Summer water temperatures in the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers in western Washington have in recent decades exceeded the water temperature criteria for aquatic life uses set by the Washington Department of Ecology. This temperature increase is of particular concern because these rivers provide critical habitat for several salmonid populations, including Endangered Species Act-listed Chinook salmon (Onchorhynchus tshawytscha), steelhead trout (O. mykiss), and bull trout (Salvelinus confluentus), thus helping sustain Endangered Species Act-listed Southern Resident orcas (Orcinus orca). To inform salmonid restoration efforts within these rivers, this study used high-resolution thermal infrared (TIR) and three-band red, green, blue imagery acquired from repeated airborne surveys conducted in August 2020 and 2021 to (1) quantify longitudinal stream temperature profiles (LTPs) and (2) identify and characterize significant thermal features (STFs), including cold-water anomalies that could represent thermal refuges and serve as salmonid habitat. In addition, drag-probe water temperature surveys (“float surveys”) were performed on the Skykomish and Middle Fork Snoqualmie Rivers during August–September 2020 and on a segment of the Middle Fork Snoqualmie River in August 2021. These float surveys were intended to evaluate this thermal profiling method in comparison to airborne TIR surveys, by employing a novel method of processing float survey data to adjust for diurnal heating.
The Middle Fork Snoqualmie River warmed about 7 degrees Celsius (°C) from upstream to downstream in the 2020 airborne TIR survey and 9 °C in the 2021 airborne TIR survey, and the Snoqualmie River warmed about 4 °C in both surveys. The water temperature of the Skykomish River cooled in the 2020 and 2021 surveys, primarily because of cold inflow from the Sultan River. The overall shapes of airborne TIR LTPs of the same river were similar in the 2020 and 2021 surveys, with increasing and decreasing gradients in temperature tending to be nearly parallel over the same reaches and abrupt changes in temperature typically identified at the same locations. A total of 854 STFs were identified in the 2020 TIR imagery, and 732 STFs were identified in the 2021 TIR imagery. Interannual persistence was detected in 36.4 to 61.3 percent of lateral groundwater, side channel, and small tributary STFs, depending on the river surveyed, and in 14.8 to 28.7 percent of hyporheic and diffuse groundwater STFs. Hyporheic flow was commonly detected at the downstream end of a riffle, but not often detected directly downstream from large woody debris. Shade from riparian vegetation did not reduce water temperatures but rather maintained the water temperature recorded just upstream from the shaded section.
The adjusted average water temperature profiles from the float surveys were comparable to the LTPs derived from the airborne TIR surveys, with differences in temperature gradient primarily because the surveys were performed under different streamflow, radiation, and shading conditions. Though float surveys were found to be a valuable means of obtaining thermal profiles comparable to profiles obtained by airborne TIR surveys, one key advantage of airborne TIR surveys is that they may be used to precisely locate STFs over long distances, during a short survey duration, and in areas inaccessible to most watercraft.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235146","collaboration":"Prepared in cooperation with the Tulalip Tribes","usgsCitation":"Restivo, D.E., Diabat, M., Miwa, C., and Bright, V.A.L., 2024, Comparison of longitudinal stream temperature profiles and significant thermal features from airborne thermal infrared and float surveys of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, King and Snohomish Counties, Washington, summer 2020 and 2021: U.S. Geological Survey Scientific Investigations Report 2023–5146, 31 p., https://doi.org/10.3133/sir20235146.","productDescription":"Report: viii, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-139968","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":428021,"rank":3,"type":{"id":39,"text":"HTML 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Data Release","description":"Restivo, D.E., Diabat, M., Miwa, C., Bright, V.A.L., Seguin, C.M., Boucher, C.D., David, J.E., and Pouley, M., 2023, Water temperature mapping of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, Washington— Longitudinal stream temperature profiles, significant thermal features, and airborne thermal infrared and RGB imagery mosaics: U.S. Geological Survey data release, https://doi.org/10.5066/P9FJCM8N.","linkHelpText":"Water temperature mapping of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, Washington— Longitudinal stream temperature profiles, significant thermal features, and airborne thermal infrared and RGB imagery mosaics"}],"country":"United States","state":"Washington","county":"King County, Snohomish County","otherGeospatial":"Skykomish, Snoqualmie, and Middle Fork Snoqualmie 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Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018–2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018–19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57–99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO3-N), median intake from water was 44 % (IQR: 26–72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R2 = 0.52) as diet (R2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.170922","usgsCitation":"Skalaban, T., Thompson, D., Madrigal, J., Blount, B., Espinosa, M., Kolpin, D., Deziel, N., Jones, R., Freeman, L., Hofmann, J., and Ward, M., 2024, Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells: Science of the Total Envionrment, v. 919, 170922, 8 p., https://doi.org/10.1016/j.scitotenv.2024.170922.","productDescription":"170922, 8 p.","ipdsId":"IP-158584","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467031,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11665930","text":"External Repository"},{"id":427395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Buchanan County, Cedar County, Delaware County, Dubuque County, Jackson County, Johnson County, Jones County, Linn 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Center","active":true,"usgs":true}],"preferred":true,"id":898072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Deziel, N.C.","contributorId":335325,"corporation":false,"usgs":false,"family":"Deziel","given":"N.C.","email":"","affiliations":[{"id":48197,"text":"Yale","active":true,"usgs":false}],"preferred":false,"id":898073,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jones, R.R.","contributorId":335326,"corporation":false,"usgs":false,"family":"Jones","given":"R.R.","email":"","affiliations":[{"id":80369,"text":"NCI","active":true,"usgs":false}],"preferred":false,"id":898074,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Freeman, L.B.","contributorId":335327,"corporation":false,"usgs":false,"family":"Freeman","given":"L.B.","email":"","affiliations":[{"id":80369,"text":"NCI","active":true,"usgs":false}],"preferred":false,"id":898075,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hofmann, J.N.","contributorId":335328,"corporation":false,"usgs":false,"family":"Hofmann","given":"J.N.","email":"","affiliations":[{"id":80369,"text":"NCI","active":true,"usgs":false}],"preferred":false,"id":898076,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ward, M.H.","contributorId":335329,"corporation":false,"usgs":false,"family":"Ward","given":"M.H.","affiliations":[{"id":80369,"text":"NCI","active":true,"usgs":false}],"preferred":false,"id":898077,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70256572,"text":"70256572 - 2024 - Fish conservation in streams of the agrarian Mississippi Alluvial Valley: Conceptual model, management actions, and field verification","interactions":[],"lastModifiedDate":"2024-08-21T23:47:39.762384","indexId":"70256572","displayToPublicDate":"2024-02-15T18:43:36","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18328,"text":"Frontiers in Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Fish conservation in streams of the agrarian Mississippi Alluvial Valley: Conceptual model, management actions, and field verification","docAbstract":"The effects of agriculture and flood control practices accrued over more than a century have impaired aquatic habitats and their fish communities in the Mississippi Alluvial Valley, the historic floodplain of the Lower Mississippi River prior to leveeing. As a first step to conservation planning and adaptive management, we developed and tested a conceptual model of how changes to this floodplain have affected stream environments and fish assemblages. The model is deliberately simple in structure because it needs to be understood by stakeholders ranging from engineers to farmers who must remain engaged to ensure effective conservation. Testing involved multivariate correlative analyses that included descriptors of land setting, water quality, and fish assemblages representing 376 stream samples taken over two decades and ranging in Strahler stream order from 1 to 8. The conceptual model was adequately corroborated by empirical data, but with unexplained variability that is not uncommon in field surveys where gear biases, temporal biases, and scale biases prevent accurate characterizations. Our conceptual model distinguishes three types of conservation actions relevant to large agricultural floodplains: reforestation of large parcels and riparian zone conservation, in-channel interventions and connectivity preservation, and flow augmentation. Complete restoration of the floodplain may not be an acceptable option to the agriculture community. However, in most cases the application of even the most basic measures can support the return of sensitive aquatic species. We suggest that together these types of conservation actions can bring improved water properties to impacted reaches, higher reach biodiversity, more intolerant species, and more rheophilic fishes.
The persistence of threatened wildlife species depends on successful conservation and restoration of habitats, but climate change and other stressors make these tasks increasingly challenging. Applying climate change vulnerability analyses to contemporary wildlife management can be difficult because most analyses predict direct effects of future climate on wildlife species at broad geographic scales, rather than assessing their habitats at local scales (<1 km) that correspond to site-specific habitat management actions. We present a framework that synthesizes vegetation-focused vulnerability assessments to assess multiple effects on wildlife species' diverse habitat needs, providing a scenario-driven climate vulnerability assessment that maps differences in vulnerability of populations within a species' range. Our flexible habitat-centered synthesis approach leverages available spatial datasets describing projected exposure to vegetation changes due to climate change and other potentially synergistic stressors, reclassifies and weights them based on available estimates of species' sensitivity to these changes, and recombines them to create <1-km resolution maps of overall species vulnerability and threat-specific habitat vulnerability. To demonstrate its potential to guide decision-making, we applied this approach to the Gunnison sage-grouse (Centrocercus minimus), a federally threatened habitat specialist that depends on sagebrush and mesic habitats that are imperiled by climate change. We mapped six threats forecasted out to the year 2070: direct effects of climate on (1) sagebrush cover loss and (2) mesic habitat drying, indirect changes in invasion risk from (3) pinyon–juniper conifers and (4) annual grasses, and potentially synergistic risk of (5) development and (6) wildfire. We then assessed species vulnerability for each of the eight extant populations under three climate scenarios: Optimistic, Continuation, and Pessimistic. We found that the extent of cumulative species vulnerability due to multiple habitat changes was far greater than the extent of any single habitat vulnerability. Over 75% of critical habitats were at risk under the Pessimistic scenario, and nearly two thirds of habitats were at high risk for three or more threats. Invasive species were the most widespread threat, highlighting the importance of indirect effects of climate change. We illustrate how our approach can be applied to the existing management planning strategies to better prioritize conservation of habitats for the persistence of threatened species.
","language":"English","publisher":"Elsevier","doi":"10.1002/ecs2.4768","usgsCitation":"Van Schmidt, N.D., Shyvers, J.E., Heinrichs, J., Saher, D., and Aldridge, C.L., 2024, A habitat-centered framework for wildlife climate change vulnerability assessments: Application to Gunnison sage-grouse: Ecosphere, v. 15, no. 2, e4768, 19 p.; Data Release, https://doi.org/10.1002/ecs2.4768.","productDescription":"e4768, 19 p.; Data Release","ipdsId":"IP-145114","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":440396,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4768","text":"Publisher Index Page"},{"id":435038,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91P2SOG","text":"USGS data release","linkHelpText":"Maps of multiple future threats and stable areas for Gunnison sage-grouse habitats across three scenarios (2016-2070)"},{"id":428356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.3,\n 39\n ],\n [\n -109.3,\n 37.5\n ],\n [\n -106,\n 37.5\n ],\n [\n -106,\n 39\n ],\n [\n -109.3,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Schmidt, Nathan D. 0000-0002-5973-7934","orcid":"https://orcid.org/0000-0002-5973-7934","contributorId":288931,"corporation":false,"usgs":true,"family":"Van Schmidt","given":"Nathan","email":"","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shyvers, Jessica E. 0000-0002-4307-0004","orcid":"https://orcid.org/0000-0002-4307-0004","contributorId":288929,"corporation":false,"usgs":true,"family":"Shyvers","given":"Jessica","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":900104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saher, D. Joanne 0000-0002-2452-2570","orcid":"https://orcid.org/0000-0002-2452-2570","contributorId":288928,"corporation":false,"usgs":false,"family":"Saher","given":"D. Joanne","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":900107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70255935,"text":"70255935 - 2024 - Geographic distribution of feather δ34S in Europe","interactions":[],"lastModifiedDate":"2024-07-11T14:09:08.653681","indexId":"70255935","displayToPublicDate":"2024-02-15T09:00:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geographic distribution of feather δGeographic distribution models of environmentally stable isotopes (the so-called “isoscapes”) are widely employed in animal ecology, and wildlife forensics and conservation. However, the application of isoscapes is limited to elements and regions for which the spatial patterns have been estimated. Here, we focused on the ubiquitous yet less commonly used stable sulfur isotopes (δ34S). To predict the European δ34S isoscape, we used 242 feather samples from Eurasian Reed Warbler (Acrocephalus scirpaceus) formed at 69 European wetland sites. We quantified the relationships between sample δ34S and environmental covariates using a random forest regression model and applied the model to predict the geographic distribution of δ34S. We also quantified within-site variation in δ34S and complementarity with other isotopes on both individual and isoscape levels. The predicted feather δ34S isoscape shows only slight differences between the central and southern parts of Europe while the coastal regions were most enriched in 34S. The most important covariates of δ34S were distance to coastline, surface elevation, and atmospheric concentrations of SO2 gases. The absence of a systematic spatial pattern impedes the application of the δ34S isoscape, but high complementarity with other isoscapes advocates the combination of multiple isoscapes to increase the precision of animal tracing. Feather δ34S compositions showed considerable within-site variation with highest values in inland parts of Europe, likely attributed to wetland anaerobic conditions and redox sensitivity of sulfur. The complex European geography and topography as well as using δ34S samples from wetlands may contribute to the absence of a systematic spatial gradient of δ34S values in Europe. We thus encourage future studies to focus on the geographic distribution of δ34S using tissues from diverse taxa collected in various habitats over large land masses in the world (i.e., Africa, South America, or East Asia).
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4690","usgsCitation":"Brlik, V., Procházka, P., Bontempo, L., Camin, F., Jiguet, F., Osvath, G., Stricker, C.A., Wunder, M., and Powell, R.L., 2024, Geographic distribution of feather δ34S in Europe: Ecosphere, v. 15, no. 2, e4690, 14 p., https://doi.org/10.1002/ecs2.4690.","productDescription":"e4690, 14 p.","ipdsId":"IP-146450","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":440398,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4690","text":"Publisher Index Page"},{"id":430959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 35.16374167173652,\n 62.27273745280422\n ],\n [\n -10.613834422827864,\n 62.27273745280422\n ],\n [\n -10.613834422827864,\n 35.9353636594584\n ],\n [\n 35.16374167173652,\n 35.9353636594584\n ],\n [\n 35.16374167173652,\n 62.27273745280422\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Brlik, Vojtech","contributorId":213771,"corporation":false,"usgs":false,"family":"Brlik","given":"Vojtech","email":"","affiliations":[{"id":38851,"text":"Ustav Biologie Obratlovcu Akademie ved Ceske Republiky","active":true,"usgs":false}],"preferred":false,"id":906073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Procházka, Petr","contributorId":289285,"corporation":false,"usgs":false,"family":"Procházka","given":"Petr","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":906074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bontempo, Luana 0000-0001-7583-1501","orcid":"https://orcid.org/0000-0001-7583-1501","contributorId":310371,"corporation":false,"usgs":false,"family":"Bontempo","given":"Luana","email":"","affiliations":[{"id":67155,"text":"Food Quality and Nutrition Department, Research and Innovation Centre, Adige, Italy","active":true,"usgs":false}],"preferred":false,"id":906075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Camin, Federica","contributorId":243295,"corporation":false,"usgs":false,"family":"Camin","given":"Federica","email":"","affiliations":[{"id":48677,"text":"University of Treno, Italy","active":true,"usgs":false}],"preferred":false,"id":906076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jiguet, Frederic","contributorId":174482,"corporation":false,"usgs":false,"family":"Jiguet","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":906077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osvath, Gergely","contributorId":340071,"corporation":false,"usgs":false,"family":"Osvath","given":"Gergely","email":"","affiliations":[],"preferred":false,"id":906078,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":906079,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wunder, Michael B.","contributorId":65406,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":906080,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Powell, Rebecca L.","contributorId":340073,"corporation":false,"usgs":false,"family":"Powell","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":906081,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70253129,"text":"70253129 - 2024 - Metabolism regimes in regulated rivers of the Illinois River basin, USA","interactions":[],"lastModifiedDate":"2024-04-19T12:04:03.466242","indexId":"70253129","displayToPublicDate":"2024-02-15T07:00:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Metabolism regimes in regulated rivers of the Illinois River basin, USA","docAbstract":"Metabolism estimates organic carbon accumulation by primary productivity and removal by respiration. In rivers it is relevant to assessing trophic status and threats to river health such as hypoxia as well as greenhouse gas fluxes. We estimated metabolism in 17 rivers of the Illinois River basin (IRB) for a total of 15,176 days, or an average of 2.5 years per site. Daily estimates of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem productivity (NEP), and the air-water gas exchange rate constant (K600) are reported, along with ancillary data such as river temperature and saturated dissolved oxygen concentration, barometric pressure, and river depth and discharge. Workflows for metabolism estimation and quality assurance are described including a new method for estimating river depth. IRB rivers are dominantly heterotrophic; however, autotrophy was common in river locations coinciding with reported harmful algal blooms (HABs) events. Metabolism of these regulated Midwestern U.S. rivers can help assess the causes and consequences of excessive algal blooms in rivers and their role in river ecological health.
Chronic wasting disease (CWD) is a highly contagious, fatal neurodegenerative disease caused by infectious prions (PrPCWD) affecting wild and captive cervids. Although experimental feeding studies have demonstrated prions in feces of crows (Corvus brachyrhynchos), coyotes (Canis latrans), and cougars (Puma concolor), the role of scavengers and predators in CWD epidemiology remains poorly understood. Here we applied the real-time quaking-induced conversion (RT-QuIC) assay to detect PrPCWD in feces from cervid consumers, to advance surveillance approaches, which could be used to improve disease research and adaptive management of CWD. We assessed recovery and detection of PrPCWD by experimental spiking of PrPCWD into carnivore feces from 9 species sourced from CWD-free populations or captive facilities. We then applied this technique to detect PrPCWD from feces of predators and scavengers in free-ranging populations. Our results demonstrate that spiked PrPCWD is detectable from feces of free-ranging mammalian and avian carnivores using RT-QuIC. Results show that PrPCWD acquired in natural settings is detectable in feces from free-ranging carnivores, and that PrPCWD rates of detection in carnivore feces reflect relative prevalence estimates observed in the corresponding cervid populations. This study adapts an important diagnostic tool for CWD, allowing investigation of the epidemiology of CWD at the community-level.
Microplastics (MPs) are environmental contaminants that are present in all environments and can enter the human body, accumulate in various organs, and cause harm through the ingestion of food, inhalation, and dermal contact. The connection between bowel and liver disease and the interplay between gut, liver, and flora has been conceptualized as the “gut-liver axis”. Microplastics can alter the structure of microbial communities in the gut and the liver can also be a target for microplastic invasion. Numerous studies have found that when MPs impair human health, they not only promote dysbiosis of the gut microbiota and disruption of the gut barrier but also cause liver damage. For this reason, the gut-liver axis provides a new perspective in understanding this toxic response. The cross-talk between MPs and the gut-liver axis has attracted the attention of the scientific community, but knowledge about whether MPs cause gut-liver interactions through the gut-liver axis is still very limited, and the effect of MPs on liver injury is not well understood. MPs can directly induce microbiota disorders and gut barrier dysfunction. As a result, harmful bacteria and metabolites in the gut enter the blood through the weak intestinal barrier (portal vein channel along the gut-liver axis) and reach the liver, causing liver damage (inflammatory damage, metabolic disorders, oxidative stress, etc.). This review provides an integrated perspective of the gut-liver axis to help conceptualize the mechanisms by which MP exposure induces gut microbiota dysbiosis and hepatic injury and highlights the connection between MPs and the gut-liver axis. Therefore, from the perspective of the gut-liver axis, targeting intestinal flora is an important way to eliminate microplastic liver damage.
Critical to Atlantic sturgeon Acipenser oxyrinchus oxyrinchus recovery and monitoring is the ability to estimate abundance and identify age- and stock-specific threats to survival. As adult Atlantic sturgeon spend much of their lives broadly distributed in marine and estuarine environments, it is challenging to collect data needed to estimate these demographic parameters in the adult population. Alternatively, data collected from juveniles and subadults before emigration may be used to calculate indices of abundance and provide insights into recruitment dynamics and stage-specific survival. However, uncertainty about stock mixture during early life stages may limit the use of juvenile and subadult data for monitoring recovery. To better understand early life stage stock composition, we conducted a genetic mixed-stock analysis of over 500 juvenile and subadult Atlantic sturgeon captured in an overwintering area in the Hudson River, New York, USA, from 2017 to 2022. The majority of Atlantic sturgeon in our study were natal to the Hudson River population, regardless of sex, size, or age. As such, indices of relative abundance estimated from survey data are expected to primarily characterize the demographic trends of Hudson River juvenile and subadult Atlantic sturgeon. We also found a small proportion of individuals that were most likely to have originated from more distantly located rivers, highlighting the potential for long-distance migration in juvenile and subadult Atlantic sturgeon. Results of this study strengthen our understanding of juvenile and subadult Atlantic sturgeon habitat use in the Hudson River and improve our ability to use data from early age classes to monitor recovery and stage-specific survival.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01292","usgsCitation":"White, S.L., Pendleton, R., Higgs, A., Lubinski, B.A., Johnson, R.L., and Kazyak, D.C., 2024, Integrating genetic and demographic data to refine indices of abundance for Atlantic sturgeon in the Hudson River, New York: Endangered Species Research, v. 55, p. 115-126, https://doi.org/10.3354/esr01292.","productDescription":"12 p.","startPage":"115","endPage":"126","ipdsId":"IP-153937","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":440408,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01292","text":"Publisher Index Page"},{"id":426425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.70544053107169,\n 43.30955978079521\n ],\n [\n -74.70544053107169,\n 40.539236572975966\n ],\n [\n -73.1124229529466,\n 40.539236572975966\n ],\n [\n -73.1124229529466,\n 43.30955978079521\n ],\n [\n -74.70544053107169,\n 43.30955978079521\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pendleton, Richard M.","contributorId":273135,"corporation":false,"usgs":false,"family":"Pendleton","given":"Richard M.","affiliations":[{"id":56428,"text":"New York Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":896128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":896129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Robin L. 0000-0003-4314-3792 rjohnson1@usgs.gov","orcid":"https://orcid.org/0000-0003-4314-3792","contributorId":224717,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"rjohnson1@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896131,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896132,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70257421,"text":"70257421 - 2024 - Estimating internal transmitter and external tag retention by Walleye in the Laurentian Great Lakes over multiple years","interactions":[],"lastModifiedDate":"2024-08-21T11:45:55.194724","indexId":"70257421","displayToPublicDate":"2024-02-15T06:44:09","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimating internal transmitter and external tag retention by Walleye in the Laurentian Great Lakes over multiple years","docAbstract":"Both electronic tags (e.g., acoustic and radio transmitters) and conventional external tags are used to evaluate movement and population dynamics of fish. External tags are also sometimes used to facilitate the recovery of internal electronic tags or other instrumentation because healing can make it difficult to identify fish with internal tags based on appearance alone. With both tag types, tag shedding and failure of electronic tags can affect accuracy and precision of study results.
We used a decade (2011–2021) of recapture data for Walleye Sander vitreus tagged in the Laurentian Great Lakes, where fish were double- or triple-tagged with external tags (T-bar, loop, or internal anchor tags) and internal acoustic transmitters, to quantify external tag and internal transmitter shedding and transmitter failure rates.
In total, 1125 (33%) Walleye were recovered that had retained at least one external tag or internal transmitter. No confirmed cases of transmitter shedding were observed; 15 of 899 transmitters (2%) that were checked for functionality failed prior to the expected battery expiration. The retention of external T-bar tags 1 year after release differed depending on whether the tag was placed anterior or posterior to the secondary dorsal fin (anterior, fish length = 420 mm: 73% retention; anterior, fish length = 700 mm: 73%, posterior: 63%) but was <26% after 4 years for both tag positions and fish sizes. Internal anchor tags had an 88% 1-year retention probability and 81% 4-year retention probability. Loop tags had the highest 1-year retention (89%) but after 4 years retention (28–34% depending on agency) was comparable to that of T-bar tags.
Better understanding of tag retention characteristics through long-term tagging studies such as this can inform study design, be considered in model design, and ultimately improve inferences from mark–recapture studies.
","language":"English","publisher":"American Fisherie Society","doi":"10.1002/nafm.10973","usgsCitation":"Colborne, S., Faust, M., Brenden, T., Hayden, T., Robinson, J., MacDougall, T., Cook, H., Isermann, D.A., Dembkowski, D., Haffley, M., and Vandergoot, C., 2024, Estimating internal transmitter and external tag retention by Walleye in the Laurentian Great Lakes over multiple years: North American Journal of Fisheries Management, v. 44, no. 2, p. 377-393, https://doi.org/10.1002/nafm.10973.","productDescription":"17 p.","startPage":"377","endPage":"393","ipdsId":"IP-156407","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":440411,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10973","text":"Publisher Index Page"},{"id":432991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Colborne, S.F.","contributorId":342705,"corporation":false,"usgs":false,"family":"Colborne","given":"S.F.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":910293,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faust, M.D.","contributorId":342707,"corporation":false,"usgs":false,"family":"Faust","given":"M.D.","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":910294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brenden, T.O.","contributorId":342709,"corporation":false,"usgs":false,"family":"Brenden","given":"T.O.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":910295,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayden, T.A.","contributorId":342711,"corporation":false,"usgs":false,"family":"Hayden","given":"T.A.","email":"","affiliations":[{"id":81915,"text":"Michigan Department of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":910296,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, J.M.","contributorId":342712,"corporation":false,"usgs":false,"family":"Robinson","given":"J.M.","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910297,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"MacDougall, T.M.","contributorId":342713,"corporation":false,"usgs":false,"family":"MacDougall","given":"T.M.","email":"","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":910298,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cook, H.A.","contributorId":342714,"corporation":false,"usgs":false,"family":"Cook","given":"H.A.","email":"","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":910299,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910300,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dembkowski, D.J.","contributorId":275185,"corporation":false,"usgs":false,"family":"Dembkowski","given":"D.J.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":910301,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haffley, M.","contributorId":342715,"corporation":false,"usgs":false,"family":"Haffley","given":"M.","email":"","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":910302,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Vandergoot, C.S.","contributorId":342716,"corporation":false,"usgs":false,"family":"Vandergoot","given":"C.S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":910303,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70251694,"text":"70251694 - 2024 - Lava flow impacts on the built environment: Insights from a new global dataset","interactions":[],"lastModifiedDate":"2024-02-23T12:49:29.020022","indexId":"70251694","displayToPublicDate":"2024-02-15T06:43:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Lava flow impacts on the built environment: Insights from a new global dataset","docAbstract":"The recent destruction of thousands of homes by lava flows from La Palma volcano, Canary Islands, and Nyiragongo volcano, Democratic Republic of Congo, serves as a reminder of the devastating impact that lava flows can have on communities living in volcanically active regions. Damage to buildings and infrastructure can have widespread and long-lasting effects on rehabilitation and livelihoods. Our understanding of how lava flows interact with buildings is limited and based upon sparse empirical data. Often a binary impact is assumed (destroyed when in contact with the flow and intact when not in contact with the flow), although previous events have shown this to be an oversimplification. Empirical damage data collected after past events provide an evidence base from which to better understand lava flow impacts across a range of building types, environments, and eruption styles, as well as to explore the temporal and spatial trends in these impacts. However, information on lava flow impacts is scattered across literature, reports, and maps; no comprehensive dataset of lava flow impacts exists. In this study, we compile and standardise lava flow impact information from previously compiled data, eruption records, and published literature to create the first comprehensive global dataset of impacts on the built environment from lava flows. We found that since the first recorded event between 5494 yr B.P. and 5387 yr B.P., lava flows from at least 155 events have impacted buildings or infrastructure (e.g., roads, electricity pylons, ski-lifts), with most (47%, n = 73) recorded as located in Europe. Over the last century, there have been approximately seven lava flow impact events per decade (n = 71 total). This greatly expands on the past compilations of lava flow impact events. Since ca. 1800 CE, impacts have been consistently documented for less than 14% of recorded eruptions with lava flows globally; prior to 1800 CE, impacts were recorded much more variably (between 0 and 70% of lava flows in any 10-year time bin). The most destructive recorded events were the 1669 CE lava flows at Etna volcano, Italy, which destroyed up to 12 villages and part of the city of Catania, and the 2002 CE lava flows at Nyiragongo volcano, Democratic Republic of Congo, which destroyed up to 14,000 buildings. We found that few studies in the dataset report building typology, damage severity, or hazard intensity at the building-level scale, limiting our ability to assess past building-lava interactions. Future collection of building-level hazard and impact data, supplemented with non-English language records, can be used to inform models that forecast future impacts, support lava flow risk assessments, and develop potential mitigation measures.
The yǻyaguak (Mariana swiftlet; Aerodramus bartschi) is an endangered cave-nesting species historically found on Guam and the southern Mariana Islands, Micronesia. The population on Guam has been severely affected by the introduction of the brown treesnake Boiga irregularis. Population status assessments have, however, been challenging due to the limitations of traditional counting methods, which rely on visual observations at cave entrances and are prone to inaccuracies. To improve count accuracy, we estimated yǻyaguak population size and relative nesting activity using thermal and near-infrared videography. The population on Guam was surveyed at the island’s 3 known occupied caves (Mahlac, Maemong, and Fachi) between 2019 and 2023. Mahlac Cave harbored the largest colony, which ranged from 506 to 665 birds; Maemong Cave held 144 to 196 birds; and Fachi Cave, which is sometimes flooded, had 28 (in 2019) and 35 birds (in 2023). Our estimates indicate a slight decline in the yǻyaguak population over the study period. This study demonstrates the potential of thermal and near-infrared videography for improved monitoring of yǻyaguak colonies and nesting activity, which will contribute to our understanding of population dynamics and the effectiveness of management strategies such as brown treesnake control.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01296","usgsCitation":"Gorresen, P., Cryan, P.M., Parker, M., Alig, F., Nafus, M., and Paxton, E.H., 2024, Videographic monitoring at caves to estimate population size of the endangered yǻyaguak (Mariana swiftlet) on Guam: Endangered Species Research, v. 53, p. 139-149, https://doi.org/10.3354/esr01296.","productDescription":"11 p.","startPage":"139","endPage":"149","ipdsId":"IP-156746","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":440417,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01296","text":"Publisher Index Page"},{"id":435039,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90R04RD","text":"USGS data release","linkHelpText":"Guam, Mariana swiftlet counts, 2019-2023"},{"id":425785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.47289655036843,\n 13.086325221106193\n ],\n [\n 144.97495380496332,\n 13.086325221106193\n ],\n [\n 144.97495380496332,\n 13.71216375840433\n ],\n [\n 144.47289655036843,\n 13.71216375840433\n ],\n [\n 144.47289655036843,\n 13.086325221106193\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"53","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Gorresen, P. 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Those motions are described by the Euler vectors (Ωi0 for the ith microplate) given by McCaffrey for each microplate. McCaffrey noticed that the Euler poles for those microplates were aligned along the great circle that connects the geometric center of the microplate distribution with the PACI pole, the pole of rotation of the Pacific Plate (PA) about the North American Plate (NA). To explain that alignment, Thatcher et al. (2016,https://doi.org/10.1002/2015jb0126678.0) proposed replacing each Ωi0 by two, vertical‐axis rotations of the microplate, one ΩiR describing the trajectory (orbit) of its center of mass (CM) and the other ΩiS its rotation(spin) about that CM, where ΩiR + ΩiS = Ωi0. Moreover, they suggested that the orbital motion was being driven by drag from the rotating PA, which suggests that the ΩiR poles coincide with the PACI pole. Then rotation vectors ΩiR and ΩiS consistent with the given Ωi0 can be found for 17 of the microplates; the other 3 microplates are apparently affected by Basin‐and‐Range extension as well as PA relative motion. The long‐term motion of each of the 17 microplates then can be described as an orbital rotation about the PACI pole plus spin about the CM of the microplate. The closer the microplate CM is to the PA, the more nearly its orbital rotation rate approaches the rotation rate of the PA about the PACI pole.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB027856","usgsCitation":"Savage, J.C., 2024, Rotation of the microplates within the plate boundary in southwestern United States: JGR Solid Earth, v. 129, no. 2, e2023JB027856, 13 p., https://doi.org/10.1029/2023JB027856.","productDescription":"e2023JB027856, 13 p.","ipdsId":"IP-158459","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","otherGeospatial":"southwestern United 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\"}}]}","volume":"129","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Savage, James C. 0000-0002-5114-7673 jasavage@usgs.gov","orcid":"https://orcid.org/0000-0002-5114-7673","contributorId":2412,"corporation":false,"usgs":true,"family":"Savage","given":"James","email":"jasavage@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927728,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70251497,"text":"ofr20241004 - 2024 - Monitoring of wave, current, and sediment dynamics along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland","interactions":[],"lastModifiedDate":"2026-01-28T18:00:43.644809","indexId":"ofr20241004","displayToPublicDate":"2024-02-14T10:51:46","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1004","displayTitle":"Monitoring of Wave, Current, and Sediment Dynamics Along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland","title":"Monitoring of wave, current, and sediment dynamics along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland","docAbstract":"Living shorelines with salt marsh species, rock breakwaters, and sand nourishment were built along the coastal areas in the Glenn Martin National Wildlife Refuge, Maryland, in 2016 in response to Hurricane Sandy (2012). The Fog Point living shoreline at Glenn Martin National Wildlife Refuge was designed with the “headland - breakwater - embayment” pattern. Scientists from the U.S. Geological Survey, Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University studied wave, current, and sediment dynamics to assess the effectiveness of the Fog Point living shoreline structures in terms of wave attenuation and erosion reduction. Wave gages, current meters, sediment traps, sediment tiles, and lateral erosion pins were deployed along the Fog Point shoreline during February 10–14, 2020. Because of COVID-19 pandemic travel restrictions, sensors were not retrieved until August 25, 2021, which was 18 months after field deployment, resulting in tremendous loss or damage of sensors and sediment measurements.
Monitoring data indicated that wave heights were substantially reduced at locations behind the breakwater (headland) compared to the wave heights in the offshore location, but not at the location in the control area (the embayment). Current patterns and current velocities at the location behind the breakwater were complex and changed dramatically compared to the current patterns and current velocities offshore. Sediments were blocked by the breakwater most of the time except during periods of storms with wave heights larger than 0.9 meter, when waves overtopped the breakwater and brought sediments to the tidal flat and salt marshes behind the breakwater. Behind the breakwater, both sediment deposition and erosion were observed during the 18 months of monitoring. Continued low elevation marsh edge erosion from wave undercutting along the embayment was observed, especially at the existing wave-cut gullies.
Monitoring results indicate that the “breakwater + marsh planting” structure along the Fog Point shoreline has limited shoreline protection capacity. Marsh edge erosion behind the breakwater was likely caused by the limited sediment supply from marine sources for transport and delivery, as well as the effects of circulation and current velocity on the settling and deposition of suspended sediments from eroded marshes. Marsh edge erosion continued in the embayment or control area where no shoreline restoration structures were implemented. Long-term (decadal scale) monitoring and adaptive management of living shoreline structures could help to assess the effectiveness of wave attenuation for reducing shoreline erosion and enhancing vegetation growth for trapping sediments and the effectiveness of marsh surface elevation growth for keeping pace with sea level rise.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241004","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University","usgsCitation":"Wang, H., Chen, Q., Capurso, W.D., Niemoczynski, L.M., Wang, N., Zhu, L., Snedden, G.A., Whitbeck, M., Wilson, C.A., and Brownley, M., 2024, Monitoring of wave, current, and sediment dynamics along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland: U.S. Geological Survey Open-File Report 2024–1004, 32 p., https://doi.org/10.3133/ofr20241004.","productDescription":"Report: x, 32 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-153204","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499204,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116048.htm","linkFileType":{"id":5,"text":"html"}},{"id":425618,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TXZX5W","text":"USGS data release","linkHelpText":"Field observation of wind waves and current velocity (2020) along the Fog Point Living Shoreline, Maryland"},{"id":425617,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1004 XML"},{"id":425616,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1004 HTML"},{"id":425615,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1004/images"},{"id":425614,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.pdf","size":"5.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1004"},{"id":425613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1004/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Glenn Martin National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.16645677294429,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 38.13763711090462\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
A suite of slate samples collected along a 2 km transect crossing the Lishan fault in central Taiwan were evaluated to assess the role of ductile deformation in natural graphitization at lower greenschist facies metamorphic conditions. The process of natural aromatization, or graphitization, of an organic precursor is well established as a thermally driven process; however, experimental studies have shown that the energy provided by deformation can substantially reduce the activation energy required for graphitization. This study provides a natural example of deformation-induced graphitization. A strain gradient approaching the Lishan fault was established by scanning electron microscope imaging and X-ray diffraction analysis of phyllosilicates and quartz that showed an increase in the strength of slaty cleavage development via dissolution-precipitation processes. Thermal conditions were constrained to be near isothermal using calcite-dolomite geothermometry. Raman spectroscopic results from carbonaceous material, including D1-full width-at-half-maximum (FWHM), G-FWHM, Raman band separation (RBS), and a lesser-known vibrational mode B2g-FWHM, showed robust linear trends across the same sampling transect. However, the G-FWHM parameter showed a trend opposite of that expected from thermally driven graphitization. The Raman results are interpreted to reflect a strain-driven reduction in graphite crystallite size (decrease in G-FWHM) but improvement in structural ordering in individual coherent domains. A multiple linear regression with an R2 value of 0.92 predicts the graphite D1-FWHM values from the XRD-derived ratio of muscovite populations and muscovite microstrain, demonstrating the concomitant recrystallization of silicates and carbonaceous material across the strain gradient, despite the disparate processes accommodating the deformation. This study demonstrates the role of deformation in natural graphitization and provides a new perspective on the use of graphite as a geothermometer in strongly deformed greenschist facies rocks.
Climate change poses a pervasive threat to humans and wildlife by altering resource availability, changing co-occurrences, and directly or indirectly influencing human-wildlife interactions. For many wildlife agencies in North America, managing bears (Ursus spp.) and human-bear interactions is a priority, yet the direct and indirect effects of climate change are exacerbating management challenges. Understanding the underlying ecological drivers of bear responses to climate variability and change, and the implications for conflict, will be critical for maintaining human-bear coexistence in North America. We synthesized 120 articles that identified direct and indirect mechanisms by which climate variability and change affect brown bears (Ursus arctos) and American black bears (Ursus americanus) in North America. The literature focused on examining climate impacts on bear diet, body size, habitat selection, space use, activity, denning chronology, and population demographics and dynamics. Across these categories, we summarized the documented and projected bear responses and resulting implications for human-bear interactions. Climate-driven changes in natural food availability were frequently implicated in influencing bear behavior and demography, and creating conditions under which interactions with humans are likely to increase. Bears in North America may face increased challenges as habitat and natural food availability continue to be altered by climate change. Our review provides a foundation upon which to identify climate drivers of bear ecology, conditions conducive to human-bear interactions, and adaptive management strategies. Given substantial evidence of climate impacts to bears, incorporating climate considerations into bear management can help managers strategically allocate resources and promote human-bear coexistence.
Declining Arctic sea ice is increasing polar bear land use. Polar bears on land are thought to minimize activity to conserve energy. Here, we measure the daily energy expenditure (DEE), diet, behavior, movement, and body composition changes of 20 different polar bears on land over 19–23 days from August to September (2019–2022) in Manitoba, Canada. Polar bears on land exhibited a 5.2-fold range in DEE and 19-fold range in activity, from hibernation-like DEEs to levels approaching active bears on the sea ice, including three individuals that made energetically demanding swims totaling 54–175 km. Bears consumed berries, vegetation, birds, bones, antlers, seal, and beluga. Beyond compensating for elevated DEE, there was little benefit from terrestrial foraging toward prolonging the predicted time to starvation, as 19 of 20 bears lost mass (0.4–1.7 kg•day−1). Although polar bears on land exhibit remarkable behavioral plasticity, our findings reinforce the risk of starvation, particularly in subadults, with forecasted increases in the onshore period.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-44682-1","usgsCitation":"Pagano, A.M., Rode, K.D., Lunn, N.J., McGeachy, D., Atkinson, S.N., Farley, S.D., Erlenbach, J., and Robbins, C.T., 2024, Polar bear energetic and behavioral strategies on land with implications for surviving the ice-free period: Nature Communications, v. 15, 947, 15 p., https://doi.org/10.1038/s41467-023-44682-1.","productDescription":"947, 15 p.","ipdsId":"IP-155899","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":440425,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-44682-1","text":"Publisher Index Page"},{"id":425573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Manitoba","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.8168742320063,\n 60.38318456710692\n ],\n [\n -95.8168742320063,\n 56.61419709748603\n ],\n [\n -88.99656081599208,\n 56.61419709748603\n ],\n [\n -88.99656081599208,\n 60.38318456710692\n ],\n [\n -95.8168742320063,\n 60.38318456710692\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2024-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":894594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":894595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lunn, Nicholas J. 0000-0003-0189-5494","orcid":"https://orcid.org/0000-0003-0189-5494","contributorId":312476,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":894596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGeachy, David 0000-0003-1958-5363","orcid":"https://orcid.org/0000-0003-1958-5363","contributorId":332301,"corporation":false,"usgs":false,"family":"McGeachy","given":"David","email":"","affiliations":[],"preferred":false,"id":894597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":894598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farley, Sean D.","contributorId":27642,"corporation":false,"usgs":false,"family":"Farley","given":"Sean","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":894599,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Erlenbach, Joy A.","contributorId":334042,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy A.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":894600,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robbins, Charles T.","contributorId":32436,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":894601,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70253922,"text":"70253922 - 2024 - Travertine records climate-induced transformations of the Yellowstone hydrothermal system from the late Pleistocene to the present","interactions":[],"lastModifiedDate":"2024-09-11T16:12:56.404239","indexId":"70253922","displayToPublicDate":"2024-02-13T10:15:13","publicationYear":"2024","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":"Travertine records climate-induced transformations of the Yellowstone hydrothermal system from the late Pleistocene to the present","docAbstract":"Chemical changes in hot springs, as recorded by thermal waters and their deposits, provide a window into the evolution of the postglacial hydrothermal system of the Yellowstone Plateau Volcanic Field. Today, most hydrothermal travertine forms to the north and south of the ca. 631 ka Yellowstone caldera where groundwater flow through subsurface sedimentary rocks leads to calcite saturation at hot springs. In contrast, low-Ca rhyolites dominate the subsurface within the Yellowstone caldera, resulting in thermal waters that rarely deposit travertine. We investigated the timing and origin of five small travertine deposits in the Upper and Lower Geyser Basins to understand the conditions that allowed for travertine deposition. New 230Th-U dating, oxygen (δ18O), carbon (δ13C), and strontium (87Sr/86Sr) isotopic ratios, and elemental concentrations indicate that travertine deposits within the Yellowstone caldera formed during three main episodes that correspond broadly with known periods of wet climate: 13.9−13.6 ka, 12.2−9.5 ka, and 5.2−2.9 ka. Travertine deposition occurred in response to the influx of large volumes of cold meteoric water, which increased the rate of chemical weathering of surficial sediments and recharge into the hydrothermal system. The small volume of intracaldera travertine does not support a massive postglacial surge of CO2 within the Yellowstone caldera, nor was magmatic CO2 the catalyst for postglacial travertine deposition.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37317.1","usgsCitation":"Harrison, L.N., Hurwitz, S., Paces, J., Whitlock, C., Peek, S., and Licciardi, J., 2024, Travertine records climate-induced transformations of the Yellowstone hydrothermal system from the late Pleistocene to the present: GSA Bulletin, v. 136, no. 9-10, p. 3605-3618, https://doi.org/10.1130/B37317.1.","productDescription":"14 p.","startPage":"3605","endPage":"3618","ipdsId":"IP-149989","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":440430,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/gsab.s.24891144","text":"External Repository"},{"id":428360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Terrace Spring","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.854,\n 44.6583\n ],\n [\n -110.854,\n 44.641667\n ],\n [\n -110.841667,\n 44.641667\n ],\n [\n -110.841667,\n 44.6583\n ],\n [\n -110.854,\n 44.6583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2024-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Lauren N. 0000-0002-6621-5958","orcid":"https://orcid.org/0000-0002-6621-5958","contributorId":336192,"corporation":false,"usgs":false,"family":"Harrison","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":900112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitlock, Cathy","contributorId":79745,"corporation":false,"usgs":false,"family":"Whitlock","given":"Cathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":900113,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900114,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Licciardi, Joseph","contributorId":229595,"corporation":false,"usgs":false,"family":"Licciardi","given":"Joseph","affiliations":[{"id":41689,"text":"U. New Hampshire","active":true,"usgs":false}],"preferred":false,"id":900115,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70253907,"text":"70253907 - 2024 - Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises","interactions":[],"lastModifiedDate":"2024-05-03T15:09:34.873647","indexId":"70253907","displayToPublicDate":"2024-02-13T10:03:53","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises","docAbstract":"Migratory, long-lived animals are an important focus for life-history theory because they manifest extreme trade-offs in life-history traits: delayed maturity, low fecundity, variable recruitment rates, long generation times, and vital rates that respond to variation across environments. Galapagos tortoises are an iconic example: they are long-lived, migrate seasonally, face multiple anthropogenic threats, and have cryptic early life-history stages for which vital rates are unknown. From 2012 to 2021, we studied the reproductive ecology of two species of Galapagos tortoises (Chelonoidis porteri and C. donfaustoi) along elevation gradients that coincided with substantial changes in climate and vegetation productivity. Specifically, we (1) measured the body and reproductive condition of 166 adult females, (2) tracked the movements of 33 adult females using global positioning system telemetry, and monitored their body condition seasonally, (3) recorded nest temperatures, clutch characteristics, and egg survival from 107 nests, and (4) used radiotelemetry to monitor growth, survival, and movements of 104 hatchlings. We also monitored temperature and rainfall from field sites, and remotely sensed primary productivity along the elevation gradient. Our study showed that environmental variability, mediated by elevation, influenced vital rates of giant tortoises, specifically egg production by adult females and juvenile recruitment. Adult females were either elevational migrants or year-round lowland residents. Migrants had higher body condition than residents, and body condition was positively correlated with the probability of being gravid. Nests occurred in the hottest, driest parts of the tortoise's range, between 6 and 165 m elevation. Clutch size increased with elevation, whereas egg survival decreased. Hatchling survival and growth were highest at intermediate elevations. Hatchlings dispersed rapidly to 100–750 m from their nests before becoming sedentary (ranging over <0.2 ha). Predicted future climates may impact the relationships between elevation and vital rates of Galapagos tortoises and other species living across elevation gradients. Resilience will be maximized by ensuring the connectivity of foraging and reproductive areas within the current and possible future elevational ranges of these species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1599","usgsCitation":"Blake, S., Cabrera, F., Cruz, S., Ellis-Soto, D., Yackulic, C., Bastille-Rousseau, G., Wikelski, M., Kuemmeth, F., Gibbs, J.P., and Deem, S.L., 2024, Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises: Ecological Monographs, v. 94, no. 2, e1599, 23 p., https://doi.org/10.1002/ecm.1599.","productDescription":"e1599, 23 p.","ipdsId":"IP-081238","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":440433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1599","text":"Publisher Index Page"},{"id":428358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Galapagos Islands, Santa Cruz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.56105950601605,\n -0.5968399941543368\n ],\n [\n -90.56105950601605,\n -0.7783452498541266\n ],\n [\n -90.1639880007019,\n -0.7783452498541266\n ],\n [\n -90.1639880007019,\n -0.5968399941543368\n ],\n [\n -90.56105950601605,\n -0.5968399941543368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"94","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Blake, Stephen","contributorId":65339,"corporation":false,"usgs":false,"family":"Blake","given":"Stephen","email":"","affiliations":[{"id":30787,"text":"Saint Louis University","active":true,"usgs":false},{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":900065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cabrera, Fredy","contributorId":177205,"corporation":false,"usgs":false,"family":"Cabrera","given":"Fredy","email":"","affiliations":[],"preferred":false,"id":900066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cruz, Sebastian","contributorId":336162,"corporation":false,"usgs":false,"family":"Cruz","given":"Sebastian","affiliations":[{"id":12472,"text":"Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":900067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis-Soto, Diego","contributorId":246177,"corporation":false,"usgs":false,"family":"Ellis-Soto","given":"Diego","email":"","affiliations":[],"preferred":false,"id":900068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":900069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bastille-Rousseau, Guillaume 0000-0001-6799-639X","orcid":"https://orcid.org/0000-0001-6799-639X","contributorId":190877,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","email":"","affiliations":[{"id":40724,"text":"Cooperative Wildlife Research Laboratory and Department of Forestry, Southern Illinois University, 251 Life Science II, Mail Code 6504, Carbondale, Illinois 62901 USA","active":true,"usgs":false}],"preferred":false,"id":900070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wikelski, Martin","contributorId":205674,"corporation":false,"usgs":false,"family":"Wikelski","given":"Martin","email":"","affiliations":[{"id":37137,"text":"Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology","active":true,"usgs":false}],"preferred":false,"id":900071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuemmeth, Franz","contributorId":336164,"corporation":false,"usgs":false,"family":"Kuemmeth","given":"Franz","email":"","affiliations":[{"id":80765,"text":"E-obs GmbH, Grünwald, Germany","active":true,"usgs":false}],"preferred":false,"id":900072,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibbs, James P.","contributorId":102418,"corporation":false,"usgs":false,"family":"Gibbs","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":900073,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deem, Sharon L.","contributorId":139277,"corporation":false,"usgs":false,"family":"Deem","given":"Sharon","email":"","middleInitial":"L.","affiliations":[{"id":12719,"text":"Whitney R. Harris, World Ecology Center, Uni. of Missouri St. Louis","active":true,"usgs":false}],"preferred":false,"id":900074,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70251780,"text":"70251780 - 2024 - Thermal traits of anurans database for the southeastern United States (TRAD): A database of thermal trait values for 40 anuran species","interactions":[],"lastModifiedDate":"2024-02-28T15:14:44.513167","indexId":"70251780","displayToPublicDate":"2024-02-13T09:09:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9341,"text":"Ichthyology & Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Thermal traits of anurans database for the southeastern United States (TRAD): A database of thermal trait values for 40 anuran species","docAbstract":"Thermal traits, or how an animal responds to changing temperatures, impacts species persistence and thus biodiversity. Trait databases, as repositories of consolidated, measured organismal attributes, allow researchers to link study species with specific trait values, enabling comparisons within and among species. Trait databases also help lay the groundwork to build mechanistic linkages between organisms and the environment. However, missing or hidden physiological trait data preclude building mechanistic estimates of climate change vulnerability for many species. Thus, physiologically focused trait databases present an opportunity to consolidate data and enable species-specific or multispecies, mechanistic evaluations of climate change vulnerability. Here, we present TRAD: thermal traits of anurans database for the southeastern United States, a database of thermal trait values related to physiological thermoregulation (critical thermal minima and maxima, preferred temperature), behavioral thermoregulation (activity period, retreat emergence temperature, basking temperature, minimum and maximum foraging temperatures), and body mass for 37 anuran species found within the southeastern United States. In total, TRAD contains 858 reported trait values for 37 of 40 species found in the region from 267 peer-reviewed papers, dissertations, or theses and is easily linked with trait data available in ATraiU, an ecological trait database for anurans in the United States. TRAD contains trait values for multiple life stages and a summarization of interspecific adult trait values. Availability of trait data varied widely among traits and species. Estimates of mass were the most common trait values reported, with values available for 32 species. Behavioral trait values comprised 23% of our database, with activity period available for 34 species. We found the most trait values for Cope's Gray Treefrog (Dryophytes chrysoscelis), with at least one trait value for eight traits in the database. Conversely, species in the genus Pseudacris generally had the fewest trait values available. Species with the largest geographic range sizes also had the greatest coverage of data across traits (rho 5 0.75, P , 0.001). TRAD can aid studies of anuran response to changing temperatures, physiological niche space and limitations, and potential drivers of anuran geographic range limits, influencing our understanding of other ecological and evolutionary patterns and processes and enabling multispecies comparisons of potential risk and resilience in the face of climate change.
","language":"English","publisher":"American society of Ichthyologists and Herpetologists","doi":"10.1643/h2022102","usgsCitation":"DuBose, T.P., Catalan, V., Moore, C.E., Farallo, V.R., Benson, A., Dade, J., Hopkins, W., and Mims, M.C., 2024, Thermal traits of anurans database for the southeastern United States (TRAD): A database of thermal trait values for 40 anuran species: Ichthyology & Herpetology, v. 112, no. 1, p. 21-30, https://doi.org/10.1643/h2022102.","productDescription":"10 p.","startPage":"21","endPage":"30","ipdsId":"IP-146981","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":467032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1643/h2022102","text":"External Repository"},{"id":426056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southeastern United 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University","active":true,"usgs":false}],"preferred":false,"id":895534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Catalan, Victorjose","contributorId":305547,"corporation":false,"usgs":false,"family":"Catalan","given":"Victorjose","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":895535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Chloe E.","contributorId":292583,"corporation":false,"usgs":false,"family":"Moore","given":"Chloe","email":"","middleInitial":"E.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":895536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farallo, Vincent R. 0000-0001-6571-2015","orcid":"https://orcid.org/0000-0001-6571-2015","contributorId":305548,"corporation":false,"usgs":false,"family":"Farallo","given":"Vincent","email":"","middleInitial":"R.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":895537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":202078,"corporation":false,"usgs":true,"family":"Benson","given":"Abigail","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":895538,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dade, Jessica","contributorId":305550,"corporation":false,"usgs":false,"family":"Dade","given":"Jessica","email":"","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":895539,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hopkins, William A.","contributorId":201553,"corporation":false,"usgs":false,"family":"Hopkins","given":"William A.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":895540,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mims, Meryl C. 0000-0003-0570-988X","orcid":"https://orcid.org/0000-0003-0570-988X","contributorId":209951,"corporation":false,"usgs":false,"family":"Mims","given":"Meryl","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":895541,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70251288,"text":"sir20235143 - 2024 - Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019","interactions":[],"lastModifiedDate":"2026-01-30T19:56:30.550181","indexId":"sir20235143","displayToPublicDate":"2024-02-13T07:37:40","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5143","displayTitle":"Water-Level and Recoverable Water in Storage Changes, High Plains Aquifer, Predevelopment to 2019 and 2017 to 2019","title":"Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019","docAbstract":"The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States: Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial groundwater irrigation (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2019 and from 2017 to 2019.
Water-level changes from predevelopment to 2019, by well, ranged from a rise of 86 feet to a decline of 265 feet; the range for 99 percent of the wells was from a rise of 42 feet to a decline of 203 feet. Water-level changes from 2017 to 2019, by well, ranged from a rise of 34 feet to a decline of 27 feet; the range for 99 percent of the wells was from a rise of 11 feet to a decline of 11 feet. The area-weighted, average water-level changes in the aquifer were an overall decline of 16.5 feet from predevelopment to 2019 and a rise of 0.1 foot from 2017 to 2019. Recoverable water in storage in the aquifer in 2019 was about 2.91 billion acre-feet, which was a decline of about 286.4 million acre-feet since predevelopment and a rise of 1.6 million acre-feet from 2017 to 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235143","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"McGuire, V.L., and Strauch, K.R., 2024, Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019: U.S. Geological Survey Scientific Investigations Report 2023–5143, 15 p., https://doi.org/10.3133/sir20235143.","productDescription":"Report: vi, 15 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-117286","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":425299,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5143/images/"},{"id":425296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5143/coverthb.jpg"},{"id":425298,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5143/sir20235143.XML"},{"id":425300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WPP01S","text":"USGS data release","linkHelpText":"Data from maps of water-level changes in the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, predevelopment (about 1950) to 2019 and 2017 to 2019"},{"id":425301,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235143/full"},{"id":499405,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116026.htm","linkFileType":{"id":5,"text":"html"}},{"id":425297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5143/sir20235143.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5143"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 44\n ],\n [\n -106,\n 32\n ],\n [\n -96,\n 32\n ],\n [\n -96,\n 44\n ],\n [\n -106,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Fluvial silicon (Si) plays a critical role in controlling primary production, water quality, and carbon sequestration through supporting freshwater and marine diatom communities. Geological, biogeochemical, and hydrological processes, as well as climate and land use, dictate the amount of Si exported by streams. Understanding Si regimes—the seasonal patterns of Si concentrations—can help identify processes driving Si export. We analyzed Si concentrations from over 200 stream sites across the Northern Hemisphere to establish distinct Si regimes and evaluated how often sites moved among regimes over their period of record. We observed five distinct regimes across diverse stream sites, with nearly 60% of sites exhibiting multiple regime types over time. Our results indicate greater spatial and interannual variability in Si seasonality than previously recognized and highlight the need to characterize the watershed and climate variables that affect Si cycling across diverse ecosystems.
We develop Attenuated ProPagation of Local Earthquake Shaking (APPLES), a new configuration for the United States West Coast version of the Propagation of Local Undamped Motion (PLUM) earthquake early warning (EEW) algorithm that incorporates attenuation into its ground-motion prediction procedures. Under APPLES, instead of using a fixed radius to forward-predict observed peak ground shaking to the area surrounding a seismic station, the forward-predicted intensity at a location depends on the distance from the station using an intensity prediction relationship. We conduct conceptual tests of maximum intensity distribution predictions in APPLES and PLUM using a catalog of ShakeMaps to confirm that the attenuation relationship in APPLES is appropriately modeling shaking distributions for West Coast earthquakes. Then, we run APPLES and PLUM in simulated real-time tests to determine warning time performance. Finally, we compare real-time alert behavior during the 2022 M6.4 Ferndale, California, earthquake and other recent events. We find that APPLES presents two potential improvements to PLUM by reducing over-alerting during smaller magnitude earthquakes and by increasing warning times in some locations during larger earthquakes. APPLES can produce missed and late alerts in locations that experience shaking intensities close to the level used to issue alerts, so preferred alerting strategies with APPLES would use alert thresholds that are lower than the intensities targeted for EEW alerts. We find alerts using APPLES are also similar to those for the source-based approaches currently used in the ShakeAlert EEW system, which will make APPLES easier to integrate into the system.
Large dam removal can trigger changes to physical and biological processes that influence vegetation dynamics in former reservoirs, along river corridors downstream of former dams, and at a river’s terminus in deltas and estuaries. We present the first comprehensive review of vegetation response to major fluvial disturbance caused by the world’s largest dam removal. After being in place for nearly a century, two large dams were removed along the Elwha River, Washington, USA, between 2011 and 2014. The exposure, erosion, transport, and deposition of large volumes of sediment and large wood that were impounded behind the dams created new fluvial surfaces where plant colonization and growth have occurred. In the former reservoirs, dam removal exposed ~290 ha of unvegetated sediment distributed on three main landforms: valley walls, high terraces, and dynamic floodplains. In addition to natural revegetation in the former reservoirs, weed control and seeding and planting of desirable plants influenced vegetation trajectories. In early years following dam removal, ~20.5 Mt of trapped sediment were eroded from the former reservoirs and transported downstream. This sediment pulse, in combination with transport of large wood, led to channel widening, an increase in gravel bars, and floodplain deposition. The primary vegetation responses along the river corridor were a reduction in vegetated area associated with channel widening, plant establishment on new gravel bars, increased hydrochory, and altered plant community composition on gravel bars and floodplains. Plant species diversity increased in some river segments. In the delta, sediment deposition led to the creation of ~26.8 ha of new land surfaces and altered the distribution and dynamics of intertidal water bodies. Vegetation colonized ~16.4 ha of new surfaces: mixed pioneer vegetation colonized supratidal beach, river bars, and river mouth bars, and emergent marsh vegetation colonized intertidal aquatic habitats. In addition to the sediment-dominated processes that have created opportunities for plant colonization and growth, biological processes such as restored hydrochory and anadromous fish passage with associated delivery of marine-derived nutrients may influence vegetation dynamics over time. Rapid changes to landforms and vegetation growth were related to the large sediment pulse in the early years following dam removal, and the rate of change is expected to attenuate as the system adjusts to natural flow and sediment regimes.