,21.70317],[86.9757,21.49556],[87.03317,20.74331],[86.49935,20.15164],[85.06027,19.47858],[83.94101,18.30201],[83.18922,17.67122],[82.19279,17.01664],[82.19124,16.55666],[81.69272,16.31022],[80.792,15.95197],[80.3249,15.89918],[80.02507,15.13641],[80.23327,13.83577],[80.28629,13.00626],[79.86255,12.05622],[79.858,10.35728],[79.34051,10.30885],[78.88535,9.54614],[79.18972,9.21654],[78.27794,8.93305],[77.94117,8.25296],[77.5399,7.96553],[76.59298,8.89928],[76.13006,10.29963],[75.74647,11.30825],[75.3961,11.78125],[74.86482,12.74194],[74.61672,13.99258],[74.44386,14.61722],[73.5342,15.99065],[73.11991,17.92857],[72.82091,19.20823],[72.82448,20.4195],[72.63053,21.35601],[71.17527,20.75744],[70.47046,20.87733],[69.16413,22.0893],[69.64493,22.45077],[69.3496,22.84318],[68.17665,23.69197],[67.44367,23.94484],[67.14544,24.66361],[66.37283,25.42514],[64.53041,25.23704],[62.9057,25.21841],[61.49736,25.07824],[61.87419,26.23997],[63.31663,26.75653],[63.2339,27.21705],[62.75543,27.37892],[62.72783,28.25964],[61.77187,28.69933],[61.36931,29.30328],[60.87425,29.82924],[62.54986,29.31857],[63.55026,29.46833],[64.148,29.34082],[64.35042,29.56003],[65.04686,29.47218],[66.34647,29.88794],[66.38146,30.7389],[66.93889,31.30491],[67.68339,31.30315],[67.79269,31.58293],[68.55693,31.71331],[68.92668,31.62019],[69.31776,31.90141],[69.26252,32.50194],[69.68715,33.1055],[70.32359,33.35853],[69.93054,34.02012],[70.8818,33.98886],[71.15677,34.34891],[71.11502,34.73313],[71.61308,35.1532],[71.49877,35.65056],[71.26235,36.07439],[71.84629,36.50994],[72.92002,36.72001],[74.06755,36.83618],[74.57589,37.02084],[75.15803,37.13303],[75.8969,36.66681],[76.19285,35.8984],[77.83745,35.49401]]],[[[81.78796,7.52306],[81.63732,6.48178],[81.21802,6.19714],[80.34836,5.96837],[79.87247,6.76346],[79.69517,8.20084],[80.1478,9.82408],[80.83882,9.26843],[81.30432,8.56421],[81.78796,7.52306]]]]},\"properties\":{\"name\":\"India\"}}]}","volume":"57","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":127590,"corporation":false,"usgs":false,"family":"Gumma","given":"Murali","email":"","middleInitial":"Krishna","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":776137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad 0000-0002-2182-8822","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":220239,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pardhasaradhi Teluguntla 0000-0001-8060-9841","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":214457,"corporation":false,"usgs":false,"family":"Pardhasaradhi Teluguntla","affiliations":[{"id":39046,"text":"Bay Area Environmental Research Institute at USGS","active":true,"usgs":false}],"preferred":false,"id":776138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliphant, Adam 0000-0001-8622-7932 aoliphant@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-7932","contributorId":192325,"corporation":false,"usgs":true,"family":"Oliphant","given":"Adam","email":"aoliphant@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":776139,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230128,"text":"70230128 - 2020 - Pleistocene lakes and paleohydrologic environments of the Tecopa basin, California: Constraints on the drainage integration of the Amargosa River","interactions":[],"lastModifiedDate":"2022-03-30T16:07:49.15533","indexId":"70230128","displayToPublicDate":"2019-11-21T11:02:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Pleistocene lakes and paleohydrologic environments of the Tecopa basin, California: Constraints on the drainage integration of the Amargosa River","docAbstract":"

The Tecopa basin in eastern California was a terminal basin that episodically held lakes during most of the Quaternary until the basin and its modern stream, the Amargosa River, became tributary to Death Valley. Although long studied for its sedimentology, diagenesis, and paleomagnetism, the basin’s lacustrine and paleoclimate history has not been well understood, and conflicting interpretations exist concerning the relations of Tecopa basin to the Amargosa River and to pluvial Lake Manly in Death Valley. Previous studies also did not recognize basinwide tectonic effects on lake-level history. In this study, we focused on: (1) establishing a chronology of shoreline deposits, as the primary indicator of lake-level history, utilizing well-known ash beds and new uranium-series and luminescence dating; (2) using ostracodes as indicators of water chemistry and water source(s); and (3) correlating lake transgressions to well-preserved fluvial-deltaic sequences. During the early Pleistocene, the Tecopa basin hosted small shallow lakes primarily fed by low-alkalinity water sourced mainly from runoff and (or) a groundwater source chemically unlike the modern springs. The first lake that filled the basin occurred just prior and up to the eruption of the 765 ka Bishop ash during marine isotope stage (MIS) 19; this lake heralded the arrival of the Amargosa River, delivering high-alkalinity water. Two subsequent lake cycles, coeval with MIS 16 (leading up to eruption of 631 ka Lava Creek B ash) and MIS 14 and (or) MIS 12, are marked by prominent accumulations of nearshore and beach deposits. The timing of the youngest of these three lakes, the High lake, is constrained by a uranium-series age of ca. 580 ± 120 ka on tufa-cemented beach gravel and by estimates from sedimentation rates. Highstand deposits of the Lava Creek and High lakes at the north end of the basin are stratigraphically tied to distinct sequences of fluvial-deltaic deposits fed by alkaline waters of the Amargosa River. The High lake reached the highest level achieved in the Tecopa basin, and it may have briefly discharged southward but did not significantly erode its threshold. The High lake was followed by a long hiatus of as much as 300 k.y., during which there is evidence for alluvial, eolian, and groundwater-discharge deposition, but no lakes. We attribute this hiatus, as have others, to blockage of the Amargosa River by an alluvial fan upstream near Eagle Mountain. A final lake, the Terminal lake, formed when the river once again flowed south into Tecopa basin, but it was likely short-lived due to rapid incision of the former threshold south of Tecopa. Deposits of the Terminal lake are inset below, and are locally unconformable on, deposits of the High lake and the nonlacustrine deposits of the hiatus. The Terminal lake reached its highstand at ca. 185 ± 21 ka, as dated by infrared-stimulated luminescence on feldspar in beach sand, a time coincident with perennial lake mud and alkaline-tolerant ostracodes in the Badwater core of Lake Manly during MIS 6. A period of stillstand occurred as the Terminal lake drained when the incising river encountered resistant Stirling Quartzite near the head of present-day Amargosa Canyon. Our studies significantly revise the lacustrine and drainage history of the Tecopa basin, show that the MIS 6 highstand was not the largest lake in the basin as previously published (with implications for potential nuclear waste storage at Yucca Mountain, Nevada), and provide evidence from shoreline elevations for ∼20 m of tectonic uplift in the northern part of the basin across an ENE-trending monoclinal flexure.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35282.1","usgsCitation":"Reheis, M.C., Caskey, J., Bright, J., Paces, J.B., Mahan, S.A., and Wan, E., 2020, Pleistocene lakes and paleohydrologic environments of the Tecopa basin, California: Constraints on the drainage integration of the Amargosa River: GSA Bulletin, v. 132, no. 7-8, p. 1537-1565, https://doi.org/10.1130/B35282.1.","productDescription":"29 p.","startPage":"1537","endPage":"1565","ipdsId":"IP-105957","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":397866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tecopa basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.25,\n 35\n ],\n [\n -115.5,\n 35\n ],\n [\n -115.5,\n 37\n ],\n [\n -117.25,\n 37\n ],\n [\n -117.25,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Reheis, Marith C. 0000-0002-8359-323X mreheis@usgs.gov","orcid":"https://orcid.org/0000-0002-8359-323X","contributorId":138571,"corporation":false,"usgs":true,"family":"Reheis","given":"Marith","email":"mreheis@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":839195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caskey, John","contributorId":289506,"corporation":false,"usgs":false,"family":"Caskey","given":"John","email":"","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":839196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bright, Jordon","contributorId":63981,"corporation":false,"usgs":false,"family":"Bright","given":"Jordon","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":839197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":215864,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839198,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":839199,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wan, Elmira 0000-0002-9255-112X ewan@usgs.gov","orcid":"https://orcid.org/0000-0002-9255-112X","contributorId":3434,"corporation":false,"usgs":true,"family":"Wan","given":"Elmira","email":"ewan@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":839200,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208919,"text":"70208919 - 2020 - The ecology of chronic wasting disease in wildlife","interactions":[],"lastModifiedDate":"2020-03-05T10:26:47","indexId":"70208919","displayToPublicDate":"2019-11-21T10:26:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of chronic wasting disease in wildlife","docAbstract":"

Prions are misfolded infectious proteins responsible for a group of fatal neurodegenerative diseases termed transmissible spongiform encephalopathy or prion diseases. Chronic Wasting Disease (CWD) is the prion disease with the highest spillover potential, affecting at least seven Cervidae (deer) species. The zoonotic potential of CWD is inconclusive and cannot be ruled out. A risk of infection for other domestic and wildlife species is also plausible. Here, we review the current status of the knowledge with respect to CWD ecology in wildlife. Our current understanding of the geographic distribution of CWD lacks spatial and temporal detail, does not consider the biogeography of infectious diseases, and is largely biased by sampling based on hunters' cooperation and funding available for each region. Limitations of the methods used for data collection suggest that the extent and prevalence of CWD in wildlife is underestimated. If the zoonotic potential of CWD is confirmed in the short term, as suggested by recent results obtained in experimental animal models, there will be limited accurate epidemiological data to inform public health. Research gaps in CWD prion ecology include the need to identify specific biological characteristics of potential CWD reservoir species that better explain susceptibility to spillover, landscape and climate configurations that are suitable for CWD transmission, and the magnitude of sampling bias in our current understanding of CWD distribution and risk. Addressing these research gaps will help anticipate novel areas and species where CWD spillover is expected, which will inform control strategies. From an ecological perspective, control strategies could include assessing restoration of natural predators of CWD reservoirs, ultrasensitive CWD detection in biotic and abiotic reservoirs, and deer density and landscape modification to reduce CWD spread and prevalence.

","language":"English","publisher":"Wiley","doi":"10.1111/brv.12568","usgsCitation":"Escobar, L.E., Pritzkow, S., Winter, S.N., Grear, D.A., Kirchgessner, M.S., Dominguez-Villegas, E., Machado, G., Peterson, A.T., and Soto, C., 2020, The ecology of chronic wasting disease in wildlife: Biological Reviews, v. 95, no. 2, p. 393-408, https://doi.org/10.1111/brv.12568.","productDescription":"16 p.","startPage":"393","endPage":"408","ipdsId":"IP-107301","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":458473,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/brv.12568","text":"External Repository"},{"id":372946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Finland, Norway, South Korea, Sweden, United States","volume":"95","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Escobar, Luis E.","contributorId":178962,"corporation":false,"usgs":false,"family":"Escobar","given":"Luis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":784013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pritzkow, Sandra","contributorId":223075,"corporation":false,"usgs":false,"family":"Pritzkow","given":"Sandra","email":"","affiliations":[{"id":40666,"text":"University of Texas Medical School at Houston","active":true,"usgs":false}],"preferred":false,"id":784014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winter, Steven N","contributorId":223076,"corporation":false,"usgs":false,"family":"Winter","given":"Steven","email":"","middleInitial":"N","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":784015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":784012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirchgessner, Megan S.","contributorId":173866,"corporation":false,"usgs":false,"family":"Kirchgessner","given":"Megan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":784016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dominguez-Villegas, Ernesto","contributorId":223077,"corporation":false,"usgs":false,"family":"Dominguez-Villegas","given":"Ernesto","email":"","affiliations":[{"id":37079,"text":"Wildlife Center of Virginia","active":true,"usgs":false}],"preferred":false,"id":784017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Machado, Gustavo","contributorId":223078,"corporation":false,"usgs":false,"family":"Machado","given":"Gustavo","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":784018,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peterson, A Townsend","contributorId":223079,"corporation":false,"usgs":false,"family":"Peterson","given":"A","email":"","middleInitial":"Townsend","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":784019,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Soto, Claudio","contributorId":223080,"corporation":false,"usgs":false,"family":"Soto","given":"Claudio","email":"","affiliations":[{"id":40666,"text":"University of Texas Medical School at Houston","active":true,"usgs":false}],"preferred":false,"id":784020,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70223511,"text":"70223511 - 2020 - Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age","interactions":[],"lastModifiedDate":"2021-08-31T13:00:27.640555","indexId":"70223511","displayToPublicDate":"2019-11-21T07:53:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age","docAbstract":"

Mercury is a widespread, naturally occurring contaminant that biomagnifies in wetlands due to the methylation of this element by sulfate-reducing bacteria. Species that feed at the top trophic level within wetlands are predicted to have higher mercury loads compared to species feeding at lower trophic levels and are therefore often used for mercury biomonitoring. However, mechanisms for mercury bioaccumulation in sentinel species are often poorly understood, due to a lack of long-term studies or an inability to differentiate between confounding variables. We examined mercury bioaccumulation patterns in the whole blood of American alligators (Alligator mississippiensis) from a long-term mark-recapture study (1979–2017) in South Carolina, USA. Using a growth model and auxiliary information on predicted age at first capture, we differentiated between age- and size-related variation in mercury bioaccumulation, which are often confounded in alligators due to their determinate growth pattern. Contrary to predictions that the oldest or largest individuals were likely to have the highest mercury concentrations, our best-supported model indicated a peak in mercury concentration at 30–40 years of age, depending on the sex, and lower concentrations in the youngest and oldest animals. To evaluate the robustness of our findings, we re-analyzed data from a previously published study of mercury in alligators sampled at Merritt Island National Wildlife Refuge in Florida. Unlike the South Carolina data, the data from Florida contained minimal auxiliary information regarding age, yet the best supported model similarly indicated a peaked rather than increasing relationship between mercury and body size, a less-precise indicator of age. These findings highlight how long-term monitoring can differentiate between confounding variables (e.g., age and size) to better elucidate complex relationships between contaminant exposure and demographic factors in sentinel species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.135103","usgsCitation":"Lawson, A., Moore, C.T., Rainwater, T., Nilsen, F., Wilkinson, P., Lowers, R., Guillett, L., McFadden, K., and Jodice, P.G., 2020, Nonlinear patterns in mercury bioaccumulation in American alligators are a function of predicted age: Science of the Total Environment, v. 707, 135103, 15 p., https://doi.org/10.1016/j.scitotenv.2019.135103.","productDescription":"135103, 15 p.","ipdsId":"IP-104151","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458476,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.135103","text":"Publisher Index Page"},{"id":437198,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98XHBCY","text":"USGS data release","linkHelpText":"Mercury concentrations in American alligators in South Carolina, 2010-2017"},{"id":388683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, South Carolina","otherGeospatial":"Merritt Island National Wildlife Refuge, Tom Yawkey Wildlife Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.82366943359375,\n 28.401064827220896\n ],\n [\n -80.69183349609375,\n 28.270520445825415\n ],\n [\n -80.52291870117188,\n 28.38173504322308\n ],\n [\n -80.52429199218749,\n 28.642389157900553\n ],\n [\n -80.6396484375,\n 28.8975881579445\n ],\n [\n -80.9307861328125,\n 28.936054482136672\n ],\n [\n -80.82366943359375,\n 28.401064827220896\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.43801879882812,\n 33.06737684108429\n ],\n [\n -79.1455078125,\n 33.06737684108429\n ],\n [\n -79.1455078125,\n 33.38099943104024\n ],\n [\n -79.43801879882812,\n 33.38099943104024\n ],\n [\n -79.43801879882812,\n 33.06737684108429\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"707","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, A.J.","contributorId":264958,"corporation":false,"usgs":false,"family":"Lawson","given":"A.J.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":822237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rainwater, T.R.","contributorId":264959,"corporation":false,"usgs":false,"family":"Rainwater","given":"T.R.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":822239,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nilsen, F.M.","contributorId":264960,"corporation":false,"usgs":false,"family":"Nilsen","given":"F.M.","email":"","affiliations":[{"id":38740,"text":"Medical University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":822240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilkinson, P.M.","contributorId":264961,"corporation":false,"usgs":false,"family":"Wilkinson","given":"P.M.","email":"","affiliations":[{"id":54598,"text":"Tom Yawkey Wildlife Center","active":true,"usgs":false}],"preferred":false,"id":822241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowers, R.H.","contributorId":264962,"corporation":false,"usgs":false,"family":"Lowers","given":"R.H.","email":"","affiliations":[{"id":54599,"text":"Integrated Mission Support Services","active":true,"usgs":false}],"preferred":false,"id":822242,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guillett, L.J. Jr","contributorId":264963,"corporation":false,"usgs":false,"family":"Guillett","given":"L.J. Jr","affiliations":[{"id":38740,"text":"Medical University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":822243,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McFadden, Katherine W. kwmcfadden@usgs.gov","contributorId":1383,"corporation":false,"usgs":true,"family":"McFadden","given":"Katherine W.","email":"kwmcfadden@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":822244,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X pjodice@usgs.gov","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":200009,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","email":"pjodice@usgs.gov","middleInitial":"G.R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822245,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70206611,"text":"70206611 - 2020 - Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake","interactions":[],"lastModifiedDate":"2020-01-03T10:52:00","indexId":"70206611","displayToPublicDate":"2019-11-20T14:53:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW 7.1 Anchorage earthquake","title":"Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake","docAbstract":"

We measure pseudospectral and peak ground motions from 44 intermediate‐depth Mw≥4.9\">Mw≥4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 Mw\">Mw 7.1 earthquake near Anchorage, to identify regional amplification features (⁠0.1–5  s\">0.1–5  s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and we compute bias, between‐, and within‐event terms through a linear mixed‐effects regression. Between‐event residuals are analyzed to assess the relative source characteristics of the Cook Inlet earthquakes and suggest a difference in the scaling of the source with depth, relative to global observations. The within‐event residuals are analyzed to investigate regional amplification, and various spatial patterns manifest, including correlations of amplification with depth of the Cook Inlet basin and varying amplifications east and west of the center of the basin. Three earthquake clusters are analyzed separately and indicate spatial amplification patterns that depend on source location and exhibit variations in the depth scaling of long‐period basin amplification. The observations inform future seismic hazard modeling efforts in the Cook Inlet region. More broadly, they suggest a greater complexity of basin and regional amplification than is currently used in seismic hazard analyses.

","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0220190179","usgsCitation":"Moschetti, M.P., Thompson, E.M., Rekoske, J., Hearne, M., Powers, P.M., McNamara, D.E., and Tape, C., 2020, Ground-motion amplification in Cook Inlet region, Alaska from intermediate-depth earthquakes, including the 2018 MW=7.1 Anchorage earthquake: Seismological Research Letters, v. 91, no. 1, p. 142-152, https://doi.org/10.1785/0220190179.","productDescription":"11 p.","startPage":"142","endPage":"152","ipdsId":"IP-111751","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437199,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y491AY","text":"USGS data release","linkHelpText":"Database of ground motions from in-slab earthquakes near Anchorage, Alaska, 2008-2019"},{"id":369572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Cook Inlet region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.6435546875,\n 58.39019698411526\n ],\n [\n -150.88623046875,\n 59.24341475839977\n ],\n [\n -148.623046875,\n 60.87700804962625\n ],\n [\n -149.2822265625,\n 61.501734289732326\n ],\n [\n -151.1279296875,\n 61.51221638411366\n ],\n [\n -154.35791015625,\n 59.512029386502704\n ],\n [\n -154.6435546875,\n 58.344100629556614\n ],\n [\n -154.6435546875,\n 58.39019698411526\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":775165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":146592,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":775166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rekoske, John 0000-0003-0539-2069","orcid":"https://orcid.org/0000-0003-0539-2069","contributorId":220108,"corporation":false,"usgs":true,"family":"Rekoske","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":775167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":775168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":775169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":775170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tape, Carl","contributorId":219960,"corporation":false,"usgs":false,"family":"Tape","given":"Carl","email":"","affiliations":[{"id":40098,"text":"Geophysical Institute, 2156 Koyukuk Drive, University of Alaska Fairbanks, Fairbanks, AK 99775","active":true,"usgs":false}],"preferred":false,"id":775171,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217558,"text":"70217558 - 2020 - The sedimentary record of the 2018 Anchorage Earthquake in Eklutna Lake, Alaska: Calibrating the lacustrine seismograph","interactions":[],"lastModifiedDate":"2021-01-21T20:40:35.59411","indexId":"70217558","displayToPublicDate":"2019-11-20T14:37:39","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The sedimentary record of the 2018 Anchorage Earthquake in Eklutna Lake, Alaska: Calibrating the lacustrine seismograph","docAbstract":"

The 30 November 2018 Mw\">MMw\">w 7.1 Anchorage earthquake caused modified Mercalli intensities of V¼ to V½ at Eklutna Lake (south central Alaska). A few hours after the earthquake, a “dirt streak” was observed on the lake surface, followed by a peak in sediment turbidity values (⁠∼80\">∼80 times normal) at a drinking water facility, which receives water from the lake through a pipe. These observations hint toward turbidity currents triggered by the earthquake in Eklutna Lake. Here, we study 32 short sediment cores retrieved from across Eklutna Lake and observe a millimeter‐to‐centimeter scale turbidite that can be confidently attributed to the 2018 earthquake in all coring locations. X‐ray computed tomography, grain‐size, and color‐spectral analyses of the turbidite show that it shares physical characteristics with the turbidite generated by the 1964 Mw\">Mw 9.2 Great Alaska earthquake, while it is considerably different from turbidites caused by historical floods. The 2018 turbidite reaches its largest thickness in the inflow‐proximal basin, but when compared to the 1964 turbidite and thereby canceling out local site effects, it is relatively thick in the inflow‐distal sub‐basin. The latter was exposed to stronger shaking during the 2018 earthquake, and this relative thickness trend may therefore be attributed to shaking intensity and gives an indication of the location of the earthquake epicenter relative to the basin axis. Furthermore, in contrast to the 1964 turbidite, which was sourced from both deltas and hemipelagic slopes, the 2018 turbidite was sourced from deltas only, as evidenced by its distribution. These results confirm that while it is generally accepted that shaking intensities of ≥VI\">≥VI are needed to trigger turbidity currents from hemipelagic slopes, intensities as low as V¼ can be sufficient to trigger turbidity currents from deltaic slopes. Our results show that proglacial lakes can sensitively record differences in shaking intensity and that investigating deposits from recent earthquakes is crucial to calibrate the lacustrine seismograph.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190204","usgsCitation":"Van Daele, M., Haeussler, P., Witter, R., Praet, N., and De Batist, M., 2020, The sedimentary record of the 2018 Anchorage Earthquake in Eklutna Lake, Alaska: Calibrating the lacustrine seismograph: Seismological Research Letters, v. 91, no. 1, p. 126-141, https://doi.org/10.1785/0220190204.","productDescription":"16 p.","startPage":"126","endPage":"141","ipdsId":"IP-112823","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":382439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Eklutna Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.19296264648438,\n 61.32200887767297\n ],\n [\n -148.93959045410156,\n 61.32200887767297\n ],\n [\n -148.93959045410156,\n 61.42464810271828\n ],\n [\n -149.19296264648438,\n 61.42464810271828\n ],\n [\n -149.19296264648438,\n 61.32200887767297\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":808666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":808667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":808668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":808669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De Batist, Marc 0000-0002-1625-2080","orcid":"https://orcid.org/0000-0002-1625-2080","contributorId":194089,"corporation":false,"usgs":false,"family":"De Batist","given":"Marc","email":"","affiliations":[],"preferred":false,"id":808670,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207514,"text":"70207514 - 2020 - Occupancy patterns in a reintroduced fisher population during reestablishment","interactions":[],"lastModifiedDate":"2020-01-20T11:45:31","indexId":"70207514","displayToPublicDate":"2019-11-20T13:46:31","publicationYear":"2020","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":"Occupancy patterns in a reintroduced fisher population during reestablishment","docAbstract":"

Monitoring population performance in the years following species reintroductions is key to assessing population restoration success and evaluating assumptions made in planning species restoration programs. From 2008–2010 we translocated 90 fishers (Pekania pennanti) from British Columbia, Canada, to Washington's Olympic Peninsula, USA, providing the opportunity to evaluate modeling assumptions used to identify the most suitable reintroduction areas in Washington and enhance understanding of fisher habitat associations in the late‐successional forest ecosystems in the coastal Pacific Northwest. From 2013–2016, we deployed 788 motion‐sensing cameras and hair (DNA)‐snaring devices distributed among 263 24‐km2 primary sampling units across the Olympic Peninsula. Our objectives were to determine whether occupancy patterns of the reestablishing population supported assumptions of the initial habitat assessment models, whether the population had expanded or shifted in distribution since the initial reintroductions, compare physical habitat attributes among land‐management designations, and determine whether the founding fishers had successfully reproduced. We predicted that site occupancy by fishers would be associated with landscapes characterized by high proportional coverage of dense forest canopies and medium‐sized and large trees, a diversity of stand structural classes, and area near the administrative boundary separating wilderness from more intensively managed forest lands. We detected fishers across designated wilderness, federal lands outside of wilderness, and other land designations in proportion to land availability on the Peninsula. We found negligible support for predictions that occupancy by fishers was associated with percent forest cover, tree‐size class, or structural class diversity. Rather, occupancy was strongly associated with lands near the wilderness boundary on both sides. We speculate that the boundary between wilderness and more intensively managed forest lands provided fishers with the most suitable prey in proximity to contiguous expanses of low‐ to mid‐elevation late‐successional forests that provided optimal resting, denning, and security values. Occupancy patterns shifted toward the west and south along a precipitation gradient during the study, indicating that population distribution had not yet stabilized 5–8 years following translocation. Genetic results indicated that ≥2 generations of fishers have been produced on the Peninsula. Annual occupancy rates across the Peninsula (0.08–0.24) were lower than in other previously studied and established fisher populations, indicating that not all habitat was fully occupied or that initial estimates of the extent of habitat was overestimated. The strong selection fishers exhibited for wilderness edge and weak selection against extensive forested wilderness areas suggested that habitat managers should strive for maintaining a suitable interspersion of required forest structures and biotic habitat components, such as prey resource availability. 

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21788","usgsCitation":"Happe, P.J., Jenkins, K., McCaffery, R.M., Lewis, J.C., Pilgrim, K., and Schwartz, M.K., 2020, Occupancy patterns in a reintroduced fisher population during reestablishment: Journal of Wildlife Management, v. 84, no. 2, p. 344-358, https://doi.org/10.1002/jwmg.21788.","productDescription":"15 p.","startPage":"344","endPage":"358","ipdsId":"IP-108753","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":437200,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q8SITV","text":"USGS data release","linkHelpText":"Fisher (Pekania pennanti) detections and analysis covariates on Washington's Olympic Peninsula, 2013-2016"},{"id":370605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.892578125,\n 45.89000815866184\n ],\n [\n -115.927734375,\n 46.01222384063236\n ],\n [\n -119.70703125,\n 56.46249048388979\n ],\n [\n -119.70703125,\n 60.06484046010452\n ],\n [\n -138.076171875,\n 59.31076795603884\n ],\n [\n -124.892578125,\n 45.89000815866184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Happe, Patricia J.","contributorId":177053,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":778326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Kurt 0000-0003-1415-6607","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":221472,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":778325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCaffery, Rebecca M. 0000-0002-0396-0387","orcid":"https://orcid.org/0000-0002-0396-0387","contributorId":211539,"corporation":false,"usgs":true,"family":"McCaffery","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":778327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, J. C.","contributorId":221473,"corporation":false,"usgs":false,"family":"Lewis","given":"J.","email":"","middleInitial":"C.","affiliations":[{"id":40386,"text":"Washington Department Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":778328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilgrim, Kristine","contributorId":150034,"corporation":false,"usgs":false,"family":"Pilgrim","given":"Kristine","email":"","affiliations":[{"id":17893,"text":"USDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59801, USA","active":true,"usgs":false}],"preferred":false,"id":778329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Michael K.","contributorId":199035,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":778330,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208803,"text":"70208803 - 2020 - Hydrologic resilience from summertime fog and recharge: A case study for coho salmon recovery planning","interactions":[],"lastModifiedDate":"2020-03-02T09:50:46","indexId":"70208803","displayToPublicDate":"2019-11-20T09:45:37","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic resilience from summertime fog and recharge: A case study for coho salmon recovery planning","docAbstract":"

Fog and low cloud cover (FLCC) and late summer recharge increase stream baseflow and decrease stream temperature during arid Mediterranean climate summers, which benefits salmon especially under climate warming conditions. The potential to discharge cool water to streams during the late summer (hydrologic capacity; HC) furnished by FLCC and recharge were mapped for the 299 subwatersheds ranked Core, Phase 1, or Phase 2 under the National Marine Fisheries Service Recovery Plan that prioritized restoration and threat abatement action for endangered Central California Coast Coho Salmon evolutionarily significant unit. Two spatially continuous gridded datasets were merged to compare HC: average hrs/day FLCC, a new dataset derived from a decade of hourly National Weather Satellite data, and annual average mm recharge from the USGS Basin Characterization Model. Two use‐case scenarios provide examples of incorporating FLCC‐driven HC indices into long‐term recovery planning. The first, a thermal analysis under future climate, projected 65% of the watershed area for 8–19 coho population units as thermally inhospitable under two global climate models and identified several units with high resilience (high HC under the range of projected warming conditions). The second use case investigated HC by subwatershed rank and coho population, and identified three population units with high HC in areas ranked Phase 1 and 2 and low HC in Core. Recovery planning for cold‐water fish species would benefit by including FLCC in vulnerability analyses.

","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12811","usgsCitation":"Torregrosa, A.A., Flint, L.E., and Flint, A.L., 2020, Hydrologic resilience from summertime fog and recharge: A case study for coho salmon recovery planning: Journal of the American Water Resources Association, v. 56, no. 1, p. 134-160, https://doi.org/10.1111/1752-1688.12811.","productDescription":"27 p.","startPage":"134","endPage":"160","ipdsId":"IP-095384","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":458480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12811","text":"Publisher Index Page"},{"id":372761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.18945312500001,\n 41.96765920367816\n ],\n [\n -128.0126953125,\n 38.39333888832238\n ],\n [\n -122.9150390625,\n 34.08906131584994\n ],\n [\n -117.79541015625001,\n 36.82687474287728\n ],\n [\n -124.18945312500001,\n 41.96765920367816\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":783455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":783457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216943,"text":"70216943 - 2020 - Could a freshwater fish be at the root of dystrophic crises in a coastal lagoon?","interactions":[],"lastModifiedDate":"2020-12-17T14:06:31.950476","indexId":"70216943","displayToPublicDate":"2019-11-20T07:52:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Could a freshwater fish be at the root of dystrophic crises in a coastal lagoon?","docAbstract":"

Eutrophication has a profound impact on ecosystems worldwide. Grass carp Ctenopharyngodon idella, an herbivorous fish, has been introduced to control aquatic plant overgrowth caused by eutrophication, but could have other, potentially detrimental, effects. We used the Po di Volano basin (south of the Po River delta, northern Italy) as a test case to explore whether grass carp effects on canal aquatic vegetation could be at the root of historical changes in N loads exported from the basin to the Goro Lagoon. We modeled the aquatic vegetation production and standing crop, its denitrification potential, and its consumption by introduced grass carp. We then examined whether changes in historical nitrogen loads matched the modeled losses of the drainage network denitrification function or other changes in agricultural practices. Our results indicate that introduced grass carp could completely remove submerged vegetation in the Po di Volano canal network, which could – in turn – lead to substantial loss of the denitrification function of the system, causing in an increase in downstream nitrogen loads. A corresponding increase, matching both timing and magnitude, was detected in historical nitrogen loads to the Goro Lagoon, which were significantly different before and after the time of modeled collapse of the denitrification function. This increase was not clearly linked to watershed use or agricultural practices, which implies that the loss of the denitrification function through grass carp overgrazing could be a likely explanation of the increase in downstream nitrogen loads. Perhaps for the first time, we provide evidence that a freshwater fish introduction could have caused long-lasting changes in nutrient dynamics that are exported downstream to areas where the fish is not present.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.135093","usgsCitation":"Milardi, M., Soana, E., Chapman, D., Fano, E.A., and Castaldelli, G., 2020, Could a freshwater fish be at the root of dystrophic crises in a coastal lagoon?: Science of the Total Environment, v. 711, 135093, 11 p., https://doi.org/10.1016/j.scitotenv.2019.135093.","productDescription":"135093, 11 p.","ipdsId":"IP-101491","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":458487,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.135093","text":"External Repository"},{"id":381435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Po River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 7.207031249999999,\n 43.8028187190472\n ],\n [\n 11.42578125,\n 43.8028187190472\n ],\n [\n 11.42578125,\n 45.644768217751924\n ],\n [\n 7.207031249999999,\n 45.644768217751924\n ],\n [\n 7.207031249999999,\n 43.8028187190472\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"711","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Milardi, Marco","contributorId":201384,"corporation":false,"usgs":false,"family":"Milardi","given":"Marco","email":"","affiliations":[],"preferred":false,"id":807037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soana, Elisa","contributorId":245792,"corporation":false,"usgs":false,"family":"Soana","given":"Elisa","email":"","affiliations":[{"id":49329,"text":"University of Ferrara, Italy","active":true,"usgs":false}],"preferred":false,"id":807038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":807039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fano, Elisa Anna","contributorId":245793,"corporation":false,"usgs":false,"family":"Fano","given":"Elisa","email":"","middleInitial":"Anna","affiliations":[{"id":49329,"text":"University of Ferrara, Italy","active":true,"usgs":false}],"preferred":false,"id":807040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castaldelli, Giuseppe","contributorId":201385,"corporation":false,"usgs":false,"family":"Castaldelli","given":"Giuseppe","email":"","affiliations":[],"preferred":false,"id":807041,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207435,"text":"70207435 - 2020 - Relaxing segmentation on the Wasatch Fault Zone: Impact on seismic hazard ","interactions":[],"lastModifiedDate":"2020-02-06T11:12:48","indexId":"70207435","displayToPublicDate":"2019-11-19T13:23:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Relaxing segmentation on the Wasatch Fault Zone: Impact on seismic hazard ","docAbstract":"

The multisegment Wasatch fault zone is a well-studied normal fault in the western United States that has paleoseismic evidence of recurrent Holocene surface-faulting earthquakes. Along the 270-km-long central part of the fault, four primary structural complexities provide possible along-strike limits to these ruptures and form the basis for models of fault segmentation. Here, we assess the impact that the Wasatch fault segmentation model has on seismic hazard by evaluating the time-independent long-term rate of ruptures on the fault that satisfy fault slip rates and paleoseismic event rates, adapting standard inverse theory used in the Uniform California Earthquake Rupture Forecast 3 (UCERF3), and implementing a segmentation constraint where ruptures across primary structural complexities are penalized. We define three models with varying degrees of rupture penalization: (1) segmented (ruptures confined to individual segments), (2) penalized (multi-segment ruptures allowed, but penalized), and (3) unsegmented (all ruptures allowed). Seismic-hazard results show that on average, hazard is highest for the segmented model, where seismic moment is accommodated by frequent moderate (moment magnitude, Mw 6.2–6.8) earthquakes. The unsegmented model yields the lowest average seismic hazard because part of the seismic moment is accommodated by large (Mw 6.9–7.9), but infrequent ruptures. We compare these results to model differences derived from other inputs such as slip rate and magnitude scaling relationships and conclude that segmentation exerts a primary control on seismic hazard. This study demonstrates the need for additional geologic constraints on rupture extent and methods by which these observations can be included in hazard-modeling efforts.

","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120190088","usgsCitation":"Valentini, A., DuRoss, C., Field, E., Gold, R.D., Briggs, R.W., Visini, F., and Pace, B., 2020, Relaxing segmentation on the Wasatch Fault Zone: Impact on seismic hazard : Bulletin of the Seismological Society of America, v. 110, no. 1, p. 83-109, https://doi.org/10.1785/0120190088.","productDescription":"27 p.","startPage":"83","endPage":"109","ipdsId":"IP-111708","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":370502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.046551,41.251716],[-111.046723,40.997959],[-110.750727,40.996847],[-110.715026,40.996347],[-110.539819,40.996346],[-110.500718,40.994746],[-110.375714,40.994947],[-110.250709,40.996089],[-110.237848,40.995427],[-110.125709,40.99655],[-110.121639,40.997101],[-110.048476,40.997555],[-110.006495,40.997815],[-110.000708,40.997352],[-109.999838,40.99733],[-109.97553,40.997912],[-109.855299,40.997614],[-109.854302,40.997661],[-109.715409,40.998191],[-109.713877,40.998266],[-109.676421,40.998395],[-109.534926,40.998143],[-109.500694,40.999127],[-109.250735,41.001009],[-109.231985,41.002059],[-109.173682,41.000859],[-109.050076,41.000659],[-109.048455,40.826081],[-109.049088,40.714562],[-109.048373,40.662602],[-109.048249,40.653601],[-109.048044,40.619231],[-109.050074,40.540358],[-109.049955,40.539901],[-109.050698,40.499963],[-109.050314,40.495092],[-109.050946,40.444368],[-109.050969,40.222662],[-109.050973,40.180849],[-109.050944,40.180712],[-109.050813,40.059579],[-109.050873,40.058915],[-109.050615,39.87497],[-109.05104,39.660472],[-109.051363,39.497674],[-109.050765,39.366677],[-109.051512,39.126095],[-109.052436,38.999985],[-109.053292,38.942878],[-109.053233,38.942467],[-109.053797,38.905284],[-109.053943,38.904414],[-109.054189,38.874984],[-109.057388,38.795456],[-109.059541,38.719888],[-109.060253,38.599328],[-109.059962,38.499987],[-109.060062,38.275489],[-109.054648,38.244921],[-109.041762,38.16469],[-109.041837,38.153022],[-109.04282,37.999301],[-109.042819,37.997068],[-109.043121,37.97426],[-109.041058,37.907236],[-109.041653,37.88117],[-109.041844,37.872788],[-109.041723,37.842051],[-109.041754,37.835826],[-109.041461,37.800105],[-109.042098,37.74999],[-109.041636,37.74021],[-109.04176,37.713182],[-109.041732,37.711214],[-109.042269,37.666067],[-109.042089,37.623795],[-109.042131,37.617662],[-109.041806,37.604171],[-109.041865,37.530726],[-109.041915,37.530653],[-109.043137,37.499992],[-109.043464,37.484711],[-109.04581,37.374993],[-109.046039,37.249993],[-109.045584,37.249351],[-109.045487,37.210844],[-109.045978,37.201831],[-109.045995,37.177279],[-109.045156,37.112064],[-109.045203,37.111958],[-109.045173,37.109464],[-109.045189,37.096271],[-109.044995,37.086429],[-109.045058,37.074661],[-109.045166,37.072742],[-109.045223,36.999084],[-109.181196,36.999271],[-109.233848,36.999266],[-109.246917,36.999346],[-109.26339,36.999263],[-109.268213,36.999242],[-109.270097,36.999266],[-109.378039,36.999135],[-109.381226,36.999148],[-109.495338,36.999105],[-109.625668,36.998308],[-109.875673,36.998504],[-110.000677,36.997968],[-110.000876,36.998502],[-110.021778,36.998602],[-110.47019,36.997997],[-110.490908,37.003566],[-110.50069,37.00426],[-110.599512,37.003448],[-110.625605,37.003416],[-110.62569,37.003721],[-110.75069,37.003197],[-111.066496,37.002389],[-111.133718,37.000779],[-111.254853,37.001077],[-111.278286,37.000465],[-111.405517,37.001497],[-111.405869,37.001481],[-111.412784,37.001478],[-112.35769,37.001025],[-112.368946,37.001125],[-112.534545,37.000684],[-112.538593,37.000674],[-112.540368,37.000669],[-112.545094,37.000734],[-112.558974,37.000692],[-112.609787,37.000753],[-112.899366,37.000319],[-112.966471,37.000219],[-113.965907,36.999976],[-113.965907,37.000025],[-114.0506,37.000396],[-114.051749,37.088434],[-114.051822,37.090976],[-114.052827,37.103961],[-114.051867,37.134292],[-114.052179,37.14711],[-114.051673,37.172368],[-114.051405,37.233854],[-114.051974,37.283848],[-114.051974,37.284511],[-114.0518,37.293044],[-114.0518,37.293548],[-114.051927,37.370459],[-114.051927,37.370734],[-114.051765,37.418083],[-114.052448,37.43144],[-114.052701,37.492014],[-114.052685,37.502513],[-114.052718,37.517264],[-114.052689,37.517859],[-114.052962,37.592783],[-114.052472,37.604776],[-114.051728,37.745997],[-114.051785,37.746249],[-114.05167,37.746958],[-114.051109,37.756276],[-114.049919,37.765586],[-114.048473,37.809861],[-114.049677,37.823645],[-114.049928,37.852508],[-114.049658,37.881368],[-114.050423,37.999961],[-114.049903,38.148601],[-114.050138,38.24996],[-114.049417,38.2647],[-114.05012,38.404536],[-114.050091,38.404673],[-114.050485,38.499955],[-114.049834,38.543784],[-114.049862,38.547764],[-114.050154,38.57292],[-114.049883,38.677365],[-114.049749,38.72921],[-114.049168,38.749951],[-114.049465,38.874949],[-114.048521,38.876197],[-114.048054,38.878693],[-114.049104,39.005509],[-114.047079,39.499943],[-114.047728,39.542742],[-114.047273,39.759413],[-114.047783,39.79416],[-114.047214,39.821024],[-114.047134,39.906037],[-114.046555,39.996899],[-114.046835,40.030131],[-114.046386,40.097896],[-114.046741,40.104231],[-114.046683,40.116931],[-114.046153,40.231971],[-114.046178,40.398313],[-114.045826,40.424823],[-114.045218,40.430282],[-114.045518,40.494474],[-114.045577,40.495801],[-114.045281,40.506586],[-114.043505,40.726292],[-114.043831,40.758666],[-114.043803,40.759205],[-114.043176,40.771675],[-114.042145,40.999926],[-114.041447,41.207752],[-114.042553,41.210923],[-114.041396,41.219958],[-114.040231,41.49169],[-114.040942,41.499921],[-114.040437,41.615377],[-114.039968,41.62492],[-114.039901,41.753781],[-114.041152,41.850595],[-114.041107,41.850573],[-114.039648,41.884816],[-114.041723,41.99372],[-113.993903,41.992698],[-113.893261,41.988057],[-113.822163,41.988479],[-113.796082,41.989104],[-113.76453,41.989459],[-113.500837,41.992799],[-113.496548,41.993305],[-113.431563,41.993799],[-113.40223,41.994161],[-113.396497,41.99425],[-113.357611,41.993859],[-113.340072,41.994747],[-113.250829,41.99561],[-113.249159,41.996203],[-113.000821,41.998223],[-113.00082,41.998223],[-112.979218,41.998263],[-112.909587,41.998791],[-112.882367,41.998922],[-112.880619,41.998921],[-112.833125,41.999345],[-112.833084,41.999305],[-112.788542,41.999681],[-112.709375,42.000309],[-112.648019,42.000307],[-112.450814,42.000953],[-112.450567,42.001092],[-112.38617,42.001126],[-112.264936,42.000991],[-112.239107,42.001217],[-112.192976,42.001167],[-112.173352,41.996568],[-112.163956,41.996708],[-112.109532,41.997598],[-112.01218,41.99835],[-111.915837,41.998519],[-111.915622,41.998496],[-111.876491,41.998528],[-111.750778,41.99933],[-111.507264,41.999518],[-111.471381,41.999739],[-111.425535,42.00084],[-111.420898,42.000793],[-111.415873,42.000748],[-111.046689,42.001567],[-111.045818,41.579845],[-111.045789,41.565571],[-111.046264,41.377731],[-111.0466,41.360692],[-111.046551,41.251716]]]},\"properties\":{\"name\":\"Utah\",\"nation\":\"USA \"}}]}","volume":"110","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentini, Alessandro","contributorId":221390,"corporation":false,"usgs":false,"family":"Valentini","given":"Alessandro","email":"","affiliations":[{"id":40356,"text":"Università degli Studi “G. d’Annunzio” di Chieti-Pescara, InGeo Department","active":true,"usgs":false}],"preferred":false,"id":778013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuRoss, Christopher B. 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":778019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Visini, Francesco","contributorId":221392,"corporation":false,"usgs":false,"family":"Visini","given":"Francesco","email":"","affiliations":[{"id":40358,"text":"Istituto Nazionale di Geofisica e Vulcanologia, sezione di Pisa","active":true,"usgs":false}],"preferred":false,"id":778017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pace, Bruno","contributorId":221391,"corporation":false,"usgs":false,"family":"Pace","given":"Bruno","email":"","affiliations":[{"id":40357,"text":"Università degli Studi “G. d’Annunzio” di Chieti-Pescara, DiSPUTer Department","active":true,"usgs":false}],"preferred":false,"id":778015,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206961,"text":"70206961 - 2020 - Using integrated population models for insights into monitoring programs: An application using pink-footed geese","interactions":[],"lastModifiedDate":"2019-12-03T06:43:13","indexId":"70206961","displayToPublicDate":"2019-11-19T11:43:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Using integrated population models for insights into monitoring programs: An application using pink-footed geese","docAbstract":"

Development of integrated population models (IPMs) assume the absence of systematic bias in monitoring programs, yet many potential sources of systematic bias in monitoring data exist (e.g., under-counts of abundance). By integrating multiple sources of data, we can assess whether various sources of monitoring data provide consistent inferences about changes in population size and, thus, whether monitoring programs appear unbiased. For the purposes of understanding how IPMs could provide insights for monitoring programs, we used the Svalbard breeding population of pink-footed goose (Anser brachyrhynchus) as a case study. The Svalbard pink-footed goose is a well-studied species, the focus of the first adaptive-harvest-management program in Europe, and the subject of a variety of long-term monitoring programs. We examined two formulations of an IPM, but ultimately relied on the one that provided a satisfactory fit to all the available data as based on Chi-squared goodness of fit tests. Our analyses suggest a negative bias in November counts (-20 %), a negative bias in capture-mark-recapture estimates of survival (-3 %), and a negative bias in indices of productivity (-23 %). We offer possible explanations for these biases, whether the degree of bias seems reasonable considering those explanations, and how bias might be investigated directly and ultimately avoided or corrected. Finally, we discuss implications of our work for developing IPMs and associated monitoring programs for managing pink-footed geese and other waterbird species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2019.108869","usgsCitation":"Johnson, F., Zimmerman, G.S., Jensen, G.H., Clausen, K.K., Frederiksen, M., and Madsen, J., 2020, Using integrated population models for insights into monitoring programs: An application using pink-footed geese: Ecological Modelling, v. 415, 108869, 13 p., https://doi.org/10.1016/j.ecolmodel.2019.108869.","productDescription":"108869, 13 p.","ipdsId":"IP-107877","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437202,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901K3RP","text":"USGS data release","linkHelpText":"Demographic parameters for Svalbard pink-footed geese, 1991-2018"},{"id":369802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"415","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":220964,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":776392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":776393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Gitte H.","contributorId":220965,"corporation":false,"usgs":false,"family":"Jensen","given":"Gitte","email":"","middleInitial":"H.","affiliations":[{"id":13685,"text":"Aarhus University, Department of Bioscience","active":true,"usgs":false}],"preferred":false,"id":776394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clausen, Kevin K.","contributorId":174355,"corporation":false,"usgs":false,"family":"Clausen","given":"Kevin","email":"","middleInitial":"K.","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":776395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frederiksen, Morten","contributorId":217509,"corporation":false,"usgs":false,"family":"Frederiksen","given":"Morten","email":"","affiliations":[{"id":13685,"text":"Aarhus University, Department of Bioscience","active":true,"usgs":false}],"preferred":false,"id":776396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":776397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236239,"text":"70236239 - 2020 - Directivity of M 3.1 earthquake near Anza, California and the effect on peak ground motion","interactions":[],"lastModifiedDate":"2022-08-31T14:19:50.242428","indexId":"70236239","displayToPublicDate":"2019-11-19T09:14:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Directivity of M 3.1 earthquake near Anza, California and the effect on peak ground motion","docAbstract":"

We show the effect of rupture directivity on peak ground‐motion values for a moderate magnitude event at Anza, California, and neighboring stations at the Imperial Valley. The event was located near Borrego Springs on the west side of the Salton Sea and was well recorded at broadband stations near Anza, California, and at stations on the west side of the Imperial Valley. After correcting for regional attenuation, an anomalously large residual in peak motion was observed at station ERR just to the southeast of the epicenter. Using the algorithm from Boatwright (2007), peak motions from the regional seismic networks in southern California were inverted to determine directivity, which was to the southeast along the trend of the San Jacinto fault toward station ERR. This algorithm uses peak values compiled for the ShakeMap system mostly at regional distances. It does not capture the main features of the source time function (STF) predicted by directivity. Consequently, we determined the second‐degree moments for this earthquake, which confirmed that station ERR has a shorter and higher STF compared to stations to the northwest suggesting rupture propagated to the southeast. The azimuthal distribution of local stations is sparse, but nevertheless the largest amplitudes (such as at station ERR) correlate well with the maximum in the radiation pattern and smaller values with the minima, which is the radiation pattern for SH plus the effect of directivity. Using the data from the analysis of the second‐degree moments, the characteristic length of the fault is 0.58 km, assuming an idealized unilateral extended rupture with a rupture time of 0.09 s. This yields an apparent rupture velocity of 6.4  km/s\">6.4  km/s for an idealized model, which is super shear. This value is model dependent and would change if, for example, the rupture was bilateral. Although this value is even greater than the P‐wave velocity, it supports the idea that the rupture velocity is super shear and would enhance the correlation between the peak motions and the radiation pattern.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120190141","usgsCitation":"Fletcher, J.P., and Boatwright, J., 2020, Directivity of M 3.1 earthquake near Anza, California and the effect on peak ground motion: Bulletin of the Seismological Society of America, v. 110, no. 1, p. 312-318, https://doi.org/10.1785/0120190141.","productDescription":"7 p.","startPage":"312","endPage":"318","ipdsId":"IP-107351","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":405996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Anza","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.9,\n 32.8\n ],\n [\n -115.2,\n 32.8\n ],\n [\n -115.2,\n 33.8\n ],\n [\n -116.9,\n 33.8\n ],\n [\n -116.9,\n 32.8\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"110","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850302,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217797,"text":"70217797 - 2020 - Estimating population size with imperfect detection using a parametric bootstrap","interactions":[],"lastModifiedDate":"2021-02-03T12:40:10.682479","indexId":"70217797","displayToPublicDate":"2019-11-19T06:38:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"Estimating population size with imperfect detection using a parametric bootstrap","docAbstract":"

We develop a novel method of estimating population size from imperfectly detected counts of individuals and a separate estimate of detection probability. Observed counts are separated into classes within which detection probability is assumed constant. Within a detection class, counts are modeled as a single binomial observation X with success probability p where the goal is to estimate index N. We use a Horvitz–Thompson‐like estimator for N and account for uncertainty in both sample data and estimated success probability via a parametric bootstrap. Unlike capture–recapture methods, our model does not require repeated sampling of the population. Our method is able to achieve good results, even with small X. We show in a factorial simulation study that the median of the bootstrapped sample has small bias relative to N and that coverage probabilities of confidence intervals for N are near nominal under a wide array of scenarios. Our methodology begins to break down when P(X=0)>0.1 but is still capable of obtaining reasonable confidence coverage. We illustrate the proposed technique by estimating (1) the size of a moose population in Alaska and (2) the number of bat fatalities at a wind power facility, both from samples with imperfect detection probabilities, estimated independently.

","language":"English","publisher":"Wiley","doi":"10.1002/env.2603","usgsCitation":"Madsen, L., Dalthorp, D., Huso, M., and Aderman, A., 2020, Estimating population size with imperfect detection using a parametric bootstrap: Environmetrics, v. 31, no. 3, e2603, 11 p., https://doi.org/10.1002/env.2603.","productDescription":"e2603, 11 p.","ipdsId":"IP-103965","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":382914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Madsen, Lisa","contributorId":210021,"corporation":false,"usgs":false,"family":"Madsen","given":"Lisa","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":809752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalthorp, Daniel 0000-0002-4815-6309 ddalthorp@usgs.gov","orcid":"https://orcid.org/0000-0002-4815-6309","contributorId":4902,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Daniel","email":"ddalthorp@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":809753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huso, Manuela 0000-0003-4687-6625 mhuso@usgs.gov","orcid":"https://orcid.org/0000-0003-4687-6625","contributorId":223969,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela","email":"mhuso@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":809754,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aderman, Andy","contributorId":248722,"corporation":false,"usgs":false,"family":"Aderman","given":"Andy","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":809755,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250177,"text":"70250177 - 2020 - Heat accumulation on coral reefs mitigated by internal waves","interactions":[],"lastModifiedDate":"2023-11-27T17:49:36.946296","indexId":"70250177","displayToPublicDate":"2019-11-18T11:47:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Heat accumulation on coral reefs mitigated by internal waves","docAbstract":"

Coral reefs are among the most species-rich, productive and economically valuable ecosystems on Earth but increasingly frequent pantropical coral bleaching events are threatening their persistence on a global scale. The 2015–2016 El Niño led to the hottest sea surface temperatures on record and widespread bleaching of shallow-water corals. However, the causes of spatial variation in bleaching are poorly understood, and near-surface estimates of heat stress, such as those inferred from satellites, cannot be generalized across the broad depth ranges occupied by corals. Here, using in situ temperatures recorded across reefs from the near surface to 30–50 m depths in the western, central and eastern Pacific, we show that during the peak of the 2015–2016 anomaly, temperature fluctuations associated with internal waves reduced cumulative heat exposure by up to 88%. The durations of severe thermal anomalies above 8 °C-days, at which point widespread coral bleaching and mortality are likely, were also decreased by >36% at some sites and were prevented entirely at others. The impact of internal waves across depths on coral reefs has the potential to create and support thermal refuges in which heat stress and coral bleaching risk may be modulated, but future effects depend on the response of internal wave climates to continued warming and strengthening ocean stratification.

","language":"English","publisher":"Nature","doi":"10.1038/s41561-019-0486-4","usgsCitation":"Wyatt, A.S., Leichter, J., Toth, L., Miyajima, T., Aronson, R.B., and Nagata, T., 2020, Heat accumulation on coral reefs mitigated by internal waves: Nature Geoscience, v. 13, p. 28-34, https://doi.org/10.1038/s41561-019-0486-4.","productDescription":"7 p.","startPage":"28","endPage":"34","ipdsId":"IP-106803","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":422976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2019-11-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wyatt, Alex S. J. 0000-0002-1339-9546","orcid":"https://orcid.org/0000-0002-1339-9546","contributorId":331743,"corporation":false,"usgs":false,"family":"Wyatt","given":"Alex","email":"","middleInitial":"S. J.","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leichter, James J.","contributorId":261128,"corporation":false,"usgs":false,"family":"Leichter","given":"James J.","affiliations":[{"id":52738,"text":"SCRIPPS INSTITUTION OF OCEANOGRAPHY, UNIVERSITY OF CALIFORNIA AT SAN DIEGO","active":true,"usgs":false}],"preferred":false,"id":888674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miyajima, Toshihiro 0000-0001-8562-6704","orcid":"https://orcid.org/0000-0001-8562-6704","contributorId":331744,"corporation":false,"usgs":false,"family":"Miyajima","given":"Toshihiro","email":"","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":888677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagata, Toshi","contributorId":331745,"corporation":false,"usgs":false,"family":"Nagata","given":"Toshi","email":"","affiliations":[{"id":79277,"text":"University of Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":888678,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227189,"text":"70227189 - 2020 - Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry","interactions":[],"lastModifiedDate":"2022-01-04T15:28:45.816391","indexId":"70227189","displayToPublicDate":"2019-11-18T09:23:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry","docAbstract":"

Life history diversity is important for population stability and is dependent on connectivity to habitat that supports all life stages and life history strategies for a species. Westslope Cutthroat Trout Oncorhynchus clarkii lewisi (WCT) exhibit plasticity in life history strategies in response to environmental variability, but fisheries managers have been challenged with evaluating the life history structure of WCT populations. The goals of this research were to use strontium isotopes (i.e., 87Sr/86Sr) derived from ambient water and sagittal otoliths to assess spatial variability and describe the life history structure of WCT. Water samples (n = 49) and WCT (n = 571) sagittal otoliths were collected throughout the Coeur d’Alene Lake basin in Idaho and analyzed for Sr isotopes. Model-based discriminant function analysis was used to assign WCT to natal tributaries and to infer maternal origins. Life history structure was inferred from maternal signatures and indicated that fluvial (68% of all fish), resident (27%), and adfluvial (5%) life history strategies were present. Connectivity in lotic systems and from lotic to lentic environments supports WCT life history diversity and contributes to a broad distribution of the species.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2019.105416","usgsCitation":"Heckel, J.W., Quist, M.C., Watkins, C.J., and Dux, A.M., 2020, Life history structure of westslope cutthroat trout: Inferences from otolith microchemistry: Fisheries Research, v. 222, 105416, 14 p., https://doi.org/10.1016/j.fishres.2019.105416.","productDescription":"105416, 14 p.","ipdsId":"IP-107684","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":393855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d'Alene Lake, Coeur d'Alene River, St, Joe River, St, Maries River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 46.75\n ],\n [\n -115,\n 46.75\n ],\n [\n -115,\n 48\n ],\n [\n -117,\n 48\n ],\n [\n -117,\n 46.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"222","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heckel, John W","contributorId":270716,"corporation":false,"usgs":false,"family":"Heckel","given":"John","email":"","middleInitial":"W","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":830023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":830022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, Carson J.","contributorId":171708,"corporation":false,"usgs":false,"family":"Watkins","given":"Carson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":830024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dux, Andrew M.","contributorId":175256,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830025,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219557,"text":"70219557 - 2020 - Post-fire aspen (Populus tremuloides) regeneration varies in response to winter precipitation across a regional climate gradient","interactions":[],"lastModifiedDate":"2021-04-13T12:48:22.205733","indexId":"70219557","displayToPublicDate":"2019-11-18T07:45:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire aspen (Populus tremuloides) regeneration varies in response to winter precipitation across a regional climate gradient","docAbstract":"

Altered climate and changing fire regimes are synergistically impacting forest communities globally, resulting in deviations from historical norms and creation of novel successional dynamics. These changes are particularly important when considering the stability of a keystone species such as quaking aspen (Populus tremuloides Michx.), which contributes critical ecosystem services across its broad North American range. As a relatively drought intolerant species, projected changes of altered precipitation timing, amount, and type (e.g. snow or rain) may influence aspen response to fire, especially in moisture-limited and winter precipitation-dominated portions of its range. Aspen is generally considered an early-seral species that benefits from fire, but increases in fire activity across much of the western United States could affect the species in unpredictable ways. This study examined post-fire aspen stands across a regional climate gradient spanning from the north-central Great Basin to the northeastern portion of the Greater Yellowstone Ecosystem (USA). We investigated the influence of seasonal precipitation and temperature variables, snowpack, and site conditions (e.g. browsing levels, topography) on density of post-fire aspen regeneration (i.e. all small trees ha−1) and recruitment (i.e. small trees ≥2 m tall ha−1) across 15 fires that occurred between 2000 and 2009. The range of post-fire regeneration (2500–71,600 small trees ha−1) and recruitment (0–32,500 small trees ≥2 m ha−1) densities varied widely across plots. Linear mixed effects models demonstrated that both response variables increased primarily with early winter (Oct-Dec) precipitation during the ‘fire-regen period’ (i.e., fire year and five years after fire) relative to the 30-year mean. The 30-year mean of early winter precipitation and fire-regen period snowpack were also positively related to recruitment densities. Both response variables decreased with higher shrub cover, highlighting the importance of considering shrub competition in post-fire environments. Regeneration and recruitment densities were negatively related to proportion browsed aspen leaders and animal pellet densities (no./m2), respectively, indicating the influence of ungulate browsing even at the relatively low levels observed across sites. A post-hoc exploratory analysis suggests that deviation in early winter precipitation during the fire-regen period (relative to 30-year means) varied among sites along directional gradients, emphasizing the need to consider multiple spatiotemporal scales when investigating climate effects on post-fire successional dynamics. We discuss our findings in terms of dynamic management and conservation strategies in light of changing fire regimes and climate conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2019.117681","usgsCitation":"McIlroy, S., and Shinneman, D.J., 2020, Post-fire aspen (Populus tremuloides) regeneration varies in response to winter precipitation across a regional climate gradient: Forest Ecology and Management, v. 455, 117681, 9 p., https://doi.org/10.1016/j.foreco.2019.117681.","productDescription":"117681, 9 p.","ipdsId":"IP-110538","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":437205,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99E9438","text":"USGS data release","linkHelpText":"Post-fire aspen (Populus tremuloides) regeneration data (2014-2015)"},{"id":385051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.4892578125,\n 45.42929873257377\n ],\n [\n -109.423828125,\n 45.42929873257377\n ],\n [\n -109.423828125,\n 46.13417004624326\n ],\n [\n -111.4892578125,\n 46.13417004624326\n ],\n [\n -111.4892578125,\n 45.42929873257377\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.7197265625,\n 44.15068115978094\n ],\n [\n -111.6650390625,\n 44.15068115978094\n ],\n [\n -111.6650390625,\n 44.715513732021336\n ],\n [\n -112.7197265625,\n 44.715513732021336\n ],\n [\n -112.7197265625,\n 44.15068115978094\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0380859375,\n 45.460130637921004\n ],\n [\n -112.1044921875,\n 45.460130637921004\n ],\n [\n -112.1044921875,\n 46.49839225859763\n ],\n [\n -114.0380859375,\n 46.49839225859763\n ],\n [\n -114.0380859375,\n 45.460130637921004\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.7080078125,\n 42.97250158602597\n ],\n [\n -113.3349609375,\n 42.97250158602597\n ],\n [\n -113.3349609375,\n 44.55916341529182\n ],\n [\n -115.7080078125,\n 44.55916341529182\n ],\n [\n -115.7080078125,\n 42.97250158602597\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.5546875,\n 41.80407814427237\n ],\n [\n -111.8408203125,\n 41.80407814427237\n ],\n [\n -111.8408203125,\n 42.58544425738491\n ],\n [\n -113.5546875,\n 42.58544425738491\n ],\n [\n -113.5546875,\n 41.80407814427237\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.05957031249999,\n 41.21172151054787\n ],\n [\n -114.2138671875,\n 41.21172151054787\n ],\n [\n -114.2138671875,\n 42.00032514831621\n ],\n [\n -116.05957031249999,\n 42.00032514831621\n ],\n [\n -116.05957031249999,\n 41.21172151054787\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"455","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":169446,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":814133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":814134,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227116,"text":"70227116 - 2020 - Compound effects of water clarity, inflow, wind and climate warming on mountain lake thermal regimes","interactions":[],"lastModifiedDate":"2022-01-03T16:08:43.642259","indexId":"70227116","displayToPublicDate":"2019-11-16T10:30:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Compound effects of water clarity, inflow, wind and climate warming on mountain lake thermal regimes","docAbstract":"

Many studies have examined the effects of climate warming on lake stability, but few have addressed environmental changes concomitant with climate change, such as alterations in water clarity and lake inflow. Although air temperature rise is a predominant factor linked to lake thermal characteristics, climate-driven changes at watershed scales can substantially alter lake clarity and inflow, exacerbating the effects of future air warming on lake thermal conditions. Without accounting for potential changes in clarity and inflow, future thermal predictions could be inaccurate. We employed the General Lake Model to simulate future thermal conditions (relative thermal resistance to mixing; RTRM) of small (< 12 ha) mountain lakes of the western United States by calibrating the model to a set of lakes in the Southern Rocky Mountains, USA. We found that after air temperature, alterations in inflow had the largest effect on lake thermal conditions, changes in wind had the least effect, and larger lakes experienced more than double the increase in lake stability than smaller lakes. Generally, clear, high inflow lakes had the lowest stability now, and in the future, while the largest overall increase in thermal stability occurred in larger lakes with low inflows and high turbidity. Assuming air temperature rise alone, summer stability of mountain lakes of the western United States was predicted to increase by 15–23% at + 2 °C air temperatures, and by 39–62% at + 5 °C air temperatures. When accounting for associated changes in clarity and inflow, lake stability was predicted to increase by 208% with + 2 °C air warming and 318% with at 5 °C air warming. Thus, ignoring the multivariate effects of climate change can substantially underestimate changes to mountain lake thermal and stratification regimes. Dimictic lakes may become more strongly stratified and polymictic lakes will experience more prolonged stratification. While predicted changes to lake temperatures may not be harmful to trout species that currently inhabit mountain lakes, longer and more intense stratification could cause indirect effects, such as hypoxia, that could reduce growth and survival of these organisms.

","language":"English","publisher":"Springer","doi":"10.1007/s00027-019-0676-6","usgsCitation":"Christianson, K.R., Johnson, B.M., and Hooten, M., 2020, Compound effects of water clarity, inflow, wind and climate warming on mountain lake thermal regimes: Aquatic Sciences, v. 82, 6, 17 p., https://doi.org/10.1007/s00027-019-0676-6.","productDescription":"6, 17 p.","ipdsId":"IP-107101","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":393652,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rawah Wilderness Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.89035034179688,\n 40.534676780615406\n ],\n [\n -105.85052490234375,\n 40.58058466412761\n ],\n [\n -105.83816528320312,\n 40.693134153308065\n ],\n [\n -105.88897705078125,\n 40.80029619806279\n ],\n [\n -105.96313476562499,\n 40.88029480552824\n ],\n [\n -106.09771728515625,\n 40.86991083161536\n ],\n [\n -106.11968994140624,\n 40.84498264925404\n ],\n [\n -106.0125732421875,\n 40.727486422997785\n ],\n [\n -105.96450805664062,\n 40.61916465186328\n ],\n [\n -105.89035034179688,\n 40.534676780615406\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2019-11-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Christianson, Kyle R.","contributorId":270655,"corporation":false,"usgs":false,"family":"Christianson","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Brett M.","contributorId":270656,"corporation":false,"usgs":false,"family":"Johnson","given":"Brett","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":829701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":829699,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209054,"text":"70209054 - 2020 - A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals","interactions":[],"lastModifiedDate":"2020-09-10T19:45:16.648168","indexId":"70209054","displayToPublicDate":"2019-11-15T12:55:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals","docAbstract":"Understanding drivers of temporal variation in demographic parameters is a central goal of mark‐recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space‐for‐time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time‐varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.","language":"English","publisher":"Wiley","doi":"10.1111/biom.13171","usgsCitation":"Hance, D.J., Perry, R., Plumb, J., and Pope, A., 2020, A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals: Biometrics, v. 76, no. 3, p. 900-912, https://doi.org/10.1111/biom.13171.","productDescription":"13 p.","startPage":"900","endPage":"912","ipdsId":"IP-106158","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":373199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton J. 0000-0002-4475-706X dhance@usgs.gov","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":206496,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","email":"dhance@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":223235,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784644,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":223236,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784645,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":784646,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211826,"text":"70211826 - 2020 - The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars","interactions":[],"lastModifiedDate":"2020-08-07T22:03:59.417806","indexId":"70211826","displayToPublicDate":"2019-11-11T17:00:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars","docAbstract":"

Noachian-aged Jezero crater is the only known location on Mars where clear orbital detections of carbonates are found in close proximity to clear fluvio-lacustrine features indicating the past presence of a paleolake; however, it is unclear whether or not the carbonates in Jezero are related to the lacustrine activity. This distinction is critical for evaluating the astrobiological potential of the site, as lacustrine carbonates on Earth are capable of preserving biosignatures at scales that may be detectable by a landed mission like the Mars 2020 rover, which is planned to land in Jezero in February 2021. In this study, we conduct a detailed investigation of the mineralogical and morphological properties of geological units within Jezero crater in order to better constrain the origin of carbonates in the basin and their timing relative to fluvio-lacustrine activity. Using orbital visible/near-infrared hyperspectral images from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) along with high resolution imagery and digital elevation models, we identify a distinct carbonate-bearing unit, the “Marginal Carbonates,” located along the inner margin of the crater, near the largest inlet valley and the western delta. Based on their strong carbonate signatures, topographic properties, and location in the crater, we propose that this unit may preserve authigenic lacustrine carbonates, precipitated in the near-shore environment of the Jezero paleolake. Comparison to carbonate deposits from terrestrial closed basin lakes suggests that if the Marginal Carbonates are lacustrine in origin, they could preserve macro- and microscopic biosignatures in microbialite rocks like stromatolites, some of which would likely be detectable by Mars 2020. The Marginal Carbonates may represent just one phase of a complex fluvio-lacustrine history in Jezero crater, as we find that the spectral diversity of the fluvio-lacustrine deposits in the crater is consistent with a long-lived lake system cataloging the deposition and erosion of regional geologic units. Thus, Jezero crater may contain a unique record of the evolution of surface environments, climates, and habitability on early Mars.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2019.113526","usgsCitation":"Horgan, B., Anderson, R.B., Dromart, G., Amador, E.S., and Rice, M.S., 2020, The mineral diversity of Jezero crater: Evidence for possible lacustrine carbonates on Mars: Icarus, v. 339, 113526, 34 p., https://doi.org/10.1016/j.icarus.2019.113526.","productDescription":"113526, 34 p.","ipdsId":"IP-111142","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":458525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2019.113526","text":"Publisher Index Page"},{"id":377214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"339","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Horgan, Briony H. N.","contributorId":237069,"corporation":false,"usgs":false,"family":"Horgan","given":"Briony H. N.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":795256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":795257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dromart, G.","contributorId":237771,"corporation":false,"usgs":false,"family":"Dromart","given":"G.","affiliations":[{"id":47605,"text":"U. Lyon","active":true,"usgs":false}],"preferred":false,"id":795258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amador, Elena S.","contributorId":237804,"corporation":false,"usgs":false,"family":"Amador","given":"Elena","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":795345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Melissa S.","contributorId":237772,"corporation":false,"usgs":false,"family":"Rice","given":"Melissa","email":"","middleInitial":"S.","affiliations":[{"id":47606,"text":"Western Washington U.","active":true,"usgs":false}],"preferred":false,"id":795259,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208112,"text":"70208112 - 2020 - Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh","interactions":[],"lastModifiedDate":"2020-01-27T19:20:35","indexId":"70208112","displayToPublicDate":"2019-11-08T19:19:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh","docAbstract":"Sediment transport across bay–marsh interfaces depends on wave energy, vegetation, and marsh-edge morphology, and varies over a range of timescales. We investigated these dynamics in a tidal salt marsh with a gently-sloped, vegetated edge adjacent to northern San Francisco Bay. Spartina foliosa (cordgrass) inhabits the lower marsh and Salicornia pacifica (pickleweed) predominates on the marsh plain. We measured suspended-sediment concentration (SSC) and hydrodynamics in bay shallows and along a 100-m cross-shore transect in the marsh, during winter and summer. Four-year averaged accretion measured with marker-horizon plots was twice as great along the marsh transect as adjacent to a tidal creek, 50 m from the bay. We estimated deposition and trapping efficiency from the time-series data to assess its variation with season and wave energy. At high tide the transition zone (between cordgrass and pickleweed) was usually erosional, the pickleweed zone was depositional, and both erosion and deposition increased with wave energy, as did the landward position of maximum deposition. Erosion from the transition zone accounted for approximately one-third of the sediment flux into the pickleweed. In the pickleweed zone, SSC, the difference between flood- and ebb-tide SSC and trapping efficiency were greater in summer than winter for comparable wave conditions, which we attribute to increased sediment trapping by dense summer cordgrass. Moderate waves in summer (46%) accounted for more annual accretion in the pickleweed zone than larger waves in winter (28%), although the contribution of winter storms was diminished by the dry winter during the study.","language":"English","publisher":"Wiley","doi":"10.1029/2019JC015268","usgsCitation":"Lacy, J.R., Foster-Martinez, M.R., Allen, R., Ferner, M.C., and Callaway, J.C., 2020, Seasonal variation in sediment delivery across the bay-marsh interface of an estuarine salt marsh: Journal of Geophysical Research C: Oceans, v. 125, no. 1, e2019JC015268, https://doi.org/10.1029/2019JC015268.","productDescription":"e2019JC015268","ipdsId":"IP-108231","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 37.21283151445594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foster-Martinez, Madeline R.","contributorId":201705,"corporation":false,"usgs":false,"family":"Foster-Martinez","given":"Madeline","email":"","middleInitial":"R.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":780521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Rachel 0000-0002-0284-6466","orcid":"https://orcid.org/0000-0002-0284-6466","contributorId":221857,"corporation":false,"usgs":true,"family":"Allen","given":"Rachel","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":780522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferner, Matthew C.","contributorId":176972,"corporation":false,"usgs":false,"family":"Ferner","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":780523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callaway, John C. 0000-0002-7364-286X","orcid":"https://orcid.org/0000-0002-7364-286X","contributorId":205456,"corporation":false,"usgs":false,"family":"Callaway","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37110,"text":"Dept. of Environmental Science, University of San Francisco, 2130 Fulton St., San Francisco, CA 94117","active":true,"usgs":false}],"preferred":false,"id":780524,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70212701,"text":"70212701 - 2020 - #EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm","interactions":[],"lastModifiedDate":"2020-08-27T15:25:27.575316","indexId":"70212701","displayToPublicDate":"2019-11-06T06:55:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm","docAbstract":"

Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake could be triggered. Within 1–2 days, different forecast models were used to evaluate the likelihood of a larger event with two agencies (the U.S. Geological Survey [USGS] and the California Governor’s Office of Emergency Services) releasing probabilities and forecasts for larger earthquakes. Our research explores communication and news media efforts, as well as how people on a microblogging social media site (Twitter) responded to these forecasts. Our findings suggest that news media used a combination of information sources, basing their articles on what they learned from social media, as well as using information provided by government agencies. As the swarm slowed down, there is evidence of the continued interplay between news media and social media, with the USGS issuing revised probability reports and scientists from the USGS and other institutions participating in media interviews. In reporting on the swarm, news media often used language more generally than the scientists; terms such as probability, likelihood, chance, and possibility were used interchangeably. Knowledge of how news media used scientific information from the 2016 Bombay Beach forecasts can assist local, state, and federal agencies in developing effective communication strategies to respond to future earthquakes.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190082","usgsCitation":"McBride, S., Llenos, A.L., Page, M.T., and van der Elst, N., 2020, #EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm: Seismological Research Letters, v. 91, no. 1, p. 438-451, https://doi.org/10.1785/0220190082.","productDescription":"14 p.","startPage":"438","endPage":"451","ipdsId":"IP-104404","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":377873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Imperial County","otherGeospatial":"Bombay Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.740966796875,\n 33.330528249028085\n ],\n [\n -115.63247680664062,\n 33.330528249028085\n ],\n [\n -115.63247680664062,\n 33.37641235124676\n ],\n [\n -115.740966796875,\n 33.37641235124676\n ],\n [\n -115.740966796875,\n 33.330528249028085\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Llenos, Andrea L. 0000-0002-4088-6737 allenos@usgs.gov","orcid":"https://orcid.org/0000-0002-4088-6737","contributorId":4455,"corporation":false,"usgs":true,"family":"Llenos","given":"Andrea","email":"allenos@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Morgan T. 0000-0001-9321-2990 mpage@usgs.gov","orcid":"https://orcid.org/0000-0001-9321-2990","contributorId":3762,"corporation":false,"usgs":true,"family":"Page","given":"Morgan","email":"mpage@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":797310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":797311,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}