Greenland White-fronted Geese Anser albifrons flavirostris exhibit prolonged parent–offspring and sibling–sibling associations, suggesting fitness advantages to such behaviour, so we used reduced representation genome sequence data to determine the degree to which marked flock members observed associating in apparent parent–offspring and sibling–sibling relationships in the field were genetically related. Among 50 bled, marked and released geese, we genetically identified members of 11 different family groups, confirming all observed male parent–offspring relationships as genetically predicted, but only 10 out of 12 (83%) possible female parent–offspring relationships (i.e. two offspring were not genetically related to the adult female in their family groups observed in the field); these two ‘adopted’ offspring were responsible for four (15%) of the cases where observed ‘siblings’ were not genetically related to other family-member first-winter birds with which they associated. One multigenerational family consisted of three genetically confirmed grandmother–mother–sibling offspring relationships, not previously reported in arctic-nesting geese, as well as one of the two ‘adopted’ first-winter geese.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.13427","usgsCitation":"Wilson, R.E., Sonsthagen, S.A., Walsh, A.J., and Fox, A.D., 2025, Adoption of non‐related goslings and intergenerational family cohesion among Greenland White‐fronted Geese (Anser albifrons flavirostris): International Journal of Avian Science , v. 167, no. 4, p. 1080-1088, https://doi.org/10.1111/ibi.13427.","productDescription":"9 p.","startPage":"1080","endPage":"1088","ipdsId":"IP-174546","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494530,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":495044,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.13427","text":"Publisher Index Page"}],"country":"Ireland","otherGeospatial":"Wexford Slobs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -6.553981049791275,\n 52.35040040236751\n ],\n [\n -6.553981049791275,\n 52.30553195975094\n ],\n [\n -6.437262464425345,\n 52.30553195975094\n ],\n [\n -6.437262464425345,\n 52.35040040236751\n ],\n [\n -6.553981049791275,\n 52.35040040236751\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"167","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E.","contributorId":360078,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert","middleInitial":"E.","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":946771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":353767,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Alyn J.","contributorId":360080,"corporation":false,"usgs":false,"family":"Walsh","given":"Alyn","middleInitial":"J.","affiliations":[{"id":85967,"text":"National Parks and Wildlife Service, Ireland","active":true,"usgs":false}],"preferred":false,"id":946773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fox, Anthony D.","contributorId":360082,"corporation":false,"usgs":false,"family":"Fox","given":"Anthony","middleInitial":"D.","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":946774,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268218,"text":"70268218 - 2025 - Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes","interactions":[],"lastModifiedDate":"2025-06-17T14:30:11.472409","indexId":"70268218","displayToPublicDate":"2025-06-13T09:19:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes","docAbstract":"We present geochemical data from gas samples from ∼1200 km of arc in the Central Volcanic Zone of the Andes (CVZA), the volcanic arc with the thickest (∼70 km) continental crust globally. The primary goals of this study are to characterize and understand how magmatic gases interact with hydrothermal systems, assess the origins of the major gas species, and constrain gas emission rates. To this end, we use gas chemistry, isotope compositions of H, O, He, C, and S, and SO2 fluxes from the CVZA. Gas and isotope ratios (CO2/ST, CO2/CH4, H2O/ST, δ13C, δ34S, 3He/4He) vary dramatically as magmatic gases are progressively affected by hydrothermal processes, reflecting removal and crustal sequestration of reactive species (e.g., S) and addition of less reactive meteoric and crustal components (e.g., He). The observed variations are similar in magnitude to those expected during the magmatic reactivation of volcanoes with hydrothermal systems. Carbon and sulfur isotope compositions of the highest temperature emissions (97–408 °C) are typical of arc magmatic gases. Helium isotope compositions reach values similar to upper mantle in some volcanic gases indicating that transcustal magma systems are effective conduits for volatiles, even through very thick continental crust. However, He isotopes are highly sensitive to even low degrees of hydrothermal interaction and radiogenic overprinting. Previous work has significantly underestimated volatile fluxes from the CVZA; however, emission rates from this study also appear to be lower than typical arcs, which may be related to crustal thickness.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108382","usgsCitation":"de Moor, J., Barry, P., Rodriguez, A., Aguilera, F., Aguilera, M., Gonzalez, C., Layana, S., Chiodi, A., Apaza, F., Masias, P., Kern, C., Barnes, J., Cullen, J.T., Bastoni, D., Bastianoni, A., Cascone, M., Jimenez, C., Salas-Navarro, J., Ramirez, C., Jessen, G., Giovannelli, D., and Lloyd, K., 2025, Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes: Journal of Volcanology and Geothermal Research, v. 466, 108382, 18 p., https://doi.org/10.1016/j.jvolgeores.2025.108382.","productDescription":"108382, 18 p.","ipdsId":"IP-170019","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":490986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108382","text":"Publisher Index Page"},{"id":490831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, Bolivia, Chile, Peru","otherGeospatial":"Central Volcanic Zone of the Andes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74,\n -14\n ],\n [\n -74,\n -28\n ],\n [\n -64,\n -28\n ],\n [\n -64,\n -14\n ],\n [\n -74,\n -14\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"466","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"de Moor, J. Maarten","contributorId":353456,"corporation":false,"usgs":false,"family":"de Moor","given":"J. 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T.","contributorId":140885,"corporation":false,"usgs":false,"family":"Cullen","given":"Jeffrey","email":"","middleInitial":"T.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":940496,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bastoni, Deborah","contributorId":356936,"corporation":false,"usgs":false,"family":"Bastoni","given":"Deborah","affiliations":[{"id":47714,"text":"University of Naples","active":true,"usgs":false}],"preferred":false,"id":940497,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bastianoni, Alessia","contributorId":356937,"corporation":false,"usgs":false,"family":"Bastianoni","given":"Alessia","affiliations":[{"id":47714,"text":"University of Naples","active":true,"usgs":false}],"preferred":false,"id":940498,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cascone, 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wildfire risk, plan management activities and evaluate fuel treatment effects. Terrestrial light detection and ranging (lidar) is a field-based 3D scanning technology with great potential to reduce labor-intensive field measurements and provide new depths of vegetation structure data.
To facilitate the integration of terrestrial lidar into fuel monitoring programs, we developed a model, training process, and Python program that produces canopy fuel, surface fuel and terrain metrics commonly used in fire behavior and fire risk modeling.
We estimated canopy and surface fuel metrics from terrestrial lidar using a semi-empirical model incorporating physically based modeling of leaf area density and occlusion and a non-destructive model calibration process leveraging Bayesian regression. We compared lidar-derived fuel estimates with conventional fuel estimates across diverse conditions in semi-arid shrubland, woodland and forest in Arizona. We also compared estimates using single- and multiple-scan modes.
In single-scan mode, our lidar-derived fuel estimates were significantly related to conventional estimates of total canopy fuel load, maximum canopy bulk density, downed surface fuel load and standing surface fuel load.
Our methods provide opportunities to increase the scalability of fuel monitoring to better understand wildfire risk and treatment effectiveness.
The range of the endangered black abalone (Haliotis cracherodii) is divided into the North Central California region, the Central California region, the Southern California Mainland region, the Channel Islands region, and the Baja California region by the National Marine Fisheries Service for management purposes. San Nicolas Island is one of eight subregions of the Channel Islands region. The black abalone recovery plan establishes five demographic criteria for the possible delisting or downlisting of the species. The U.S. Geological Survey monitors nine long-term intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. This report uses data collected between 2013 and 2022 and the delisting criteria to analyze and describe the density, recruitment, size structure, and population trends at the nine U.S. Geological Survey monitoring sites at San Nicolas Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251015","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22: U.S. Geological Survey Open-File Report 2025–1015, 10 p., https://doi.org/10.3133/ofr20251015.","productDescription":"vi, 10 p.","onlineOnly":"Y","ipdsId":"IP-174146","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490728,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251014","text":"Open-File Report 2025-1014","description":"OFR 2025-1014","linkHelpText":"- Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report"},{"id":486255,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.XML"},{"id":486254,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1015/images"},{"id":486253,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251015/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1015"},{"id":486252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1015"},{"id":486251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1015/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.41565036125932,\n 33.22855822061233\n ],\n [\n -119.4322978602211,\n 33.233849792002204\n ],\n [\n -119.46292925831023,\n 33.2600242059834\n ],\n [\n -119.53051810409356,\n 33.29036557133239\n ],\n [\n -119.58545485066676,\n 33.281459107969354\n ],\n [\n -119.57180390151814,\n 33.25000088849947\n ],\n [\n -119.54217135336674,\n 33.228836776039614\n ],\n [\n -119.47857790733391,\n 33.21379600415082\n ],\n [\n -119.45160895901617,\n 33.21379600415082\n ],\n [\n -119.41565036125932,\n 33.22855822061233\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey monitors a suite of intertidal black abalone (Haliotis cracherodii) sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated southern sea otters (Enhydra lutris nereis) on the intertidal black abalone population at San Nicolas Island. The sites were monitored, typically annually or biennially, from 1981 to 1997. Monitoring resumed in 2001 and has been completed annually thereafter. Since 2018, the monitoring has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important from a management perspective after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992, and during the next few years, withering syndrome reduced the black abalone population on San Nicolas Island by more than 99 percent. The black abalone was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2022 survey of the sites and the status of the measured population of black abalone in comparison to long-term patterns (based on data collected since 1981) at San Nicolas Island. Between the years 2000 and 2022, the total monitored black abalone population on the island has grown from roughly 200 to more than 2,000, approximately a ten-fold increase following the disease-related decline. Since it was first consistently measured in 2005, the distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that black abalone are sufficiently close together at several of the sites to reproduce successfully. The total black abalone count in 2022 was 2,156, which was 7.9 percent lower than the total count in 2020 but 6.6 percent higher than in 2021. There were increases and decreases among the sites and transects within each site in 2022, but six of the nine sites had higher counts than in the previous year. The 2022 count is one of the highest since 1993, second only to the 2020 count. In 2022, the annual recruitment rate, defined as the percentage of measured black abalone with a shell length of 3 centimeters or less, was the second highest recorded, only slightly less than in 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251014","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report: U.S. Geological Survey Open-File Report 2025–1014, 34 p., https://doi.org/10.3133/ofr20251014.","productDescription":"viii, 34 p.","onlineOnly":"Y","ipdsId":"IP-159889","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490412,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1014/images"},{"id":491626,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251015","text":"Open-File Report 2025-1015","description":"OFR 2025-1015","linkHelpText":"- Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22"},{"id":490413,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.XML"},{"id":490410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1014"},{"id":490411,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251014/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1014"},{"id":490409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1014/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base, Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.41565036125932,\n 33.22855822061233\n ],\n [\n -119.4322978602211,\n 33.233849792002204\n ],\n [\n -119.46292925831023,\n 33.2600242059834\n ],\n [\n -119.53051810409356,\n 33.29036557133239\n ],\n [\n -119.58545485066676,\n 33.281459107969354\n ],\n [\n -119.57180390151814,\n 33.25000088849947\n ],\n [\n -119.54217135336674,\n 33.228836776039614\n ],\n [\n -119.47857790733391,\n 33.21379600415082\n ],\n [\n -119.45160895901617,\n 33.21379600415082\n ],\n [\n -119.41565036125932,\n 33.22855822061233\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35.
With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas:
Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1556","usgsCitation":"Otto, C.R.V., Graves, T.A., Robertson-Thompson, D., Pearse, I., Thogmartin, W.E., Murphy, C., Webb, L., Droege, S., Steinkamp, M., and Grundel, R., 2025, U.S. Geological Survey Pollinator Science Strategy, 2025–35—A review and look forward (ver. 1.1, June 26, 2025): U.S. Geological Survey Circular 1556, 16 p., https://doi.org/10.3133/cir1556.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172990","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490448,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1556/images/"},{"id":490447,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.XML"},{"id":490449,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1556/full"},{"id":490446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Cir 1556"},{"id":490445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1556/coverthb4.jpg"},{"id":491238,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1556/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: June 12, 2025; Version 1.1: June 26, 2025","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Highly pathogenic avian influenza (HPAI) is an ecologically and economically important animal disease that can also directly affect humans (a “zoonotic” disease). HPAI was once limited almost exclusively to domestic poultry but has rapidly adapted to diverse animal hosts. Viruses causing HPAI now appear to be maintained and dispersed by wild birds largely independent of poultry, though HPAI continues to cause considerable economic losses and supply chain disruptions in the domestic poultry trade. Coincident with the adaptation of HPAI viruses to wild birds, particularly waterfowl and gulls, increasingly diverse wild bird hosts are becoming exposed to HPAI, often resulting in disease and death. More sporadically, HPAI has caused mass mortality events, particularly among seabirds. Furthermore, viral spillover to wild and domestic mammals has become more common. Spillover to wild mammals has resulted in mortality among diverse terrestrial and marine taxa, including episodic losses of such scale as to represent potential conservation challenges. Since approximately March 2024, HPAI has also affected dairy cows, which represents a new threat to the agricultural economy. Lastly, HPAI has increasingly affected humans through domestic animal exposures, exemplifying the considerable implications of this disease beyond animal health.
Rapid changes in the ecology of HPAI are currently outpacing research efforts. For example, it is not entirely clear which newly established hosts may become reservoirs for HPAI viruses (in other words, capable of maintaining HPAI viruses within a broad population indefinitely) and how this may influence viral evolution and dissemination. As a result, there are considerable information gaps regarding HPAI in wildlife that, if filled, would improve the ability of scientists, managers, agricultural industry representatives, and healthcare professionals to understand and to anticipate the effects of HPAI on wild animal, domestic animal, environmental, and human health (“One Health”).
The U.S. Geological Survey (USGS) is the lead Federal agency providing scientific research on avian influenza viruses (AIVs), including HPAI viruses, that affect wildlife for which the Department of the Interior (DOI) has management authority. States have jurisdiction over wildlife on Federal lands within their borders (43 CFR § 24.3), so the USGS Ecosystems Mission Area (EMA) coordinates with State natural resource management agencies. The EMA focuses its research on HPAI through priorities identified by the USGS Avian Influenza Science Team (app. 1). Priorities identified by the USGS Avian Influenza Science Team are based on Administration priorities, Congressional direction, and discussions with State, Federal, and Tribal natural resource management agencies that identify specific scientific gaps that need to be filled to inform sound wildlife management decisions. Notable non-DOI Federal partners include the U.S. Department of Agriculture, the lead for the HPAI regulatory response in poultry and livestock, and the Centers for Disease Control and Prevention (CDC), the lead agency for the HPAI response pertaining to human health.
The USGS offers unique expertise and capacity pertaining to research on diseases affecting free-ranging wildlife populations. This expertise has been critical to interjurisdictional surveillance and capacity-building efforts, including programs administered by the U.S. Department of Agriculture and the CDC. The USGS also provides resources, guidance, and tools to inform surveillance and interventions conducted by natural resource management agencies. More specifically, the USGS EMA provides objective and rigorous scientific data for inferring (1) the utility of new methods to detect and characterize AIVs, including those maintained in wildlife and the environment; (2) effects of HPAI on wildlife; (3) spatiotemporal patterns of wildlife host and AIV dispersal; (4) the presence and persistence of AIVs in the environment; (5) how HPAI in wildlife influences consumptive and nonconsumptive utilization of wildlife; (6) how new tools and scientific methods may promote sound management decisions for HPAI-affected wildlife, particularly species of conservation concern; and (7) the combined effects of HPAI and other stressors on ecosystem health and resiliency.
This science strategy builds upon research outlined in a previous USGS science strategy for HPAI (2016–20) by Harris and others (2016). This strategy also details research priorities identified by the Administration (for example, U.S. Department of Agriculture, 2025) and others based on USGS Avian Influenza Science Team discussions with natural resource management agencies to address HPAI and wildlife health over the next 5 years (2025–29). This strategy presents 7 goals and 26 objectives that focus USGS and partner efforts on priorities that will fill data gaps regarding the effects of HPAI on wildlife managed by or co-managed with the U.S. Department of the Interior such that agencies and partners might anticipate or limit adverse effects on public resources. This strategy also identifies research priorities intended to address HPAI in wildlife and wildlife habitat that are anticipated to support interjurisdictional One Health efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1558","usgsCitation":"Ramey, A.M., Prosser, D.J., Hubbard, L.E., Vazquez-Meves, G., George, A., and Hopkins, M.C., 2025, U.S. Geological Survey science strategy to address highly pathogenic avian influenza and its effects on wildlife health 2025–29:\nU.S. Geological Survey Circular 1558, 26 p., https://doi.org/10.3133/cir1558.","productDescription":"vi, 26 p.","onlineOnly":"Y","ipdsId":"IP-174779","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":490570,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161121","text":"Open-File Report 2016-1121","description":"OFR 2016-1121","linkHelpText":"- U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)"},{"id":490421,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1558/cir1558.XML"},{"id":490420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1558/cir1558.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1558"},{"id":490419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1558/coverthb.jpg"}],"contact":"Director, Alaska Science Center
4210 University Drive
Anchorage, Alaska 99508
Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] (10.1029/2024JB029194) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network (VOISS-Net) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.
Salt marshes play a critical role in providing economic and ecological benefits but are susceptible to shoreline erosion. Natural and nature-based features (NNBF), such as breakwater reefs, are often used to reduce shoreline exposure to wave action and provide biogenic benefits. However, waves and water level are also responsible for the sediment supply necessary for marsh accretion, a critical component of marsh resilience to sea level rise. The goal of this study was to evaluate the effects of two subtidal breakwater reefs on wave energy, marsh shoreline erosion, and sediment deposition onto the marsh platform. As a restoration intervention, oyster shell and limestone gravel reefs were constructed within the nearshore zone of a high-energy shoreline where active shoreline erosion is causing marsh habitat loss. Although both sediment deposition and shoreline erosion were reduced after reef installation at all sites, the reefs demonstrated a statistically significant reduction in sediment deposition, whereas its effect on decreasing shoreline erosion was less pronounced. This variability in erosion reduction may be partly influenced by the physical dimensions of the reefs, affecting wave attenuation and leeward circulation. Wave measurements indicate that the reef reduced wave energy, particularly during south and southeast winds that could lead to the largest onshore waves. Given that these strong onshore winds are seasonal, extending the duration of data collection could provide deeper insights into the reef's influence on marsh shoreline erosion. This study is novel in that there are limited experimental or observational studies quantifying the wave reduction capacity and effects of subtidal reefs on marsh shoreline erosion and sediment dynamics. Studies such as these are critical to evaluate the capacity of subtidal reefs to protect marsh shorelines from erosion, but also to measure their impact on accretion processes necessary for the marsh to maintain elevation under future sea level rise.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01564-7","usgsCitation":"Smith, K., Pitchford, J.L., Sparks, E., Archer, M., Virden, M., Terrano, J.F., and Smith, C., 2025, Evaluating the influence of constructed subtidal reefs on marsh shoreline erosion, sediment deposition, and wave energy: Estuaries and Coasts, v. 48, 128, 19 p., https://doi.org/10.1007/s12237-025-01564-7.","productDescription":"128, 19 p.","ipdsId":"IP-166569","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01564-7","text":"Publisher Index Page"},{"id":490713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Grand Bay National Estuarine Research Reserve, Point Aux Chenes Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.45901043533199,\n 30.376549622657805\n ],\n [\n -88.45901043533199,\n 30.326593096623256\n ],\n [\n -88.40111942768058,\n 30.326593096623256\n ],\n [\n -88.40111942768058,\n 30.376549622657805\n ],\n [\n -88.45901043533199,\n 30.376549622657805\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitchford, Jonathan L.","contributorId":301251,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":940245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sparks, Eric L.","contributorId":356848,"corporation":false,"usgs":false,"family":"Sparks","given":"Eric L.","affiliations":[{"id":85257,"text":"Mississippi-Alabama Sea Grant","active":true,"usgs":false}],"preferred":false,"id":940246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Michael J.","contributorId":356849,"corporation":false,"usgs":false,"family":"Archer","given":"Michael J.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":940247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Virden, Matthew","contributorId":350892,"corporation":false,"usgs":false,"family":"Virden","given":"Matthew","affiliations":[{"id":83862,"text":"Mississippi State University, Mississippi","active":true,"usgs":false}],"preferred":false,"id":940248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terrano, Joseph F. 0000-0003-3060-7682 jterrano@usgs.gov","orcid":"https://orcid.org/0000-0003-3060-7682","contributorId":173263,"corporation":false,"usgs":true,"family":"Terrano","given":"Joseph","email":"jterrano@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940250,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268294,"text":"70268294 - 2025 - Population growth of threatened Gulf Sturgeon may be limited by the frequency of adult episodic mortality events","interactions":[],"lastModifiedDate":"2025-06-20T14:47:48.754686","indexId":"70268294","displayToPublicDate":"2025-06-11T09:42:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20748,"text":"Marine and Coastal Fisheries: Dynamics, Management and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Population growth of threatened Gulf Sturgeon may be limited by the frequency of adult episodic mortality events","docAbstract":"We identified spatial and temporal variation in population trends for Gulf Sturgeon Acipenser desotoi (previously known as Acipenser oxyrinchus desotoi) across the species’ range to inform recovery strategies. We also assessed whether adult survival or recruitment more strongly influences population change.
We analyzed adult Gulf Sturgeon capture–recapture data from 1990 to 2022 across seven Gulf of Mexico river systems. Using temporal symmetry models and fixed estimates of adult survival from a companion study, we estimated seniority probability (γi + 1), capture probability (p), recruitment (f), and population growth rate (λ) for adult fish. Models were compared using Akaike information criterion adjusted for small sample sizes, and parameter estimates were derived at both river-specific and rangewide scales.
Adult survival (φ) was the primary driver of λ across the species’ range, with γ consistently >0.5 in most rivers and time periods. While rangewide λ suggested stable or slightly increasing adult populations, river-level trends varied. Recent declines in λ and f were observed in the Escambia, Apalachicola, and Suwannee rivers—systems affected by red tide, hurricanes, or oil exposure following the Deepwater Horizon spill. Capture probabilities remained low across rivers and time periods.
Long-term recovery of Gulf Sturgeon is likely more sensitive to adult survival than recruitment to the adult population. Population trajectories differ across rivers and may reflect both demographic changes and inconsistencies in monitoring. Restoring consistent, standardized adult monitoring in select rivers will improve the ability to detect meaningful trends and guide conservation efforts focused on minimizing adult mortality.
Most previous research has used an individual water quality parameter, such as calcium, to predict likelihood of zebra mussel establishment in lakes; we employed two multiple-factor methods, our own susceptibility index for zebra mussels in lakes (SIZL) and aragonite saturation state, to evaluate the risk of mussel establishment. Thirty sites in Voyageurs National Park (VNP) were sampled in 2023 for water quality conditions, including those that play a key role in mussel survivability. These results were combined with existing data sets to determine which lakes, and which locations within the larger lakes, are at greatest risk for zebra mussel establishment. Results for VNP indicate that physical lake characteristics and water quality conditions (both single- and multiple-factor methods) put the large, interconnected lakes in VNP at greater risk of zebra mussel establishment than the smaller interior lakes. All sampled interior lakes had alkalinity and calcium concentrations below thresholds conducive to zebra mussel establishment, although Mukooda and O’Leary lakes were identified as the most at-risk interior lakes. The area in the large lakes most at risk was Sullivan Bay in Kabetogama Lake, where water quality conditions were found to be conducive to zebra mussel establishment. Results from this study could be used by resource managers to focus additional inspections, decontaminations, and regulations to protect the most at-risk lakes. These multiple-factor methods may be useful in determining the risk of zebra mussel infestation in other water bodies.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2025.2488829","usgsCitation":"Christensen, V., Katona, L.R., Trompeter, H., Maki, R., Smith, J., and Sandborn, D., 2025, Water quality-based risk assessment for zebra mussel establishment: A case study of single- and multiple-factor methods in northern temperate lakes: Lake and Reservoir Management, v. 41, no. 2, p. 124-142, https://doi.org/10.1080/10402381.2025.2488829.","productDescription":"19 p.","startPage":"124","endPage":"142","ipdsId":"IP-167134","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":492828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.44469471404027,\n 48.25812750188285\n ],\n [\n -92.43814232688678,\n 48.30708718825505\n ],\n [\n -92.47445207574346,\n 48.377421556342625\n ],\n [\n -92.46304044038844,\n 48.41324094675181\n ],\n [\n -92.52009861716228,\n 48.4559157257907\n ],\n [\n -92.62902786373112,\n 48.4442181433015\n ],\n [\n -92.70890931121498,\n 48.4559157257907\n ],\n [\n -92.68504861910944,\n 48.49992951737704\n ],\n [\n -92.6321401279189,\n 48.50199172694181\n ],\n [\n -92.63628981350283,\n 48.538410262889045\n ],\n [\n -92.95374076064601,\n 48.61254059167456\n ],\n [\n -93.08134359234099,\n 48.62694220072322\n ],\n [\n -93.16952441099208,\n 48.62831356824623\n ],\n [\n -93.17367409657537,\n 48.578920857403915\n ],\n [\n -93.06267000721486,\n 48.45935567841727\n ],\n [\n -93.00872409462822,\n 48.42288032028864\n ],\n [\n -92.94544138947879,\n 48.40015601627843\n ],\n [\n -92.77841654473997,\n 48.40635456089478\n ],\n [\n -92.71409641819443,\n 48.387067719148206\n ],\n [\n -92.57300710835281,\n 48.324334982522885\n ],\n [\n -92.5055747176201,\n 48.284311171440095\n ],\n [\n -92.51076946771622,\n 48.257714102321444\n ],\n [\n -92.44469471404027,\n 48.25812750188285\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katona, Leon R. 0000-0001-5323-1871","orcid":"https://orcid.org/0000-0001-5323-1871","contributorId":331458,"corporation":false,"usgs":true,"family":"Katona","given":"Leon","email":"","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trompeter, Hailey Elizabeth 0009-0007-6855-5642","orcid":"https://orcid.org/0009-0007-6855-5642","contributorId":358493,"corporation":false,"usgs":true,"family":"Trompeter","given":"Hailey Elizabeth","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maki, Ryan P.","contributorId":190131,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":943856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, James C.","contributorId":351486,"corporation":false,"usgs":false,"family":"Smith","given":"James C.","affiliations":[{"id":82351,"text":"U.S. National Park Service (NPS)","active":true,"usgs":false}],"preferred":false,"id":943857,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sandborn, Daniel E.","contributorId":358495,"corporation":false,"usgs":false,"family":"Sandborn","given":"Daniel E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":943858,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70268116,"text":"70268116 - 2025 - High-pass corner frequency selection and review tool for use in ground-motion processing","interactions":[],"lastModifiedDate":"2025-09-09T14:38:21.181387","indexId":"70268116","displayToPublicDate":"2025-06-11T08:49:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"High-pass corner frequency selection and review tool for use in ground-motion processing","docAbstract":"Raw seismological waveform data contain noise from the instrument’s surroundings and the instrument itself that can dominate recordings at low and high frequencies. To use these data in ground‐motion modeling, the effects of noise on the signals must be reduced and the signals’ usable frequency range identified. We present automated procedures to efficiently reduce low‐frequency noise that are implemented in the software package gmprocess. These procedures check for, and as needed remove, low‐frequency artifacts in the displacement record using polynomial fits, which can be used in combination with existing signal‐to‐noise ratio (SNR)‐based corner‐frequency selection procedures. The automated selections are then efficiently verified and refined using a graphical user interface (GUI) that plots relevant ground‐motion time series and spectra and tracks modifications to signal processing parameters. We demonstrate these procedures using recordings from the 2020 M 5.1 Sparta, North Carolina, and the 2013 M 4.7 southern Ontario earthquakes. Data processed with the SNR‐only and polynomial criteria for these events contain displacement artifacts in 37% and 23% of processed traces, respectively. Records with remaining artifacts are corrected manually using the GUI. These processing steps illustrate the workflow for efficient data processing with quality control.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240265","usgsCitation":"Ramos-Sepulveda, M.E., Brandenberg, S.J., Buckreis, T.E., Parker, G.A., and Stewart, J., 2025, High-pass corner frequency selection and review tool for use in ground-motion processing: Seismological Research Letters, v. 96, no. 5, p. 3244-3252, https://doi.org/10.1785/0220240265.","productDescription":"9 p.","startPage":"3244","endPage":"3252","ipdsId":"IP-163865","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":490720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos-Sepulveda, Maria E.","contributorId":294748,"corporation":false,"usgs":false,"family":"Ramos-Sepulveda","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":940267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandenberg, Scott J.","contributorId":303895,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":940268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckreis, Tristan E","contributorId":295733,"corporation":false,"usgs":false,"family":"Buckreis","given":"Tristan","email":"","middleInitial":"E","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":940269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":940270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, Jonathan P.","contributorId":350854,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan P.","affiliations":[{"id":83855,"text":"University of California, Los Angeles, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":940271,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269937,"text":"70269937 - 2025 - Co-location of sheep grazing and solar energy production yields agrotechnological synergies","interactions":[],"lastModifiedDate":"2025-08-07T15:19:27.071437","indexId":"70269937","displayToPublicDate":"2025-06-11T08:10:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":679,"text":"Agricultural Systems","active":true,"publicationSubtype":{"id":10}},"title":"Co-location of sheep grazing and solar energy production yields agrotechnological synergies","docAbstract":"CONTEXT
Agrivoltaics—the co-location of solar energy and agricultural production—may reduce land-use competition and boost revenues for landowners. Sheep grazing in solar facilities (i.e., solar grazing/agrivoltaic grazing systems) is increasingly common in agricultural areas. Solar grazing can provide land access to flock owners and support agricultural viability via payments for vegetation management. However, there is a need for more data on how co-location of sheep grazing and solar energy production affects flock health, stocking rates, and feedback loops for maintenance of vegetation in solar facilities across regions.
OBJECTIVE
Our objective was to better understand synergies and tradeoffs associated with agrivoltaic grazing systems by investigating applied grazing management questions as well as questions regarding agrotechnological co-benefits related to simultaneous flock health and vegetation management in solar facilities.
METHODS
We tested effects of sheep stocking rates (0 to 10 sheep per ha–1), site preparation (fallow vs. legume seed-mix planting), and microclimate (panel-shaded areas vs. panel interspaces) on herbage yield and nutritional quality, flock health and condition, and a vegetation management success index. We collected these data across two grazing seasons in an operational, 21.85-ha photovoltaic solar facility (18 MW) established on a previous old field in New York State, USA.
RESULTS AND CONCLUSIONS
Shade from solar panels negatively affected herbage yield. We detected no significant differences in herbage yield or vegetation management outcomes between fallow and planted legume plots, suggesting that regrowth from native seed banks in solar facilities on previous old fields may be an economical alternative to seeding for sheep forage relative. Sheep stocking rates affected flock health and condition; we identified an optimal stocking rate of 8 sheep per ha–1 for achieving sufficient herbage yield and quality, maintaining flock health, and preventing vegetation overgrowth from shading solar panels at our study site. Solar grazing can yield an agrotechnological synergy supporting healthy forage, healthy sheep, and vegetation management in community-scale (i.e., <25 MW) solar facilities without mowing. In a well-managed solar grazing system, high herbage yield and quality promote high flock health and condition, and the healthy flock suppresses vegetation enough to prevent panel shading. SIGNIFICANCE Our study highlights the potential for sheep grazing in solar facilities to simultaneously benefit sheep and solar energy production systems. Solar grazing can present a “win-win” scenario for solar developers and sheep producers in the northeastern U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agsy.2025.104403","usgsCitation":"Kochendoerfer, N., Westbrook, A., McMillan, C.E., Lapierre, P., Zaman, M.A., Morris, S.H., DiTommaso, A., and Grodsky, S.M., 2025, Co-location of sheep grazing and solar energy production yields agrotechnological synergies: Agricultural Systems, v. 229, 104403, 11 p., https://doi.org/10.1016/j.agsy.2025.104403.","productDescription":"104403, 11 p.","ipdsId":"IP-162126","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493798,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agsy.2025.104403","text":"Publisher Index Page"},{"id":493713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"Dryden","otherGeospatial":"Cornell University","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.33898335492889,\n 42.509702788259034\n ],\n [\n -76.33898335492889,\n 42.4773611777818\n ],\n [\n -76.26572491357251,\n 42.4773611777818\n ],\n [\n -76.26572491357251,\n 42.509702788259034\n ],\n [\n -76.33898335492889,\n 42.509702788259034\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"229","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kochendoerfer, Nikola","contributorId":359134,"corporation":false,"usgs":false,"family":"Kochendoerfer","given":"Nikola","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westbrook, A. Sophie","contributorId":359361,"corporation":false,"usgs":false,"family":"Westbrook","given":"A. Sophie","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":945184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMillan, Christina E.","contributorId":359135,"corporation":false,"usgs":false,"family":"McMillan","given":"Christina","middleInitial":"E.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lapierre, P. Andrew","contributorId":359137,"corporation":false,"usgs":false,"family":"Lapierre","given":"P. Andrew","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zaman, Muhammad A.","contributorId":359140,"corporation":false,"usgs":false,"family":"Zaman","given":"Muhammad","middleInitial":"A.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, Scott H.","contributorId":359143,"corporation":false,"usgs":false,"family":"Morris","given":"Scott","middleInitial":"H.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiTommaso, Antonio","contributorId":359146,"corporation":false,"usgs":false,"family":"DiTommaso","given":"Antonio","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":944994,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grodsky, Steven Mark 0000-0003-0846-7230","orcid":"https://orcid.org/0000-0003-0846-7230","contributorId":328517,"corporation":false,"usgs":true,"family":"Grodsky","given":"Steven","email":"","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":944995,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70268846,"text":"70268846 - 2025 - Estimating disease prevalence from preferentially sampled, pooled data","interactions":[],"lastModifiedDate":"2025-07-08T15:00:11.237294","indexId":"70268846","displayToPublicDate":"2025-06-11T07:51:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5531,"text":"Journal of Data Science","onlineIssn":"1683-8602","printIssn":"1680-743X","active":true,"publicationSubtype":{"id":10}},"title":"Estimating disease prevalence from preferentially sampled, pooled data","docAbstract":"Since 1985, the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex (hereafter, Hakalau) has protected the largest endemic forest bird diversity in the State of Hawaii. This includes three endangered and one threatened species and their habitats. Hakalau’s vast area (155 km2), mostly high elevation (>1500 m) montane forest, provides refuge from avian malaria (Plasmodium relictum) vectored by introduced southern house mosquitoes (Culex quinquefasciatus). However, increases in the seasonal temperatures optimal for disease carrying mosquitoes associated with climate change have coincided with recent downward trends of native species in the closed forest area of the refuge (1450–1750 m), where disease is most likely to occur. Therefore, to inform refuge management with the most updated information on these populations and their trends, we analyzed forest bird survey data collected using point transect distance sampling with new survey data from 2021–2024. We stratified our analysis across management units, including the open forest and pasture since 1987, and the closed forest since 1999, and across four elevation ranges (<1500, 1500–1700, 1700–1900, and >1900 m) since 1999. We used distance sampling to estimate species- and strata-specific abundances and applied log-linear regression to detect trends across the timeseries. We found a continuation of previous trends, wherein most native forest birds declined in the closed forest strata (mostly below 1700 m) and increased in the highest elevation and pasture strata. Patterns were highly species-specific for the three lower elevations and open forest strata. ‘Apapane (Himatione sanguinea) and warbling white-eye (Zosterops japonicus), the most abundant native and introduced bird species, respectively, increased in nearly all strata. ‘I‘iwi (Drepanis coccinea) and Hawai‘i ‘amakihi (Chlorodrepanis virens virens), also common, decreased in closed forest, were stable in open forest, and increased in pasture. Both species were generally stable or increasing across all elevation bands, except Hawaiʻi ʻamakihi decreased in the below 1500 m and the 1500–1700 m elevation bands. All three of the federally endangered forest bird species declined in closed forest. Hawai‘i ‘ākepa (Loxops coccineus) also declined in the open forest and 1700–1900 m band and was the only species to decline overall. ‘Akiapōlā‘au (Hemignathus wilsoni) declined in closed forest but increased overall. ‘Alawī (Loxops mana, also known as Hawai‘i creeper) also decreased in the closed forest, but was stable to increasing in most strata and remained stable overall. Hawaiʻi ʻelepaio (Chasiempis sandwichensis) declined in closed forest, was stable in open forest and most elevation strata, and increased in pasture. ʻŌmaʻo (Myadestes obscurus) was stable in open and closed forest and at middle elevations and increased in the pasture. Introduced red-billedleiothrix (Leiothrix lutea) declined in closed forest, was stable in the open forest and at most elevations, and increased in the pasture. Coinciding with these changes, seasonal conditions for vector occurrence have continued to lengthen in the lower elevation strata through 2024, while Hakalau’s outplanting efforts continued to increase forest cover in the pasture, suggesting that disease-free habitat may have decreased in the closed forest and increased in the pasture. The declines in the closed forest and mixture of trends in the open forest and middle elevations bands suggest emigration into the higher elevation strata from lower elevation strata, and that possible threats have suppressed forest birds even at elevations >1500 m.
","largerWorkTitle":"Hawai‘i Cooperative Studies Unit Technical Report Series","language":"English","publisher":"University of Hawai'i at Hilo","usgsCitation":"Hunt, N., Kendall, S., Bak, T., and Camp, R.J., 2025, Status and trends of forest bird populations at Hakalau Forest National Wildlife Refuge, 1987–2024: Hawaii Cooperative Studies Unit Technical Report HCSU-117, iii, 159 p.","productDescription":"iii, 159 p.","ipdsId":"IP-179408","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":491896,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":491886,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://hdl.handle.net/10790/5400"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.36090692408706,\n 19.96645706445993\n ],\n [\n -155.36090692408706,\n 19.740582700116107\n ],\n [\n -155.19266790064404,\n 19.740582700116107\n ],\n [\n -155.19266790064404,\n 19.96645706445993\n ],\n [\n -155.36090692408706,\n 19.96645706445993\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunt, Noah","contributorId":355564,"corporation":false,"usgs":false,"family":"Hunt","given":"Noah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":942459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Steve","contributorId":213517,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","affiliations":[],"preferred":false,"id":942461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bak, Trevor","contributorId":292157,"corporation":false,"usgs":false,"family":"Bak","given":"Trevor","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":942460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":942462,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267590,"text":"ofr20251028 - 2025 - Preliminary field report of landslide hazards following Hurricane Helene","interactions":[],"lastModifiedDate":"2025-08-14T19:21:57.113137","indexId":"ofr20251028","displayToPublicDate":"2025-06-09T10:45:00","publicationYear":"2025","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":"2025-1028","displayTitle":"Preliminary Field Report of Landslide Hazards Following Hurricane Helene","title":"Preliminary field report of landslide hazards following Hurricane Helene","docAbstract":"This report reflects our knowledge regarding the widespread landslide activity associated with Hurricane Helene observed during the U.S. Geological Survey’s (USGS) mission assignment to North Carolina in October 2024. The material in this report was originally prepared for the Federal Emergency Management Agency under mission assignment DR-4827-NC. The data and commentary in this report are reflective of a report provided to the Federal Emergency Management Agency (FEMA) on October 18, 2024, as well as information provided in briefings at the Buncombe County Emergency Operations Center. The report has been modified for public dissemination.
This assessment was based on systematic visual examination and mapping of landslide locations from aerial and satellite imagery, visual and photographic observations from low-level helicopter overflights and conversations with local landslide experts from the North Carolina Geological Survey and Appalachian Landslide Consultants PLLC, and more than 50 years of combined landslide hazard professional experience of the mission-assigned field team. No systematic field investigations were done by the USGS.
While responding to the event, the USGS did not identify any landslides that posed an immediate major threat to recovery personnel in parts of nine counties in North Carolina (Avery, Buncombe, Henderson, McDowell, Mitchell, Polk, Rutherford, Watauga, and Yancey); however, threats from renewed landslide activity may remain heightened in localized areas for months or even years. Known areas of the most abundant landslide occurrence include Bat Cave, Lake Lure, Chimney Rock, Swannanoa, Black Mountain, Fairview, steep areas in Asheville, and the Blue Ridge Parkway. The USGS shared detailed locations of known landslides with the Emergency Operations Centers. The thousands of landslide scars on hillsides and landslide deposits on flatter ground may present some threat to recovery activities. Soil and rocks will continue to erode from newly exposed landslide scars and may pose a threat to people and infrastructure who are immediately nearby. In general, the steeper and taller the landslide scar, the greater the potential threat. This threat is heightened during periods of rainfall and increases with the duration and intensity of rainstorms. Very heavy rainfall, or repeated rainfall events during short periods, could also initiate new landslides on steep slopes. Excavation of landslide deposits, particularly excavation of those deposits directly adjacent to steep slopes, may also pose a threat to nearby people and equipment.
An interagency collaborative mapping effort led by the USGS that informed this assessment identified 1,155 landslide locations by the October 2024 briefings, but that number increased to 2,217 in a final reviewed version of the locations published in January 2025. Locations were mapped from satellite imagery, fixed-wing and helicopter surveys, media and social media, and field reports in the 3 weeks following the passage of the remnants of Hurricane Helene. USGS products outlined in this report are publicly available and include geotagged photographs from aerial reconnaissance, hazard models, an interactive view of mapped landslide locations, and landslide safety and education resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20251028","programNote":"Landslide Hazards Program","usgsCitation":"Allstadt, K.E., McBride, S.K., Godt, J.W., Slaughter, S.L., Baxstrom, K.W., Sobieszczyk, S., and Stull, A., 2025, Preliminary field report of landslide hazards following Hurricane Helene: U.S. Geological Survey Open-File Report 2025–1028, 15 p., https://doi.org/10.3133/ofr20251028.","productDescription":"Report vi, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-175853","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494134,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118637.htm","linkFileType":{"id":5,"text":"html"}},{"id":490259,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1028"},{"id":488392,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1028/ofr20251028.xml"},{"id":488391,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1028/images"},{"id":486657,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1C5W3PQ","text":"USGS data release","description":"USGS data release for OFR 2025-1028","linkHelpText":"Oblique Aerial Photographs from October 13 and 17, 2024, of Landslides and Flooding Caused by Hurricane Helene (ver 1.1, March 2025)"},{"id":486656,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1028/ofr20251028.pdf","text":"Report","size":"7.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1028"},{"id":486655,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1028/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81,\n 36.667\n ],\n [\n -83.25,\n 36.667\n ],\n [\n -83.25,\n 35\n ],\n [\n -81,\n 35\n ],\n [\n -81,\n 36.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Hybridization and interspecific gene flow play a substantial role in the evolution of plant taxa. The eastern North American white oak syngameon, a group of approximately 15 ecologically, morphologically and genomically distinguishable species, has long been recognised as a model system for studying introgressive hybridization in temperate trees. However, the prevalence, genomic context and environmental correlates of introgression in this system remain largely unknown. To assess introgression in the eastern North American white oak syngameon and population structure within the widespread Quercus macrocarpa, we conducted a rangewide survey of Q. macrocarpa and four sympatric eastern North American white oak species. Using a Hyb-Seq approach, we assembled a dataset of 3412 thinned single-nucleotide polymorphisms (SNPs) in 445 enriched target loci including 62 genes putatively associated with various ecological functions, as well as associated intronic regions and some off-target intergenic regions (not associated with the exons). Admixture analysis and hybrid class inference demonstrated species coherence despite hybridization and introgressive gene flow (due to backcrossing of F1s to one or both parents). Additionally, we recovered a genetic structure within Q. macrocarpa associated with latitude. Generalised linear mixed models (GLMMs) indicate that proximity to range edge predicts interspecific admixture, but rates of genetic differentiation do not appear to vary between putative functional gene classes. Our study suggests that gene flow between eastern North American white oak species may not be as rampant as previously assumed and that hybridization is most strongly predicted by proximity to a species' range margin.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.17822","usgsCitation":"Ribicoff, G., Garner, M., Pham, K., Althaus, K., Cavendar-Bares, J., Crowl, A., Gray, S., Gugger, P.F., Hahn, M., Liao, S., Manos, P., Mohn, R., Pearse, I.S., Steichmann, N., Tuffin, A., Whittemore, A.T., and Hipp, A., 2025, Introgression, phylogeography, and genomic species cohesion in the eastern North American white oak syngameon: Molecular Ecology, v. 34, no. 21, e17822, 22 p., https://doi.org/10.1111/mec.17822.","productDescription":"e17822, 22 p.","ipdsId":"IP-173668","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":497374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/mec.17822","text":"Publisher Index Page"},{"id":497284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n 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data","interactions":[],"lastModifiedDate":"2025-07-18T14:20:50.575081","indexId":"70269339","displayToPublicDate":"2025-06-09T09:13:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Assessing uncertainty in forecasts of refugia for Joshua trees using high-density distribution data","docAbstract":"Joshua trees (Yucca brevifolia and Yucca jaegeriana) are iconic, foundational species of the Mojave and Sonoran Deserts in North America. Due to their ecosystem importance, long generation times, and low resilience to disturbance, these hybridizing sister species are increasingly the focus of conservation efforts. Predicting Joshua tree responses to impending climate variability, along with the extent of suitable future habitat and/or climate refugia, is critical to ongoing management planning. Previous modeling efforts have been hampered by incomplete distribution data and are now out-of-date with the most recent global climate projections. We used a high-resolution, field-validated distributional database of nearly complete presence and absence records, along with a simulation of dispersal, to project Joshua tree distributions into future time periods and Coupled Model Intercomparison Project phase 6 (CMIP6) emissions scenarios. Overall, our models predict widespread habitat loss with limited availability of newly suitable habitat. Under the highest emissions scenario (SSP5–8.5), we project that up to 80% of current habitat may become unsuitable by 2100. Even so, our models predict a larger area of potential refugia than some previous efforts, particularly in the southern parts of the range, where we project persistent refugia through 2100. We also found a non-negligible influence of baseline climate period (the period used to represent “current” climate) on predicted future habitat probabilities. Simulations of dispersal based on the Joshua tree's limited capacity suggest that over 25% of suitable future habitat could be inaccessible, while much of the remaining future habitat area consists of refugia within the upper elevations of the species' current range. An increasing frequency of wildfire appears to be the greatest rangewide threat to future suitable habitat for Joshua trees, followed by renewable energy development. Over 80% of future suitable habitat occurs on federally managed lands, including up to 47% within Bureau of Land Management-administered areas and 15% within National Park Service units.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70308","usgsCitation":"Shryock, D., Esque, T., Berr, G.A., and DeFalco, L., 2025, Assessing uncertainty in forecasts of refugia for Joshua trees using high-density distribution data: Ecosphere, v. 16, no. 6, e70308, 25 p., https://doi.org/10.1002/ecs2.70308.","productDescription":"e70308, 25 p.","ipdsId":"IP-169416","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":492861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70308","text":"Publisher Index Page"},{"id":492533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120,\n 39\n ],\n [\n -120,\n 34\n ],\n [\n -112,\n 34\n ],\n [\n -112,\n 39\n ],\n [\n -120,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":943483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":943484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berr, Gabrielle A. 0009-0004-1531-7761","orcid":"https://orcid.org/0009-0004-1531-7761","contributorId":333759,"corporation":false,"usgs":false,"family":"Berr","given":"Gabrielle","email":"","middleInitial":"A.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":943485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":943486,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267973,"text":"70267973 - 2025 - Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology","interactions":[],"lastModifiedDate":"2025-06-10T14:27:36.321627","indexId":"70267973","displayToPublicDate":"2025-06-07T09:26:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Rainfall thresholds for postfire debris-flow initiation vary with short-duration rainfall climatology","docAbstract":"The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris-flow initiation are commonly expressed as rainfall intensity-duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass-movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff-generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris-flow initiation thresholds vary systematically with short-duration rainfall-intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much-needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field-based hazard assessment. Furthermore, if the observed variation in thresholds reflects long-term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris-flow likelihood.
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Survey","active":true,"usgs":false}],"preferred":false,"id":939840,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":939841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":939842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trugman, Daniel T.","contributorId":197011,"corporation":false,"usgs":false,"family":"Trugman","given":"Daniel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":939843,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267962,"text":"70267962 - 2025 - Understanding the evolution of scoria cone morphology using multivariate models","interactions":[],"lastModifiedDate":"2025-06-09T15:14:31.734183","indexId":"70267962","displayToPublicDate":"2025-06-06T10:11:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8956,"text":"Communications Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the evolution of scoria cone morphology using multivariate models","docAbstract":"Scoria cones are the most abundant type of volcano in the Solar System. They occur in every tectonic setting and often overlap with human populations, yet our ability to provide complete geochronology within volcanic fields remains limited. Appropriate geochronology underpins the reconstruction of size-frequency distribution and is a key input for robust volcanic hazard assessment. Morphometric data have long been used to estimate relative ages of scoria cones; however, they have only shown promise at single volcanic fields and simple cones with homogenous pyroclastics. Here, we present a new global inventory of dated scoria cones (n = 572) from 71 volcanic fields formed under diverse magmatic, tectonic and climatic regimes, and build data-driven age models for dating scoria cones using easily accessible morphometric, reflectance and climatic variables. Our models suggest chemical composition of ascending magma may influence the initial scoria cone morphology which is then gradually modified by erosion over time.
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The global Landsat archive is made available in the Universal Transverse Mercator (UTM) projection system which preserves geographic shape across small area but introduces small errors in distance and area. As remote sensing-based studies develop from local scales to regional and global, they need to adopt more appropriate map projections from which accurate area measurements can be made. While effects of resampling on recorded values have been studied in the past, the impacts on higher-level results such as land cover have not been widely reported. This study investigates an approach for monitoring land cover and land change using two input datasets derived from identical source Landsat data, where one input dataset is transformed to an equal-area map projection and thereby resampled. Recorded surface reflectance values are changed through the reprojection/resampling process, and our study highlights observed differences in derived land cover from these two different input datasets throughout the various stages of deriving land cover and related characteristics. Our findings suggest that large-scale analyses of land cover will not be substantially impacted by reprojection of input data, but small-scale analyses should exercise caution when interpreting timing and magnitude of pixel-level change and classification dynamics.
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Many physical processes contribute to spatial variations in observed ground motions, including earthquake radiation pattern, directivity, variable path attenuation, and site effects. Current nonergodic ground‐motion models use spatially varying coefficients for path and site effects, but they do not address trade‐offs with complex earthquake source effects. To quantify the influence of directivity on ground‐motion amplitudes, we use records from multiple smaller earthquakes with epicenters near that of a larger event. We use these small magnitude events as eGfs and estimate repeatable path and site effects at individual stations, assuming that the average adjustments are not controlled by directivity. We adjust residuals from the larger earthquake using the eGf terms, isolating effects related to the rupture. This method clearly enhances the observed broadband directivity observed in the 2022 M 5.1 and 2007 M 5.4 Alum Rock earthquake ground motions, reinforcing the conclusion that their ruptures were unilateral. For the 2004 M 6.0 Parkfield earthquake, we find a bilateral rupture model better fits the data because variations in rupture velocity, slip rate, and slip distribution seem to have a stronger effect on the ground motions than rupture direction alone. Applying eGf adjustments reduces the standard deviation of the rupture models over the three earthquakes by 32% on average and by up to 57% for the 2022 Alum Rock earthquake, confirming we have effectively removed repeatable effects related to the wave propagation path and site response. We propose a novel measure of the frequency‐dependent directivity amplification strength as the reduction in ground‐motion residual variability gained by fitting a directivity model; for the three earthquakes considered, this parameter varies between 25% and 75%, indicating that directivity can strongly influence ground motions and should be considered in ground‐motion modeling.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240264","usgsCitation":"Parker, G.A., Baltay Sundstrom, A.S., and Hirakawa, E.T., 2025, An empirical Green’s function approach for isolating directivity effects in earthquake ground-motion amplitudes: Bulletin of the Seismological Society of America, v. 115, no. 5, p. 2336-2354, https://doi.org/10.1785/0120240264.","productDescription":"19 p.","startPage":"2336","endPage":"2354","ipdsId":"IP-171011","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":490708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 38.5\n ],\n [\n -123,\n 36\n ],\n [\n -120.5,\n 36\n ],\n [\n -120.5,\n 38.5\n ],\n [\n -123,\n 38.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":940272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":940273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hirakawa, Evan Tyler 0000-0002-5720-0850","orcid":"https://orcid.org/0000-0002-5720-0850","contributorId":295776,"corporation":false,"usgs":true,"family":"Hirakawa","given":"Evan","email":"","middleInitial":"Tyler","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":940274,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265826,"text":"70265826 - 2025 - A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable)","interactions":[],"lastModifiedDate":"2025-06-16T14:31:10.9429","indexId":"70265826","displayToPublicDate":"2025-06-06T09:12:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable)","docAbstract":"The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding-based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data-driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA-specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready-to-use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user-driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long-term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70100","usgsCitation":"Takahashi, M., Frøslev Guldberg, T., Pauperio, J., Thalinger, B., Klymus, K.E., Helbing, C., Villacorta-Rath, C., Silliman, K., Thompson, L., Jungbluth, S., Yee Yong, S., Formel, S., Jenkins, G., Laporte, M., Deagle, B., Rajbhandari, S., Jeppesen Stjernegaard, T., Bissett, A., Jerde, C.L., Hahn, E.E., Schriml, L., Hunter, C., Newman, P., Woollard, P., Harper, L., Dunn, N., West, K., Haderlé, R., Wilkinson, S., Acharya-Patel, N., Lopez, M., Cochrane, G., and Berry, O., 2025, A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable): Environmental DNA, v. 7, no. 3, e70100, 20 p., https://doi.org/10.1002/edn3.70100.","productDescription":"e70100, 20 p.","ipdsId":"IP-173048","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":491007,"rank":0,"type":{"id":40,"text":"Open Access 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In New Mexico, USA, minimum counts from aerial surveys are the primary basis for management decisions regarding desert bighorn sheep (Ovis canadensis mexicana); therefore, there is a need to assess methods that account for imperfect detection. Common survey methods for large mammals (i.e., sightability, double-observer, and double-observer sightability models) are known to result in biased estimates, but the presence of radio-collared individuals within a population allows for estimation of residual heterogeneity. Consequently, we explored the use of hybrid double-observer sightability approaches that account for residual heterogeneity when estimating abundance of desert bighorn sheep in the Fra Cristobal Mountains of New Mexico. We collected double-observer sightability data for 167 desert bighorn groups across 3 surveys between December 2016 and November 2017 and compared abundance estimates under 5 modeling methods: a standard sightability model (MS), a standard double-observer sightability model (MDS), a hybrid double-observer sightability model incorporating a recapture-type heterogeneity parameter (MR), a hybrid double-observer sightability model incorporating a mark-type heterogeneity parameter (MH), and a Lincoln-Petersen estimator. Across all model types, group behavior (moving vs. stationary) and group size influenced detection the most, followed by vegetation class, terrain type, and proportion of obscuring vegetation cover. Standard sightability models produced higher and less precise abundance estimates than all double-observer sightability models. Of the double-observer sightability models, MR was better supported and estimated greater abundance than MH and accounted for more bias than MDS. Both MR and MH yielded greater precision than MS. The MR models produced an average detection probability of p = 0.72 (SE = 0.02) and abundance estimates of N⌃ = 302 (95% CI = 262−385), N⌃= 290 (95% CI = 261−340), and N⌃= 352 (95% CI = 264−548) for the December 2016, May 2017, and November 2017 surveys, respectively. Lincoln-Petersen estimates of abundance were greater than all double-observer sightability models and similarly precise, but their usefulness is reduced given the requirement to permanently maintain a subset of animals with radio-collars combined with the inability to incorporate information from factors influencing detection probability. Further, because residual heterogeneity models better estimate visibility bias, are flexible in their accommodation of radio-collar data, and can be adapted to unique survey occasions, they present a viable and robust option for estimating desert bighorn sheep abundance.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70050","usgsCitation":"Ruhl, C., Cain, J.W., Abadi, F., and Hennig, J.D., 2025, Estimating abundance of desert bighorn sheep with double-observer sightability modeling with residual heterogeneity: Journal of Wildlife Management, v. 89, no. 6, e70050, 18 p., https://doi.org/10.1002/jwmg.70050.","productDescription":"e70050, 18 p.","ipdsId":"IP-173007","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70050","text":"Publisher Index Page"},{"id":500645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Fra Cristobal Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.21201322745647,\n 33.36445095764847\n ],\n [\n -107.21201322745647,\n 33.151779198257444\n ],\n [\n -107.07244373145068,\n 33.151779198257444\n ],\n [\n -107.07244373145068,\n 33.36445095764847\n ],\n [\n -107.21201322745647,\n 33.36445095764847\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruhl, Caitlin Q.","contributorId":353983,"corporation":false,"usgs":false,"family":"Ruhl","given":"Caitlin Q.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":956626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abadi, Fitsum","contributorId":366806,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","affiliations":[],"preferred":false,"id":956628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hennig, Jacob D.","contributorId":177569,"corporation":false,"usgs":false,"family":"Hennig","given":"Jacob","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":956629,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272280,"text":"70272280 - 2025 - Reevaluation of an adaptive management framework for invasive Grass Carp within Lake Erie","interactions":[],"lastModifiedDate":"2025-11-20T15:52:04.970413","indexId":"70272280","displayToPublicDate":"2025-06-06T08:46:28","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Reevaluation of an adaptive management framework for invasive Grass Carp within Lake Erie","docAbstract":"Objective
Response efforts to control invasive species frequently require making decisions in the face of substantial uncertainty. Adaptive management, which emphasizes learning during the process of managing, can be useful in cases where uncertainty impedes the decision-making process. Here, we describe how technical and institutional learning led to reformulating decision-making elements, known as double-loop learning, and how uncertainty stemming from a lack of knowledge influenced the selection of alternative strategies in an ongoing adaptive management process for invasive Grass Carp Ctenopharyngodon idella in Lake Erie.
Methods
When response efforts began, little was known about the population dynamics, ecology, and biology of Grass Carp within the lake. The availability of funding for sustained response efforts was also unknown. A network population model was constructed that relied heavily on values and estimates from limited data to project adult Grass Carp abundance in Lake Erie and evaluate the ability of various response strategies to achieve the desired objectives. After this initial assessment, the collection of new information was emphasized as response efforts increased to aid future assessments. With this expanded knowledge and including additional input from stakeholders, we modified the population model, evaluated new response scenarios, refined objectives, and examined the influence of uncertainty (parameter and expert opinion) on Grass Carp response efforts.
Results
Under uncertainty of population model parameters and expert opinion, the value-of-information analysis revealed that uncertainties in spawning deterrent efficacy, survival, and the underlying stock–recruitment relationship were important and could change the preferred decision. The efficiency of spawning deterrents influenced the preferred decision outcome among alternative strategies, particularly when >80% of fish were allowed to pass and spawn, indicating that a deterrent may not be worth implementing if passing rates are above this threshold.
Conclusions
We thereby demonstrate the benefits for invasive species management programs of implementing learning and resolving uncertainties within an adaptive management framework to improve decision making.
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