Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241048","usgsCitation":"Windham-Myers, L., Root, T.L., Petkewich, M.D., Musgrove, M., Gill, A.C., Weaver, J.C., Conaway, C.H., Lindsey, B.D., Parchaso, F., Knowles, N., and Tomaszewski, E.J., 2024, State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes: U.S. Geological Survey Open-File Report 2024–1048, 64 p., https://doi.org/10.3133/ofr20241048.","productDescription":"vii, 64 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-158415","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":497944,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117648.htm","linkFileType":{"id":5,"text":"html"}},{"id":462753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1048/ofr20241048.pdf","text":"Report","size":"8.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1048"},{"id":462752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1048/coverthb.jpg"}],"country":"United States","otherGeospatial":"southeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.26046308814853,\n 43.34065198513025\n ],\n [\n -71.1713607133797,\n 43.55896502744753\n ],\n [\n -75.09417377891708,\n 40.41702622060157\n ],\n [\n -76.94176883383484,\n 39.38997863980981\n ],\n [\n -77.22164958897736,\n 35.4797326167386\n ],\n [\n -81.98694844837883,\n 31.03632790667575\n ],\n [\n -91.39626305044476,\n 30.5137107036077\n ],\n [\n -91.2989713852823,\n 28.512692779158414\n ],\n [\n -88.18175904626855,\n 28.79591613221004\n ],\n [\n -86.89387148001948,\n 29.79601367137508\n ],\n [\n -83.99773737243493,\n 28.705053633372273\n ],\n [\n -82.26744490204806,\n 24.549161920326497\n ],\n [\n -81.77772710856374,\n 24.25613293881912\n ],\n [\n -79.25395823346736,\n 25.669131592981728\n ],\n [\n -80.8137017138734,\n 30.79934564119985\n ],\n [\n -75.38603247990801,\n 34.830905137914925\n ],\n [\n -74.53299323261764,\n 37.55917715000662\n ],\n [\n -72.8924569187813,\n 40.11126942721674\n ],\n [\n -69.38684780759837,\n 40.8712632604325\n ],\n [\n -69.5648600647653,\n 42.87442943706927\n ],\n [\n -68.26046308814853,\n 43.34065198513025\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth System Processes Division
Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Rivers convey a broad range of materials, such as sediment, nutrients, and contaminants. Much of this transport can occur during or immediately after an episodic, pulsed event like a flood or an oil spill. Understanding the flow processes that influence the motion of these substances is important for managing water resources and conserving aquatic ecosystems. This study introduces a new remote sensing framework for characterizing dynamic phenomena at the scale of a channel cross-section: Hyperspectral Image Transects during Transient Events in Rivers (HITTER). We present a workflow that uses repeated hyperspectral scan lines acquired from a hovering uncrewed aircraft system (UAS) to quantify how a water attribute of interest varies laterally across the river and evolves over time. Data from a tracer experiment on the Missouri River are used to illustrate the components of the end-to-end processing chain we used to quantify the passage of a visible dye. The framework is intended to be flexible and could be applied in a number of different contexts. The results of this initial proof-of-concept investigation suggest that HITTER could potentially provide insight regarding the dispersion of a range of materials in rivers, which would facilitate ecological and geomorphic studies and help inform management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16193743","usgsCitation":"Legleiter, C.J., Scholl, V.M., Sansom, B.J., and Burgess, M.A., 2024, Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA: Remote Sensing, v. 19, no. 16, 3743, 33 p., https://doi.org/10.3390/rs16193743.","productDescription":"3743, 33 p.","ipdsId":"IP-169440","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":466867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16193743","text":"Publisher Index Page"},{"id":462788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"16","noUsgsAuthors":false,"publicationDate":"2024-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":915478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scholl, Victoria Mary 0000-0002-2085-1449","orcid":"https://orcid.org/0000-0002-2085-1449","contributorId":295713,"corporation":false,"usgs":true,"family":"Scholl","given":"Victoria","email":"","middleInitial":"Mary","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":915479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sansom, Brandon James 0000-0001-7999-9547","orcid":"https://orcid.org/0000-0001-7999-9547","contributorId":289636,"corporation":false,"usgs":true,"family":"Sansom","given":"Brandon","email":"","middleInitial":"James","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":915480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burgess, Matthew Alexander 0000-0003-3487-4972 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0003-3487-4972","contributorId":225090,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"Alexander","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":915481,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259588,"text":"70259588 - 2024 - Discerning sediment provenance in the Outer Banks (USA) through detrital zircon geochronology","interactions":[],"lastModifiedDate":"2024-10-16T11:46:42.605329","indexId":"70259588","displayToPublicDate":"2024-10-09T06:44:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Discerning sediment provenance in the Outer Banks (USA) through detrital zircon geochronology","docAbstract":"Globally, aquatic ecosystems are one of the largest but most uncertain sources of methane, a potent greenhouse gas. It is unclear how climate change will affect methane emissions, but recent work suggests that glacial systems, which are melting faster with climate change, may be an important source of methane to the atmosphere. Currently, studies quantifying glacial emissions are limited in number, and the role of methanotrophy, or microbial methane oxidizers, in reducing atmospheric emissions from source and receiving waters is not well known. Here we discuss three potential sites for methane oxidation that could mitigate emissions from glaciers into the atmosphere: under ice oxidation, oxidation within proglacial lakes, and oxidation within melt rivers. The research presented here increases the number of glacial sites with methane concentration data and is one of only a few studies to quantify the net microbial activity of methane production and oxidation in two types of land-terminating glacial runoff (lake and river). We find that oxidation in a glacial river may reduce atmospheric methane emissions from glacial melt by as much as 53%. Incorporating methane oxidation in estimates of glacial methane emissions may significantly reduce the estimated magnitude of this source in budgeting exercises.
Terrestrial evapotranspiration is the second-largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross-disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.
","language":"English","publisher":"Wiley","doi":"10.1029/2024WR037622","usgsCitation":"Yi, K., Senay, G.B., Fisher, J., Wang, L., Suvocarev, K., Chu, H., Moore, G., Novick, K.A., Barnes, M.L., Keenan, T.F., Mallick, K., Luo, X., Missik, J., Delwiche, K.B., Nelson, J., Good, S., Xiao, X., Kannenberg, S., Ahmadi, A., Wang, T., Bohrer, G., Litvak, M., Reed, D., Oishi, A., Torn, M.S., and Baldocchi, D., 2024, Challenges and future directions in quantifying terrestrial evapotranspiration: Water Resources Research, v. 60, no. 10, e2024WR037622, 12 p., https://doi.org/10.1029/2024WR037622.","productDescription":"e2024WR037622, 12 p.","ipdsId":"IP-173029","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":466872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr037622","text":"Publisher Index Page"},{"id":466626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Yi, K.","contributorId":223703,"corporation":false,"usgs":false,"family":"Yi","given":"K.","email":"","affiliations":[],"preferred":false,"id":924061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":924062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Jousha B.","contributorId":349151,"corporation":false,"usgs":false,"family":"Fisher","given":"Jousha B.","affiliations":[{"id":83441,"text":"Schmid College of Science and Technology, Chapman University","active":true,"usgs":false}],"preferred":false,"id":924063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Lixin","contributorId":300466,"corporation":false,"usgs":false,"family":"Wang","given":"Lixin","affiliations":[{"id":65165,"text":"Department of Earth Sciences, Indiana University–Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA.","active":true,"usgs":false}],"preferred":false,"id":924064,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Suvocarev, Kosana","contributorId":196381,"corporation":false,"usgs":false,"family":"Suvocarev","given":"Kosana","email":"","affiliations":[],"preferred":false,"id":924065,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chu, Housen","contributorId":330059,"corporation":false,"usgs":false,"family":"Chu","given":"Housen","affiliations":[{"id":78784,"text":"Lawrence Berkeley National Lab, Berkeley, CA 94702, USA","active":true,"usgs":false}],"preferred":false,"id":924066,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Georgianne W.","contributorId":349152,"corporation":false,"usgs":false,"family":"Moore","given":"Georgianne W.","affiliations":[{"id":48171,"text":"Department of Biology, Georgia Southern University","active":true,"usgs":false}],"preferred":false,"id":924067,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Novick, Kimberly A.","contributorId":196379,"corporation":false,"usgs":false,"family":"Novick","given":"Kimberly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":924068,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barnes, Mallory L.","contributorId":239670,"corporation":false,"usgs":false,"family":"Barnes","given":"Mallory","email":"","middleInitial":"L.","affiliations":[{"id":39756,"text":"School of Public and Environmental Affairs, Indiana University, Bloomington, IN","active":true,"usgs":false}],"preferred":false,"id":924069,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Keenan, Trevor F. 0000-0002-3347-0258","orcid":"https://orcid.org/0000-0002-3347-0258","contributorId":217397,"corporation":false,"usgs":false,"family":"Keenan","given":"Trevor","email":"","middleInitial":"F.","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":924070,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mallick, Kanishka","contributorId":345844,"corporation":false,"usgs":false,"family":"Mallick","given":"Kanishka","email":"","affiliations":[{"id":82729,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":924071,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Luo, Xiangzhong","contributorId":349153,"corporation":false,"usgs":false,"family":"Luo","given":"Xiangzhong","affiliations":[{"id":83444,"text":"Department of Geography, National University of Singapore, Singapore","active":true,"usgs":false}],"preferred":false,"id":924072,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Missik, Justine E.C.","contributorId":349154,"corporation":false,"usgs":false,"family":"Missik","given":"Justine E.C.","affiliations":[{"id":83445,"text":"Department of Civil, Environmental and Geodetic Engineering, Ohio State University","active":true,"usgs":false}],"preferred":false,"id":924073,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Delwiche, Kyle B.","contributorId":139866,"corporation":false,"usgs":false,"family":"Delwiche","given":"Kyle","email":"","middleInitial":"B.","affiliations":[{"id":13299,"text":"Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":924074,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Nelson, Jacob A.","contributorId":349155,"corporation":false,"usgs":false,"family":"Nelson","given":"Jacob A.","affiliations":[{"id":83446,"text":"Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Germany","active":true,"usgs":false}],"preferred":false,"id":924075,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Good, Stephen P.","contributorId":349156,"corporation":false,"usgs":false,"family":"Good","given":"Stephen P.","affiliations":[{"id":83447,"text":"Department of Biological and Ecological Engineering, Oregon State University, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":924076,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Xiao, Xiangming","contributorId":150759,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","affiliations":[{"id":18095,"text":"Center for Spatial Analysis, U of OK, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":924077,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kannenberg, Steven A.","contributorId":349157,"corporation":false,"usgs":false,"family":"Kannenberg","given":"Steven A.","affiliations":[{"id":83448,"text":"Department of Biology, West Virginia University, Morgantown","active":true,"usgs":false}],"preferred":false,"id":924078,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ahmadi, Arman","contributorId":349158,"corporation":false,"usgs":false,"family":"Ahmadi","given":"Arman","affiliations":[{"id":83449,"text":"Department ERIN, Luxembourg Institute of Science and Technology, Luxembourg","active":true,"usgs":false}],"preferred":false,"id":924079,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wang, Tianxin","contributorId":333378,"corporation":false,"usgs":false,"family":"Wang","given":"Tianxin","email":"","affiliations":[{"id":79858,"text":"Unversity of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":924080,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Bohrer, Gil 0000-0002-9209-9540","orcid":"https://orcid.org/0000-0002-9209-9540","contributorId":217401,"corporation":false,"usgs":false,"family":"Bohrer","given":"Gil","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":924081,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Litvak, Marcy E.","contributorId":349159,"corporation":false,"usgs":false,"family":"Litvak","given":"Marcy E.","affiliations":[{"id":83450,"text":"Department of Biology, The University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":924082,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Reed, David E.","contributorId":349160,"corporation":false,"usgs":false,"family":"Reed","given":"David E.","affiliations":[{"id":83451,"text":"School of the Environment, Yale University, New Haven","active":true,"usgs":false}],"preferred":false,"id":924083,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Oishi, A. Christopher","contributorId":349161,"corporation":false,"usgs":false,"family":"Oishi","given":"A. Christopher","affiliations":[{"id":83452,"text":"U.S. Department of Agriculture Forest Service Southern Research Station, Coweeta Hydrologic Laboratory, NC, USA","active":true,"usgs":false}],"preferred":false,"id":924084,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Torn, Margaret S. 0000-0002-8174-0099","orcid":"https://orcid.org/0000-0002-8174-0099","contributorId":177740,"corporation":false,"usgs":false,"family":"Torn","given":"Margaret","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":924085,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Baldocchi, Dennis 0000-0003-3496-4919","orcid":"https://orcid.org/0000-0003-3496-4919","contributorId":167495,"corporation":false,"usgs":false,"family":"Baldocchi","given":"Dennis","affiliations":[{"id":24725,"text":"Ecosystem Science Division, Department of Environmental Science","active":true,"usgs":false}],"preferred":false,"id":924086,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70259631,"text":"70259631 - 2024 - Body size and early marine conditions drive changes in Chinook salmon productivity across northern latitude ecosystems","interactions":[],"lastModifiedDate":"2024-10-18T11:59:17.555913","indexId":"70259631","displayToPublicDate":"2024-10-08T06:57:13","publicationYear":"2024","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":"Body size and early marine conditions drive changes in Chinook salmon productivity across northern latitude ecosystems","docAbstract":"Disentangling the influences of climate change from other stressors affecting the population dynamics of aquatic species is particularly pressing for northern latitude ecosystems, where climate-driven warming is occurring faster than the global average. Chinook salmon (Oncorhynchus tshawytscha) in the Yukon-Kuskokwim (YK) region occupy the northern extent of their species' range and are experiencing prolonged declines in abundance resulting in fisheries closures and impacts to the well-being of Indigenous people and local communities. These declines have been associated with physical (e.g., temperature, streamflow) and biological (e.g., body size, competition) conditions, but uncertainty remains about the relative influence of these drivers on productivity across populations and how salmon–environment relationships vary across watersheds. To fill these knowledge gaps, we estimated the effects of marine and freshwater environmental indicators, body size, and indices of competition, on the productivity (adult returns-per-spawner) of 26 Chinook salmon populations in the YK region using a Bayesian hierarchical stock-recruitment model. Across most populations, productivity declined with smaller spawner body size and sea surface temperatures that were colder in the winter and warmer in the summer during the first year at sea. Decreased productivity was also associated with above average fall maximum daily streamflow, increased sea ice cover prior to juvenile outmigration, and abundance of marine competitors, but the strength of these effects varied among populations. Maximum daily stream temperature during spawning migration had a nonlinear relationship with productivity, with reduced productivity in years when temperatures exceeded thresholds in main stem rivers. These results demonstrate for the first time that well-documented declines in body size of YK Chinook salmon were associated with declining population productivity, while taking climate into account.
In 2020, Colorado experienced the most severe wildfire season in recorded history, with wildfires burning 625 357 acres across the state. Two of the largest fires burned parts of Rocky Mountain National Park (RMNP), and a study was initiated to address concerns about potential effects on drinking water quality from mobilization of ash and sediment. The study took advantage of a wealth of pre-fire data from adjacent burned and unburned basins in western RMNP. Pre- and post-fire data collection included discrete sample collection and high-frequency water-quality measurements using in-stream sensors. Kruskal–Wallis tests on discrete data indicated that specific conductance, base cations, sulphate, chloride, nitrate, and total dissolved nitrogen concentrations increased post-fire, whereas silica and dissolved organic carbon (DOC) did not (p ≤ 0.05). In-stream sensors captured large spikes in concentrations of nutrients, turbidity, and DOC in the burned basin that were missed by discrete sampling. Sensor data indicated nitrate and turbidity increased by up to one and two orders of magnitude, respectively, from pre-event concentrations during storms, and DOC increased up to 3.5×. Empirical regression equations were developed using pre-fire data and applied to the post-fire period to estimate expected stream chemistry in the absence of fire (a ‘no-fire’ scenario). Overlays of actual post-fire chemistry showed the timing and magnitude of differences between observed and ‘estimated’ chemistry. For most solutes, observed post-fire concentrations were notably greater than expected under the ‘no-fire’ scenario, and differences were greatest during storm events. Comparison of data from the burned and unburned basins indicated DOC concentrations were affected by climate as well as fire. Results from this study demonstrate the importance of both pre-fire data and high-frequency data for characterizing dynamic hydrochemical responses in wildfire-affected areas.
Non-spatial models of competition between floating aquatic vegetation (FAV) and submersed aquatic vegetation (SAV) predict a stable state of pure SAV at low total available limiting nutrient level, N, a stable state of only FAV for high N, and alternative stable states for intermediate N, as described by an S-shaped bifurcation curve. Spatial models that include physical heterogeneity of the waterbody show that the sharp transitions between these states become smooth. We examined the effects of heterogeneous initial conditions of the vegetation types. We used a spatially explicit model to describe the competition between the vegetation types. In the model, the FAV, duckweed (L. gibba), competed with the SAV, Nuttall's waterweed (Elodea nuttallii). Differences in the initial establishment of the two macrophytes affected the possible stable equilibria. When initial biomasses of SAV and FAV differed but each had the same initial biomass in each spatial cell, the S-shaped bifurcation resulted, but the critical transitions on the N-axis are shifted, depending on FAV:SAV biomass ratio. When the initial biomasses of SAV and FAV were randomly heterogeneously distributed among cells, the vegetation pattern of the competing species self-organized spatially, such that many different stable states were possible in the intermediate N region. If N was gradually increased or decreased through time from a stable state, the abrupt transitions of non-spatial models were changed into smoother transitions through a series of stable states, which resembles the Busse balloon observed in other systems.
Designated in 1978, Kaloko-Honokōhau National Historical Park is located on the west coast of the Island of Hawaiʻi. The Kaloko-Honokōhau National Historical Park encompasses about 1,200 acres of coastal land and nearshore ecosystems, which include wetlands, anchialine pools (landlocked bodies of brackish water with hydrologic connections to the ocean), fishponds, a fishtrap, and coral reefs. These nearshore ecosystems are dependent on groundwater discharge with a freshwater component and provide habitat for threatened and endangered, endemic species, such as the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) and the Hawaiian coot (ʻAlae keʻokeʻo, Fulica alai). The populations of these native species, however, are threatened because of habitat loss related to urban development and environmental changes. Kaloko-Honokōhau National Historical Park is within the Keauhou aquifer system and the North Kona District, which experienced a 52 percent resident-population increase between 2000 and 2020 and a 41 percent visitor increase between 2008 and 2019. To support the current water demand associated with this growing population, groundwater is the primary source of freshwater used in the North Kona District, with about 15 million gallons of groundwater withdrawn from the Keauhou aquifer system per day since 2009. With anticipated development, future (2015–35) groundwater withdrawal from the Keauhou aquifer system is projected to be about 55 percent greater than recent (2012–14) withdrawal. Because Kaloko-Honokōhau National Historical Park is located within a coastal aquifer, natural and human-induced changes can affect the quality and quantity of groundwater, which can threaten groundwater-dependent ecosystems.
To improve understanding of recent groundwater conditions, the U.S. Geological Survey, in cooperation with the National Park Service, undertook this study to document correlations between hydrologic time-series datasets from sites in and near Kaloko-Honokōhau National Historical Park using the nonparametric (distribution-free) Kendall’s tau statistical test.
For the statistical analyses, dependent variables representing the groundwater system include groundwater level, the groundwater-level difference between pairs of sites, and specific conductance, and independent variables include datasets of sea level, rainfall, and groundwater withdrawal. About 34 percent of the 140 non-time-lagged Kendall’s tau statistical tests evaluated in this report are statistically significant (p-value ≤ 0.050) with generally weak (0.1 ≤ tau ≤ 0.2) to moderate (0.2 ≤ tau ≤ 0.3) correlations. Groundwater levels measured at monitoring sites have the strongest correlation with the multivariate El Niño–Southern Oscillation index and withdrawal from production wells at the nearby Kohanaiki Private Club Community. Specific conductance is not consistently and significantly correlated with the independent hydrologic variables investigated in this report.
Because the relations between hydrologic variables are commonly not instantaneous, a second set of correlations was evaluated after applying a range of time lags to the independent variable datasets. Relative to the non-time-lagged case (the set of correlations that did not use time-lagged independent variables), some of the time-lagged independent variables improved correlations with some of the dependent variables. For a particular independent variable, similar time lags were expected between the independent variable and dependent variable at all four monitoring sites. However, different time lags among the four sites sometimes produced the strongest correlations.
This study identified several correlations that are statistically significant and hydrologically plausible, but the correlations could indicate that multiple concurrent factors are controlling the observed groundwater-system response, which might be better addressed using multivariate analyses. This study only investigates bivariate correlations, which may not explain all the variance in the data. The correlations analyzed in this report are limited by the quantity of available hydrologic data in the area near Kaloko-Honokōhau National Historical Park and are based on 14 years of time-series data, which were aggregated to a relatively coarse monthly temporal resolution that represents the minimum resolution common to all datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245084","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Okuhata, B.K., and Oki, D.S., 2024, Correlation analysis of groundwater and hydrologic data, Kaloko-Honokōhau National Historical Park, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2024–5084, 38 p., https://doi.org/10.3133/sir20245084.","productDescription":"ix, 38 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-154287","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":462626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5084/covrthb.jpg"},{"id":462627,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5084/sir20245084.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":462628,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5084/sir20245084.xml"},{"id":462629,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5084/images"},{"id":462630,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245084/full"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaloko-Honokōhau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.083351222759,\n 19.721737271204077\n ],\n [\n -156.083351222759,\n 19.65199485292854\n ],\n [\n -155.98955903724118,\n 19.65199485292854\n ],\n [\n -155.98955903724118,\n 19.721737271204077\n ],\n [\n -156.083351222759,\n 19.721737271204077\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
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The Boston Harbor Islands is the only coastal drumlin archipelago in the USA, featuring a distinctive and uncommon geological intertidal habitat known as mixed coarse substrate, which supports a range of coastal species and ecological processes. Recently designated as one of America’s 11 most endangered historic places due to climate change impacts, coastal adaptation and restoration efforts are crucial to their preservation. Such efforts can benefit from historic and current knowledge of endemic and emergent biodiversity. To investigate broad trends in coastal biodiversity, we compiled an inventory of marine coastal macroalgae, macroinvertebrates, fish, mammals, and shorebirds observed in the harbor since 1861. Records span 159 years, consisting of 451 unique taxa from 19 phyla. Analysis of average taxonomic distinctness (AvTD) revealed increases in diversity towards the end of the twentieth and early twenty-first century, likely associated with improved water quality (dissolved oxygen; AvTD > 85, p = 0.01) due to harbor restoration in the 1980s. Macroinvertebrates comprised 50% of the records, making this the most diverse taxonomic group in the time series. A significant increase of non-indigenous species, primarily macroinvertebrates and macroalgae, was observed over the last 20 years near human infrastructure and across multiple islands, a consequence of global change and characteristic of most urban harbors. The mixed coarse intertidal habitat, which makes up > 70% of Boston Harbor’s inner islands and supports high macroinvertebrate and macroalgal diversity (47% of species records), is not routinely monitored; our findings serve as a foundational resource for climate adaptation projects and decision-making.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12526-024-01462-4","usgsCitation":"Putnam, A., Endyke, S.C., Jones, A., Lockwood, L., Taylor, J., Albert, M., and Staudinger, M., 2024, Historical insights, current challenges: Tracking marine biodiversity in an urban harbor ecosystem in the face of climate change: Marine Biodiversity, v. 54, 78, 19 p., https://doi.org/10.1007/s12526-024-01462-4.","productDescription":"78, 19 p.","ipdsId":"IP-165901","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":487966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12526-024-01462-4","text":"Publisher Index Page"},{"id":486520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Boston Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.06841368855036,\n 42.367993628173906\n ],\n [\n -71.06841368855036,\n 42.24541634591702\n ],\n [\n -70.85625966758792,\n 42.24541634591702\n ],\n [\n -70.85625966758792,\n 42.367993628173906\n ],\n [\n -71.06841368855036,\n 42.367993628173906\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","noUsgsAuthors":false,"publicationDate":"2024-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Putnam, Alysha B.","contributorId":336857,"corporation":false,"usgs":false,"family":"Putnam","given":"Alysha B.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":938102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Endyke, Sarah C.","contributorId":335365,"corporation":false,"usgs":false,"family":"Endyke","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":938103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Ally Rose 0009-0009-3686-1623","orcid":"https://orcid.org/0009-0009-3686-1623","contributorId":336861,"corporation":false,"usgs":true,"family":"Jones","given":"Ally Rose","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":938104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lockwood, Lucy A.D. 0000-0002-7162-3198","orcid":"https://orcid.org/0000-0002-7162-3198","contributorId":352258,"corporation":false,"usgs":false,"family":"Lockwood","given":"Lucy A.D.","affiliations":[{"id":63571,"text":"University of Massachusetts Boston","active":true,"usgs":false}],"preferred":false,"id":938105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Justin","contributorId":336859,"corporation":false,"usgs":false,"family":"Taylor","given":"Justin","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":938106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Albert, Marc","contributorId":335163,"corporation":false,"usgs":false,"family":"Albert","given":"Marc","email":"","affiliations":[],"preferred":false,"id":938107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":206655,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":938108,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261889,"text":"70261889 - 2024 - Distribution and trends of endemic Hawaiian waterbirds, 1986–2023","interactions":[],"lastModifiedDate":"2024-12-31T16:26:54.091554","indexId":"70261889","displayToPublicDate":"2024-10-07T10:19:20","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":138,"text":"Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"HCSU-113","title":"Distribution and trends of endemic Hawaiian waterbirds, 1986–2023","docAbstract":"This study updates the status assessment of four endemic endangered Hawaiian waterbird species—ae‘o (Hawaiian stilt, Himantopus mexicanus knudseni), ‘alae ke‘oke‘o (Hawaiian coot, Fulica alai), ‘alae ‘ula (Hawaiian gallinule, Gallinula galeata sandvicensis), and koloa maoli (Hawaiian duck, Anas wyvilliana)—from 1986 to 2016 by incorporating new data from 2017–2023. State-space models, which account for biological and sampling variation, were fitted to estimate population sizes and trends from both core and non-core wetland survey sites. Long-term trends (1986–2023) largely show increasing populations for all four species, but recent short-term trajectories (2013–2023) are to a greater degree than previous analyses, predominantly negative, indicating accentuated declines in some island populations. Summer counts have declined relative to winter counts over the 38-year period, indicating potential changes in habitat availability and breeding patterns due to shifting rainfall patterns. Although negative trends were apparent in some non-core wetlands, our study underscores the importance of both core and non-core wetlands for waterbird populations.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gorresen, P. Marcos 0000-0002-0707-9212","orcid":"https://orcid.org/0000-0002-0707-9212","contributorId":196628,"corporation":false,"usgs":false,"family":"Gorresen","given":"P. Marcos","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":922162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":922163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":922164,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270828,"text":"70270828 - 2024 - Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range","interactions":[],"lastModifiedDate":"2025-08-25T15:00:00.72447","indexId":"70270828","displayToPublicDate":"2024-10-07T09:54:52","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range","docAbstract":"Forest and woodland decline is predicted to be increasingly influenced by meteorological variation and climate change in the future. By determining how meteorological variation leads to similar versus differing ecohydrological dynamics of forest and woodland ecosystems, we can gain insight on how future climate-driven declines may be realized. We characterized 23 mixed conifer forest (MC), ponderosa pine forest (PP) and piñon pine–juniper woodland (PJ) sites with different canopy covers in southern Nevada, USA. We compared meteorological variation between these sites and employed water balance modelling and information theory to estimate similarity in the density distributions of soil temperature (Ts), soil water potential (SWP) and transpiration partitioning into total evapotranspiration (T/ET) within and across ecosystems in wetter and drier seasons and in cooler and warmer decades. From 1941 to 2020, this location experienced declines in meteorological water deficit due to higher precipitation, although temperatures increased over more recent time periods (1981–2020). From 1981 to 2020, we generally found greater similarity in SWP and T/ET distributions within MC sites and PP sites in the cool season and in the warm season generally found greater similarity in Ts and T/ET distributions within and between PP and PJ sites (excepting T/ET between PJ sites and higher canopy cover PP sites). Recent warm decades promoted convergence in warm and cool season Ts dynamics, such that Ts dynamics generally became more similar between higher elevation MC sites and lower elevation PP–PJ sites. At the same time, warmer decades initiated divergence of SWP and T/ET dynamics within groups of MC–PP and PP–PJ sites that were formerly more similar to each other (excepting SWP in wet seasons). Although their dynamics will remain strongly coupled to precipitation, warming temperatures have the potential to promote divergence in the ecohydrological dynamics of ecosystems at lower and higher elevations in this sky island system and may also promote novel within-ecosystem divergence associated with variation in vegetation structural attributes.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.2703","usgsCitation":"Petrie, M., Bradford, J.B., and Schlaepfer, D.R., 2024, Temperature-driven convergence and divergence of ecohydrological dynamics in the ecosystems of a sky island mountain range: Ecohydrology, v. 17, no. 7, e2703, 20 p., https://doi.org/10.1002/eco.2703.","productDescription":"e2703, 20 p.","ipdsId":"IP-164379","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":494739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.95435956484613,\n 36.566365259428736\n ],\n [\n -115.95435956484613,\n 36.25503150669982\n ],\n [\n -115.03667455367618,\n 36.34361887573249\n ],\n [\n -115.04986536016149,\n 36.59813625773428\n ],\n [\n -115.95435956484613,\n 36.566365259428736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Petrie, M.D.","contributorId":192983,"corporation":false,"usgs":false,"family":"Petrie","given":"M.D.","email":"","affiliations":[],"preferred":false,"id":947152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":222784,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":947154,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259599,"text":"70259599 - 2024 - Applying portfolio theory to benefit endangered amphibians in coastal wetlands threatened by climate change, high uncertainty, and significant investment risk","interactions":[],"lastModifiedDate":"2024-10-16T11:58:54.698279","indexId":"70259599","displayToPublicDate":"2024-10-06T06:57:07","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Applying portfolio theory to benefit endangered amphibians in coastal wetlands threatened by climate change, high uncertainty, and significant investment risk","docAbstract":"The challenge of selecting strategies to adapt to climate change is complicated by the presence of irreducible uncertainties regarding future conditions. Decisions regarding long-term investments in conservation actions contain significant risk of failure due to these inherent uncertainties. To address this challenge, decision makers need an arsenal of sophisticated but practical tools to help guide spatial conservation strategies. Theory asserts that managing risks can be achieved by diversifying an investment portfolio to include assets – such as stocks and bonds – that respond inversely to one another under a given set of conditions. We demonstrate an approach for formalizing the diversification of conservation assets (land parcels) and actions (restoration, species reintroductions) by using correlation structure to quantify the degree of risk for any proposed management investment. We illustrate a framework for identifying future habitat refugia by integrating species distribution modeling, scenarios of climate change and sea level rise, and impacts to critical habitat. Using the plains coqui (Eleutherodactylus juanariveroi), an endangered amphibian known from only three small wetland populations on Puerto Rico’s coastal plains, we evaluate the distribution of potential refugia under two model parameterizations and four future sea-level rise scenarios. We then apply portfolio theory using two distinct objective functions and eight budget levels to inform investment strategies for mitigating risk and increasing species persistence probability. Models project scenario-specific declines in coastal freshwater wetlands from 2% to nearly 30% and concurrent expansions of transitional marsh and estuarine open water. Conditional on the scenario, island-wide species distribution is predicted to contract by 25% to 90%. Optimal portfolios under the first objective function – benefit maximization – emphasizes translocating frogs to existing protected areas rather than investing in the protection of new habitat. Alternatively, optimal strategies using the second objective function – a risk-benefit tradeoff framework – include significant investment to protect parcels for the purpose of reintroduction or establishing new populations. These findings suggest that leveraging existing protected areas for species persistence, while less costly, may contain excessive risk and could result in diminished conservation benefits. Although our modeling includes numerous assumptions and simplifications, we believe this framework provides useful inference for exploring resource dynamics and developing robust adaptation strategies using an approach that is generalizable to other conservation problems which are spatial or portfolio in nature and subject to unresolvable uncertainty.
As part of a cooperative investigation between the U.S. Geological Survey and the Alabama Department of Agriculture and Industries, a network of 22 groundwater wells were sampled from 2014 through 2020 for about 230 pesticide and pesticide degradate compounds. Wells were located in three regions of intensive agricultural land use in Alabama: Baldwin County, the Wiregrass region, and the Tennessee River valley region.
Metolachlor sulfonic acid, a degradate of the herbicide metolachlor, was the most frequently detected compound, occurring in about 70 percent of the samples. Three other compounds, metolachlor, atrazine, and 2-chloro-4-isopropylamino-6-amino-s-triazine, were also detected in more than half of the samples. Metolachlor and its degradates accounted for 33 of the 50 greatest compound concentrations study-wide, including the maximum pesticide concentration across all compounds (62,500 nanograms per liter). The frequency and magnitude of detections of many specific pesticide compounds varied among the three regions, but all detected pesticide concentrations were well below the U.S. Environmental Protection Agency maximum contaminant levels and applicable human health benchmarks.
Sample results were combined with results of previous (2009–13) sampling to provide a continuous time-series of data for 2009–20. More than half of the 289 pesticide compounds analyzed during 2009–20 were not detected in any samples. Only four compounds were detected at great enough frequency throughout the 10 sampling years to evaluate patterns of change through time. Metolachlor and its degradate, metolachlor sulfonic acid, were frequently detected in all regions. Atrazine and its degradate, 2-chloro-4-isopropylamino-6-amino-s-triazine, were also detected in wells from all regions, but the variability and magnitude of concentrations were greatest in the Tennessee River valley region. No apparent temporal pattern in concentrations was found.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245069","issn":"2328-0328","collaboration":"Prepared in cooperation with the Alabama Department of Agriculture and Industries","usgsCitation":"Gill, A.C., 2024, Pesticide occurrence in shallow groundwater in three regions of agricultural land use: Baldwin County, the Wiregrass region, and the Tennessee River valley region of Alabama, 2009–20: U.S. Geological Survey Scientific Investigations Report 2024–5069, 50 p., https://doi.org/10.3133/sir20245069.","productDescription":"Report: viii, 50 p.; 2 Data Releases","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-124243","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":499053,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117645.htm","text":"Baldwin County and Wiregrass region region","linkFileType":{"id":5,"text":"html"}},{"id":462612,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS NWIS Data Release","linkHelpText":"- USGS water data for the Nation"},{"id":462618,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245069/full","description":"SIR 2024-5069 HTML"},{"id":462609,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5069/sir20245069.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2024-5069 XML"},{"id":462608,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5069/sir20245069.pdf","size":"5.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5069"},{"id":462607,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5069/images"},{"id":462606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5069/coverthb.jpg"},{"id":499052,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117644.htm","text":"Tennessee Valley region","linkFileType":{"id":5,"text":"html"}},{"id":462611,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96OOHNZ","text":"USGS Data Release","linkHelpText":"- Pesticide concentration and related water-quality data for selected groundwater sites near areas of agricultural land use in Alabama, 2009–2020"}],"country":"United States","state":"Alabama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.23168853448631,\n 30.191218364802225\n ],\n [\n -87.23168853448631,\n 31.202019682928764\n ],\n [\n -88.02270415948634,\n 31.202019682928764\n ],\n [\n -88.02270415948634,\n 30.191218364802225\n ],\n [\n -87.23168853448631,\n 30.191218364802225\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.69335845636155,\n 31.032720603772802\n ],\n [\n -85.0234365813612,\n 31.032720603772802\n ],\n [\n -85.0234365813612,\n 32.11842944019466\n ],\n [\n -86.69335845636155,\n 32.11842944019466\n ],\n [\n -86.69335845636155,\n 31.032720603772802\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.28675227176826,\n 35.04758320679862\n ],\n [\n -88.28675227176826,\n 34.115944393543984\n ],\n [\n -86.59485774051834,\n 34.115944393543984\n ],\n [\n -86.59485774051834,\n 35.04758320679862\n ],\n [\n -88.28675227176826,\n 35.04758320679862\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"Changes in the pressure or location of magma can stress or break surrounding rocks and trigger flow of nearby waters and gases, causing seismic signals, such as discrete earthquakes and tremor. These phenomena are types of seismic unrest that commonly precede eruption and can be used to forecast volcanic activity. Mass movements at the surface, including avalanches, debris flows, and lahars, may also generate seismic signals that are specifically addressed in chapter H, this volume (Thelen and others, 2024). Our focus in this chapter is to determine the levels of instrumentation recommended to produce high-quality, well-constrained seismic observations important for early warning of impending eruptions, detecting changes in ongoing eruptions, and characterizing other hazardous volcanic events.
There are emerging techniques and new types of instrumentation, such as distributed acoustic sensing or rotational seismometers, that we do not consider here. These types of instrumentation show promise for monitoring but still require maturation before being considered more generally in volcano monitoring.
Most of the capabilities mentioned below are universal for all types of volcanic systems, although some are best applied to stratovolcanoes with an apical single vent. In some settings, such as calderas or shield volcanoes, we must broaden coverage to include multiple possible storage regions or vent locations. As an example, Thelen (2014) discretized the long rift zones of shield volcanoes in Hawaiʻi as a set of evenly spaced “vents.” In this construct, each vent comes with recommendations, and several thousand network configurations were simulated to assess the effect on network quality levels and to determine the most efficient network design. The same process could be applied in a caldera setting or a volcanic field, where an evenly spaced grid of potential vents is considered. Localized recommendations for each unique system are beyond the scope of this report and left up to local experts to assess based on the conditions, restrictions, and requirements of each volcano.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062B","usgsCitation":"Thelen, W.A., Lyons, J.J., Wech, A.G., Moran, S.C., Haney, M.M., and Flinders, A.F., 2024, Seismic techniques and suggested instrumentation to monitor volcanoes, chap. B of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–B, 9 p., https://doi.org/10.3133/sir20245062B.","productDescription":"iii, 9 p.","numberOfPages":"9","onlineOnly":"N","ipdsId":"IP-150995","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462620,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/b/covrthbb.jpg"},{"id":462621,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/b/sir20245062b.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Mangroves can increase their elevation relative to tidal flooding through biogeomorphic feedbacks but can submerge if rates of sea-level rise are too great. There is an urgent need to understand the vulnerability of mangroves to sea-level rise so local communities and resource managers can implement and prioritize actions. The need is especially pressing for small islands, which have been identified as an area of concern by the IPCC. We developed a generalizable modeling framework for tidal wetlands (WARMER-3) that accounts for species interactions and the belowground processes that dictate soil elevation building relative to sea levels. The model was calibrated with extensive field datasets, including accretion rates derived from 29 soil cores, over 300 forest inventory plots, water level, and elevation. The model included five mangrove tree species and was applied across seven regions around the Pacific Island of Pohnpei, Federated States of Micronesia, where mangrove forest is a critical ecosystem that supports subsistence living for local communities. We explored mangrove resilience and carbon accumulation under six sea-level rise scenarios. We also conducted an analysis to determine the sea-level rise rate threshold above which mangroves would be lost. The results suggest that Pohnpei mangroves can build their elevations relative to low and moderate rates of sea-level rise to prevent submergence, with limited loss of mangrove area through 2150. Under higher sea-level rise rates, however, forest elevation decreased substantially relative to mean sea level and there was extensive loss of mangrove area by that year. Regarding mangrove community composition, for all sea-level rise scenarios, the model predicted a change to increasing relative abundance of flood tolerant species and decreasing relative abundance of high-elevation species, which started to being realized by 2100. Variation in sediment supply, water levels, and elevation capital led to differential vulnerability around the island. We identified a threshold for Pohnpei mangroves where if local sea-level rise rates exceed 7.8 ± 2.2 mm/year they are projected to eventually submerge and be lost. Our modeling framework is novel by addressing both species interactions and critical belowground processes to better understand potential tidal ecosystem responses to sea-level rise.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-024-01422-y","usgsCitation":"Buffington, K., Carr, J., Mackenzie, R., Apwong, M., Krauss, K., and Thorne, K., 2024, Projecting mangrove forest resilience to sea-level rise on a Pacific Island: Species dynamics and ecological thresholds: Estuaries and Coasts, v. 47, p. 2174-2189, https://doi.org/10.1007/s12237-024-01422-y.","productDescription":"17 p.","startPage":"2174","endPage":"2189","ipdsId":"IP-165799","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":464362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Federated States of Micronesia","otherGeospatial":"Pohnpei","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 158.07984414004875,\n 7.009358068074874\n ],\n [\n 158.07984414004875,\n 6.766699284998481\n ],\n [\n 158.36071659346305,\n 6.766699284998481\n ],\n [\n 158.36071659346305,\n 7.009358068074874\n ],\n [\n 158.07984414004875,\n 7.009358068074874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2024-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":918965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mackenzie, Richard","contributorId":264789,"corporation":false,"usgs":false,"family":"Mackenzie","given":"Richard","affiliations":[{"id":34924,"text":"U. Florida","active":true,"usgs":false}],"preferred":false,"id":918966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Apwong, Maybeleen","contributorId":251804,"corporation":false,"usgs":false,"family":"Apwong","given":"Maybeleen","email":"","affiliations":[{"id":25408,"text":"Institute of Pacific Islands Forestry, Pacific Southwest Research Station, Hilo, HI, USA","active":true,"usgs":false}],"preferred":true,"id":918967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":223022,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":918968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918969,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259169,"text":"sir20245062K - 2024 - Special topic—Boreholes","interactions":[{"subject":{"id":70259169,"text":"sir20245062K - 2024 - Special topic—Boreholes","indexId":"sir20245062K","publicationYear":"2024","noYear":false,"chapter":"K","displayTitle":"Special Topic—Boreholes","title":"Special topic—Boreholes"},"predicate":"IS_PART_OF","object":{"id":70259167,"text":"sir20245062 - 2024 - Recommended capabilities and instrumentation for volcano monitoring in the United States","indexId":"sir20245062","publicationYear":"2024","noYear":false,"title":"Recommended capabilities and instrumentation for volcano monitoring in the United States"},"id":1}],"isPartOf":{"id":70259167,"text":"sir20245062 - 2024 - Recommended capabilities and instrumentation for volcano monitoring in the United States","indexId":"sir20245062","publicationYear":"2024","noYear":false,"title":"Recommended capabilities and instrumentation for volcano monitoring in the United States"},"lastModifiedDate":"2024-10-17T20:43:58.628693","indexId":"sir20245062K","displayToPublicDate":"2024-10-04T10:29:35","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5062","chapter":"K","displayTitle":"Special Topic—Boreholes","title":"Special topic—Boreholes","docAbstract":"Installation of instrument packages in deep (several hundred to several thousand meters) boreholes near volcanoes is relatively expensive (a few million to tens of millions of U.S. dollars), but can provide a low-noise, high-quality source of geophysical (seismic, strain, tilt, and pore pressure), physical (temperature and water level), and geochemical data. Observations from instruments at depth have the potential to provide insights into processes associated with magma intrusion, unrest, and eruption that would not otherwise be possible (Lowenstern and others, 2017; Eichelberger, 2020). Examples of instrumented boreholes in volcanic areas include the 3-kilometer (km)-deep Long Valley Exploratory Well (LVEW) in California (for example, Priest and others, 1998; Prejean and Ellsworth, 2001; Fischer and others, 2003; Roeloffs and others, 2003; Sorey and others, 2003), the 1,262 meter-deep NSF Well (commonly referred to as the “Keller Well”) within the summit caldera of Kīlauea, Hawaiʻi (Keller and others, 1979; Myren and others, 2006), and the Caribbean Andesite Lava Island-volcano Precision Seismo-geodetic Observatory (CALIPSO) project at Soufrière Hills, Montserrat, which includes a series of four 200-meter (m)-deep holes (for example, Mattioli and others, 2004; Voight and others, 2006). The Plate Boundary Observatory (PBO) of the National Science Foundation’s Earthscope project placed seismometers, tiltmeters, strainmeters, and pore-pressure sensors at depths of 100 to 250 m in more than 100 boreholes scattered in western North America, including at Mount St. Helens, Washington, and Yellowstone Caldera, Wyoming. The total cost for an instrumented PBO borehole ranged from $250,000 to $270,000 U.S. dollars (USD) and a few thousand USD are required annually for maintenance (David Mencin, UNAVCO, written commun., October 2020).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062K","usgsCitation":"Hurwitz, S., and Lowenstern, J.B., 2024, Special topic—Boreholes, chap. K of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062K.","productDescription":"iii, 5 p.","numberOfPages":"5","onlineOnly":"N","ipdsId":"IP-148975","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/k/covrthbk.jpg"},{"id":462414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/k/sir20245062k.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Submarine volcanoes produce much of the same seismicity and eruptive activity as subaerial volcanoes and can pose hazards to society. Although they can be monitored with similar techniques and methods as described in other chapters of this volume, their submerged location brings unique challenges. This chapter addresses these challenges and provides recommendations for monitoring volcanoes fully or partly in marine environments to meet the capabilities described in other chapters of this volume.
The United States and its territories host dozens of submarine volcanoes with most (around 60) in the Commonwealth of the Northern Mariana Islands. Approximately 20 of the Northern Mariana Islands submarine volcanoes are known to be hydrothermally active, and 10 have confirmed eruptions since the 1950s (for example, Baker and others, 2008; Tepp and others, 2019a). Nine of those volcanoes were considered by the National Volcanic Threat Assessment (Ewert and others, 2018) to have a combination of eruptive type and summit depth that poses a higher risk of hazardous eruptions, although only one was listed as a moderate (level 3) threat. Other notable submarine volcanoes of interest to the United States that have historically erupted are Axial Seamount off the Washington State coast, Kamaʻehuakanaloa in Hawaiʻi, and Vailuluʻu seamount in American Samoa. All of these, however, have a low risk of hazards because of their depth (greater than 600 meters below sea level) and eruptive type and so are not included in the National Volcanic Threat Assessment. In addition to submarine volcanoes, the submerged flanks of island volcanoes can also be a source of hazardous submarine eruptions—for example, the 1877 eruption of Mauna Loa, Hawai‘i, in Kealakekua Bay (Wanless and others, 2006).
The most notable submarine eruption in recent times was the 2022 eruption of Hunga Tonga–Hunga Haʻapai in Tonga, which was one of the largest eruptions on Earth in the past 100 years. It created a massive volcanic plume, unprecedented shock waves, and far-reaching tsunami (Lynett and others, 2022). Other recent submarine eruptions in the Pacific Ocean Basin have produced subaerial plumes that reached aircraft heights (Carey and others, 2014) and large pumice rafts that can affect marine traffic and harbors (for example, Jutzeler and others, 2014; Kornei, 2019). These examples illustrate the potential hazards of major submarine eruptions. Yet, submarine volcanoes are largely unmonitored, and many eruptions occur that are unnoticed or only identified hours or days afterward.
Within U.S. territory, submarine volcanoes in the Northern Mariana Islands have been known to produce eruptive activity that can affect society. Reports from fishermen and other marine vessels in the Northern Mariana Islands have noted underwater explosions, sea-surface discoloration, and bubbling water, all of which are known to be signs of submarine volcanic activity. South Sarigan seamount, located about 160 kilometers (km) north of Saipan, erupted in 2010 from greater than 150 meters below the sea surface, resulting in a gas and ash plume that reached more than 11.9 km into the atmosphere (for example, Searcy, 2013; Embley and others, 2014), high enough to affect international air traffic. Precursory and co-eruptive seismicity was detected on the regional Northern Mariana Islands seismic network (Searcy, 2013) and on global monitoring instruments (Green and others, 2013).
Monitoring of submarine volcanoes is best accomplished with marine-based instrumentation, which is also useful for monitoring small island volcanoes that may not have the land area necessary for comprehensive subaerial monitoring. The primary marine-based instrumentation used for submarine volcanoes includes ocean-bottom pressure sensors to assess sea-floor deformation, ocean-bottom seismometers (OBSs) to detect seismicity, and both moored and ocean-bottom hydrophones to detect submarine explosions. Other sensors offer important monitoring data, such as turbidity, temperature, and chemistry of hydrothermal emissions. Marine-based instruments are typically deployed in campaign-style networks with no real-time telemetry owing to cost considerations and technical limitations. However, when necessary, marine instruments can be operated in real time using cables to transmit data to land-based facilities; other technologies for this purpose are in use or in development, such as acoustic transmission from the instrument to a moored buoy (Matsumoto and others, 2016) and a winch-based system with a satellite antenna that is part of the instrument mooring (Matsumoto and others, 2019). Emerging technologies for marine-based monitoring may be considered as part of a future monitoring plan. These technologies include ocean gliders and floats with on-board hydrophones that have been used to record earthquakes and submarine eruptions (for example, Matsumoto and others, 2013; Sukhovich and others, 2015) and fiber-optic cables that have been used as strainmeters to detect earthquakes (for example, Marra and others, 2018; Lindsey and others, 2019). Land-based instruments and satellites can also provide some capability for monitoring submarine volcanoes, but they provide more limited observations than marine-based instrumentation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062I","usgsCitation":"Tepp, G., 2024, Monitoring marine eruptions, chap. I of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–I, 7 p., https://doi.org/10.3133/sir20245062I.","productDescription":"iii, 7 p.","numberOfPages":"7","onlineOnly":"N","ipdsId":"IP-149126","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/i/covrthbi.jpg"},{"id":462444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/i/sir20245062i.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Volcanic unrest can trigger appreciable change to surface waters such as streams, springs, and volcanic lakes. Magma degassing produces gases and soluble salts that are absorbed into groundwater that feeds streams and lakes. As magma ascends, the amount of heat and degassing will increase, and so will any related geochemical and thermal signal. Subsurface magma movement can cause pressurization that alters hydrostatic head and may induce groundwater discharge. Fluid-pressure changes have been linked to distal volcano-tectonic earthquakes (White and McCausland, 2016; Coulon and others, 2017) and phreatic eruptions (for example, Yamaoka and others, 2016). Clearly, changes in groundwater and surface waters are both indicators of unrest and clues to how and where magma is rising toward the surface. Where possible, it is prudent to incorporate real-time hydrologic data into multiparameter monitoring of restless volcanoes. Hydrologic dynamics can also be tracked by changes in groundwater levels that are commonly measured in shallow boreholes (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. \">chapter K, this volume, on boreholes; Hurwitz and Lowenstern, 2024).
Although inferred to be common, relatively few volcano-hydrology anomalies are well documented, and many are essentially anecdotal (Newhall and others, 2001), reflecting the fact that high-resolution time series remain rare. Extreme examples include the 2008 eruption of Nevado del Huila, Colombia, where relatively minor phreatomagmatic eruptions were accompanied by expulsion of as much as 300 million cubic meters of groundwater from fissures high on the volcano (Worni and others, 2011), generating large lahars. Substantial decreases in flow rate from springs about 8 kilometers from the summit of Mayon Volcano, Philippines, have been noted before most eruptions in the 20th century (Newhall and others, 2001). Stream monitoring at Redoubt Volcano in 2009 allowed Werner and others (2012) to recognize that groundwater was unable to absorb (or scrub) the high flux of volcanic gas and that a high CO2/SO2 precursor signal had been evident for 5 months prior to the eruption. A key to better interpreting hydrologic anomalies—or even identifying them—is therefore obtaining adequate baseline data.
Most hydrologic monitoring at U.S. volcanoes has been accomplished by intermittent sampling surveys with annual or less frequent sampling (for example, https://hotspringchem.wr.usgs.gov/index.php). More frequent sampling, however, generally is needed to establish reliable baselines. A recent hydrologic and hydrothermal monitoring experiment at 25 sites and 10 of the 12 level 4 (very high threat) volcanoes in the U.S. portion of the Cascade Range demonstrated that there is sufficient temporal variability in hydrothermal fluxes, even during quiescent periods, that one-time measurements will commonly have limited interpretive value (Crankshaw and others, 2018). Thus, surveys are best augmented with data from streamgages (for example, Evans and others, 2004; Bergfeld and others, 2008). Streamflow (water discharge) data allow measured temperature and specific conductance to be converted to heat and solute mass fluxes, which could be insightful parameters for detecting anomalous activity (McCleskey and others, 2012). At the Yellowstone Caldera, long-term monitoring of river solutes has allowed calculation of the chloride flux, a proxy for heat discharge (Hurwitz and others, 2007; McCleskey and others, 2016) from the subsurface magma. This is readily accomplished because data from streamgages are continuously recorded and archived by the U.S. Geological Survey (USGS) National Water Information System (NWIS) (USGS, 2024).
Similar studies on stratovolcanoes or shield volcanoes would be scientifically useful, and yet are logistically challenging, requiring streamgages on numerous radial drainages complemented by either frequent manual sampling or numerous deployments of equipment to measure water temperature and specific conductance as a proxy for water chemistry. Another challenge is that some volcanic areas, especially shield volcanoes, are characterized by near-surface porous rocks and soils, such that surface streams are rare and replaced by distant, dilute large-volume springs with only a trace of any original volcanically sourced water (Manga, 2001; Hurwitz and others, 2021).
Volcanic lakes are worthy of special attention for monitoring efforts, as their temperature and composition can provide evidence of increased flux of volatile-rich fluids from below. Quantifying changes in volatile and heat release from magma can be simpler in lakes than for volcanoes with radial drainages and no major lakes. Moreover, volcanic lakes pose a range of hazards themselves, including phreatomagmatic eruptions, debris flows, flank collapse, tsunamis, and toxic gas release (Mastin and Witter, 2000; Delmelle and others, 2015; Manville, 2015; Rouwet and others, 2015)—hazards that have historically been responsible for substantial loss of life at many volcanoes worldwide (Manville, 2015). Catastrophic CO2 release at Lake Nyos, Cameroon, in 1986 suffocated about 1,750 people and about 3,500 livestock and was probably triggered by a large landslide into the gas-saturated lake (Kling and others, 1987; Evans and others, 1993). Gas-charged springs in Soda Bay within Clear Lake (California) have caused almost a dozen deaths to bathers in the past hundred years (ABC News, 2000). A 2005 example of lake overturn and abundant gas release was documented at Mount Chiginagak in Alaska (Schaefer and others, 2008) but did not result in any human casualties. Although thermally stratified lakes, which promote trapping of exsolved magmatic gas, tend to develop in tropical regions, the phenomenon can also arise where salinity creates meromixis (a condition in which a lake does not mix completely), as occurs in Mono Lake, California (Jellison and Melack, 1993; Jellison and others, 1998).
If magma erupts or flows into a lake, the interaction between hot magma and cold water can be explosive (Mastin and others, 2004; Zimanowski and others, 2015) and substantially expand the area affected by the eruption. Another hazard is the breaching of crater rims by landslides triggered by volcanic and (or) seismic activity. Under some circumstances, substantial volumes of water can be displaced, leading to large floods and lahars. Late Holocene lake flooding from Aniakchak Crater in the Alaska Peninsula (Waythomas, 2022) and from Paulina Lake in Newberry Crater, Oregon (Chitwood and Jensen, 2000), caused by the failure of outlet sills, testify to the substantial hazards at lake-filled calderas.
Several volcanic systems in the United States host lakes known to receive heat and gas from underlying magma. These lakes vary widely in area, depth, and chemical composition. Lakes are present at level 4 volcanoes, including Crater Lake and Newberry Volcano in Oregon; Yellowstone Caldera in Wyoming; Long Valley Caldera, Clear Lake volcanic field, Medicine Lake, and Salton Buttes in California; and Aniakchak Crater, Mount Katmai, Fisher Caldera, Mount Okmok, and Kaguyak Crater, among others, in Alaska. A water lake was present in Halemaʻumaʻu, the crater of Kīlauea, Hawai‘i (fig. F1), from October 2019 to December 2020. Level 3 volcanoes with lakes include Mono Lake volcanic field (Calif.), Mount Bachelor (Ore.), Ukinrek Maars and Mount Chiginagak (Alaska), and Soda Lake (Nevada). In addition, there are lakes at many levels 1 and 2 volcanoes. In the United States, there are no strongly acidic lakes that receive abundant input of magmatic gas, such as those found at Mount Ruapehu (New Zealand), Ijen and Kelud (Indonesia), and Poás (Costa Rica). Nevertheless, many contain fluids that provide clues to magmatic processes below.
Since publication of a previous report on recommended instrumentation for volcano monitoring (Moran and others, 2008), continuous hydrologic monitoring has become increasingly feasible. However, changes in water pressure, temperature, and chemistry remain, in general, poorly studied phenomena at volcanoes (Sparks, 2003; National Academies of Sciences, Engineering, and Medicine, 2017). Recent efforts by the USGS have included the temporary study of Cascade Range volcanoes, which included frequent (15 minute to hourly) temporal sampling of temperature, depth, and conductivity (Crankshaw and others, 2018; Ingebritsen and Evans, 2019). At Yellowstone Caldera, many streamgages have now added thermistors and specific conductance sensors, allowing estimation of time-dependent chloride flux as a proxy for variations in subsurface heat flux (McCleskey and others, 2012, 2016). Efforts to better understand lakes have also accelerated, with bathymetric mapping and sampling carried out at several locations in the United States. Especially thorough work was done at Yellowstone Lake thanks to the Hydrothermal Dynamics of Yellowstone Lake (HD-YLAKE, https://hdylake.org) project, funded primarily by the National Science Foundation. In addition to geophysical surveys and recovery of cores and other samples, HD-YLAKE investigations included remotely operated vehicle (ROV) investigations of hydrothermal vents on the lake floor (fig. F2). Data collected by the ROV provided a better understanding of the thermal and chemical influx from lake-bottom hydrothermal systems (Sohn and others, 2017).
In this chapter, we focus on detecting changes in the chemistry, temperature, discharge, or water levels of streams, springs, and lakes that can be caused by seismicity, volumetric strains, or increases in gas flux associated with ascending magma. There is unavoidable overlap with other chapters of this report. Samples of water and gas can also be obtained in boreholes (of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. \">chapter K, this volume; Hurwitz and Lowenstern, 2024), both shallow and deep. Gas monitoring (of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–E, 11 p., https://doi.org/10.3133/sir20245062e.\">chapter E, this volume; Lewicki and others, 2024) relies in part on samples from springs and wells, particularly where measurable gas plumes are absent. Water acts as a trigger and lubricant for landslides and sediment-rich floods, and so hydrology has obvious relevance for lahar monitoring, as discussed in of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–H, 6 p., https://doi.org/10.3133/sir20245062h. \">chapter H (this volume; Thelen and others, 2024). Shared situational awareness among scientists engaged in geophysical, gas, and hydrologic monitoring will improve overall understanding of the volcanic hazard.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062F","usgsCitation":"Ingebritsen, S.E., and Hurwitz, S., 2024, Streams, springs, and volcanic lakes for volcano monitoring, chap. F of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–F, 9 p., https://doi.org/10.3133/sir20245062F.","productDescription":"iii, 9 p.","numberOfPages":"9","onlineOnly":"N","ipdsId":"IP-149695","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462449,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/f/covrthbf.jpg"},{"id":462450,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/f/sir20245062f.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
As magma rises through the crust, decreasing pressure conditions allow volatiles to exsolve from the magma. These volatiles then migrate upward through the crust, where they can be stored at shallower levels or escape to the atmosphere. Rising magma also heats rock masses beneath volcanic centers, causing water in shallow aquifers and hydrothermal systems to boil and release additional gases and steam (see chapter F, this volume; Ingebritsen and Hurwitz, 2024). The chemistry and quantity of gases that reach the surface during periods of quiescence or volcanic unrest can reveal that gas-rich magma is ascending, crystallizing, or alternatively stalling, with important implications for volcanic hazard (for example, Sutton and others, 1992; Aiuppa and others, 2007, 2021; Werner and others, 2009, 2011, 2012; Moretti and others, 2013; de Moor and others, 2016; Lewicki and others, 2019; Edmonds and others, 2022; Kern and others, 2022; Kunrat and others, 2022).
Most volcanoes in Alaska and the western United States are characterized by weak degassing, with one or more low-temperature fumaroles (typically near the local boiling temperature of water) and connect to a deeper and sometimes extensive hydrothermal system (for example, McGee and others, 2001; Symonds and others, 2003a, b). Hydrothermal systems will affect the chemistry of rising gases exsolved from deeper magma (Symonds and others, 2001), including sulfur dioxide (SO2), hydrogen chloride (HCl), and water vapor (for example, Doukas and Gerlach, 1995; Gerlach and others, 1998, 2008; Symonds and others, 2001; Werner and others, 2013). As an example, depending on factors such as temperature, pressure, and oxidation state, rising SO2 will react with groundwater to form hydrogen sulfide (H2S) gas, dissolved sulfate (SO42−), or elemental sulfur (Christenson, 2000; Symonds and others, 2001; Werner and others, 2008). The reaction and dissolution of SO2 into shallow groundwater is commonly referred to as scrubbing, and can reduce the likelihood that ascending, degassing magma can be detected. Carbon dioxide, however, in addition to exsolving from magma early in the ascent process, is not easily removed by hydrothermal fluids (Lowenstern, 2001). As scrubbing and other processes take place, the SO2/H2S, CO2/SO2, and CO2/H2S ratios may change. High rates of SO2 emission indicate that magma has moved to relatively shallow levels in the volcano and that the system has heated up enough to establish dry pathways from depth to the surface. Monitoring multiple gas species and the total output of those species is thereby useful for volcano monitoring during both periods of quiescence, to establish background degassing conditions, and during unrest, when gas geochemistry and emission rates can provide information on changing conditions, such as magma ascent.
To provide context for multidisciplinary volcano forecasts, we focus on the following two key required capabilities: (1) characterizing baseline geochemistry and gas discharge from volcanoes and volcanic regions and (2) monitoring changes in gas geochemistry and discharge to inform forecasts of volcanic eruptions and their effects. Sufficient baseline data must be collected to identify and interpret anomalous degassing associated with volcanic unrest (for example, Sorey and others, 1998; Rouwet and others, 2014). Differences in volcano type, baseline degassing rates, local hydrology, and geography (for example, high versus low latitude) will result in a different baseline for each volcano. Volcanoes of any threat level that exhibit one or more degassing phenomena would ideally be monitored by techniques needed to establish baseline degassing data, with the sampling frequency of baseline data dictated by the threat level (table E1). Additional monitoring techniques become necessary during periods of unrest.
In general, three of the most important techniques for gas monitoring are (1) direct sampling of fumarole, spring, and soil gases for laboratory geochemical measurements, (2) measurements of the chemical composition of the volcanic plume and emission rates of major gas species (for example, H2O, CO2, SO2, and H2S) by satellite, airborne, or ground-based techniques, and (3) measurements of diffuse emissions of CO2 and other gases through soils. Various methods and instruments may be useful both for baseline studies and during unrest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245062E","usgsCitation":"Lewicki, J.L., Kern, C., Kelly, P.J., Nadeau, P.A., Elias, T., and Clor, L.E., 2024, Volcanic gas monitoring, chap. E of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–E, 11 p., https://doi.org/10.3133/sir20245062E.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"N","ipdsId":"IP-150252","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5062/e/sir20245062e.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":462451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5062/e/covrthbe.jpg"}],"contact":"Director,
Volcano Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, AK 99508
Water is an increasingly precious resource in California as years of drought, climate change, pollution, as well as an expanding population have all stressed the state's drinking water supplies. Currently, there are increasing concerns about whether regulated and unregulated contaminants in drinking water are linked to a variety of human-health outcomes particularly in socially disadvantaged communities with a history of health risks. To begin to address this data gap by broadly assessing contaminant mixture exposures, the current study was designed to collect tapwater samples from communities in Gold Country, the San Francisco Bay Area, two regions of the Central Valley (Merced/Fresno and Kern counties), and southeast Los Angeles for 251 organic chemicals and 32 inorganic constituents. Sampling prioritized low-income areas with suspected water quality challenges and elevated breast cancer rates. Results indicated that mixtures of regulated and unregulated contaminants were observed frequently in tapwater throughout the areas studied and the types and concentrations of detected contaminants varied by region, drinking-water source, and size of the public water system. Multiple exceedances of enforceable maximum contaminant level(s) (MCL), non-enforceable MCL goal(s) (MCLG), and other health advisories combined with frequent exceedances of benchmark-based hazard indices were also observed in samples collected in all five of the study regions. Given the current focus on improving water quality in socially disadvantaged communities, our study highlights the importance of assessing mixed-contaminant exposures in drinking water at the point of consumption to adequately address human-health concerns (e.g., breast cancer risk). Data from this pilot study provide a foundation for future studies across a greater number of communities in California to assess potential linkages between breast cancer rates and tapwater contaminants.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2024.122485","usgsCitation":"Smalling, K., Romanok, K., Bradley, P., Hladik, M.L., Gray, J.L., Kanagy, L.K., McCleskey, R., Stavreva, D.A., Alexander-Ozinskas, A.K., Alonso, J., Avila, W., Breitmeyer, S.E., Bustillo, R., Gordon, S.E., Hager, G.L., Jones, R.R., Kolpin, D., Newton, S., Reynolds, P., Sloop, J., Ventura, A., Von Behren, J., Ward, M.H., and Solomon, G.M., 2024, Mixed contaminant exposure in tapwater and the potential implications for human-health in disadvantaged communities in California: Water Research, v. 267, 122485, 18 p., https://doi.org/10.1016/j.watres.2024.122485.","productDescription":"122485, 18 p.","ipdsId":"IP-132707","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":466881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2024.122485","text":"Publisher Index Page"},{"id":462746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Callifornia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.4780141117476,\n 33.38214013511279\n ],\n [\n -117.0137634893847,\n 34.63804038963741\n ],\n [\n -118.9178740720775,\n 36.41544295333733\n ],\n [\n -121.31207993232795,\n 39.36561371857371\n ],\n [\n -123.45430122708109,\n 38.55271441652263\n ],\n [\n -122.39081480148963,\n 37.237131631622205\n ],\n [\n -121.82420632584103,\n 36.28237723543127\n ],\n [\n -119.35559571042745,\n 34.63804973561979\n ],\n [\n -118.74189049260241,\n 34.120808464956255\n ],\n [\n -118.30821804827679,\n 33.74109773655418\n ],\n [\n -117.4780141117476,\n 33.38214013511279\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"267","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":205651,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":205658,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":915373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kanagy, Leslie K. 0000-0001-5073-8538 lkkanagy@usgs.gov","orcid":"https://orcid.org/0000-0001-5073-8538","contributorId":4543,"corporation":false,"usgs":true,"family":"Kanagy","given":"Leslie","email":"lkkanagy@usgs.gov","middleInitial":"K.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":915374,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCleskey, R. 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2024 - A data exchange standard for wadeable stream habitat monitoring data","interactions":[],"lastModifiedDate":"2025-12-23T21:52:51.073362","indexId":"tm16B2","displayToPublicDate":"2024-10-03T14:10:20","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"16-B2","displayTitle":"A Data Exchange Standard for Wadeable Stream Habitat Monitoring Data","title":"A data exchange standard for wadeable stream habitat monitoring data","docAbstract":"Data from wadeable streams collected by monitoring programs are used to assess watershed condition status and trends. Federally managed programs collect a suite of similar habitat measurements using compatible methods and produce individual program datasets for their prescribed geographic and temporal range. We identified four programs that produce similar data: the Bureau of Land Management Assessment, Inventory, and Monitoring lotic division, the U.S. Environmental Protection Agency National Aquatic Resource Surveys National Rivers and Streams Assessment survey section, the Federal interagency Aquatic and Riparian Effectiveness Monitoring Program, and the PacFish/InFish Biological Opinion Monitoring Program. Their datasets answer agency-specific management questions and fulfill reporting requirements, but the datasets are not released in full, or at all, and in some cases, there was no method to integrate data from the four programs to provide data at a larger spatial scale.
The Pacific Northwest Aquatic Monitoring Partnership (PNAMP) led a working group of experts from the four monitoring programs to determine data compatibility, develop a Stream Habitat Metrics Integration (SHMI) data exchange standard, and integrate compatible wadeable stream data. The resulting SHMI data exchange standard contains a data mapping file used to transform data from the source program data to a conformed format based on a controlled vocabulary. After extensive discussions assessing and comparing program collection and analyses methods, the working group found 26 stream habitat metrics to be sufficiently comparable to be integrated into a meaningful dataset. Furthermore, a subset of PIBO MP data previously available only by request and AREMP data available only as a proprietary ESRI ArcGIS geodatabase were made publicly available in non-proprietary formats via the integrated SHMI dataset.
A selection of data from the four programs determined to be compatible among 14 datasets were filtered, transformed, standardized, and combined using R code to create the integrated SHMI dataset containing about 12,000 locations, 19,000 events, and 200,000 measurements from 2000 to 2022.
This report describes the SHMI data exchange standard and its development, the metric compatibility assessment, and the data integration process, so that others may reuse the SHMI data exchange standard and its components as well as the data integration processes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm16B2","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Bureau of Land Management, and the U.S. Forest Service","usgsCitation":"Scully, R.A., Dlabola, E.K., Bayer, J.M., Heaston, E., Courtwright, J., Snyder, M.N., Hockman-Wert, D., Saunders, W.C., Blocksom, K.A., Hirsch, C., and Miller, S.W., 2024, A data exchange standard for wadeable stream habitat monitoring data: U.S. Geological Survey Techniques and Methods, book 16, chap. B2, 28 p., https://doi.org/10.3133/tm16B2.","productDescription":"Report: vii, 28 p.; Data Release; Software Release","onlineOnly":"Y","ipdsId":"IP-139478","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":497946,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117643.htm","linkFileType":{"id":5,"text":"html"}},{"id":462494,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/16/b2/images"},{"id":462493,"rank":5,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P9KON2PK","text":"USGS software release","description":"USGS software release","linkHelpText":"- SHMI-DES"},{"id":462492,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J3P7SN","text":"USGS data release","description":"USGS data release","linkHelpText":"Wadeable stream habitat data integrated from multiple monitoring programs for the US from 2000–2022"},{"id":462491,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm16B2/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"TM 16-B2"},{"id":462490,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/16/b2/tm16b2.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 16-B2"},{"id":462495,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/16/b2/tm16b2.XML"},{"id":462489,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/16/b2/tm16b2.jpg"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th Street, Suite 400
Corvallis, Oregon 97330
This Research Topic compiles contemporary studies on cold seeps, hydrothermal vents, mud volcanoes, and related seafloor features that are associated with focused fluid emissions and the transfer of carbon, other chemical species, and sometimes heat from the geosphere to the ocean. Because these features sometimes tap fluids and gas originating kilometers below the seafloor, they provide an important window into deep processes that are otherwise inaccessible to scientists. At the shallow portion of their journey, migrating fluids nearing the seafloor contribute to a range of unique biological, physical, and chemical processes within the sediments themselves and at the sediment-water interface.
Seafloor fluid emissions play a critical role in global biogeochemical cycles, ocean chemistry, and possibly even climate change. Seafloor leakage points often emit hydrocarbon gases (especially methane and CO2) and are sometimes the loci for deposition of seafloor minerals that have economic value. A burgeoning area of research focuses on natural products generated at these features, seeking compounds with potential pharmaceutical or other applications.
Multidisciplinary studies have become routine for characterization of seafloor fluid emission sites, attesting to the inseparability of geologic, physical, chemical, and biological processes in these settings. It is increasingly common for researchers to combine in a single research cruise: subbottom imaging and seafloor mapping; porewater and water column geochemistry and gas sampling; sediment retrieval for lithologic, biostratigraphic, and solid phase analyses; and studies of benthic and subseafloor communities at the microbial to macrofaunal scales. This multidisciplinary approach has the advantage of ensuring the spatial and temporal coincidence of surveys and samples, an important factor at highly dynamic seafloor fluid emission sites. In addition, researchers often use remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), or human-occupied vehicles (HOVs) to record video of the seafloor, compile photomosaics, collect targeted samples, and survey with high-resolution geophysical near-seafloor systems, providing a degree of detail about seafloor fluid emission sites that is unprecedented compared to most areas of the deep ocean. While rarer, long-term cabled observatories or shorter-term deployments of portable observatories are also used at some loci for seafloor fluid flux and are particularly helpful for capturing temporal variations at these dynamic features.
Here we summarize the Research Topic’s contribution to multidisciplinary seafloor emission studies in the categories of cold seeps, mud volcanoes, and hydrothermal vents. Figure 1 shows the geographic distribution of the studies in this Research Topic and key features referred to in this Introduction.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2024.1496572","usgsCitation":"Snyder, G.T., Thurber, A.R., Dupre, S., Ketzer, M., and Ruppel, C.D., 2024, Editorial: From cold seeps to hydrothermal vents: Geology, chemistry, microbiology, and ecology in marine and coastal environments: Frontiers in Earth Science, v. 12, 1496572, 5 p., https://doi.org/10.3389/feart.2024.1496572.","productDescription":"1496572, 5 p.","ipdsId":"IP-170113","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2024.1496572","text":"Publisher Index Page"},{"id":464121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2024-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Glen T.","contributorId":299211,"corporation":false,"usgs":false,"family":"Snyder","given":"Glen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":918541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurber, Andrew R.","contributorId":346259,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":918542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dupre, Stephanie","contributorId":346260,"corporation":false,"usgs":false,"family":"Dupre","given":"Stephanie","email":"","affiliations":[{"id":82806,"text":"Institut Français de Recherche pour l'Exploitation de la Mer","active":true,"usgs":false}],"preferred":false,"id":918543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ketzer, Marcelo","contributorId":346261,"corporation":false,"usgs":false,"family":"Ketzer","given":"Marcelo","email":"","affiliations":[{"id":49394,"text":"Linnaeus University","active":true,"usgs":false}],"preferred":false,"id":918544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260487,"text":"70260487 - 2024 - Dust in the Critical Zone: North American case studies","interactions":[],"lastModifiedDate":"2024-11-27T16:03:50.34186","indexId":"70260487","displayToPublicDate":"2024-10-02T10:06:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Dust in the Critical Zone: North American case studies","docAbstract":"The dust cycle facilitates the exchange of particles among Earth's major systems, enabling dust to traverse ecosystems, cross geographic boundaries, and even move uphill against the natural flow of gravity. Dust in the atmosphere is composed of a complex and ever-changing mixture that reflects the evolving human footprint on the landscape. The emission, transport, and deposition of dust interacts with and connects Critical Zone processes at all spatial and temporal scales. Landscape properties, land use, and climatic factors influence the wind erosion of soil and nutrient loss, which alters the long-term ecological dynamics at erosional locations. Once in the atmosphere, dust particles influence the amount of solar radiation reaching Earth, and interact with longwave (terrestrial) radiation, with cascading effects on the climate system. Finally, the wet and dry deposition of particles influences ecosystem structure, composition, and function over both short and long-term scales. Tracking dust particles from source to sink relies on monitoring and measurement of the geochemical composition and size distribution of the particles, space-borne and ground-based remote sensing, and dust modeling. Dust is linked to human systems via land use and policies that contribute to dust emissions and the health-related consequences of particulate loads and composition. Despite the significant influence dust has in shaping coupled natural-human systems, it has not been considered a key component of the Critical Zone. Here, we demonstrate that dust particles should be included as a key component of the Critical Zone by outlining how dust interacts with and shapes Earth System processes from generation, through transport, to deposition. We synthesize current understanding from global research and identify critical data and knowledge gaps while showcasing case studies from North America.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2024.104942","usgsCitation":"Brahney, J., Heindel, R.C., Gill, T.E., Carling, G., Gonzalez-Olalla, J.M., Hand, J.L., Mallia, D.V., Munroe, J.S., Perry, K., Putman, A.L., Skiles, S.M., Adams, B.R., Aanderud, Z.T., Aarons, S.M., Aguirre, D., Ardon-Dryer, K., Blakowski, M.A., Creamean, J.M., Fernandez, D.P., Foroutan, H., Gaston, C.J., Hahnenberger, M., Hoch, S.W., Jones, D.K., Kelly, K.E., Lang, O.I., Lemonte, J., Reynolds, R.L., Singh, R.P., Sweeney, M., and Merrill, T.K., 2024, Dust in the Critical Zone: North American case studies: Earth-Science Reviews, v. 258, 104942, 34 p., https://doi.org/10.1016/j.earscirev.2024.104942.","productDescription":"104942, 34 p.","ipdsId":"IP-165083","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":486931,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index 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2018–21","interactions":[],"lastModifiedDate":"2024-12-03T19:55:55.265095","indexId":"sir20245077","displayToPublicDate":"2024-10-01T15:01:27","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5077","displayTitle":"Quantifying Fine Sediment Infiltration in Spawning Gravel Used by Chinook Salmon (Oncorhynchus tshawytscha) in the Sauk River Basin, Washington, 2018–21","title":"Quantifying fine sediment infiltration in spawning gravel used by Chinook salmon (Oncorhynchus tshawytscha) in the Sauk River Basin, Washington, 2018–21","docAbstract":"Fine sediment can infiltrate into river substrate that salmonid fish species (Oncorhynchus spp.) use to spawn. High levels of sediment infiltration can increase egg-to-fry mortality, which corresponds to the period when salmonids are still residing in the subsurface gravels. This study quantifies fine sediment infiltration of Chinook salmon (Oncorhynchus tshawytscha) spawning habitat during the egg-to-fry emergence period over three years in the Sauk River, which has naturally high fine sediment loads and important native salmon populations. Additionally, this study qualitatively assesses how grain size distribution of the riverbed and adjacent gravel bars compare to grain size distribution following fine sediment infiltration to evaluate if riverbed or gravel bar grain size distributions may provide information on the potential for fine sediment infiltration in spawning gravels.
Fine sediment infiltration into spawning gravels was quantified using sediment boxes and infiltration bags that were installed in artificial redds constructed at known Chinook salmon spawning locations at three study sites on the Sauk River over the expected egg-to-fry period. Over the three-year study period (August 2018–April 2021), fraction finer of sediment (grain sizes of less than two millimeters), ranged from 0.12 to 0.23 across the three study sites and years. Based on a comparison of field observations from this study and percentage egg-to-fry survival curves found in the literature, the expected survival for Chinook salmon eggs in the Sauk River is roughly 30 percent. Expected survival increases to approximately 90 percent if eggs are eyed and thus farther along in their development. Our field study did not evaluate the progression of infiltration, so it is unknown if observed fine sediment infiltration was at this relatively high rate during the period that corresponded to early egg development, when eggs are more sensitive to fine sediment infiltration. Dissolved oxygen in the gravels is largely above critically low levels (4 milligrams per liter) during sensitive periods corresponding to egg development and is interpreted not to affect egg-to-fry mortality. Active channel morphology in the middle reaches of the Sauk River may pose an additional challenge to pre-emergence survival. Channel change, deposition, and potential scour at the middle Sauk River study site likely contributed to low recovery rates of both sediment boxes and infiltration bags in two of the three study years.
In terms of grain size distributions of riverbed sediment and adjacent gravel bars representing the potential for fine sediment infiltration into spawning gravels, both riverbed and gravel bar bulk subsurface sediment samples had higher fraction finer for the representative fine grain size of two millimeters compared to the sediment boxes and infiltration bags. Therefore, riverbed and gravel bar samples may serve as a conservative first order proxy for potential fine sediment infiltration into spawning gravels, with the understanding that these samples may overestimate fine sediment infiltration by up to 15 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245077","collaboration":"Prepared in cooperation with the Sauk-Suiattle Indian Tribe","usgsCitation":"Jaeger, K.L., Anderson, S.W., Leach, A.C., and Morris, S.T., 2024, Quantifying fine sediment infiltration in spawning gravel used by Chinook salmon (Oncorhynchus tshawytscha) in the Sauk River Basin, Washington, 2018–21: U.S. Geological Survey Scientific Investigations Report 2024–5077, 36 p., https://doi.org/10.3133/sir20245077.","productDescription":"Report: viii, 36 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-156004","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":462435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5077/sir20245077.jpg"},{"id":462436,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5077/sir20245077.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5077"},{"id":462437,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245077/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5077"},{"id":462438,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RV73FO","text":"USGS data release","description":"USGS data release","linkHelpText":"Sediment and dissolved oxygen data to support fine sediment intrusion in Chinook salmon spawning gravels, Sauk River, Washington"},{"id":462439,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5077/images"},{"id":462440,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5077/sir20245077.XML"}],"country":"United States","state":"Washington","otherGeospatial":"Sauk River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.30874041064037,\n 48.47425854928386\n ],\n [\n -121.30874041064037,\n 47.81450909416341\n ],\n [\n -120.27602556689018,\n 47.81450909416341\n ],\n [\n -120.27602556689018,\n 48.47425854928386\n ],\n [\n -121.30874041064037,\n 48.47425854928386\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402