The volcanic complex of Nevados de Chillán, located in the Southern Volcanic Zone (SVZ) of the Andes, has been active for the past 640 ± 20 ka. Its volcanic activity includes dome forming eruptions, explosive events, and lava flows. The most recent eruption cycle started in January 2016. We employ DInSAR time-series from Sentinel-1 data to investigate the unrest episode from January 2019 to November 2020. Two distinct periods of unrest are recognized in the time series. The first period (from January to October 2019) coincides with explosive events, dome growth inside the active crater, and a decrease in seismic activity but does not present a significant deformation. The second period (October 2019 to November 2020) is characterized by a displacement towards the sensor's line-of-sight of 100–120 mm. The observed surface deformation is compatible with an inflation source approximately 1.5 km south-southwest of the present active vent, at 5.5 ± 0.5 km depth from the surface, and with a volume change of 0.044 ± 0.014 km3. The most likely explanation for the observed inflation of Nevados de Chillan is the intrusion of magma in a reservoir feeding the current eruption cycle.
Field and laboratory studies of the 1959 Kīlauea Iki lava lake have provided insight into differentiation processes in mafic magma chambers. This paper explores how partially molten basaltic mushes responded to unloading as a consequence of drilling. Most holes drilled from 1967 to 1979 terminated in a melt-rich internal differentiate with a sharp crust-melt interface. These interfaces were not stable, so the boreholes were backfilled by melt-rich (<5% crystal) ooze. This process, with melt ascent rates of 1.3–4.2 m/s, occurred within minutes of intersecting the bodies, mimicking volcanic eruptions, albeit on a small scale.
One borehole (KI79-1), which did not encounter such a discontinuity, was backfilled over a period of 16 days by upward flow of crystal-rich mushes rather than melt-rich ooze. The first interval of ooze recovered had undergone extensive internal differentiation. Its most conspicuous feature was production of melt-rich layers by lateral migration of interstitial melt from the wallrock into the rising crystal-rich mush. In addition, two smaller-scale processes occurred within the rising mush: segregation of melt into discrete blebs within the rising mush column and aggregation of groundmass crystals into crystal-rich clumps formed adjacent to coarser olivine crystals. The upper parts of the ooze are enriched in melt relative to deeper samples, which suggests that the melt blebs rose relative to their olivine-rich matrix. Similar melt blebs and crystal-rich clumps are observed in naturally occurring diapiric bodies within the lava lake. These processes appear to be intrinsic to the upwelling of narrow cylindrical mush bodies whether constrained within a borehole (like the oozes) or unconstrained (as were the diapirs in the lava lake).
The most striking behavior observed during repeated reentry of KI79-1 was a sharp change in rheology during the second and third re-entries of the borehole. The shift in behavior observed was that the oozes rose up the borehole, with ascent rates of 1.0–1.7 m/s, which are comparable to the rates of the crystal-poor oozes from melt-rich internal differentiates. These oozes contain more melt than the original core at equivalent depths, presumably because melt moved relative to crystals down the pressure gradient created by the open borehole. Groundmass textures in these inflated mushes show erosion of crystal outlines, especially of grain-to-grain contacts between different phases, so that the tenuous crystalline network observed in the original core samples was replaced by rounded crystals in continuous melt at crystallinities of 55–65 vol%. The transition from stable coherent mush to inflatable mush occurred at 25–28 vol% melt. This behavior appears similar to certain types of reactive transport observed in other studies.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36248.1","usgsCitation":"Helz, R.L., 2022, Melt surges, flow differentiation, and remobilization of crystal-rich mushes in response to unloading: Observations from Kīlauea Iki lava lake, Hawaii: GSA Bulletin, v. 134, no. 11-12, p. 3123-3141, https://doi.org/10.1130/B36248.1.","productDescription":"9 p.","startPage":"3123","endPage":"3141","ipdsId":"IP-121979","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":448456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b36248.1","text":"Publisher Index Page"},{"id":404990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Iki lava lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.45654296875,\n 19.134789188332523\n ],\n [\n -155.006103515625,\n 19.134789188332523\n ],\n [\n -155.006103515625,\n 19.482128945320483\n ],\n [\n -155.45654296875,\n 19.482128945320483\n ],\n [\n -155.45654296875,\n 19.134789188332523\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"134","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2022-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Helz, Rosalind L. 0000-0003-1550-0684 rhelz@usgs.gov","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":1952,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind","email":"rhelz@usgs.gov","middleInitial":"L.","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":848574,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239283,"text":"70239283 - 2022 - Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions","interactions":[],"lastModifiedDate":"2023-01-06T12:40:06.995804","indexId":"70239283","displayToPublicDate":"2022-03-17T06:34:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions","docAbstract":"Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high-frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady-state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub-daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation-based approach to estimate the sub-daily flux under highly dynamic flow conditions using multi-depth temperature observations at a 5-min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi-depth temperature data at 1- or 2-hr time intervals assuming one-dimensional flow and heat transport governing equation. By comparing estimated fluxes with model-generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation-based flux estimation method was able to capture the vertical sub-daily fluxes using multi-depth high-resolution temperature data alone, even in the presence of multi-dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1-D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.
Missouri, one of only two States that borders eight different States, lies in the heart of the United States. Distinguished by its farm fields and forests, substantial rivers and lakes, and cities filled with culture and industry, the “Show Me State” has abundant beauty and a long history of connecting the East and the West. The Pony Express, Oregon Trail, Santa Fe Trail, and California Trail all began in Missouri.
The land and the people of Missouri contribute to its resiliency. Landsat data provide important tools for Missourians to protect their landscapes and waterways and enhance their economy under a variety of circumstances, from fast-arising natural disasters to longer-term environmental phenomena.
Here are several ways that Landsat data benefit Missouri.
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\"}}]}","edition":"Version 1.0: March 16, 2022; Version 1.1: January 19, 2023","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The estuarine habitat mosaic supports the reproduction, growth, and survival of resident and migratory fish species by providing a diverse portfolio of unique habitats with varying physical and biological features. Global climate change is expected to result in increasing temperatures, rising sea levels, and changes in riverine hydrology, which will have profound effects on the extent and composition of the estuarine habitat mosaic and its associated nursery quality for juvenile fish. We used a spatially explicit bioenergetics model to assess how different climate change scenarios might affect juvenile salmon growth rate potential relative to present day conditions in the Nisqually River Delta, WA, USA. The model indicated that prey-rich habitats such as emergent salt marshes and eelgrass meadows were most likely to facilitate growth, and that reductions in their areal extent and accessibility could have severe consequences for salmon. For instance, unmitigated sea-level rise halved the predicted extent of low- and high-elevation emergent salt marsh, leading to a 30% reduction in end-of-season weights. Increasing water temperatures compounded these effects during the late spring and summer such that the average daily growth rate of an individual fish decreased by an additional 5–50% when compared to the effects of sea-level rise alone. Lethal temperatures (> 24 °C) were infrequently observed, but they were more likely to occur during summer low tides in the mudflat and eelgrass habitats when accessibility to prey-rich marsh was minimal, thereby limiting foraging capacity and the availability of thermal refugia. Our findings indicate that, barring the enactment of targeted management strategies, rising tidal levels and increasing ocean temperatures may reduce the quality of the estuarine habitat mosaic for out-migrating salmon and other sensitive fish species.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-021-01003-3","usgsCitation":"Davis, M.J., Woo, I., Ellings, C.S., Hodgson, S., Beauchamp, D., Nakai, G., and De La Cruz, S.E., 2022, A climate-mediated shift in the estuarine habitat mosaic limits prey availability and reduces nursery quality for juvenile salmon: Estuaries and Coasts, v. 45, p. 1445-1464, https://doi.org/10.1007/s12237-021-01003-3.","productDescription":"20 p.","startPage":"1445","endPage":"1464","ipdsId":"IP-129415","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":397156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta, Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7385711669922,\n 47.06731569299121\n ],\n [\n -122.73273468017578,\n 47.067900315766245\n ],\n [\n -122.71350860595702,\n 47.06836800936954\n ],\n [\n -122.69496917724608,\n 47.07526601334617\n ],\n [\n -122.67488479614258,\n 47.08239690925263\n ],\n [\n -122.67454147338866,\n 47.11172875008271\n ],\n [\n -122.73822784423828,\n 47.11137826571562\n ],\n [\n -122.7385711669922,\n 47.06731569299121\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellings, Christopher S.","contributorId":149343,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":17711,"text":"Dep't Natural Resources, Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hodgson, Sayre","contributorId":172121,"corporation":false,"usgs":false,"family":"Hodgson","given":"Sayre","email":"","affiliations":[{"id":26985,"text":"Nisqually Indian Tribe, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":838149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nakai, Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":838150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":838151,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230233,"text":"70230233 - 2022 - Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","interactions":[],"lastModifiedDate":"2022-04-06T14:45:12.0395","indexId":"70230233","displayToPublicDate":"2022-03-16T09:52:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Urban landcover differentially drives day and nighttime air temperature across a semi-arid city","docAbstract":"Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m2) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (−0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to −0.022 °C per % cover, while tree canopy effects are reduced from −0.026 °C during the day to −0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies.
Groundwater/surface-water (GW/SW) exchange and hyporheic processes are topics receiving increasing attention from the hydrologic community. Hydraulic, chemical, temperature, geophysical, and remote sensing methods are used to achieve various goals (e.g., inference of GW/SW exchange, mapping of bed materials, etc.), but the application of these methods is constrained by site conditions such as water depth, specific conductance, bed material, and other factors. Researchers and environmental professionals working on GW/SW problems come from diverse fields and rarely have expertise in all available field methods; hence there is a need for guidance to design field campaigns and select methods that both contribute to study goals and are likely to work under site-specific conditions. Here, we present the spreadsheet-based GW/SW-Method Selection Tool (GW/SW-MST) to help practitioners identify methods for use in GW/SW and hyporheic studies. The GW/SW-MST is a Microsoft Excel-based decision support tool in which the user selects answers to questions about GW/SW-related study goals and site parameters and characteristics. Based on user input, the tool indicates which methods from a toolbox of 32 methods could potentially contribute to achieving the specified goals at the site described.
","language":"English","publisher":"National Groundwater Association (NGWA)","doi":"10.1111/gwat.13194","usgsCitation":"Hammett, S., Day-Lewis, F., Trottier, B.R., Barlow, P.M., Briggs, M., Delin, G.N., Harvey, J., Johnson, C., Lane, J., Rosenberry, D., and Werkema, D.D., 2022, GW/SW-MST: A groundwater/surface-water method selection tool: Groundwater, v. 60, no. 6, p. 784-791, https://doi.org/10.1111/gwat.13194.","productDescription":"8 p.","startPage":"784","endPage":"791","ipdsId":"IP-128682","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":448467,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9477975","text":"Publisher Index Page"},{"id":435922,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YFJALF","text":"USGS data release","linkHelpText":"GW/SW-MST: A Groundwater/Surface-Water Method Selection Tool"},{"id":401640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammett, Steven 0000-0002-6051-966X","orcid":"https://orcid.org/0000-0002-6051-966X","contributorId":292207,"corporation":false,"usgs":false,"family":"Hammett","given":"Steven","email":"","affiliations":[{"id":38050,"text":"Contractor","active":true,"usgs":false}],"preferred":false,"id":844072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trottier, Brett Russell 0000-0002-6148-0875","orcid":"https://orcid.org/0000-0002-6148-0875","contributorId":291383,"corporation":false,"usgs":true,"family":"Trottier","given":"Brett","email":"","middleInitial":"Russell","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":844080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":844074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":844075,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delin, Geoffrey N. 0000-0001-7991-6158","orcid":"https://orcid.org/0000-0001-7991-6158","contributorId":224981,"corporation":false,"usgs":true,"family":"Delin","given":"Geoffrey","email":"","middleInitial":"N.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":844076,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844077,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844082,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":844078,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rosenberry, D.O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":38500,"corporation":false,"usgs":true,"family":"Rosenberry","given":"D.O.","affiliations":[],"preferred":true,"id":844079,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":844081,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70229727,"text":"70229727 - 2022 - Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","interactions":[],"lastModifiedDate":"2022-03-16T14:42:57.642502","indexId":"70229727","displayToPublicDate":"2022-03-16T09:29:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?","docAbstract":"Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2022.120131","usgsCitation":"Xu, W., He, H.S., Huang, C., Duan, S., Hawbaker, T., Henne, P., Liang, Y., and Zhu, Z., 2022, Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?: Forest Ecology and Management, v. 510, p. 1-10, https://doi.org/10.1016/j.foreco.2022.120131.","productDescription":"120131, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-130289","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":448469,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2022.120131","text":"Publisher Index Page"},{"id":435923,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YREDMC","text":"USGS data release","linkHelpText":"Data inputs and outputs for simulations of species distributions in response to future fire size and climate change in the boreal-temperate ecotone of northeastern China"},{"id":397150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Great Xing'an Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120.16845703125,\n 51.713416052417614\n ],\n [\n 121.04736328125,\n 51.39920565355378\n ],\n [\n 121.55273437499999,\n 50.47149085139956\n ],\n [\n 124.16748046874999,\n 49.92293545449574\n ],\n [\n 126.91406249999999,\n 51.069016659603896\n ],\n [\n 126.97998046875001,\n 51.41291212935532\n ],\n [\n 126.76025390624999,\n 51.631657349449995\n ],\n [\n 126.73828125,\n 51.754240074033525\n ],\n [\n 126.54052734374999,\n 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phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liang, Yu","contributorId":145642,"corporation":false,"usgs":false,"family":"Liang","given":"Yu","affiliations":[],"preferred":false,"id":838115,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhu, Zhiliang 0000-0002-6860-6936 zzhu@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-6936","contributorId":150078,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhiliang","email":"zzhu@usgs.gov","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":505,"text":"Office of the AD Climate and Land-Use 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method was initially proposed to retrieve the site amplification function and its resonance frequencies produced by unconsolidated sediments overlying high-velocity bedrock. Presently, MHVSR measurements are predominantly conducted to obtain an estimate of the fundamental site frequency at sites where a strong subsurface impedance contrast exists. Of the earthquake site characterization methods presented in this special issue, the MHVSR method is the furthest behind in terms of consensus towards standardized guidelines and commercial use. The greatest challenges to an international standardization of MHVSR acquisition and analysis are (1) the what — the underlying composition of the microtremor wavefield is site-dependent, and thus, the appropriate theoretical (forward) model for inversion is still debated; and (2) the how — many factors and options are involved in the data acquisition, processing, and interpretation stages. This paper reviews briefly a historical development of the MHVSR technique and the physical basis of an MHVSR (the what). We then summarize recommendations for MHVSR acquisition and analysis (the how). Specific sections address MHVSR interpretation and uncertainty assessment.
","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10062-9","usgsCitation":"Molnar, S., Sirohey, A., Assaf, J., Bard, P., Castellaro, C., Cornou, C., Cox, B., Guillier, B., Hassani, B., Kawase, H., Matsushima, S., Sánchez-Sesma, F., and Yong, A., 2022, A review of the microtremor horizontal-to-vertical spectral ratio (MHVSR) method: Journal of Seismology, v. 26, p. 653-685, https://doi.org/10.1007/s10950-021-10062-9.","productDescription":"33 p.","startPage":"653","endPage":"685","ipdsId":"IP-127918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10062-9","text":"Publisher Index Page"},{"id":406138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Molnar, S.","contributorId":203574,"corporation":false,"usgs":false,"family":"Molnar","given":"S.","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":850685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sirohey, A.","contributorId":296125,"corporation":false,"usgs":false,"family":"Sirohey","given":"A.","email":"","affiliations":[],"preferred":false,"id":850686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Assaf, J.","contributorId":296126,"corporation":false,"usgs":false,"family":"Assaf","given":"J.","email":"","affiliations":[],"preferred":false,"id":850708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bard, P.-Y.","contributorId":296110,"corporation":false,"usgs":false,"family":"Bard","given":"P.-Y.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castellaro, C.","contributorId":296111,"corporation":false,"usgs":false,"family":"Castellaro","given":"C.","email":"","affiliations":[{"id":63993,"text":"Alma Mater Studiorum Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":850688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cornou, C.","contributorId":296112,"corporation":false,"usgs":false,"family":"Cornou","given":"C.","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cox, B.","contributorId":296113,"corporation":false,"usgs":false,"family":"Cox","given":"B.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":850690,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guillier, B.","contributorId":296114,"corporation":false,"usgs":false,"family":"Guillier","given":"B.","email":"","affiliations":[{"id":63992,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":850691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hassani, B.","contributorId":296115,"corporation":false,"usgs":false,"family":"Hassani","given":"B.","email":"","affiliations":[{"id":37568,"text":"BC Hydro","active":true,"usgs":false}],"preferred":false,"id":850692,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kawase, H.","contributorId":296116,"corporation":false,"usgs":false,"family":"Kawase","given":"H.","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850693,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Matsushima, S.","contributorId":296117,"corporation":false,"usgs":false,"family":"Matsushima","given":"S.","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":850694,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sánchez-Sesma, F. J.","contributorId":296118,"corporation":false,"usgs":false,"family":"Sánchez-Sesma","given":"F. J.","affiliations":[{"id":25354,"text":"Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":850695,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850696,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70236346,"text":"70236346 - 2022 - A review of near-surface QS estimation methods using active and passive sources","interactions":[],"lastModifiedDate":"2022-09-02T14:12:47.588487","indexId":"70236346","displayToPublicDate":"2022-03-16T09:10:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2453,"text":"Journal of Seismology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A review of near-surface QS estimation methods using active and passive sources","title":"A review of near-surface QS estimation methods using active and passive sources","docAbstract":"Seismic attenuation and the associated quality factor (Q) have long been studied in various sub-disciplines of seismology, ranging from observational and engineering seismology to near-surface geophysics and soil/rock dynamics with particular emphasis on geotechnical earthquake engineering and engineering seismology. Within the broader framework of seismic site characterization, various experimental techniques have been adopted over the years to measure the near-surface shear-wave quality factor (QS). Common methods include active- and passive-source recording techniques performed at the free surface of soil deposits and within boreholes, as well as laboratory tests. This paper intends to provide an in-depth review of what Q is and, in particular, how QS is estimated in the current practice. After motivating the importance of this parameter in seismology, we proceed by recalling various theoretical definitions of Q and its measurement through laboratory tests, considering various deformation modes, most notably QP and QS. We next provide a review of the literature on QS estimation methods that use data from surface and borehole sensor recordings. We distinguish between active- and passive-source approaches, along with their pros and cons, as well as the state-of-the-practice and state-of-the-art. Finally, we summarize the phenomena associated with the high-frequency shear-wave attenuation factor (kappa) and its relation to Q, as well as other lesser-known attenuation parameters.
","language":"English","publisher":"Springer","doi":"10.1007/s10950-021-10066-5","usgsCitation":"Parolai, S., Lai, C.G., Dreossi, I., Ktenidou, O., and Yong, A., 2022, A review of near-surface QS estimation methods using active and passive sources: Journal of Seismology, v. 26, p. 823-862, https://doi.org/10.1007/s10950-021-10066-5.","productDescription":"40 p.","startPage":"823","endPage":"862","ipdsId":"IP-132752","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":448475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10950-021-10066-5","text":"Publisher Index Page"},{"id":406135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Parolai, Stefano 0000-0002-9084-7488","orcid":"https://orcid.org/0000-0002-9084-7488","contributorId":296105,"corporation":false,"usgs":false,"family":"Parolai","given":"Stefano","email":"","affiliations":[{"id":63989,"text":"Instituto Nazionale di Oceonografia","active":true,"usgs":false}],"preferred":false,"id":850680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lai, Carlo G.","contributorId":296106,"corporation":false,"usgs":false,"family":"Lai","given":"Carlo","email":"","middleInitial":"G.","affiliations":[{"id":63990,"text":"Department of Civil and Architectural Engineering, University of Pavia, Pavia, Italy","active":true,"usgs":false}],"preferred":false,"id":850681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreossi, Ilaria","contributorId":296107,"corporation":false,"usgs":false,"family":"Dreossi","given":"Ilaria","email":"","affiliations":[{"id":63991,"text":"National Institute of Oceanography and Applied Geophysics – OGS, Udine, Italy","active":true,"usgs":false}],"preferred":false,"id":850682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ktenidou, Olga-Joan","contributorId":271026,"corporation":false,"usgs":false,"family":"Ktenidou","given":"Olga-Joan","email":"","affiliations":[{"id":56255,"text":"National Observatory of Athens","active":true,"usgs":false}],"preferred":false,"id":850683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yong, Alan K. 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":296108,"corporation":false,"usgs":true,"family":"Yong","given":"Alan K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850684,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230023,"text":"70230023 - 2022 - Modeling the dynamics of salt marsh development in coastal land reclamation","interactions":[],"lastModifiedDate":"2022-03-24T14:12:06.779505","indexId":"70230023","displayToPublicDate":"2022-03-16T08:55:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the dynamics of salt marsh development in coastal land reclamation","docAbstract":"The valuable ecosystem services of salt marshes are spurring marsh restoration projects around the world. However, it is difficult to determine the final vegetated area based on physical drivers. Herein, we use a 3D fully coupled vegetation-hydrodynamic-morphological modeling system (COAWST), to simulate the final vegetation cover and the timescale to reach it under various forcing conditions. Marsh development in our simulations can be divided in three distinctive phases: a preparation phase characterized by sediment accumulation in the absence of vegetation, an encroachment phase in which the vegetated area grows, and an adjustment phase in which the vegetated area remains relatively constant while marsh accretes vertically to compensate for sea level rise. Sediment concentration, settling velocity, sea level rise and tidal range each comparably affect equilibrium coverage and timescale in different ways. Our simulations show that the Unvegetated-Vegetated Ratio (UVVR) also relates to sediment budget in marsh development under most conditions.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL095559","usgsCitation":"Xu, Y., Kalra, T., Ganju, N., and Fagherazzi, S., 2022, Modeling the dynamics of salt marsh development in coastal land reclamation: Geophysical Research Letters, v. 49, no. 6, e2021GL095559, 11 p., https://doi.org/10.1029/2021GL095559.","productDescription":"e2021GL095559, 11 p.","ipdsId":"IP-131905","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448480,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gl095559","text":"External Repository"},{"id":397522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Yiyang","contributorId":289206,"corporation":false,"usgs":false,"family":"Xu","given":"Yiyang","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":838716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":838781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":838718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagherazzi, Sergio","contributorId":207153,"corporation":false,"usgs":false,"family":"Fagherazzi","given":"Sergio","email":"","affiliations":[{"id":37465,"text":"Boston University, Earth and Environment, Boston, 02215, USA.","active":true,"usgs":false}],"preferred":false,"id":838719,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239267,"text":"70239267 - 2022 - Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks","interactions":[],"lastModifiedDate":"2023-01-06T14:34:50.408914","indexId":"70239267","displayToPublicDate":"2022-03-16T08:29:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks","docAbstract":"Understanding the influence of population attributes on genetic diversity is important to advancement of biological conservation. Because bighorn sheep (Ovis canadensis) populations vary in size and management history, the species provides a unique opportunity to observe the response of average pairwise kinship, inversely related to genetic diversity, to a spectrum of natural and management influences. We estimated average pairwise kinship of bighorn sheep herds and compared estimates with population origin (native/indigenous/extant or reintroduced), historical minimum count, connectivity, and augmentation history, to determine which predictors were the most important. We evaluated 488 bighorn sheep from 19 wild populations with past minimum counts of 16–562 animals, including native and reintroduced populations that received 0–165 animals in augmentations. Using the Illumina High Density Ovine array, we generated a dataset of 7728 single nucleotide polymorphisms and calculated average pairwise kinship for each population. Multiple linear regression analysis determined that connectivity between populations via dispersal, greater number of animals received in augmentations, and greater minimum count were correlated with lower average pairwise kinship at the population level, and whether the population was extant or reintroduced was less important. Thus, our results indicated that genetic isolation of populations can result in increased levels of inbreeding. By determining that natural and human-assisted gene flow were likely the most important influences of average pairwise kinship at the population level, this study can serve as a benchmark for future management of bighorn sheep populations and aid in identifying populations of genetic concern to define priorities for conservation of wild populations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3972","usgsCitation":"Flesch, E.P., Graves, T., Thomson, J., Proffitt, K., and Garrott, R.A., 2022, Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks: Ecosphere, v. 13, no. 3, e3972, 19 p., https://doi.org/10.1002/ecs2.3972.","productDescription":"e3972, 19 p.","ipdsId":"IP-123033","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":488768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3972","text":"Publisher Index Page"},{"id":411486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.78094692827673,\n 43.20819189911293\n ],\n [\n -107.87478246478094,\n 43.46432073825207\n ],\n [\n -105.38522276615836,\n 47.31273522708753\n ],\n [\n -106.94850703787552,\n 48.95098006865928\n ],\n [\n -116.04022455322576,\n 48.995371199230505\n ],\n [\n -115.43136405543936,\n 47.5027919613581\n ],\n [\n -114.77745582859464,\n 46.867640242508855\n ],\n [\n -114.42311195285694,\n 46.465058107358715\n ],\n [\n -114.4197823602259,\n 45.56395759707192\n ],\n [\n -113.70839351291886,\n 45.38622209814852\n ],\n [\n -112.22430921762538,\n 44.50809933614741\n ],\n [\n -111.26330199120804,\n 44.53201508738698\n ],\n [\n -110.78094692827673,\n 43.20819189911293\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Flesch, Elizabeth P 0000-0002-7592-8124","orcid":"https://orcid.org/0000-0002-7592-8124","contributorId":222685,"corporation":false,"usgs":false,"family":"Flesch","given":"Elizabeth","email":"","middleInitial":"P","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":860960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":860961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomson, Jennifer 0000-0003-1921-0975","orcid":"https://orcid.org/0000-0003-1921-0975","contributorId":248418,"corporation":false,"usgs":false,"family":"Thomson","given":"Jennifer","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":860962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Proffitt, Kelly M.","contributorId":275167,"corporation":false,"usgs":false,"family":"Proffitt","given":"Kelly M.","affiliations":[{"id":48627,"text":"mtfwp","active":true,"usgs":false}],"preferred":false,"id":860963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrott, Robert A.","contributorId":171537,"corporation":false,"usgs":false,"family":"Garrott","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":860964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231194,"text":"70231194 - 2022 - Influence of offshore oil and gas structures on seascape ecological connectivity","interactions":[],"lastModifiedDate":"2022-05-03T12:12:50.95425","indexId":"70231194","displayToPublicDate":"2022-03-16T07:10:25","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Influence of offshore oil and gas structures on seascape ecological connectivity","docAbstract":"Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure.
Disturbances are a key component of ecological processes in coastal ecosystems. Investigating factors that affect tidal marsh accretion and elevation change is important, largely due to accelerating sea-level rise and the ecological and economic value of wetlands. Sediment accumulation rates, elevation change, and flooding were examined at five marshes along a riverine-tidal gradient in the northern San Francisco Bay-Delta, California, USA during an Atmospheric River storm event in 2017 using Surface Elevation Tables (SETs), feldspar marker horizons (MH), and continuous water-level sensors. Our results showed that localized marsh flooding increased during the storm event, but not evenly across sites. Marsh surface elevation increased the most at the tidal freshwater marsh site in response to the storms, with an average surface elevation gain of 45.6 ± 13.1 mm, and the least at a tidal saline marsh with an average surface elevation gain of 4.0 ± 1.2 mm. A marsh located on the large embayment did not exhibit an immediate response to the storm but had a surface elevation gain of 21.5 ± 13.7 mm 6 months after the storm. During the storm period, marsh distance to the bay was the strongest predictor of elevation change, followed by SET-MH elevations. Conversely, during non-storm periods, SET-MH elevation was a relatively strong predictor of elevation change. Atmospheric Rivers appear to be a major factor affecting short-term spatial and temporal variability in flooding and sedimentation rates in tidal marsh systems. Incorporating information about storms into monitoring could increase our understanding of how episodic storms can impact marshes.
Salmonella enterica serovar Typhimurium is typically considered a host generalist; however, certain isolates are associated with specific hosts and show genetic features of host adaptation. Here, we sequenced 131 S. Typhimurium isolates from wild birds collected in 30 U.S. states during 1978-2019. We found that isolates from broad taxonomic host groups including passerine birds, water birds (Aequornithes), and larids (gulls and terns) represented three distinct lineages and certain S. Typhimurium CRISPR types presented in individual lineages. We also showed that lineages formed by wild bird isolates differed from most isolates originating from domestic animal sources, and genomes from these lineages substantially improved source attribution of Typhimurium genomes to wild birds by a machine learning classifier. Furthermore, virulence gene signatures that differentiated S. Typhimurium from passerines, water birds, and larids were detected. Passerine isolates tended to lack S. Typhimurium-specific virulence plasmids. Isolates from the passerine, water bird, and larid lineages had close genetic relatedness with human clinical isolates, including those from a 2021 U.S. outbreak linked to passerine birds. These observations indicate that S. Typhimurium from wild birds in the United States are likely host-adapted, and the representative genomic dataset examined in this study can improve source prediction and facilitate outbreak investigation.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/aem.01979-21","usgsCitation":"Fu, Y., M’ikanatha, N.M., Lorch, J., Blehert, D.S., Berlowski-Zier, B.M., Whitehouse, C.A., Li, S., Deng, X., Smith, J., Shariat, N.W., Nawrocki, E.M., and Dudley, E.G., 2022, Salmonella enterica serovar Typhimurium from wild birds in the United States represent distinct lineages defined by bird type: Applied and Environmental Microbiology, v. 88, no. 6, e01979-21, 16 p., https://doi.org/10.1128/aem.01979-21.","productDescription":"e01979-21, 16 p.","ipdsId":"IP-131992","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":448497,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/aem.01979-21","text":"Publisher Index Page"},{"id":397112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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headwater stream permanence estimates from a monthly water balance model in the Pacific Northwest, USA","docAbstract":"Stream permanence classifications (i.e., perennial, intermittent, ephemeral) are a primary consideration to determine stream regulatory status in the United States (U.S.) and are an important indicator of environmental conditions and biodiversity. However, at present, no models or products adequately describe surface water presence for regulatory determinations. We modified the Thornthwaite monthly water balance model (MWBM) with a flow threshold parameter to estimate flow permanence and evaluated the model’s accuracy and precision for more than 1.3 million headwater stream reaches in the U.S. Pacific Northwest (PNW). Stream reaches were assigned to one of eight calibration groups by unsupervised classification based on sensitivity to MWBM parameters. Suitable MWBM parameter sets were identified by comparing modeled stream permanence estimates to surface water presence observations (SWPO). Parameter sets with accuracies > 65% were considered suitable. The MWBM estimated stream permanence with high precision at 40% of reaches, with poor precision at 20% of reaches, and no suitable parameter sets were identified for 40% of reaches. Results highlight the need for increased SWPO collection to improve calibration and assessment of stream permanence models. Additionally, implementation of the MWBM to estimate surface water presence indicates potential for process-based models to predict stream permanence with future development.
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Processes","active":true,"publicationSubtype":{"id":10}},"title":"Forest cover lessens the impact of drought on streamflow in Puerto Rico","docAbstract":"Tropical regions are experiencing high rates of forest cover loss coupled with changes in the volume and timing of rainfall. These shifts can compromise streamflow and water provision, highlighting the need to identify how forest cover influences streamflow generation under variable rainfall conditions. Although rainfall is the key driver of streamflow regimes, the role of forests is less clear, particularly in tropical regions where forest loss is an ongoing risk. Forest cover loss alters evapotranspiration, rainfall infiltration and storage, and may increase stream ecosystem vulnerability to rainfall extremes. Puerto Rico, an island with spatially heterogenous forest cover and a marked geographic rainfall gradient, is projected to experience more frequent droughts and flash flooding. Using 15-minute streamflow data collected between 2005 and 2016 from 20 USGS stream gages and 3-hourly Multi-Source Weighted-Ensemble Precipitation rainfall estimates, we utilized flow-duration curves and linear mixed regression models to examine the role of forest cover in regulating the timing and volume of streamflow. The mixed model approach helps to account for differences in watershed characteristics. We determined the effects of rainfall and forest cover on low and peak flows in Puerto Rican streams, then evaluated changes in these relationships under dry and wet antecedent rainfall conditions. Watersheds with high forest cover had consistently greater low and peak streamflow than deforested ones under all rainfall conditions, although the effect was more marked during wet antecedent conditions, suggesting that peak flow is largely the result of saturation excess overland flow. During dry antecedent rainfall conditions, highly forested watersheds had higher streamflow than deforested ones, suggesting greater hillslope storage and release may also be at play. Our results demonstrate that forest cover generated a net increase in hillslope infiltration and storage and may lessen drought impacts on streamflow in Puerto Rico. Resilience to prolonged drought may be limited by finite water storage potential in this steep, mountainous setting, highlighting maintenance of forest cover as an important water management strategy to increase infiltration.
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Yuri","contributorId":290689,"corporation":false,"usgs":false,"family":"Gorokhovich","given":"Yuri","email":"","affiliations":[{"id":39562,"text":"City University of New York","active":true,"usgs":false}],"preferred":false,"id":841587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uriarte, Maria","contributorId":287019,"corporation":false,"usgs":false,"family":"Uriarte","given":"Maria","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":841588,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230147,"text":"70230147 - 2022 - Complex life-cycles in trophically transmitted helminths: Do the benefits of increased growth and transmission outweigh generalism and complexity costs?","interactions":[],"lastModifiedDate":"2022-03-30T12:09:56.574531","indexId":"70230147","displayToPublicDate":"2022-03-15T07:08:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10528,"text":"Current Research in Parasitology & Vector-borne Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Complex life-cycles in trophically transmitted helminths: Do the benefits of increased growth and transmission outweigh generalism and complexity costs?","docAbstract":"Why do so many parasitic worms have complex life-cycles? A complex life-cycle has at least two hypothesized costs: (i) worms with longer life-cycles, i.e. more successive hosts, must be generalists at the species level, which might reduce lifetime survival or growth, and (ii) each required host transition adds to the risk that a worm will fail to complete its life-cycle. Comparing hundreds of trophically transmitted acanthocephalan, cestode, and nematode species with different life-cycles suggests these costs are weaker than expected. Helminths with longer cycles exhibit higher species-level generalism without impaired lifetime growth. Further, risk in complex life-cycles is mitigated by increasing establishment rates in each successive host. Two benefits of longer cycles are transmission and production. Longer cycles normally include smaller (and thus more abundant) first hosts that are likely to consume parasite propagules, as well as bigger (and longer-lived) definitive hosts, in which adult worms grow to larger and presumably more fecund reproductive sizes. Additional factors, like host immunity or dispersal, may also play a role, but are harder to address. Given the ubiquity of complex life-cycles, the benefits of incorporating or retaining hosts in a cycle must often exceed the costs.
The risk of a newly discovered non-native fish species in Florida (USA): Cichlasoma dimerus ([Heckel, 1840]; Family: Cichlidae) is assessed. Its tolerance to cold temperatures was experimentally evaluated and information on its biology and ecology was synthesized. In the cold-temperature tolerance experiment, temperature was lowered from 24 °C by increments of 1 °C per hour, mimicking a typical cold weather front. Fish lost equilibrium at a mean temperature of 7.8 °C and died at 4.7 °C. Those values are lower than most other non-native fishes from the state that have been experimentally evaluated, and it appears C. dimerus is the most cold-tolerant cichlid established in Florida. The combination of cold-temperature tolerance and other biological/ecological factors (e.g., adult size, reproduction and parental care, diet, habitat, and other behaviors) along with the geographic range and habitat diversity of specimens vouchered in museums, indicate C. dimerus may be able to invade many freshwater ecosystems in the state, including environmentally sensitive freshwater springs.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.10","usgsCitation":"Brown, M., Robins, R.H., and Schofield, P., 2022, Risk assessment of chanchita Cichlasoma dimerus (Heckel, 1840), a newly identified non-native cichlid fish in Florida: Management of Biological Invasions, v. 13, no. 2, p. 435-448, https://doi.org/10.3391/mbi.2022.13.2.10.","productDescription":"14 p.; Data Release","startPage":"435","endPage":"448","ipdsId":"IP-133716","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":448503,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2022.13.2.10","text":"Publisher Index Page"},{"id":401743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417841,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P949CEKG"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5947265625,\n 25.005972656239187\n ],\n [\n -79.4970703125,\n 25.005972656239187\n ],\n [\n -79.4970703125,\n 31.015278981711266\n ],\n [\n -84.5947265625,\n 31.015278981711266\n ],\n [\n -84.5947265625,\n 25.005972656239187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Mary 0000-0002-5580-137X","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":205227,"corporation":false,"usgs":true,"family":"Brown","given":"Mary","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robins, Robert H.","contributorId":292263,"corporation":false,"usgs":false,"family":"Robins","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":40459,"text":"Florida Museum, University of Florida","active":true,"usgs":false}],"preferred":false,"id":844161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schofield, Pam 0000-0002-8752-2797","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":216025,"corporation":false,"usgs":true,"family":"Schofield","given":"Pam","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":844162,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70255076,"text":"70255076 - 2022 - Carnivores in color: Pelt color patterns among carnivores in Idaho","interactions":[],"lastModifiedDate":"2024-06-13T11:15:44.724402","indexId":"70255076","displayToPublicDate":"2022-03-15T06:12:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Carnivores in color: Pelt color patterns among carnivores in Idaho","docAbstract":"Pelt color serves many functions from signaling to crypsis to thermoregulation and its purpose has been a lively source of debate in biology for over a century. Determining the effects of both habitat and human influences on pelt color patterns can be difficult. We made novel use of a multispecies occupancy model by defining “pelt color” as “species.” We then used this model to test predictions and estimate pelt color patterns concurrently for three carnivore species in Idaho, United States. We predicted pelt patterns of all three carnivores would be affected by environmental variables as well as human disturbance. Areas of Idaho where baiting was allowed and preferential harvest possible did not explain pelt patterns in black bears and neither did forest cover. Road density was positively associated with detection probability but negatively associated with occupancy of both black and brown pelt bears, however. Gray pelt wolves were found more often in areas with higher road densities than black wolves. As predicted, black, but not gray, wolves were positively associated with forest cover. Both red and black pelt foxes were positively associated with increasing elevation and road density. Black pelt foxes were negatively associated with forest cover, mirroring the habitat use described for native black pelt foxes. We demonstrate how using noninvasively collected data and extending multispecies occupancy models can allow biologists to study the distribution of different pelt colors in wild populations.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyab166","usgsCitation":"Ausband, D.E., and Krohner, J.M., 2022, Carnivores in color: Pelt color patterns among carnivores in Idaho: Journal of Mammalogy, v. 103, no. 3, p. 598-607, https://doi.org/10.1093/jmammal/gyab166.","productDescription":"10 p.","startPage":"598","endPage":"607","ipdsId":"IP-130703","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyab166","text":"Publisher Index Page"},{"id":430060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"103","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krohner, Jessica M.","contributorId":338521,"corporation":false,"usgs":false,"family":"Krohner","given":"Jessica","email":"","middleInitial":"M.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":903327,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229658,"text":"sir20225013 - 2022 - Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","interactions":[],"lastModifiedDate":"2026-04-08T17:28:23.084393","indexId":"sir20225013","displayToPublicDate":"2022-03-14T11:12:51","publicationYear":"2022","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":"2022-5013","displayTitle":"Evaluation of Salinity and Nutrient Conditions in the Heart River Basin, North Dakota, 1970–2020","title":"Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020","docAbstract":"The Heart River Basin is predominantly an agricultural basin in western North Dakota and is approximately 3,350 square miles. The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and the Grant County Soil Conservation District, completed a study to assess spatial and temporal patterns of water quality in the Heart River Basin. The purpose of this report is to describe the methods and results of a study to evaluate salinity and nutrients in the Heart River Basin in western North Dakota. Water-quality and streamflow data used in the study were compiled from 1970 to 2020 using the National Water Quality Monitoring Council Water Quality Portal and National Water Information System.
Changes in streamflow characteristics were investigated at three sites from 1970 to 2020, and changes in water quality were investigated at four sites from 1974 to 2019. Streamflow analysis indicated decreasing streamflow from 1970 until the late 1990s followed by increasing streamflow through 2020, with the largest increase in the 7-day minimum streamflow or base flow. For the historical water-quality trend period (1974–2019), total dissolved solids, sulfate, sodium, chloride, and sodium adsorption ratio concentrations have increased since the mid-1970s through 2019. Potassium concentrations during the historical period remained mostly constant with some small fluctuations. Calcium and magnesium concentrations increased since the mid-1970s at all sites, except for a decrease at one site between 1974 and 1999. During the recent trend period (1999–2019), increasing concentrations in total dissolved solids, sulfate, sodium, chloride, calcium, magnesium, and sodium adsorption ratios were observed across the Heart River Basin. The magnitude of the increases was smaller at tributary sites compared to main-stem sites. During the recent period, potassium was mostly constant, although small (−0.9 milligram per liter or less) decreases on tributaries and minor (1.3 milligrams per liter) increases on the main-stem sites were detected. Unlike dissolved ion concentrations, significant increases in nutrient concentrations were not detected from 1999 to 2019, but nitrate plus nitrite concentrations most likely decreased upstream from Lake Tschida.
Inverse modeling for period 1 (1974–99) in model zone 1 (Heart River reach from site 5 to site 6) had eight reasonable models that indicated the clay mineral-water interactions and dissolution of evaporites control the geochemistry. Results of the inverse modeling for period 2 (1999–2019) in model zone 1 also had eight reasonable models that indicated that the dissolution of evaporites was the major geochemical control. Results of the geochemical modeling for period 1 (1974–99) in model zone 2 (Heart River and Sweetbriar Creek reach from sites 20 and 21 to site 22) produced seven reasonable models, and the geochemical control of the system was the dissolution of sulfate evaporite minerals. Geochemical modeling results for period 2 (1999–2019) in model zone 2 produced 11 reasonable models and was also controlled by the dissolution of sulfate evaporite minerals. Differences between the two model zones indicated that geology controls some of the water-quality changes in the Heart River Basin.
Loads were estimated for total dissolved solids, sulfate, sodium, and chloride and total phosphorus. Annual loads estimated for the Heart River from 2013 through 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) were generally greatest in 2014 and least in 2016 for total dissolved solids, sulfate, sodium, and chloride. Most of the annual loads of total dissolved solids, sulfate, sodium, and chloride are delivered in March through July in the Heart River at these sites and are likely from snowmelt and spring and summer rains. The mean annual yields of total dissolved solids and sodium from 2013 to 2020 generally were largest in Big Muddy Creek (site 18), whereas yields of sulfate and chloride were largest at Sweetbriar Creek (site 21) compared to the other selected sites in the Heart River Basin. Larger yields of total dissolved solids, sulfate, sodium, and chloride at sites located on Big Muddy Creek and Sweet Briar Creek in the lower Heart River Basin were likely a result of differences in geology and soils upstream from the selected sites.
A mass balance of total dissolved solids, sulfate, sodium, and chloride was estimated for the lower Heart River Basin, specifically the reach below Lake Tschida to Mandan (site 7 to site 22). Intervening flow was the largest contributor to the dissolved ion loads in the lower Heart River Basin and is an important part of understanding the transport of dissolved ions in the basin. The intervening load can include groundwater discharge, irrigation return flow, local runoff, and input from smaller ephemeral tributaries. Tributaries in the lower Heart River Basin contributed portions of the total dissolved solids, sulfate, sodium, and chloride loads at the Heart River near Mandan (site 22) that generally were proportional to the streamflow contributions.
Annual loads for total phosphorus between 2013 and 2020 at the Heart River site upstream from Lake Tschida (site 5) and near Mandan (site 22) generally were largest in 2019 and smallest in 2016. Most of the total phosphorus loads for main-stem sites 5 and 22 were transported in March, April, and June, likely from snowmelt and early summer rains. The mean annual yields of total phosphorus for 2013–20 were largest on the main-stem site upstream from Lake Tschida (site 5) and Sweetbriar Creek (site 21), whereas the smallest yields were in Big Muddy Creek (site 18). Much of the phosphorus that enters Lake Tschida from the upper basin does not get transported downstream to the lower basin, and much of the phosphorus in the lower basin was attributed to intervening flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225013","collaboration":"Prepared in cooperation with the Department of Agriculture Natural Resources Conservation Service and Grant County Soil Conservation District","usgsCitation":"Tatge, W.S., Nustad, R.A., and Galloway, J.M., 2022, Evaluation of salinity and nutrient conditions in the Heart River Basin, North Dakota, 1970–2020: U.S. Geological Survey Scientific Investigations Report 2022–5013, 76 p., https://doi.org/10.3133/sir20225013.","productDescription":"Report: ix, 76; Data Release; Dataset","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-131163","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":397042,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397041,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P987APZ8","text":"USGS data release","linkHelpText":"Data and scripts used in water-quality trend and load analysis in the Heart River Basin, North Dakota, 1970–2020"},{"id":502299,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112690.htm","linkFileType":{"id":5,"text":"html"}},{"id":398527,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225013/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397040,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5013/images"},{"id":397039,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.XML"},{"id":397038,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5013/sir20225013.pdf","text":"Report","size":"21.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5013"},{"id":397037,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5013/coverthb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Heart River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.2769775390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 46.27863122156088\n ],\n [\n -100.8160400390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 47.25\n ],\n [\n -103.2769775390625,\n 46.27863122156088\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
You can learn a lot about rivers, lakes, estuaries, and oceans by looking down at them from the sky. Scientists use a technique called remote sensing to measure the amount of light or heat energy reflected and emitted from the Earth. Sensors can be on satellites or mounted on airplanes, helicopters, or drones. Scientists use this information to map the quality of water in the San Francisco Bay-Delta estuary. Remote sensing helps scientists see where and when there might be problems for human health or for the plants and animals living in the estuary.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frym.2022.619716","usgsCitation":"Mejia, F.H., Torgersen, C.E., and Fichot, C.G., 2022, Keeping an eye on water quality from the sky: Frontiers for Young Minds, HTML Document, https://doi.org/10.3389/frym.2022.619716.","productDescription":"HTML Document","ipdsId":"IP-123673","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":448507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frym.2022.619716","text":"Publisher Index Page"},{"id":398217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.55249023437501,\n 37.32430451813815\n ],\n [\n -121.57470703125,\n 37.32430451813815\n ],\n [\n -121.57470703125,\n 38.244651696093634\n ],\n [\n -122.55249023437501,\n 38.244651696093634\n ],\n [\n -122.55249023437501,\n 37.32430451813815\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":839741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":839742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fichot, Cedric G","contributorId":289767,"corporation":false,"usgs":false,"family":"Fichot","given":"Cedric","email":"","middleInitial":"G","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":839743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}