Climate change is exacerbating shoreline erosion and flooding, posing significant risks to coastal communities. Although traditional coastal defenses such as seawalls, dykes, and breakwaters offer protection from these hazards, their high environmental and economic costs are driving interest in cost-competitive nature-based solutions. Coral reef restoration is a nature-based solution that may be particularly apt to mitigate tropical coastal flooding and shoreline erosion while providing benefits to local tourism, fisheries, and nature. However, the novelty of this field requires studies demonstrating the benefits of reefs for coastal protection. While the flood protection benefits of reefs have been well-documented, their effects on shoreline erosion are comparatively less understood. Here, we investigate the effects of coral reefs on shoreline erosion by comparing tropical beach responses at short and long timescales, as well as identifying important reef structural features influencing coastal erosion rates. Our analyses leveraged two key datasets created in this study: the first derived from a literature review on short-term shoreline erosion due to storm events, and another compiling >80 years of long-term erosion rates, bathymetry, habitat, and wave energy for the Hawaiian Islands of Kauaʻi, Oʻahu, and Maui. Our analyses reveal three key findings regarding the effects of reefs on shoreline erosion. Firstly, we find evidence for the role of reefs in mitigating shoreline erosion during storm events, with coral reef-protected beaches experiencing 97 % less beach volume loss than unprotected beaches. Secondly, a linear regression analysis demonstrates that coral reef structure and wave energy are important predictors of long-term shoreline erosion rates, explaining 34 % of the variation across the Hawaiian Islands. Consistent with prior research, we find beaches protected by coral reefs with shallow reef crests, wide reef flats, calmer offshore conditions, and positioned farther from the shore exhibit lower erosion rates than others. Finally, when comparing historical erosion rates of protected and unprotected beaches in Hawai'i, we find a seemingly incongruous pattern where coral reef-protected beaches eroded up to 2x faster than beaches without reefs. While the cause of the enhanced erosion is yet to be fully understood, a combination of coral reef structural degradation and sea-level rise is likely shifting the equilibrium profiles of reef-protected beaches inshore. These results emphasize the role of coral reefs in reducing coastal erosion during storm events while revealing contrasting erosion patterns over long timescales. Future studies would ideally broaden the scope to include various regions, utilize advanced sediment transport models, and undertake field experiments to deepen our understanding of coral reef-coupled shoreline dynamics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.nbsj.2024.100174","usgsCitation":"Bitterwolf, S., Reguero, B., Storlazzi, C.D., and Beck, M.W., 2024, Shifting sands: The influence of coral reefs on shoreline erosion from short-term storm protection to long-term disequilibrium: Nature-Based Solutions, v. 6, no. 6, 100174, 8 p., https://doi.org/10.1016/j.nbsj.2024.100174.","productDescription":"100174, 8 p.","ipdsId":"IP-167854","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.nbsj.2024.100174","text":"Publisher Index Page"},{"id":433437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bitterwolf, Stephan","contributorId":245650,"corporation":false,"usgs":false,"family":"Bitterwolf","given":"Stephan","email":"","affiliations":[{"id":17620,"text":"UCSC","active":true,"usgs":false}],"preferred":false,"id":912035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reguero, Borja","contributorId":264485,"corporation":false,"usgs":false,"family":"Reguero","given":"Borja","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":912036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":912037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Michael W.","contributorId":259298,"corporation":false,"usgs":false,"family":"Beck","given":"Michael","email":"","middleInitial":"W.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":true,"id":912038,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257629,"text":"ofr20231053 - 2024 - Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","interactions":[],"lastModifiedDate":"2026-01-28T17:31:19.551324","indexId":"ofr20231053","displayToPublicDate":"2024-08-30T12:45:57","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1053","displayTitle":"Learning from a High-Severity Fire Event: Conditions Following the 2018 Carr Fire at Whiskeytown National Recreation Area","title":"Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area","docAbstract":"The 2018 Carr Fire burned more than 90 percent of Whiskeytown National Recreation Area, with much of the park burning at high severity. California yellow pine and mixed conifer forests are not well adapted to large, high-severity fires, and forest recovery after these events may be problematic. Large, high-severity fire patches pose difficulties for recruitment with interiors that are long distances from potential seed trees and may develop fuel structures that can promote further high-severity fire. This report details patterns of forest structure derived from field plots measured 2–3 years after the Carr Fire, providing a characterization of immediate fire effects. We coupled these observations with remotely sensed information, including data collected from unoccupied aircraft system surveys. The remotely sensed data were used to depict erosion after the Carr Fire as well as to create a high-resolution land cover classification map, a debris flow risk map and hazard assessment, and a post-fire canopy vegetation loss map. Results indicated high levels of tree mortality after the Carr Fire, including high-value old growth forest stands, supporting remotely sensed assessments of fire severity. The high-resolution tree mortality model also aligned well with other remotely sensed estimates of immediate burn severity. Results of the land cover classification illustrated the high percentage of dead vegetation remaining in the understory and canopy 8 months post-fire. Changes in vegetation height identified areas with canopy vegetation loss from 1- to 8-months post-fire. Pairing the post-fire debris accumulation with debris flow probabilities may identify high-risk debris flow areas. The results of this study will help inform future decisions concerning wildland fire and vegetation management strategies at Whiskeytown National Recreation Area and are broadly relevant for management in the aftermath of large, high-severity fires in mixed, dry coniferous forests in the western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231053","collaboration":"Prepared in cooperation with the National Park Service","programNote":"Ecosystems Mission Area—Land Change Science Program","usgsCitation":"van Mantgem, P.J., Wright, M.C., Thorne, K.M., Beckmann, J., Buffington, K., Rankin, L.L., Colley, A., and Engber, E.A., 2024, Learning from a high-severity fire event—Conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey Open-File Report 2023–1053, 52 p., https://doi.org/10.3133/ofr20231053.","productDescription":"Report: viii, 52 p.; 2 Data Releases","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-145882","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":499189,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117307.htm","linkFileType":{"id":5,"text":"html"}},{"id":432970,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231053/full"},{"id":432965,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97Y21L1","text":"USGS Data Release","description":"Wright, M.C., Engber, E., and van Mantgem, P.J., 2024, Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area: U.S. Geological Survey data release, available at https://doi.org/10.5066/P97Y21L1.","linkHelpText":"Forest conditions following the 2018 Carr Fire at Whiskeytown National Recreation Area"},{"id":432964,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GS9V1J","text":"USGS Data Release","description":"Thorne, K.M., Freeman, C.M., and Rankin, L.L., 2024, UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire: U.S. Geological Survey data release, available at https://doi.org/10.5066/P9GS9V1J.","linkHelpText":"UAS imagery at Whiskeytown National Recreation Area in 2018 and 2019 following the Carr Fire"},{"id":432969,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1053/images"},{"id":432968,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.xml"},{"id":432967,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1053/ofr20231053.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":432966,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1053/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Whiskeytown National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.82661214645721,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.425804364692084\n ],\n [\n -122.42999478567339,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.713227651132485\n ],\n [\n -122.82661214645721,\n 40.425804364692084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Extraordinary floods surged down the Yellowstone River and its tributaries in northwestern Wyoming and south-central Montana on June 13–15, 2022. During the flood, U.S. Geological Survey staff worked to maintain real-time data from streamgages by making field measurements of streamflow and repairing damaged equipment while communicating the latest streamflow information with the public and with local, State, and Federal agencies. After the flood, staff surveyed high-water marks, computed peak streamflow at streamgages unreachable during the flood, and updated flood-frequency estimates for streamgages in the Upper Yellowstone River Basin. Streamflows were the highest on record at 17 streamgages in the Upper Yellowstone River Basin. River stages were highest on record at most of those streamgages. The flood-related data and analyses are summarized in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243035","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation and the Federal Emergency Management Agency","usgsCitation":"Chase, K.J., Dutton, D., Hamilton, W.B., Siefken, S.A., Vander Voort, C., and Whiteman, A., 2024, June 2022 floods in the Upper Yellowstone River Basin: U.S. Geological Survey Fact Sheet 2024–3035, 6 p., https://doi.org/10.3133/fs20243035.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-164447","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":433365,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243035/full"},{"id":433364,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3035/images/"},{"id":433363,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.XML"},{"id":433362,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3035/fs20243035.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024–3035"},{"id":492687,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117264.htm","linkFileType":{"id":5,"text":"html"}},{"id":433361,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3035/coverthb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Upper Yellowstone River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.3465081870854,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 43.44596974043597\n ],\n [\n -108.70978943708536,\n 45.25268386886597\n ],\n [\n -111.3465081870854,\n 45.25268386886597\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Biscayne National Park, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243024","collaboration":"Prepared in collaboration with the National Park Service","usgsCitation":"Thurman, H.R., Enwright, N.M., Osland, M.J., Passeri, D.L., Day, R.H., Simons, B.M., Danielson, J.J., and Cushing, W.M., 2024, Projected sea-level rise and high tide flooding at Biscayne National Park, Florida: U.S. Geological Survey Fact Sheet 2024–3024, 6 p., https://doi.org/10.3133/fs20243024.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-156837","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499123,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117263.htm","linkFileType":{"id":5,"text":"html"}},{"id":462374,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243008","text":"USGS Fact Sheet 2024-3008","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Timucuan Ecological and Historic Preserve, Florida"},{"id":433350,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FM6V0T","text":"USGS Data Release","linkHelpText":"Sea-level rise and high tide flooding inundation probability and depth statistics at Biscayne National Park, Florida"},{"id":433349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3024/fs20243024.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024–3024"},{"id":462377,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243022","text":"USGS Fact Sheet 2024-3022","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Big Cypress National Preserve, Florida"},{"id":462376,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243021","text":"USGS Fact Sheet 2024-3021","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at San Juan National Historic Site, Puerto Rico"},{"id":462375,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243016","text":"USGS Fact Sheet 2024-3016","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at De Soto National Memorial, Florida"},{"id":462378,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20243023","text":"USGS Fact Sheet 2024-3023","linkHelpText":"- Projected Sea-Level Rise and High Tide Flooding at Dry Tortugas National Park, Florida"},{"id":433348,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3024/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.02512700796882,\n 25.761290873328747\n ],\n [\n -80.20652874795097,\n 25.746219053334585\n ],\n [\n -80.3416151500655,\n 25.65233220546078\n ],\n [\n -80.44196504877935,\n 25.166577096317894\n ],\n [\n -80.38664395077035,\n 25.123482598415634\n ],\n [\n -80.29015366354582,\n 25.224784951621928\n ],\n [\n -80.02512700796882,\n 25.761290873328747\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"The Shinnecock Indian Nation on Long Island, New York, faces challenges of shoreline retreat, saltwater intrusion, and flooding of the Tribal lands under changing climate and rising sea level. However, understanding of the dynamics of tidal circulation and waves and their impacts on the Shinnecock Indian Nation’s shoreline remains limited. This numerical study employs the integrated modeling capabilities of the hydrodynamic model Delft3D-FLOW and the spectral-wave model Simulating WAves Nearshore (SWAN) to investigate the circulation and wave dynamics along the shoreline of Shinnecock Indian Nation. The results of the 1-year long simulation indicate the majority of wind waves approach the Shinnecock Nation shorelines at normal wave angles, with yearly averaged offshore wave height of around 0.2 meter, maximum wave height reaching 0.65 meter, and yearly averaged offshore wave power of approximately 50 watts per meter. Boulders, acting as natural barriers, have been placed along the shoreline to reduce erosive wave forcing. Simulation results indicate the boulders to the north end effectively attenuate wave energy and reduce annual wave power, while the boulders near the two tidal ponds adjacent to the Tribal cemetery only have a slight influence on wave energy. There are large spatial variabilities in wave attenuation and current velocity reduction by the boulders. The model framework developed in this study can be utilized for the optimal design of nature-based solutions, guiding decisions on the placement of living shoreline structures and determining their optimal size. This study further identifies data and knowledge gaps as well as future research opportunities that can enhance the performance of numerical models and contribute to the scientific understanding of coastal processes and facilitate the optimal design of hybrid living shorelines in the future to achieve the maximum protective efficacy. This research can help to inform strategies for safeguarding vulnerable coastal communities and promoting resilience and sustainability of shoreline along the Shinnecock Indian Nation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241050","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University","usgsCitation":"Zhu, L., Wang, H., Chen, Q., Capurso, W., and Noll, M., 2024, Numerical modeling of circulation and wave dynamics along the shoreline of Shinnecock Indian Nation in Long Island, New York: U.S. Geological Survey Open-File Report 2024–1050, 32 p., https://doi.org/10.3133/ofr20241050.","productDescription":"Report: viii, 32 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-163925","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":434899,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241050/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1050 HTML"},{"id":433221,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG0AAO","text":"USGS Data Release","linkHelpText":"Three-dimensional point cloud data collected with a scanning total station on the western shoreline of the Shinnecock Nation Tribal lands, Suffolk County, New York, 2022"},{"id":433217,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1050/images"},{"id":433215,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1050/coverthb.jpg"},{"id":433218,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.pdf","size":"3.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1050"},{"id":433219,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1050/ofr20241050.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1050 XML"},{"id":499260,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117308.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Shinnecock Indian Nation relative to Shinnecock Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.53273633004311,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.82631366731101\n ],\n [\n -72.40468479043905,\n 40.90389205501435\n ],\n [\n -72.53273633004311,\n 40.90389205501435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Contact Us- USGS Publications Warehouse
","tableOfContents":"Excess nutrient loading and other factors are driving eutrophication and other negative effects on water-quality conditions in Lake Champlain and other receiving waters in Vermont. Two common best management practices were evaluated to determine how these practices can be optimized by targeting maintenance and operation to align better with seasonally driven needs, specifically to help municipalities remove a greater proportion of seasonal leaves and organic debris, reduce nutrient loading, and achieve water-quality goals.
To characterize solid materials typically removed by the municipal BMPs of catch-basin (CB) cleaning and street cleaning (SC), subsamples of CB and SC materials were collected each month from nine participating municipalities in central and northwestern Vermont between September 2017 and November 2018. Monthly and seasonal composites of CB and SC samples were created from the subsamples of available materials from all municipalities. Samples were analyzed for concentrations of total organic carbon, total Kjeldahl nitrogen, and total phosphorus (P), and separated into three particle-size fractions. Distribution of particle-size fractions was similar between CB and SC as both practices generally collect the coarser fraction of solid materials (greater than 125 micrometers in diameter). In the fall, however, the range of the coarser fraction of materials increased. This is attributed to the ability of SC to collect leaves and other light organic materials that commonly pass through a CB system designed to trap heavier materials.
Total organic carbon, total Kjeldahl nitrogen, and total P concentrations were highest in the catch-basin samples in the fall of 2017, and concentrations in the SC samples were highest in the fall of 2018. The collection of fewer samples in 2017 may account for some of the variability between fall 2017 and fall 2018 results. A subset of SC samples collected from piles representing specific street-cleaning routes in September and November 2018 were also analyzed. Materials collected in November were dominated by leaves, and the concentrations of the analyzed species of carbon, nitrogen, and phosphorus in some samples were more than double those in samples collected on the same street-cleaning routes in September.
The Vermont Department of Environmental Conservation and the University of Vermont developed estimates of load-reduction credits for CB and SC practices based on a policy developed by the Wisconsin Department of Natural Resources that determined the potential for credits associated with leaf-removal activities. This process also considered BMPs that were initiated during the U.S. Environmental Protection Agency’s Lake Champlain Basin Total Maximum Daily Load monitoring period (2000 to 2009) and adapted the Wisconsin Department of Natural Resources policies to apply to existing SC routes in the cooperating Vermont municipalities that possessed at least 17 percent tree cover. This exercise demonstrated that applying the Wisconsin Department of Natural Resources policy to existing street-cleaning routes possessing 17 percent or more tree cover would result in reductions in total P loads up to 65 percent of mandated target reductions, and about a 25 percent reduction on average.
Continuous simulations of stormwater runoff volume, and of loads of suspended sediments and total P, also were created for Englesby Brook Basin, an urbanized basin in Burlington and South Burlington that drains to Lake Champlain. Although the basin is more developed than the average of the nine cooperating municipalities, streamflow and P loading data collected by the U.S. Geological Survey were available to evaluate model performance. Simulations based on a year of average climatic conditions projected potential small reductions in total P of 0.08 to 0.10 percent as a result of CB cleaning and SC practices. Simulated weekly SC practices, however, reduced street-solid loads by as much as 7 percent. When the proportion of total P seen in fall SC materials collected in Vermont was applied to these simulated street-solid loads, estimated reductions of total P were about 29 percent. The combination of analytical results, estimated load-reduction credits, and simulated reductions indicate that targeted increases of SC activities to reduce leaf loading in the fall have the potential to reduce loading to receiving waters and could help regulated communities meet their water-quality goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235104","collaboration":"Prepared in cooperation with the Chittenden County Regional Planning Committee, the City of South Burlington, and the Vermont Department of Environmental Conservation","usgsCitation":"Sorenson, J.R., Pease, J.M., Foote, J.K., Chalmers, A.T., Ainley, D.H., and Williams, C.J., 2024, Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont: U.S. Geological Survey Scientific Investigations Report 2023–5104, 46 p., https://doi.org/10.3133/sir20235104.","productDescription":"Report: viii, 46 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-121578","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":433177,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A44LIX","text":"USGS data release","linkHelpText":"Data supporting phosphorus load-reduction estimates from leaf-litter removal in central and northwestern Vermont"},{"id":499382,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117265.htm","linkFileType":{"id":5,"text":"html"}},{"id":433176,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.XML","description":"SIR 2023-5104 XML"},{"id":433174,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235104/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5104 HTML"},{"id":433173,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5104/sir20235104.pdf","text":"Report","size":"9.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5104 PDF"},{"id":433164,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5104/coverthb.jpg"},{"id":433175,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5104/images/"}],"country":"United States","state":"Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.3,\n 44.875\n ],\n [\n -73.3,\n 44.15\n ],\n [\n -72.5,\n 44.15\n ],\n [\n -72.5,\n 44.875\n ],\n [\n -73.3,\n 44.875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
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The U.S. Geological Survey hosted a Mississippi River Science Forum with Federal agencies; Tribal, State, and local governments located in States that border the Mississippi River; academia; and other interested stakeholders. The purpose of the forum was to share current (2023) science; identify data gaps and areas of concern; and to prioritize next steps needed to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters along the Mississippi River. The forum was a directive for the U.S. Geological Survey in the Consolidated Appropriations Act of 2022 (Public Law 117—103, 136 Stat. 49).
Participants and stakeholders that attended the Mississippi River Science Forum indicated the following.
This report highlights data gaps and areas of concern discussed during the forum, and it identifies needs to advance the goals of improving water quality, restoring habitat and natural systems, improving navigation, eliminating aquatic invasive species, and building local resilience to natural disasters with specific emphasis on data collection and measurement, and scientific investigation. The report also summarizes stakeholder input and feedback and outlines next steps identified by forum participants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241053","usgsCitation":"Nelson, J.C., Rebich, R.A., Jankowski, K., Edwards, T.M., Larson, J.H., Robertson, D.M., Sprague, L.A., Stackpoole, S.M., Summers, K.M., Cinotto, P.J., Rydlund, P.H., Churchill, C.J., Daniel, W.M., Mckenna, O.P., Middleton, B.A.,\nCarter, J., Hartley, S.B., Frey, J.W., and Warner, K.L., 2024, U.S. Geological Survey Mississippi River Science Forum—Summary of data and science needs and next steps: U.S. Geological Survey Open-File Report 2024–1053, 4 p.,\nhttps://doi.org/10.3133/ofr20241053.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-159348","costCenters":[{"id":82110,"text":"Midcontinent Regional Director's Office","active":true,"usgs":true}],"links":[{"id":433267,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241053/full"},{"id":433266,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1053/images/"},{"id":433265,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.XML"},{"id":433264,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1053/ofr20241053.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1053"},{"id":433263,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1053/coverthb.jpg"}],"otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.59374999999999,\n 30.14512718337613\n ],\n [\n -90.263671875,\n 31.12819929911196\n ],\n [\n -90.52734374999999,\n 33.063924198120645\n ],\n [\n -88.505859375,\n 35.460669951495305\n ],\n [\n -86.66015624999999,\n 35.10193405724606\n ],\n [\n -84.0234375,\n 35.31736632923788\n ],\n [\n -81.82617187499999,\n 36.73888412439431\n ],\n [\n -79.89257812499999,\n 37.996162679728116\n ],\n [\n -78.92578124999999,\n 39.70718665682654\n ],\n [\n -76.201171875,\n 42.032974332441405\n ],\n [\n -76.025390625,\n 42.87596410238256\n ],\n [\n -77.080078125,\n 42.87596410238256\n ],\n [\n -79.189453125,\n 41.31082388091818\n ],\n [\n -83.232421875,\n 40.38002840251183\n ],\n [\n -86.748046875,\n 41.178653972331674\n ],\n [\n -88.41796875,\n 41.376808565702355\n ],\n [\n -89.296875,\n 44.402391829093915\n ],\n [\n -90.17578124999999,\n 44.33956524809713\n ],\n [\n -89.384765625,\n 46.558860303117164\n ],\n [\n -92.900390625,\n 46.49839225859763\n ],\n [\n -93.955078125,\n 47.69497434186282\n ],\n [\n -96.767578125,\n 46.01222384063236\n ],\n [\n -103.18359375,\n 48.69096039092549\n ],\n [\n -109.86328125,\n 49.15296965617042\n ],\n [\n -112.06054687499999,\n 48.980216985374994\n ],\n [\n -112.763671875,\n 48.86471476180277\n ],\n [\n -112.412109375,\n 47.754097979680026\n ],\n [\n -111.97265625,\n 46.31658418182218\n ],\n [\n -112.32421875,\n 45.398449976304086\n ],\n [\n -113.5546875,\n 45.460130637921004\n ],\n [\n -111.796875,\n 44.08758502824516\n ],\n [\n -108.369140625,\n 42.16340342422401\n ],\n [\n -105.46875,\n 41.50857729743935\n ],\n [\n -105.29296874999999,\n 39.90973623453719\n ],\n [\n -105.8203125,\n 39.436192999314095\n ],\n [\n -105.29296874999999,\n 38.54816542304656\n ],\n [\n -104.58984375,\n 36.31512514748051\n ],\n [\n -105.1171875,\n 35.88905007936091\n ],\n [\n -105.29296874999999,\n 35.38904996691167\n ],\n [\n -103.095703125,\n 32.84267363195431\n ],\n [\n -99.931640625,\n 32.175612478499325\n ],\n [\n -95.625,\n 31.653381399664\n ],\n [\n -93.955078125,\n 31.052933985705163\n ],\n [\n -93.955078125,\n 29.458731185355344\n ],\n [\n -90.52734374999999,\n 28.459033019728043\n ],\n [\n -88.857421875,\n 28.536274512989916\n ],\n [\n -88.59374999999999,\n 30.14512718337613\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Midcontinent Regional Director’s Office
U.S. Geological Survey
1992 Folwell Avenue
St. Paul, MN 55108
One of the most significant features of the Northwest Atlantic, the Gulf Stream influences high magnitude environmental fluctuations in deep habitats across the South Atlantic Bight. Amid this variability, the Blake Plateau harbors extensive reefs formed by cold-water corals that were previously assumed to rely on narrow ranges of temperature, currents, and particulate supply. A benthic lander collected near-bed conditions at the Richardson Reef Complex, a cold-water reef dominated by the scleractinian Desmophyllum pertusum at 830 m within the path of the Gulf Stream. Specific behavior of the Gulf Stream resulted in recurring environmental patterns at depth. During offshore meanders, deep stream components intruded onto the reef and caused rapid (3.74°C per hour) temperature increases up to 10.8°C (> 5°C above the site mean) and increased chlorophyll. Within 2 d of peak temperatures, intrusions were replaced by strong, turbid upwelling currents that rapidly cooled the site to temperature minima (4.13°C). While considerable environmental variability from the Gulf Stream may otherwise implicate a thermally stressful setting for corals, high-temperature events were likely mitigated by their short duration (< 37.4 h) and physical coupling with enhanced organic material. This hypothesis was supported by high-density clustering of D. pertusum occurrences within 50 km around the Gulf Stream's position along the South Atlantic Bight. This suggests that cold-water corals experiencing environmental variability can be sustained by relationships between food supply, temperature, and currents that vary in strength along stochastic time scales, shedding further light on the niche of cold-water corals.
To assess changes in substrate conditions and the efficacy of artificially placed substrates at select sites on the Kootenai River near Bonners Ferry, Idaho, the U.S. Geological Survey, in cooperation with the Kootenai Tribe of Idaho, completed repeat bathymetric, velocimetric, and underwater videography surveys. Collectively, three project sites throughout the Kootenai River make up the Substrate Enhancement Pilot Project (SEPP), an effort intended to improve spawning and egg incubation viability at locations identified to be aquatic habitat limited for the endangered Kootenai River white sturgeon (Acipenser transmontanus). Following the placement of coarse substrates at each site, bathymetric, velocimetric, and underwater videography data were collected from 2012 to 2022 to assess the role of deposition and erosion on maintaining suitable white sturgeon spawning and incubation substrates. Minimal erosion and deposition occurred at all Substrate Enhancement Pilot Project sites, according to interannual and intra-annual net volumetric changes between bathymetric surveys. Depending on the timing of bathymetric surveys relative to the annual peak streamflow conditions, isolated locations of deposition or erosion were observed at each site and the potential for deposition or erosion was supported by measured mean depth-averaged velocities. This study concluded that variability of deposition and scour were common at each site throughout the monitoring period and may be attributed to fluctuations in streamflow. Repeat bathymetric, underwater videography, and velocity mapping surveys were used to verify the interstitial spaces and surfaces of substrates at each SEPP site remained free of fine sediments for intervals longer than a year but were susceptible to deposition between high streamflow events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245070","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Dudunake, T.J., 2024, Substrate Enhancement Pilot Project—Monitoring summary and evaluation, Kootenai River, Idaho, 2012–22 (ver. 1.1, March 6, 2025): U.S. Geological Survey Scientific Investigations Report 2024–5070, 18 p., https://doi.org/10.3133/sir20245070.","productDescription":"Report: vii, 18 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150368","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":492698,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117304.htm","linkFileType":{"id":5,"text":"html"}},{"id":433328,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC824R","text":"USGS data release","description":"USGS data release","linkHelpText":"Kootenai river substrate enhancement pilot projects near Bonners Ferry, ID (ver. 3.0, January 2023)"},{"id":433326,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5070"},{"id":433325,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5070/coverthb.jpg"},{"id":433330,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5070/sir20245070.XML"},{"id":483010,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2024/5070/VersionHistory.txt","description":"Version History"},{"id":433329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5070/images"},{"id":433332,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245070/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5070"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.10215863331214,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.83333398808213\n ],\n [\n -116.46984612347813,\n 48.646078728701696\n ],\n [\n -116.10215863331214,\n 48.646078728701696\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 29, 2024; Version 1.1: March 6, 2025","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Paleoenvironmental data are essential for reconstructing environmental conditions in the distant past, and these reconstructions strongly depend on proxies and age–depth models. Proxies are indirect measurements that substitute for variables that cannot be directly measured, such as past precipitation. Conversely, an age–depth model is a tool that correlates the observed proxy with a specific moment in time. Bayesian age–depth modelling has proved to be a powerful method for estimating sediment ages and their associated uncertainties. However, there remains considerable potential for further integration into proxy analysis. In this paper, we explore a mathematical justification and a computational approach that integrates uncertainty at the age–depth level and propagates it to the proxy scale in the form of a posterior predictive distribution. This method mitigates potential biases and errors by removing the need to assign a single age to a given proxy measurement. It allows for quantifying the likelihood that proxy data values correspond to modelled ages, thus enabling the quantification of uncertainty in both the temporal and proxy value domains. The use of Bayesian statistics in proxy analysis represents a relatively recent advancement. We aim to mathematically justify incorporating the Markov chain Monte Carlo output from age–depth models into proxy analysis and to present a novel methodology for constructing environmental reconstructions using this approach.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-024-00647-5","usgsCitation":"Aquino-Lopez, M.A., Anderson, L., Sanchez-Cabeza, J., Ruiz-Fernandez, A.C., and Christen, J.A., 2024, Bayesian approaches to proxy uncertainty quantification in paleoecology: A mathematical justification and practical integration: Journal of Agricultural, Biological and Environmental Statistics, v. 31, p. 162-175, https://doi.org/10.1007/s13253-024-00647-5.","productDescription":"14 p.","startPage":"162","endPage":"175","ipdsId":"IP-153062","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":463766,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466943,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s13253-024-00647-5","text":"Publisher Index Page"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2024-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Aquino-Lopez, Marco A.","contributorId":346064,"corporation":false,"usgs":false,"family":"Aquino-Lopez","given":"Marco","email":"","middleInitial":"A.","affiliations":[{"id":82759,"text":"Cabridge University, UK","active":true,"usgs":false}],"preferred":false,"id":917924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lysanna 0000-0001-5650-9744 landerson@usgs.gov","orcid":"https://orcid.org/0000-0001-5650-9744","contributorId":5339,"corporation":false,"usgs":true,"family":"Anderson","given":"Lysanna","email":"landerson@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":917925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanchez-Cabeza, Joan-Albert","contributorId":346065,"corporation":false,"usgs":false,"family":"Sanchez-Cabeza","given":"Joan-Albert","email":"","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917926,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruiz-Fernandez, Ana Carolina","contributorId":346066,"corporation":false,"usgs":false,"family":"Ruiz-Fernandez","given":"Ana","email":"","middleInitial":"Carolina","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917927,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christen, J. Andres","contributorId":346067,"corporation":false,"usgs":false,"family":"Christen","given":"J.","email":"","middleInitial":"Andres","affiliations":[{"id":82761,"text":"CIMAT","active":true,"usgs":false}],"preferred":false,"id":917928,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257885,"text":"70257885 - 2024 - Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","interactions":[],"lastModifiedDate":"2024-08-30T12:26:31.615205","indexId":"70257885","displayToPublicDate":"2024-08-29T07:24:59","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Methane emissions associated with bald cypress knees across the Mississippi River Alluvial Valley","docAbstract":"In freshwater forested wetlands, bald cypress knees (Taxodium distichum (L.) Rich.) have the potential to emit large amounts of methane (CH4), but only a few studies have examined their greenhouse gas contribution. In this study, we measured CH4 fluxes associated with cypress knees across various climate and flooding gradients of the Mississippi River Alluvial Valley in southcentral United States. Greenhouse gases were measured using a portable gas analyzer with a custom-made chamber placed over the knees. We also conducted 3D lidar scans of knees using a smartphone to estimate the surface area and volume of knees. We investigated the following: (1) What parameters influence CH4 fluxes (i.e., knee height, distance to stream, temperature, relative humidity, water level, precipitation)? and (2) Which type of knee shape measurement (i.e., cone, frustrum, or lidar scan) provides the best fit to model data while maximizing measurement efficiency? We found that knee CH4 flux rates ranged from − 0.005 to 182 mmol m− 2 d− 1. There were positive correlations between CH4 fluxes, water levels, and temperature, and a negative correlation with knee height. Sites that had been dry for longer periods of time emitted less CH4 than sites where the soil remained saturated. The frustrum shape produced a knee volume estimate that was within 12% of lidar scans, whereas cone shapes underestimate knee dimensions (-100%). Further research of emissions and fluxes in cypress knees could fill knowledge gaps within the carbon cycle and could represent a major component of wetland CH4 budgets.
Coastal imaging systems have been developed to measure wave runup and total water level (TWL) at the shoreline, which is a key metric for assessing coastal flooding and erosion. However, extracting quantitative measurements from coastal images has typically been done through the laborious task of hand-digitization of wave runup timestacks. Timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. We utilize over 7000 hand-digitized timestacks from six diverse locations to train and validate machine learning models to automate the process of TWL extraction. Using these data, we evaluate two deep learning model architectures for the task of runup detection. One is based on a fully convolutional architecture trained from scratch, and the other is a transformer-based architecture trained using transfer learning. The deep learning models provide a probability of each pixel being either wet or dry. When contoured at the 50% level (equal chance of being wet or dry), the deep learning models more accurately identified TWL maxima than minima at all sites. This resulted in accurate predictions of 2% exceedance runup, but under predictions of significant swash and over predictions of wave setup. Improved agreement with the complete TWL time series was obtained through post-processing by utilizing the wet/dry probability of each pixel to weight the contouring toward lower dryness probabilities for runup minima (maxima agreed well with observations without tuning). Overall, a transformer-based model using transfer learning provided the best agreement with wave runup statistics, including a) the 2% exceedance runup, b) significant swash, and c) wave setup at the shoreline. For a random subset of images, the model was found to be within the uncertainty range of hand-digitization. The relative success of the transfer learning model suggests that fine-tuning a large model has advantages compared to training a smaller model from scratch. Models provide per-pixel probabilistic estimates in less than 10 s per timestack on a single computational unit, versus the more than 5 min required for hand-digitization. The model is therefore well-suited for near real-time applications, allowing for the development of early warning systems for difficult to forecast events. Real-time wave runup and total water level observations can also be incorporated into coastal hazards forecasts for data assimilation and continual model validation and improvement.
The emergence of white-nose syndrome (WNS) in North America has resulted in mass mortalities of hibernating bats and total extirpation of local populations. The need to mitigate this disease has stirred a significant body of research to understand its pathogenesis. Pseudogymnoascus destructans, the causative agent of WNS, is a psychrophilic (cold-loving) fungus that resides within the class Leotiomycetes, which contains mainly plant pathogens and is unrelated to other consequential pathogens of animals. In this review, we revisit the unique biology of hibernating bats and P. destructans and provide an updated analysis of the stages and mechanisms of WNS progression. The extreme life history of hibernating bats, the psychrophilic nature of P. destructans, and its evolutionary distance from other well-characterized animal-infecting fungi translate into unique host–pathogen interactions, many of them yet to be discovered.
Climate change is expected to influence aquatic habitats and associated fish populations, yet we know little about the impact on recreational anglers. Our goal was to explore whether interannual fluctuations in waterbody surface area and other explanatory variables could be used as indicators of changes in angler fishing effort. Our approach leveraged a combination of remotely sensed waterbody surface area, environmental and fish population data, and onsite angler survey monitoring data for Devils Lake, North Dakota, USA during the open-water fishing period (May 1st to August 31st) for 9 years (1992–2021). The information was used to develop a dynamic waterbody size-angler effort model. Changes in waterbody surface area reliably predicted changes in angler effort (r2 = 0.60). Increases in waterbody surface area led to increases in angler effort, and decreases in waterbody surface area led to decreases in angler effort. Our findings show promise that remotely sensed fluctuations in waterbody surface area could be used as an indicator of interannual angler effort dynamics. Dynamic waterbody size-angler effort models could provide managers the ability to predict changes in angler effort via climate-related hydrological cycles that affect the size and distribution of waterbodies on the landscape.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107156","usgsCitation":"Maldonado, M., Mahmood, T., Coulter, D., Coulter, A., Chipps, S.R., Siller, M., Neal, M., Saha, A., and Kaemingk, M., 2024, Water-level changes impact angler effort in a large lake: Implications for climate change: Fisheries Research, v. 279, 107156, 5 p., https://doi.org/10.1016/j.fishres.2024.107156.","productDescription":"107156, 5 p.","ipdsId":"IP-160734","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.fishres.2024.107156","text":"Publisher Index Page"},{"id":466011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Devils Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.36050675879237,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 47.77201003721444\n ],\n [\n -98.24927832713699,\n 48.39597416139583\n ],\n [\n -99.36050675879237,\n 48.39597416139583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"279","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maldonado, Matthew L.","contributorId":347887,"corporation":false,"usgs":false,"family":"Maldonado","given":"Matthew L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahmood, Taufique H.","contributorId":347888,"corporation":false,"usgs":false,"family":"Mahmood","given":"Taufique H.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922732,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coulter, David P.","contributorId":347889,"corporation":false,"usgs":false,"family":"Coulter","given":"David P.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922733,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coulter, Alison A.","contributorId":347890,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922735,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siller, Maddy K.","contributorId":347891,"corporation":false,"usgs":false,"family":"Siller","given":"Maddy K.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":922736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neal, Michaela L.","contributorId":347892,"corporation":false,"usgs":false,"family":"Neal","given":"Michaela L.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922737,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saha, Ayon","contributorId":347893,"corporation":false,"usgs":false,"family":"Saha","given":"Ayon","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922738,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kaemingk, Mark A.","contributorId":347895,"corporation":false,"usgs":false,"family":"Kaemingk","given":"Mark A.","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":922739,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256185,"text":"70256185 - 2024 - Supporting climate adaptation for rural Mekong River Basin communities in Thailand","interactions":[],"lastModifiedDate":"2024-08-28T15:09:21.686987","indexId":"70256185","displayToPublicDate":"2024-08-28T09:57:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2764,"text":"Mitigation and Adaptation Strategies for Global Change","active":true,"publicationSubtype":{"id":10}},"title":"Supporting climate adaptation for rural Mekong River Basin communities in Thailand","docAbstract":"Climate change impacts on large river basins, such as the Mekong River Basin (MRB), are complex due to shared governance and interconnected socioeconomic areas, making them highly vulnerable to change. The MRB, spanning six countries including Thailand, is crucial for the food and economic security of > 60 million people. However, in 2021, Thailand was ranked as the 9th highest risk country affected by climate change. To integrate climate adaptation in Thailand's MRB, we examined the effects of climate change on rapidly developing farmer and fisher communities in northeastern Thailand and explored feasible adaptation options. Using an interdisciplinary approach that included literature review, participatory action methods, and the resist-accept-direct (RAD) framework, we found that climate change is projected to increase temperatures, precipitation, extreme events, erosion, and water clarity, while decreasing heavy sediment transport. These changes negatively impact agriculture, fisheries, human health, and tourism. We identified several adaptation strategies across environmental, ecological, and human health categories to accommodate local needs, such as preventing habitat degradation (e.g., from dams and deforestation), providing fish refuge and passage, and supporting technical capacity. Community-driven adaptation planning and implementation are essential for supporting global sustainable development in a changing climate.
","language":"English","publisher":"Springer","doi":"10.1007/s11027-024-10154-0","usgsCitation":"Embke, H.S., Lynch, A., and Beard, 2024, Supporting climate adaptation for rural Mekong River Basin communities in Thailand: Mitigation and Adaptation Strategies for Global Change, v. 29, 67, 29 p., https://doi.org/10.1007/s11027-024-10154-0.","productDescription":"67, 29 p.","ipdsId":"IP-153560","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":433249,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Thailand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 103.58713075502806,\n 18.415675046149772\n ],\n [\n 103.25074086691765,\n 18.334290245472285\n ],\n [\n 102.68316462566526,\n 17.813439961628113\n ],\n [\n 102.59999202106795,\n 17.84871117664857\n ],\n [\n 102.60900709222325,\n 17.95083485538415\n ],\n [\n 102.33917708734333,\n 18.048914557116312\n ],\n [\n 102.13127818612654,\n 18.217320023448924\n ],\n [\n 101.84223130367957,\n 18.12127146242109\n ],\n [\n 101.84381496679299,\n 17.360034521893695\n ],\n [\n 103.50389523271065,\n 17.326503169572362\n ],\n [\n 103.58713075502806,\n 18.415675046149772\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2024-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":907028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lynch, Abigail 0000-0001-8449-8392 ajlynch@usgs.gov","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":169460,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","email":"ajlynch@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":907029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, Jr. 0000-0003-2632-2350 dbeard@usgs.gov","orcid":"https://orcid.org/0000-0003-2632-2350","contributorId":169459,"corporation":false,"usgs":true,"family":"Beard","suffix":"Jr.","email":"dbeard@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907030,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260831,"text":"70260831 - 2024 - Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake","interactions":[],"lastModifiedDate":"2024-11-27T16:05:26.865603","indexId":"70260831","displayToPublicDate":"2024-08-28T09:51:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake","docAbstract":"Background. Fish and rice are the main dietary sources of methylmercury (MeHg); however, rice does not contain the same beneficial nutrients as fish, and these differences can impact the observed health effects of MeHg. Hence, it is important to validate a biomarker, which can distinguish among dietary MeHg sources. Methods. Mercury (Hg) stable isotopes were analyzed in hair samples from peripartum mothers in China (n = 265). Associations between mass dependent fractionation (MDF) (δ202Hg) and mass independent fractionation (MIF) (Δ199Hg) (dependent variables) and dietary MeHg intake (independent variable) were investigated using multivariable regression models. Results. In adjusted models, hair Δ199Hg was positively correlated with serum omega-3 fatty acids (a biomarker for fish consumption) and negatively correlated with maternal rice MeHg intake, indicating MIF recorded in hair can be used to distinguish MeHg intake predominantly from fish versus rice. Conversely, in adjusted models, hair δ202Hg was not correlated with measures of dietary measures of MeHg intake. Instead, hair δ202Hg was strongly, negatively correlated with hair Hg, which explained 27–29% of the variability in hair δ202Hg. Conclusions. Our results indicated that hair Δ199Hg can be used to distinguish MeHg intake from fish versus rice. Results also suggested that lighter isotopes were preferentially accumulated in hair, potentially reflecting Hg binding to thiols (i.e., cysteine); however, more research is needed to elucidate this hypothesis. Broader impacts include 1) validation of a non-invasive biomarker to distinguish MeHg intake from rice versus fish, and 2) the potential to use Hg isotopes to investigate Hg binding in tissues.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D4EM00231H","usgsCitation":"Rothenburg, S.E., Korrick, S.A., Harrington, D., Thurston, S.W., Janssen, S., Tate, M., Nong, Y., Nong, H., Liu, J., Hong, C., and Ouyang, F., 2024, Hair mercury isotopes, a noninvasive biomarker for dietary methylmercury exposure and biological uptake: Environmental Science: Processes & Impacts, v. 26, p. 1975-1985, https://doi.org/10.1039/D4EM00231H.","productDescription":"11 p.","startPage":"1975","endPage":"1985","ipdsId":"IP-167813","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497361,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11560691/","text":"External Repository"},{"id":463874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rothenburg, Sarah E","contributorId":346139,"corporation":false,"usgs":false,"family":"Rothenburg","given":"Sarah","email":"","middleInitial":"E","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":918234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Korrick, Susan A","contributorId":346141,"corporation":false,"usgs":false,"family":"Korrick","given":"Susan","email":"","middleInitial":"A","affiliations":[{"id":82779,"text":"Harvard T.H. Chan School of Public Health","active":true,"usgs":false}],"preferred":false,"id":918235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, Donald","contributorId":346142,"corporation":false,"usgs":false,"family":"Harrington","given":"Donald","email":"","affiliations":[{"id":82781,"text":"University of Rochester Medical Center","active":true,"usgs":false}],"preferred":false,"id":918236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurston, Sally W","contributorId":346143,"corporation":false,"usgs":false,"family":"Thurston","given":"Sally","email":"","middleInitial":"W","affiliations":[{"id":82781,"text":"University of Rochester Medical Center","active":true,"usgs":false}],"preferred":false,"id":918237,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918238,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918239,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nong, YanFen","contributorId":346144,"corporation":false,"usgs":false,"family":"Nong","given":"YanFen","email":"","affiliations":[{"id":82782,"text":"Maternal and Child Health Hospital, Daxin County, China","active":true,"usgs":false}],"preferred":false,"id":918240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nong, Hua","contributorId":346145,"corporation":false,"usgs":false,"family":"Nong","given":"Hua","email":"","affiliations":[{"id":82782,"text":"Maternal and Child Health Hospital, Daxin County, China","active":true,"usgs":false}],"preferred":false,"id":918241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Jihong","contributorId":346146,"corporation":false,"usgs":false,"family":"Liu","given":"Jihong","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":918242,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hong, Chuan","contributorId":346148,"corporation":false,"usgs":false,"family":"Hong","given":"Chuan","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":918243,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ouyang, Fengxiu","contributorId":346149,"corporation":false,"usgs":false,"family":"Ouyang","given":"Fengxiu","email":"","affiliations":[{"id":82784,"text":"Ministry of Education and Shanghai Key Laboratory of Children’s Environmental Health,","active":true,"usgs":false}],"preferred":false,"id":918244,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70259255,"text":"70259255 - 2024 - Evolution and current state of continuous volcano gravimetry","interactions":[],"lastModifiedDate":"2024-10-02T14:36:37.275011","indexId":"70259255","displayToPublicDate":"2024-08-28T09:35:16","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18725,"text":"IEEE Instrumentation & Measurement Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Evolution and current state of continuous volcano gravimetry","docAbstract":"Most processes controlling volcanic activity involve underground mass redistribution (e.g., magma accumulation or withdrawal). Because of its unique ability to provide direct information on subsurface mass/density changes over time, gravimetry has important advantages over other volcano-monitoring techniques. As an example, if pre-eruptive magma accumulation occurs in voids, surface uplift or seismicity may not occur because the stress transmitted to the surrounding rock is not enough to induce fracturing or deformation; nevertheless, the addition of new mass would be associated with a gravity increase that may be measurable at the surface [1].
","language":"English","publisher":"IEEE","doi":"10.1109/MIM.2024.10654724","usgsCitation":"Carbone, D., Poland, M.P., Greco, F., Contrafatto, D., Messina, A., and Mirabella, L.T., 2024, Evolution and current state of continuous volcano gravimetry: IEEE Instrumentation & Measurement Magazine, v. 27, no. 6, p. 32-39, https://doi.org/10.1109/MIM.2024.10654724.","productDescription":"8 p.","startPage":"32","endPage":"39","ipdsId":"IP-161058","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carbone, Daniele","contributorId":124561,"corporation":false,"usgs":false,"family":"Carbone","given":"Daniele","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":914564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":914565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greco, Filippo","contributorId":192761,"corporation":false,"usgs":false,"family":"Greco","given":"Filippo","email":"","affiliations":[],"preferred":false,"id":914566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Contrafatto, Danilo","contributorId":344704,"corporation":false,"usgs":false,"family":"Contrafatto","given":"Danilo","email":"","affiliations":[{"id":52964,"text":"INGV-OE","active":true,"usgs":false}],"preferred":false,"id":914567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Messina, Alfio","contributorId":344706,"corporation":false,"usgs":false,"family":"Messina","given":"Alfio","email":"","affiliations":[{"id":52964,"text":"INGV-OE","active":true,"usgs":false}],"preferred":false,"id":914568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mirabella, Luca Timoteo","contributorId":344708,"corporation":false,"usgs":false,"family":"Mirabella","given":"Luca","email":"","middleInitial":"Timoteo","affiliations":[{"id":52964,"text":"INGV-OE","active":true,"usgs":false}],"preferred":false,"id":914569,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261511,"text":"70261511 - 2024 - Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","interactions":[],"lastModifiedDate":"2024-12-12T15:26:18.641308","indexId":"70261511","displayToPublicDate":"2024-08-28T09:18:13","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"displayTitle":"Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","title":"Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland","docAbstract":"The Eastern box turtle (Terrapene carolina carolina) population at the Jug Bay Wetlands Sanctuary, Lothian, MD has been monitored continuously for 29 years (1995-2023). We used open population capture-recapture models (Jolly-Seber) to estimate annual population size, survival probability, and recruitment rate. The model allows for unknown sex of individuals and includes information on individuals found dead. Our analysis documents a long-term decline of approximately 67% in box turtle population size at the Sanctuary over this nearly three-decade period. We estimate annual survival for both males and females, which does not show a systematic increase or decrease over time, averaging about 0.90 (95% CI: 0.86, 0.93) for females and 0.97 (95% CI: 0.94, 0.98) for males. Conversely, per-capita recruitment shows a marked decline over the first 15 years of the record, suggesting that population declines may be due to reduced recruitment. Conservation efforts for the species could benefit from a formal population viability analysis to understand the relative effects of survival and recruitment on changes in population size for this long-lived species.
","language":"English","publisher":"BioaRxiv","doi":"10.1101/2024.08.28.610102","usgsCitation":"Royle, A., Quinlan, M., and Swarth, C., 2024, Evidence for recruitment-mediated decline in an Eastern box turtle (Terrapene carolina carolina) population based on a 30-year capture-recapture data set from Maryland: BioRxiv, https://doi.org/10.1101/2024.08.28.610102.","productDescription":"22 p.","ipdsId":"IP-164958","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466948,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2024.08.28.610102","text":"External Repository"},{"id":465062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":920842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinlan, Mike","contributorId":347120,"corporation":false,"usgs":false,"family":"Quinlan","given":"Mike","email":"","affiliations":[{"id":83074,"text":"Jug Bay Wetlands Sanctuary","active":true,"usgs":false}],"preferred":false,"id":920843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarth, Christopher","contributorId":347121,"corporation":false,"usgs":false,"family":"Swarth","given":"Christopher","email":"","affiliations":[{"id":83075,"text":"no affiliations","active":true,"usgs":false}],"preferred":false,"id":920844,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259258,"text":"70259258 - 2024 - From field station to forecast: Managing data at the Alaska Volcano Observatory","interactions":[],"lastModifiedDate":"2024-10-02T14:06:15.606438","indexId":"70259258","displayToPublicDate":"2024-08-28T08:56:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"From field station to forecast: Managing data at the Alaska Volcano Observatory","docAbstract":"The Alaska Volcano Observatory (AVO) uses multidisciplinary data to monitor and study dozens of active and potentially active volcanoes. Here, we provide an overview of internally and externally generated data types, tools and resources used in their management, and challenges faced. Data sources include the following: (1) a multiparameter (seismic, infrasound, GNSS, web cameras) ground-based monitoring network that spans 3000 km and transmits data in real time; (2) a variety of satellite-borne sensors that provide information about surface change and volcanic emissions; (3) geologic and gas field campaigns; and (4) other external data products that provide situation awareness. Each data type requires distinct acquisition, processing, storage, visualization, and archiving approaches. AVO uses a variety of externally and internally developed tools to handle individual data types as well as multidisciplinary volcanological data. A primary tool is the Geologic Database of Information on Volcanoes in Alaska (GeoDIVA), which stores detailed, searchable information on more than 140 volcanoes and over 1000 eruptions and unrest events, including images, eruption descriptions, and geologic station and sample data, metadata, and analyses. It interacts with other internal tools that store monitoring reports and other operational records. Additional data management resources used by AVO assist with alarms and alerts, state-of-health monitoring, and multiparameter visualization. Requirements for 24/7 accessibility, the ever-expanding portfolio of data, and transitioning new tools from development to operations are all challenges faced by AVO and other volcano observatories. AVO strives to meet FAIR data practices and ensure that data are available to national and international community efforts using external repositories as well as those hosted by AVO and its parent institutions.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-024-01766-0","usgsCitation":"Coombs, M.L., Cameron, C., Dietterich, H., Boyce, E., Wech, A., Grapenthin, R., Wallace, K.L., Parker, T., Lopez, T., Crass, S., Fee, D., Haney, M.M., Ketner, D.M., Loewen, M.W., Lyons, J.J., Nakai, J.S., Power, J., Botnick, S.M., Brewster, I., Enders, M.L., Harmon, D., Kelly, P.J., and Randall, M., 2024, From field station to forecast: Managing data at the Alaska Volcano Observatory: Bulletin of Volcanology, v. 86, 79, 22 p., https://doi.org/10.1007/s00445-024-01766-0.","productDescription":"79, 22 p.","ipdsId":"IP-163867","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":914590,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":914591,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Randall, Michael J. 0000-0001-7750-9612","orcid":"https://orcid.org/0000-0001-7750-9612","contributorId":44819,"corporation":false,"usgs":true,"family":"Randall","given":"Michael J.","affiliations":[],"preferred":false,"id":914592,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70258798,"text":"70258798 - 2024 - Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","interactions":[],"lastModifiedDate":"2024-09-26T13:48:12.795406","indexId":"70258798","displayToPublicDate":"2024-08-28T08:44:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","title":"Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal","docAbstract":"Large mammals with general habitat needs can persist throughout mixed used landscapes, however, human-wildlife conflict frequently leads to their restriction to protected areas. Conservation efforts, especially for reducing conflicts with humans, can enhance tolerance of humans towards species like Asian elephants (Elephas maximus) in human-dominated landscapes. Here, we examine how elephant use in the Chure Terai Madhesh Landscape (CTML) covering the entire elephant range of Nepal changed between 2012 and 2020 in relationship to protection status and environmental conditions. We systematically surveyed ~ 42,000 km2 of potential habitat, by dividing the study area into 159 grid cells of 15 × 15 km2 and recorded elephant signs during the cool, dry season in three years (2012, 2018 and 2020). We analyzed the survey data in a single-species, multi-season (dynamic) occupancy modeling framework to test hypotheses regarding the influence of environmental conditions and protected area status on landscape use by elephants over time. The best-supported model included protected area effects on initial use, colonization, and detection probability as well as temporal variation in colonization and detection probability. Initial use and colonization rates were higher in protected areas, however elephants increasingly used cells located both inside and outside the protected areas, and the difference in use between protected areas and outside declined as elephants use became prevalent across most of the landscape. While elephant use was patchily distributed in the first year of surveys consistent with past descriptions of four sub-populations, elephant use consolidated into a western and eastern region in subsequent years with a gap in their distribution occurring between Chitwan and Bardiya National Parks. Our manuscript highlights the increasing landscape use by elephants in both protected areas and areas outside protected areas and suggests that management interventions that focus on reducing conflicts can promote greater use of both protected areas and areas outside of protected areas.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-70092-4","usgsCitation":"Ram, A.K., Lamichhane, B.R., Subedi, N., Yadav, N.K., Karki, A., Pandav, B., Brown, C., Khatri, T.B., and Yackulic, C., 2024, Dynamic occupancy modelling of Asian elephants (Elephas maximus) reveals increasing landscape use in Nepal: Scientific Reports, v. 14, 20023, 9 p., https://doi.org/10.1038/s41598-024-70092-4.","productDescription":"20023, 9 p.","ipdsId":"IP-160993","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":466949,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-70092-4","text":"Publisher Index Page"},{"id":462277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[88.12044,27.87654],[88.04313,27.44582],[88.1748,26.81041],[88.06024,26.41462],[87.22747,26.3979],[86.02439,26.63098],[85.25178,26.7262],[84.67502,27.2349],[83.30425,27.36451],[81.99999,27.92548],[81.0572,28.4161],[80.08842,28.79447],[80.47672,29.72987],[81.11126,30.18348],[81.5258,30.42272],[82.32751,30.11527],[83.33712,29.46373],[83.89899,29.32023],[84.23458,28.83989],[85.01164,28.64277],[85.82332,28.20358],[86.95452,27.97426],[88.12044,27.87654]]]},\"properties\":{\"name\":\"Nepal\"}}]}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Ram, Ashok Kumar","contributorId":344543,"corporation":false,"usgs":false,"family":"Ram","given":"Ashok","email":"","middleInitial":"Kumar","affiliations":[{"id":82383,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamichhane, Babu Ram","contributorId":201694,"corporation":false,"usgs":false,"family":"Lamichhane","given":"Babu","email":"","middleInitial":"Ram","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Subedi, Naresh","contributorId":201695,"corporation":false,"usgs":false,"family":"Subedi","given":"Naresh","email":"","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914074,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yadav, Nabin Kumar","contributorId":344544,"corporation":false,"usgs":false,"family":"Yadav","given":"Nabin","email":"","middleInitial":"Kumar","affiliations":[{"id":82385,"text":"Ministry of Forests and Environment, Madhesh Pradesh, Janakpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":914075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karki, Ajay","contributorId":344545,"corporation":false,"usgs":false,"family":"Karki","given":"Ajay","email":"","affiliations":[{"id":82383,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914076,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pandav, Bivash","contributorId":344546,"corporation":false,"usgs":false,"family":"Pandav","given":"Bivash","email":"","affiliations":[{"id":82387,"text":"Wildlife Institute of India, Dehradun","active":true,"usgs":false}],"preferred":false,"id":914077,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brown, Cory","contributorId":344547,"corporation":false,"usgs":false,"family":"Brown","given":"Cory","email":"","affiliations":[{"id":82388,"text":"US Fish and Wildlife Service, Washington D.C., USA","active":true,"usgs":false}],"preferred":false,"id":914078,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Khatri, Top B.","contributorId":344548,"corporation":false,"usgs":false,"family":"Khatri","given":"Top","email":"","middleInitial":"B.","affiliations":[{"id":82389,"text":"Ecosystem Based Adaptation Program (EBA) II, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":914079,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":914080,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70257859,"text":"70257859 - 2024 - Trees have similar growth responses to first-entry fires and reburns following long-term fire exclusion","interactions":[],"lastModifiedDate":"2024-08-29T12:21:04.445324","indexId":"70257859","displayToPublicDate":"2024-08-28T07:19:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Trees have similar growth responses to first-entry fires and reburns following long-term fire exclusion","docAbstract":"Managing fire ignitions for resource benefit decreases fuel loads and reduces the risk of high-severity fire in fire-suppressed dry conifer forests. However, the reintroduction of low-severity wildfire can injure trees, which may decrease their growth after fire. Post-fire growth responses could change from first-entry fires to reburns, as first-entry fires reduce fuel loads and the vulnerability among trees to fire effects, which may result in trees sustaining less damage during reburns. To determine whether trees had growth responses that varied from first-entry fires to reburns, we cored 87 ponderosa pine trees in the Gila Wilderness, New Mexico, USA that experienced 3–5 fires between 1950 and 2012 following long-term fire-exclusion and 67 unburned control trees from the Gila and Apache-Sitgreaves National Forests. We assessed tree growth response to fire by comparing tree-ring growth among burned and unburned trees from two years before to two years after fires. We compared growth between burned and unburned trees using a bootstrapping procedure to calculate annual median tree-ring width index values with 95 % confidence intervals. We compared post-fire growth after first-entry fires and reburns following long-term fire-exclusion. Burned trees had similar growth responses following first-entry fires and reburns, with lower growth during the fire year through two years post-fire compared to unburned controls. Burned tree growth returned to expected rates following these immediate post-fire growth reductions. Interestingly, trees had lower growth during the year before and the year of reburns compared to the first-entry fire, reflecting greater aridity before reburns. Greater aridity may have contributed to larger-than-expected growth reductions following reburns, which could explain similar growth responses to first-entry fires and reburns. Our results indicate that trees had consistent short-term growth responses to low-severity fires following long-term fire-exclusion. As trees retained vigor after multiple fires, managing fires for resource benefit is an effective approach to reduce the likelihood of high-severity fire without long-term negative effects on tree growth.
Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and-transition simulation model that integrates climate, land-use change, water demand, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand in five counties along the Central Coast from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future from a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows. Results indicate that future changes in climate-driven groundwater recharge, coupled with cumulative increases in agricultural water demand, result in overall declines in future groundwater balance, with a Hot/Dry future resulting in cumulative groundwater decline in all but Santa Cruz County. Cumulative declines by 2060 are especially prominent in San Luis Obispo (−2.9 to −5.1 Bm3) and Monterey counties (−6.5 to −8.7 Bm3), despite limited changes in agricultural water demand over the model period. These two counties show declining groundwater reserves in a Warm/Wet future as well, while San Benito and Santa Barbara County barely reach equilibrium. These results suggest future groundwater supplies may not be able to keep pace with regional demand and declining climate-driven recharge, resulting in a potential reduction in water security in the region. However, our county-scale projections showed new housing and associated water demand does not conflict with California's groundwater sustainability goals. Rather, future climate coupled with increasing agricultural groundwater demand may reduce water security in some counties, potentially limiting available groundwater supplies for new housing.
Our aim was to determine the movement patterns of three abundant salmonids—Brown Trout Salmo trutta, Mountain Whitefish Prosopium williamsoni, and Rainbow Trout Oncorhynchus mykiss—in the Smith River watershed of Montana.
We tagged 7172 fish with passive integrated transponder (PIT) tags, monitored their movements past 15 stationary PIT arrays over 4 years, and located tagged fish between arrays by conducting mobile surveys.
Movement patterns varied seasonally, among species, and among locations. Movement was greatest in the middle portion of the watershed, which included a pristine main‐stem canyon and lower reaches of major tributaries. Fish rarely left the canyon, but movement into the canyon from other regions was common. Mountain Whitefish were most likely to move, and Brown Trout were least likely to move. Most fish travelled less than 10 km, but some fish travelled over 100 km. Distinct movement patterns were not evident; rather, a continuous spectrum of movement behaviors was apparent. Movements by Mountain Whitefish and Rainbow Trout increased during their spawning periods. Movements peaked when mean daily water temperatures were between 11.3 and 17.1°C.
Movements were diverse and probably contributed to metapopulation dynamics, population resiliency, and species diversity. Fish movements along stream networks connect populations across diverse landscapes, and therefore, protecting and restoring stream connectivity along inland streams such as the Smith River is critical to maintaining productive fish assemblages.