We present a practical approach to intercompare a range of candidate digital elevation models (DEMs) based on predefined criteria and a statistically sound ranking approach. The presented approach integrates the randomized complete block design (RCBD) into a novel framework for DEM comparison. The method presented provides a flexible, statistically sound, and customizable tool for evaluating the quality of any raster—in this case, a DEM—by means of a ranking approach, which takes into account a confidence level and can use both quantitative and qualitative criteria. The users can design their own criteria for the quality evaluation in relation to their specific needs. The application of the RCBD method to rank six 1′′ global DEMs, considering a wide set of study sites, covering different morphological and land cover settings, highlights the potentialities of the approach. We used a suite of criteria relating to the differences in the elevation, slope, and roughness distributions compared to reference DEMs aggregated from 1- to 5-m light detection and ranging (LiDAR)-derived DEMs. Results confirmed the significant superiority of Copernicus DEM (CopDEM) 1′′ and its derivative forests and buildings removed DEM (FABDEM) as the overall best 1′′ global DEMs. They are slightly better than Advanced Land Observing Satellite (ALOS) and clearly outperform NASADEM and SRTM, which are, in turn, much better than advanced spaceborne thermal emission and reflection radiometer (ASTER).
The hydrological effects of climate change are documented in many regions; however, climate-driven impacts to the source and transport of river nutrients remain poorly understood. Understanding the factors controlling nutrient dynamics across river systems is critical to preserve ecosystem function yet challenging given the complexity of landscape and climate interactions. Here, we harness a large regional dataset of nitrate (NO3–) yield, concentration, and isotopic composition (δ15N and δ18O) to evaluate the strength of hydroclimate and landscape variables in controlling the seasonal source and transport of NO3–. We show that hydroclimate strongly influenced the seasonality of river NO3–, producing distinct, source-dependent NO3– regimes across rivers from two mountain ranges. Riverine responses to hydroclimate were also constrained by watershed-scale topographic features, demonstrating that while regional climate strongly influences the timing of river NO3– transport, watershed topography plays a distinct role in mediating the sensitivity of river NO3– dynamics to future change.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s43247-024-01235-8","usgsCitation":"Elmstrom, E., Holtgrieve, G., Scheuerell, M.D., Andrew J. Schauer, and Leazer, K., 2024, Climate and landform interact to control the source and transport of nitrate in Pacific Northwest rivers: Communications Earth and Environment, v. 5, 90, 13 p., https://doi.org/10.1038/s43247-024-01235-8.","productDescription":"90, 13 p.","ipdsId":"IP-149744","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01235-8","text":"Publisher Index Page"},{"id":486521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Washington","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.87855871265536,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.69978264689745\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.3245432375632,\n 49.988705305763744\n ],\n [\n -122.3245432375632,\n 45.99397202023496\n ],\n [\n -119.56144227480337,\n 45.99397202023496\n ],\n [\n -119.56144227480337,\n 49.988705305763744\n ],\n [\n -122.3245432375632,\n 49.988705305763744\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Elmstrom, Elizabeth J.","contributorId":355859,"corporation":false,"usgs":false,"family":"Elmstrom","given":"Elizabeth J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtgrieve, Gordon W.","contributorId":355860,"corporation":false,"usgs":false,"family":"Holtgrieve","given":"Gordon W.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrew J. Schauer","contributorId":355861,"corporation":false,"usgs":false,"family":"Andrew J. Schauer","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leazer, Karrin","contributorId":355862,"corporation":false,"usgs":false,"family":"Leazer","given":"Karrin","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":938287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261843,"text":"70261843 - 2024 - GRACE and GRACE Follow-On gravity observations of intermediate-depth earthquakes contrasted with those of shallow events","interactions":[],"lastModifiedDate":"2024-12-30T17:18:50.481926","indexId":"70261843","displayToPublicDate":"2024-02-19T09:08:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"GRACE and GRACE Follow-On gravity observations of intermediate-depth earthquakes contrasted with those of shallow events","docAbstract":"Earthquakes involve mass redistribution within the solid Earth and the ocean, and as a result, perturb the Earth's gravitational field. For most of the shallow (<60 km) earthquakes with Mw > 8.0, the GRACE satellite gravity measurements suggest considerable volumetric disturbance of rocks. At a spatial scale of hundreds of km, the effect of volumetric change exceeds gravity change by vertical deformation; for example, negative gravity anomalies associated with volumetric expansion are characteristic patterns after shallow thrust events. In this study, however, we report contrasting observations of gravity change from two intermediate-depth (100–150 km) earthquakes of 2016 & 2017 Mw 8.0 (two combined) Papua New Guinea thrust faulting events and 2019 Mw 8.0 Peru normal faulting and highlight the importance of compressibility in earthquake deformation. The combined 2016/17 thrust events resulted in a positive gravity anomaly of 5–6 microGal around the epicenter, while the 2019 normal faulting produced a negative gravity anomaly of 3–4 microGal. Our modeling found that these gravity changes are manifestation of vertical deformation with limited volumetric change, distinct from gravity changes after the shallow earthquakes. The stronger resistance of rocks to volume change at intermediate-depth results in largely incompressible deformation and thus in a gravity change dominated by vertical deformation. In addition, malleable rocks under high pressure and temperature at depth facilitated substantial afterslip and/or fast viscoelastic relaxation causing additional vertical deformation and gravity change equivalent to the coseismic change. For the Papua New Guinea events, this means that postseismic relaxation enhanced coseismic uplift and relative sea level decrease.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB028362","usgsCitation":"Han, S., Sauber, J., Broerse, T., Pollitz, F., Okal, E., Jeon, T., Seo, K., and Stanaway, R., 2024, GRACE and GRACE Follow-On gravity observations of intermediate-depth earthquakes contrasted with those of shallow events: Journal of Geophysical Research: Solid Earth, v. 129, e2023JB028362, 18 p., https://doi.org/10.1029/2023JB028362.","productDescription":"e2023JB028362, 18 p.","ipdsId":"IP-152518","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":467030,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jb028362","text":"Publisher Index Page"},{"id":465528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","noUsgsAuthors":false,"publicationDate":"2024-02-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Han, Shin-Chan","contributorId":187537,"corporation":false,"usgs":false,"family":"Han","given":"Shin-Chan","affiliations":[],"preferred":false,"id":922002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauber, Jeanne","contributorId":243991,"corporation":false,"usgs":false,"family":"Sauber","given":"Jeanne","affiliations":[{"id":40052,"text":"NASA Goddard","active":true,"usgs":false}],"preferred":false,"id":922003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Broerse, Taco","contributorId":347568,"corporation":false,"usgs":false,"family":"Broerse","given":"Taco","affiliations":[{"id":83193,"text":"Utrecht University, Utrecht, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":922004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":922005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Okal, Emile","contributorId":347569,"corporation":false,"usgs":false,"family":"Okal","given":"Emile","affiliations":[{"id":83194,"text":"Northwestern University, Evanston, IL","active":true,"usgs":false}],"preferred":false,"id":922006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jeon, Taehwan","contributorId":347570,"corporation":false,"usgs":false,"family":"Jeon","given":"Taehwan","affiliations":[{"id":83195,"text":"Seoul National University, Seoul, Korea","active":true,"usgs":false}],"preferred":false,"id":922007,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seo, Ki-Weon","contributorId":347571,"corporation":false,"usgs":false,"family":"Seo","given":"Ki-Weon","affiliations":[{"id":83195,"text":"Seoul National University, Seoul, Korea","active":true,"usgs":false}],"preferred":false,"id":922008,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stanaway, Richard","contributorId":347586,"corporation":false,"usgs":false,"family":"Stanaway","given":"Richard","affiliations":[],"preferred":false,"id":922022,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252515,"text":"70252515 - 2024 - PFAS river export analysis highlights the urgent need for catchment-scale mass loading data","interactions":[],"lastModifiedDate":"2024-03-27T12:12:29.714027","indexId":"70252515","displayToPublicDate":"2024-02-19T07:11:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"PFAS river export analysis highlights the urgent need for catchment-scale mass loading data","docAbstract":"Source apportionment of per- and polyfluoroalkyl substances (PFAS) requires an understanding of the mass loading of these compounds in river basins. However, there is a lack of temporally variable and catchment-scale mass loading data, meaning identification and prioritization of sources of PFAS to rivers for management interventions can be difficult. Here, we analyze PFAS concentrations and loads in the River Mersey to provide the first temporally robust estimates of PFAS export for a European river system and the first estimates of the contribution of wastewater treatment works (WwTWs) to total river PFAS export. We estimate an annual PFAS export of 68.1 kg for the River Mersey and report that the yield of perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in the catchment is among the highest recorded globally. Analysis of river and WwTW loads indicates approximately one-third of PFOA emitted from WwTWs is potentially stored in the catchment and approximately half of PFOS transported by the River Mersey may not originate from WwTWs. As governments move toward regulation of PFAS in WwTW effluents, our findings highlight the complexity of PFAS source apportionment and the need for catchment-scale mass loading data. This study indicates that strategies for reducing PFAS loading that focus solely on WwTW effluents may not achieve river water quality targets.
Water production from petroleum (oil and natural gas) wells is a topic of increasing environmental and economic importance, yet quantification efforts have been limited to date, and patterns between and within petroleum plays are largely unscrutinized. Additionally, classification of reservoirs as “unconventional” (also known as “continuous”) carries scientific and regulatory importance, but in some cases the distinction from \"conventional\" wells is unclear. Using water, oil, and gas production data, we calculated a set of quantitative metrics that elucidate trends in the water-to-petroleum ratio over the life of each producing well. The percent growth of the water-to-petroleum ratio quantifies the degree to which a well “waters out” over time; values calculated for 153,900 wells in 18 oil and gas plays show generally much higher values for conventional wells than for continuous/unconventional wells. Analysis of the percent growth along with the slope and median metrics reveals greater variation between conventional plays and between continuous (unconventional) plays than previously recognized. Further, an example from the Bakken Formation in the Williston Basin, USA, illustrates that, within a single play, the metrics provide insight into spatial variation of water production trends, as influenced by geology and reservoir characteristics. By quantifying the variability of water production trends within individual plays and between plays, including differences between conventional and continuous (unconventional) plays, these results provide a more nuanced view of water production from oil and gas wells than has previously been possible and they illustrate the degree to which water management considerations vary spatially and temporally.
The Mid-Piacenzian Warm Period (MPWP; 3.0–3.3 Ma), a warm geological period about three million years ago, has been deemed as a good past analog for understanding the current and future climate change. Based on 12 climate model outputs from Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), we investigate tropical atmospheric circulation (TAC) changes under the warm MPWP and associated underlying mechanisms by diagnosing both atmospheric static stability and diabatic processes. Our findings underscore the advantage of analyzing atmospheric diabatic processes in elucidating seasonal variations of TAC compared to static stability assessments. Specifically, by diagnosing alterations in diabatic processes, we achieve a quantitative understanding and explanation the following TAC changes (incl. Strength and edge) during the MPWP: the weakened (annual, DJF, JJA) Northern Hemisphere and (DJF) Southern Hemisphere Hadley circulation (HC), reduced (annual, DJF) Pacific Walker circulation (PWC) and enhanced (annual, JJA) Southern Hemisphere HC and (JJA) PWC, and westward shifted (annual, DJF, JJA) PWC. We further addressed that the increasing bulk subtropical static stability and/or decreasing vertical shear of subtropical zonal wind - two crucial control factors for changes in subtropical baroclinicity - may promote HC widening, and vice versa. Consequently, our study of spatial diabatic heating and cooling, corresponding to upward and downward motions within the TAC, respectively, provides a new perspective for understanding the processes controlling seasonal TAC changes in response to surface warming.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2024.01.001","usgsCitation":"Zhang, K., Sun, Y., Zhang, X., Stepanek, C., Feng, R., Hill, D., Lohmann, G., Dolan, A.M., Haywood, A.M., Abe-Ouchi, A., Otto-Bliesner, B., Contoux, C., Chandan, D., Ramstein, G., Dowsett, H.J., Tindall, J.C., Baatsen, M., Tan, N., Peltier, W.R., Liu, Q., Chan, W., Wang, X., and Zhang, X., 2024, Revisiting the physical processes controlling the tropical atmospheric circulation changes during the Mid-Piacenzian Warm Period: Quaternary International, v. 682, p. 46-59, https://doi.org/10.1016/j.quaint.2024.01.001.","productDescription":"14 p.","startPage":"46","endPage":"59","ipdsId":"IP-147577","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":440381,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.science/hal-04426531v1/document","text":"External Repository"},{"id":429246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"682","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhang, Ke","contributorId":336899,"corporation":false,"usgs":false,"family":"Zhang","given":"Ke","email":"","affiliations":[{"id":80906,"text":"Key Laboratory of Western China’s Environmental Systems (Ministry of Education)","active":true,"usgs":false}],"preferred":false,"id":901358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sun, Yong","contributorId":336900,"corporation":false,"usgs":false,"family":"Sun","given":"Yong","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":901359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Xuan","contributorId":288840,"corporation":false,"usgs":false,"family":"Zhang","given":"Xuan","email":"","affiliations":[{"id":61842,"text":"College of Water Sciences, Beijing Normal University, Beijing 100875, China","active":true,"usgs":false}],"preferred":false,"id":901360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stepanek, Christian","contributorId":220691,"corporation":false,"usgs":false,"family":"Stepanek","given":"Christian","email":"","affiliations":[{"id":40240,"text":"Alfred Wegener Institute-Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany","active":true,"usgs":false}],"preferred":false,"id":901361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feng, Ran","contributorId":269581,"corporation":false,"usgs":false,"family":"Feng","given":"Ran","email":"","affiliations":[{"id":55991,"text":"Department of Geosciences, College of Liberal Arts and Sciences, University of Connecticut, Connecticut, USA","active":true,"usgs":false}],"preferred":false,"id":901409,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hill, Daniel","contributorId":206286,"corporation":false,"usgs":false,"family":"Hill","given":"Daniel","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":901410,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lohmann, Gerrit","contributorId":336927,"corporation":false,"usgs":false,"family":"Lohmann","given":"Gerrit","email":"","affiliations":[],"preferred":false,"id":901411,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dolan, Aisling M","contributorId":206287,"corporation":false,"usgs":false,"family":"Dolan","given":"Aisling","email":"","middleInitial":"M","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":901412,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Haywood, Alan M","contributorId":206288,"corporation":false,"usgs":false,"family":"Haywood","given":"Alan","email":"","middleInitial":"M","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":901413,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Abe-Ouchi, Ayako","contributorId":94942,"corporation":false,"usgs":true,"family":"Abe-Ouchi","given":"Ayako","email":"","affiliations":[],"preferred":false,"id":901414,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Otto-Bliesner, Bette","contributorId":58171,"corporation":false,"usgs":true,"family":"Otto-Bliesner","given":"Bette","affiliations":[],"preferred":false,"id":901415,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Contoux, Camille","contributorId":269584,"corporation":false,"usgs":false,"family":"Contoux","given":"Camille","email":"","affiliations":[{"id":55994,"text":"Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France","active":true,"usgs":false}],"preferred":false,"id":901416,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chandan, Deepak","contributorId":269588,"corporation":false,"usgs":false,"family":"Chandan","given":"Deepak","email":"","affiliations":[{"id":55996,"text":"Department of Physics, University of Toronto, Toronto, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":901417,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ramstein, Gilles","contributorId":269585,"corporation":false,"usgs":false,"family":"Ramstein","given":"Gilles","email":"","affiliations":[{"id":55994,"text":"Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France","active":true,"usgs":false}],"preferred":false,"id":901418,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":901419,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tindall, Julia C.","contributorId":147376,"corporation":false,"usgs":false,"family":"Tindall","given":"Julia","email":"","middleInitial":"C.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":901420,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Baatsen, Michiel","contributorId":269586,"corporation":false,"usgs":false,"family":"Baatsen","given":"Michiel","email":"","affiliations":[{"id":55995,"text":"Centre for Complex Systems Science, Utrecht University, Utrecht, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":901421,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tan, Ning","contributorId":269583,"corporation":false,"usgs":false,"family":"Tan","given":"Ning","email":"","affiliations":[{"id":55993,"text":"Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, CHINA","active":true,"usgs":false}],"preferred":false,"id":901422,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Peltier, William Richard","contributorId":336928,"corporation":false,"usgs":false,"family":"Peltier","given":"William","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":901423,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Liu, Qiang","contributorId":216855,"corporation":false,"usgs":false,"family":"Liu","given":"Qiang","email":"","affiliations":[{"id":39533,"text":"4.\tGraduate student, CHWR, Hohai University, NO.1, Xikang Road, Nanjing 210098, China","active":true,"usgs":false}],"preferred":false,"id":901424,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Chan, Wing-Le","contributorId":94941,"corporation":false,"usgs":true,"family":"Chan","given":"Wing-Le","email":"","affiliations":[],"preferred":false,"id":901425,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wang, Xin","contributorId":177411,"corporation":false,"usgs":false,"family":"Wang","given":"Xin","email":"","affiliations":[],"preferred":false,"id":901426,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zhang, Xu","contributorId":298298,"corporation":false,"usgs":false,"family":"Zhang","given":"Xu","email":"","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":901427,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70251794,"text":"70251794 - 2024 - Precipitation uncertainty estimation and rainfall-runoff model calibration using iterative ensemble smoothers","interactions":[],"lastModifiedDate":"2024-02-29T13:05:02.300022","indexId":"70251794","displayToPublicDate":"2024-02-19T07:02:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation uncertainty estimation and rainfall-runoff model calibration using iterative ensemble smoothers","docAbstract":"The introduction of iterative ensemble smoothers (IES) for parameter calibration opens avenues for expanding parameter space in surface water hydrologic modeling. Here, we have introduced independent parameters into a model calibration experiment to estimate errors in rainfall forcing data. This approach has the potential to estimate rainfall errors using other hydrological observations and to improve model calibration. Using high-resolution rain gauge data, we estimated “real” rainfall errors across the Turkey River watershed at storm and daily scales. Tests on synthetic and real-world scenarios successfully estimated errors correlated with observed values – even at daily scales. However, a bias remained from model parameter compensation, and identifying errors was challenging for low precipitation and snowfall. Despite synthetic results showing good error correlation, the biases in parameter identification masked potential improvements in hydrological calibration. This study highlights the potential of IES to provide additional information on rainfall errors, even only using streamflow observations.
Conservation is increasingly focused on preventing losses in species’ populations before they occur. Tracking changes in demographic parameters that can impact a population’s resilience in response to drivers of global change can support early conservation efforts. We assessed trends in population productivity (late summer juveniles per 100 females) relative to drivers of global change in 40 pronghorn (Antilocapra americana) herds across sagebrush (Artemisia spp.) steppe in Wyoming. Pronghorn are an iconic rangeland species that have been exposed to increasing levels of anthropogenic, climatic, and land-use change. Using data collected across the state of Wyoming, we (1) assessed long-term trends in population productivity, (2) identified patterns in large-scale drivers of global change (i.e., climate, land cover change) across pronghorn habitat, and (3) determined the relationship between drivers of global change and population productivity over a 35-year (1984–2019) period. While Wyoming hosts some of the most abundant populations of pronghorn in North America that have been largely stable in recent years, we found many herds are experiencing long-term declines in productivity. Long-term declines in productivity were associated with increases in oil and gas development and woody encroachment. Although increasing across almost all herd units, woody vegetation cover remains at low levels, suggesting that pre-emptive management may help to prevent losses in pronghorn populations.
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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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 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B.","contributorId":335323,"corporation":false,"usgs":false,"family":"Blount","given":"B.","email":"","affiliations":[{"id":80371,"text":"NCEH","active":true,"usgs":false}],"preferred":false,"id":898070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Espinosa, M.M.","contributorId":335324,"corporation":false,"usgs":false,"family":"Espinosa","given":"M.M.","email":"","affiliations":[{"id":80371,"text":"NCEH","active":true,"usgs":false}],"preferred":false,"id":898071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science 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":70251797,"text":"70251797 - 2024 - The chytrid insurance hypothesis: Integrating parasitic chytrids into a biodiversity–ecosystem functioning framework for phytoplankton–zooplankton population dynamics","interactions":[],"lastModifiedDate":"2024-03-11T14:42:05.063837","indexId":"70251797","displayToPublicDate":"2024-02-16T06:42:26","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The chytrid insurance hypothesis: Integrating parasitic chytrids into a biodiversity–ecosystem functioning framework for phytoplankton–zooplankton population dynamics","docAbstract":"In temperate lakes, eutrophication and warm temperatures can promote cyanobacteria blooms that reduce water quality and impair food-chain support. Although parasitic chytrids of phytoplankton might compete with zooplankton, they also indirectly support zooplankton populations through the “mycoloop”, which helps move energy and essential dietary molecules from inedible phytoplankton to zooplankton. Here, we consider how the mycoloop might fit into the biodiversity–ecosystem functioning (BEF) framework. BEF considers how more diverse communities can benefit ecosystem functions like zooplankton production. Chytrids are themselves part of pelagic food webs and they directly contribute to zooplankton diets through spore production and by increasing host edibility. The additional way that chytrids might support BEF is if they engage in “kill-the-winner” dynamics. In contrast to grazers, which result in “eat-the-edible” dynamics, kill-the-winner dynamics can occur for host-specific infectious diseases that control the abundance of dominant (in this case inedible) hosts and thus limit the competitive exclusion of poorer (in this case edible) competitors. Thus, if phytoplankton diversity provides functions, and chytrids support algal diversity, chytrids could indirectly favour edible phytoplankton. All three mechanisms are linked to diversity and therefore provide some “insurance” for zooplankton production against the impacts of eutrophication and warming. In our perspective piece, we explore evidence for the chytrid insurance hypothesis, identify exceptions and knowledge gaps, and outline future research directions.
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.
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U.S. Geological Survey
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