Assessing the potential for geothermal energy and liquid water presence in the Martian subsurface is crucial for future exploration and habitability studies. In this work, we employed comprehensive finite element model simulations adapted specifically for Martian conditions to estimate subsurface temperatures and the potential for liquid water at depth within Martian crater basins. Rock and fluid property values for basin fill were carefully adjusted to match Martian gravity, radiogenic heat generation, and compositional characteristics derived from rover analyses, Martian meteorite samples, and orbital spectroscopy data. Multiple modeling scenarios were explored to systematically evaluate end-member cases across critical variables such as heat flow, lithological composition, and average surface temperature. Sensitivity testing revealed that heat flow and average annual surface temperatures are the most important variables. Results were used in calculations based on a database of Martian craters to estimate the temperature of crater fill at depth. Our model results indicate significant potential for sustained liquid water in the subsurface within sedimentary deposits across a range of crater sizes and latitudes. They further suggest that viable geothermal reservoirs likely exist and are potentially accessible for future Martian missions seeking energy sources or exploring astrobiological hypotheses. This study provides a methodological framework for geothermal and hydrological assessments for the subsurface of Mars, contributing to ongoing planetary exploration strategies.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Gardner, R., Birdwell, J.E., French, K.L., Okubo, C., Pitman, J., Paxton, S.T., and Flaum, J.A., 2025, Exploring Martian geothermal and liquid water potential with basin modeling, in Using the Earth to save the Earth, v. 49, p. 1526-1541.","productDescription":"16 p.","startPage":"1526","endPage":"1541","ipdsId":"IP-180860","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499005,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035310"}],"otherGeospatial":"Mars","volume":"49","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":954444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":954445,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Okubo, Chris 0000-0001-9776-8128 cokubo@usgs.gov","orcid":"https://orcid.org/0000-0001-9776-8128","contributorId":174209,"corporation":false,"usgs":true,"family":"Okubo","given":"Chris","email":"cokubo@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":954446,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitman, Janet K. 0000-0002-0441-779X","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":228982,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet K.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paxton, Stanley T. 0000-0002-9098-1740 spaxton@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-1740","contributorId":739,"corporation":false,"usgs":true,"family":"Paxton","given":"Stanley","email":"spaxton@usgs.gov","middleInitial":"T.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954448,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flaum, Jason A. 0000-0003-1251-1142","orcid":"https://orcid.org/0000-0003-1251-1142","contributorId":300809,"corporation":false,"usgs":true,"family":"Flaum","given":"Jason","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954449,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272001,"text":"70272001 - 2025 - Evaluating mountain goat population structure in Glacier National Park and Waterton Lakes National Park","interactions":[],"lastModifiedDate":"2026-03-16T14:24:14.993784","indexId":"70272001","displayToPublicDate":"2025-12-01T09:14:30","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Evaluating mountain goat population structure in Glacier National Park and Waterton Lakes National Park","docAbstract":"Mountain goats are an iconic, climate-sensitive species across their North American alpine range. Among its nearly complete complement of native wildlife, no single species embodies Glacier National Park (GNP) more than the mountain goat. They play an important role as an alpine food source for many of the park’s carnivores including wolverines, mountain lions, and grizzly bears. Mountain goats face many increasing threats, particularly at the southern extent of their range. These include changes in precipitation and temperature, shifts in forage and fire frequency and intensity, and rapidly increasing visitation and recreation. Although the high latitude and elevations of GNP offer refugia, the mountain goat population likely declined between 2008 and 2019 and may also have a smaller distribution. In Montana, many other native mountain goat populations are also declining or have disappeared entirely. Using a combination of staff and citizen scientists, we collected fecal pellets across GNP in Montana, USA, and adjoining Waterton Lakes National Park (WLNP) in Alberta, Canada, between 2019 and 2023. We used genotypes of 6 to 19 loci microsatellites to identify individuals and assess isolation by distance, genetic structure, and genetic diversity. We found no evidence of genetic structure and only limited isolation by distance. This suggests that mountain goats in GNP and WLNP can be considered a single population, so samples can be combined across the area to estimate a single population size. Genetic diversity was similar to recent mountain goat studies conducted in other regions; allelic richness was 3.54 and inbreeding coefficients (FIS) ranged from 0.01–0.19, with values >0.11 only in the Livingston Range in the northwest of the study area. The high FIS in the Livingston Range suggests several closely related groups with little interchange, and perhaps a recent decrease in gene flow, both of which are consistent with a recent population decline in that area. We detected a high number of closely related individuals throughout our study area, consistent with the high adult survival, low reproductive success life history of goats, but also suggesting that we sampled much of the overall population.
","language":"English","publisher":"National Park Service","usgsCitation":"Graves, T., Stein, E., Dose, L.M., Crowhurst, R.S., Thomas, H., Epps, C.W., Found, R., Belt, J., and Biel, M., 2025, Evaluating mountain goat population structure in Glacier National Park and Waterton Lakes National Park, 23 p.","productDescription":"23 p.","ipdsId":"IP-175367","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501173,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2314005"}],"country":"Canada, United States","state":"Alberta, Montana","otherGeospatial":"Glacier National Park, Waterton Lakes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.65813170614295,\n 49.01864965992118\n ],\n [\n -113.9402382048133,\n 49.21093114844521\n ],\n [\n -114.19203574081646,\n 49.15606962898178\n ],\n [\n -114.0684684314816,\n 49.0064161433462\n ],\n [\n -114.47414223948681,\n 49.0064161433462\n ],\n [\n -114.11742906348216,\n 48.46980034937002\n ],\n [\n -113.865631527479,\n 48.4512474620191\n ],\n [\n -113.56020972371306,\n 48.22963785940766\n ],\n [\n -113.42964803837785,\n 48.24827158953556\n ],\n [\n -113.19883363037496,\n 48.406384328301044\n ],\n [\n -113.40400199304446,\n 48.70267920865706\n ],\n [\n -113.59285014504675,\n 48.92988954507129\n ],\n [\n -113.5951816037133,\n 48.994180616558\n ],\n [\n -113.65813170614295,\n 49.01864965992118\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":949682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stein, Eliza 0009-0009-1939-4971","orcid":"https://orcid.org/0009-0009-1939-4971","contributorId":361933,"corporation":false,"usgs":true,"family":"Stein","given":"Eliza","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":949683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dose, Lindsay M","contributorId":361935,"corporation":false,"usgs":false,"family":"Dose","given":"Lindsay","middleInitial":"M","affiliations":[{"id":27609,"text":"Contractor to USGS","active":true,"usgs":false}],"preferred":false,"id":949684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":949685,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thomas, Heather","contributorId":361939,"corporation":false,"usgs":false,"family":"Thomas","given":"Heather","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":949686,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Epps, Clinton W.","contributorId":359530,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","middleInitial":"W.","affiliations":[{"id":85841,"text":"Department of Fisheries, Wildlife, and Conservation Sciences, Oregon State University, Nash Hall Room 104, Corvallis, OR, 97331, USA","active":true,"usgs":false}],"preferred":false,"id":949687,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Found, Rob","contributorId":361942,"corporation":false,"usgs":false,"family":"Found","given":"Rob","affiliations":[{"id":6658,"text":"Parks Canada","active":true,"usgs":false}],"preferred":false,"id":949688,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belt, Jami","contributorId":177314,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","affiliations":[],"preferred":false,"id":949689,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Biel, Mark","contributorId":317264,"corporation":false,"usgs":false,"family":"Biel","given":"Mark","email":"","affiliations":[{"id":68985,"text":"GNP","active":true,"usgs":false}],"preferred":false,"id":949690,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70273723,"text":"70273723 - 2025 - Potential for co-production of lithium and geothermal resources in the Gulf Coast","interactions":[],"lastModifiedDate":"2026-01-26T15:53:11.820202","indexId":"70273723","displayToPublicDate":"2025-12-01T09:13:50","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Potential for co-production of lithium and geothermal resources in the Gulf Coast","docAbstract":"Lithium brine extractions and geothermal resource developments often are not economically viable as standalone projects, but they May become cost effective when the potential for both resources exist within the same reservoir. Subsurface datasets were analyzed to identify areas in the U.S. Gulf Coast region with potential for lithium brine and geothermal heat recovery. Temperature, lithium brine content, and reservoir quality data for thirty-four depositional units were evaluated using spatial analysis to interpret high-grade areas where both resources likely coexist. For sedimentary geothermal systems, potential resource areas are sorted by resource grade: as low temperature (<90°C, direct use potential), moderate temperature (90–150°C, direct use and electricity generation), and high temperature (>150°C, primarily electricity generation). Lithium resources were defined by Li lithium brine concentrations in parts per million (ppm): low potential (<100ppm), moderate potential (100–200ppm), and high potential (>200ppm). Reservoir quality affects the viability of both resources and is evaluated using interpreted lithofacies that describe the depositional environments of each unit. Using the results, a series of play fairway analysis maps were generated to support regional evaluations of lithium and geothermal resources and to identify areas of interest for detailed, prospect-scale studies.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Gardner, R., and Birdwell, J.E., 2025, Potential for co-production of lithium and geothermal resources in the Gulf Coast, in Using the Earth to save the Earth, v. 49, p. 410-418.","productDescription":"9 p.","startPage":"410","endPage":"418","ipdsId":"IP-180858","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":499004,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1035250"}],"country":"United States","state":"Alabama, Flroida, Georgia, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.52415578331033,\n 33.70981542560081\n ],\n [\n -102.52415578331033,\n 24.00347152136203\n ],\n [\n -79.56997834883599,\n 24.00347152136203\n ],\n [\n -79.56997834883599,\n 33.70981542560081\n ],\n [\n -102.52415578331033,\n 33.70981542560081\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":954441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":954442,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273756,"text":"70273756 - 2025 - Effects of climate change on Midwestern ecosystems: Central and Eastern North American Grassland and Shrubland","interactions":[],"lastModifiedDate":"2026-01-28T15:15:53.882062","indexId":"70273756","displayToPublicDate":"2025-12-01T09:10:37","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Effects of climate change on Midwestern ecosystems: Central and Eastern North American Grassland and Shrubland","docAbstract":"The Central and Eastern North American Grassland and Shrubland ecosystem may be increasingly shaped by intensifying drought and shifting seasonality. Rising temperatures and more variable precipitation, marked by longer dry spells, are projected to increase evapotranspiration and soil moisture deficits, and yield more frequent drought. At the same time, warming temperatures are projected to advance spring onset and extend the growing season. Drought may alter habitat structure by accelerating soil erosion, disrupting nutrient cycling, increasing physiological stress on plants, and reducing productivity. These changes are expected to shift community composition toward species adapted to water limitation and fluctuating resources, reducing much of the herbaceous cover that characterizes this ecosystem. Seasonal shifts may restructure habitat by altering phenology and f lowering dynamics, potentially increasing productivity but also heightening the risk of late-season frost damage. Community composition is expected to shift toward early-emerging species, particularly coolseason (C3) grasses, and species with phenological flexibility. Altered phenology may also lead to mismatches between plants and pollinators and increase pollinator competition at the beginning and end of the growing season, with potential consequences for reproduction.
Although these overarching stressors affect the entire ecosystem, their specific impacts likely vary with local habitat conditions. In the Central and Northern Tallgrass Prairie, which are historically firemaintained habitats dominated by a mix of warm-season (C4) and cool-season (C3) grasses and forbs, climate change may shift community composition by favoring deep-rooted forbs and established shrubs while displacing shallow-rooted species, including many native grasses. These changes, especially in the absence of fire, may promote woody encroachment and drive long-term community reassembly. In the Central Interior Acidic Open Glade and Barrens, characterized by shallow, drought-prone soils, climate change may reinforce xeric assemblages and reduce the abundance of mesic species. In the absence of f ire, shrubs rather than larger woody species, are more likely to increase, as water limitations constrain the establishment of trees. In the Eastern North American Ruderal Meadow and Shrubland, which lack native species richness and structural stability, disturbance-tolerant invaders may increasingly dominate. Drought and earlier springs are expected to reinforce early successional dynamics and further constrain the restoration potential of these already degraded habitats.
Across the region, invasive species, herbivory, and microbial and fungal communities are also expected to respond to climate change. Invasive plants with ruderal traits and flexible phenologies are likely to benefit from drought-driven disturbance, post-drought resource pulses, and longer, earlier growing seasons. These species often germinate and flower earlier than natives, gaining priority access to resources as seasonal timing shifts. Herbivory by increasing white-tailed deer (Odocoileus virginianus) populations is expected to intensify, particularly during drought, when plant defenses are weakened, and during extended growing seasons, which prolong forage availability. This selective browsing may contribute to declines in native forbs while indirectly promoting non-native grasses. Microbial and fungal communities, like plant communities, are likely vulnerable to both drought and shifting seasonality. Reduced soil moisture may suppress microbial activity and decomposition, while shifts in fungal community composition, particularly declines in arbuscular mycorrhizal fungi, may impair plant drought tolerance.
Adaptation strategies for the Central and Eastern North American Grassland and Shrubland may require managers to anticipate and respond to these changes through both resistance-based approaches, such as restoring fire regimes and reinforcing native species dominance, and acceptance of some potential transitions, such as facilitating drought-tolerant and phenologically flexible species establishment and adjusting fire regimes to align with altered phenology.
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Due to anthropogenic activities and climate change, many fens around the world are at risk. This paper presents the results of a study of the hydrology and geochemistry of fens in Big Smoky Valley, central Nevada to support the Bureau of Land Management’s activities in the area. A water sample from the largest fen in the study area was analyzed for its water chemistry and compared to a nearby alluvial aquifer and hot spring. The high SiO2 concentration of the fen sample implies that the fen water may originate from geothermal water. A soil core was taken to analyze radiocarbon age and soil type. A majority of the core was composed of silt and clay interlayered with water-filled voids. Changes in the character of the clay with depth suggest that there may have been changes in the depositional environment over time. Radiocarbon dating of Ruppia seeds showed longevity of the fen, with the minimum 14C age of the core as 4,375±40 years. This paper provides reconnaissance-level information on the Big Smoky Valley fens, but further information would be needed to better understand the source of water to the fens or how the fen environment has changed over time with climate.
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","language":"English","publisher":"NOAA","doi":"10.25923/f3tr-5759","usgsCitation":"O'Donnell, J.A., Carey, M.P., Koch, J.C., Baughman, C., Hill, K., Evinger, T., Pruitt, A., Thompson, C., Graham, E.B., and Poulin, B.A., 2025, Rusting rivers: Assessing the causes and consequences in Alaska and across the Arctic: NOAA Technical Report OAR ARC 25-14, 8 p., https://doi.org/10.25923/f3tr-5759.","productDescription":"8 p.","ipdsId":"IP-183425","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":501441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -140.44781012140473,\n 70\n ],\n [\n -167.44863507680367,\n 70\n ],\n [\n -167.44863507680367,\n 64\n ],\n [\n -140.44781012140473,\n 64\n ],\n [\n -140.44781012140473,\n 70\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Jonathan A.","contributorId":367250,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Jonathan","middleInitial":"A.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":957216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":957217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":957218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":957219,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hill, Kenneth","contributorId":244049,"corporation":false,"usgs":false,"family":"Hill","given":"Kenneth","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":957220,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evinger, Taylor","contributorId":332163,"corporation":false,"usgs":false,"family":"Evinger","given":"Taylor","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":957221,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pruitt, Abagael","contributorId":367253,"corporation":false,"usgs":false,"family":"Pruitt","given":"Abagael","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":957222,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Claire","contributorId":367254,"corporation":false,"usgs":false,"family":"Thompson","given":"Claire","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":957223,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Graham, Emily B.","contributorId":202683,"corporation":false,"usgs":false,"family":"Graham","given":"Emily","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":957224,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Poulin, Brett A","contributorId":367256,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett","middleInitial":"A","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":957225,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70272971,"text":"70272971 - 2025 - Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","interactions":[],"lastModifiedDate":"2025-12-11T14:50:29.76691","indexId":"70272971","displayToPublicDate":"2025-12-01T08:41:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":787,"text":"Annals of Applied Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data","docAbstract":"Classification of massive datasets by machine learning (ML) algorithms is promising for many scientific domains, especially wildlife monitoring programs that rely on passive acoustic surveys for detecting species. However, treating ML-predicted class labels (e.g., species identity) as truth biases inferences of focal parameters within common modeling frameworks. One solution is to model the misclassification process explicitly using human-validated true-class labels for a subset of observations. Validation by experts can present a substantial bottleneck in otherwise efficient workflows that use ML predictions. Bioacoustics practitioners seek guidance on both the quantity and process for selecting ML-labeled data to validate by an expert. We derive an alternative model formulation that jointly models human-validated and ML-predicted class labels with an observed-data likelihood (ODL) and use empirically informed simulations motivated by a real-data application to explore different probability designs for selecting class labels for validation. Simulation results suggest that with smaller validation sets the ODL formulation increases computational speed and reduces estimation error compared to a default MCMC data augmentation routine. Our methodology is transferable to applications that treat predictions from classification algorithms as the response variable of interest.
","language":"English","publisher":"Project Euclid","doi":"10.1214/25-AOAS2096","usgsCitation":"Oram, J., Banner, K.M., Stratton, C., Hoegh, A., and Irvine, K., 2025, Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data: Annals of Applied Statistics, v. 19, no. 4, p. 2957-2980, https://doi.org/10.1214/25-AOAS2096.","productDescription":"24 p.","startPage":"2957","endPage":"2980","ipdsId":"IP-149507","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":497379,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1214/25-aoas2096","text":"Publisher Index Page"},{"id":497320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oram, Jacob 0009-0001-8405-529X","orcid":"https://orcid.org/0009-0001-8405-529X","contributorId":353522,"corporation":false,"usgs":false,"family":"Oram","given":"Jacob","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banner, Katharine M.","contributorId":363761,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stratton, Christian","contributorId":265905,"corporation":false,"usgs":false,"family":"Stratton","given":"Christian","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoegh, Andrew","contributorId":265906,"corporation":false,"usgs":false,"family":"Hoegh","given":"Andrew","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":951957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":951945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273848,"text":"70273848 - 2025 - Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes","interactions":[],"lastModifiedDate":"2026-02-06T15:14:32.840311","indexId":"70273848","displayToPublicDate":"2025-12-01T08:07:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes","docAbstract":"Objective
Environmental DNA (eDNA) metabarcoding provides an attractive option for monitoring biodiversity in remote freshwater ecosystems, where the deployment of conventional gears encounters major logistical constraints. We evaluated eDNA metabarcoding for monitoring fish communities and early detection of nonnative species in three remote lakes on Isle Royale, Michigan, USA.
Methods
At each of the three lakes, we collected surface, midwater, and lake bottom samples from 10 sites during spring and fall sampling events. We performed metabarcoding on all the water samples, targeting the 12S region of all fish species.
Results
Despite a relatively small sample size (N = 60 samples per lake across two visits; 10 locations with three depths per location), we recovered 70% of all the species that were previously observed using conventional methods. We recovered several detections of putative Cisco Coregonus artedi, a vulnerable coldwater species, providing evidence that Cisco have persisted in these lakes. However, we found disentangling likely false positives from rare species challenging, which we overcame by employing multiple types of detection thresholds and a species-specific quantitative PCR assay.
Conclusions
Although we were able to successfully characterize the fish communities using eDNA metabarcoding, more attention needs to be given to the detection thresholds and communication protocols that provide guidance in interpretating new eDNA detections and using eDNA detections to inform management decisions. Although eDNA metabarcoding has limitations that should be accounted for at the outset of the project, the ease of sample collection makes eDNA metabarcoding an option for monitoring freshwater biodiversity in remote systems.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/najfmt/vqaf106","usgsCitation":"Iacaruso, N.J., Myers, J.T., Seider, M.J., and Davis, M.A., 2025, Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes: North American Journal of Fisheries Management, v. 46, no. 1, p. 84-100, https://doi.org/10.1093/najfmt/vqaf106.","productDescription":"17 p.","startPage":"84","endPage":"100","ipdsId":"IP-176505","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":499648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Isle Royale, Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.31231479627827,\n 48.18989928985803\n ],\n [\n -89.31231479627827,\n 47.823253980655494\n ],\n [\n -88.40909564980919,\n 47.823253980655494\n ],\n [\n -88.40909564980919,\n 48.18989928985803\n ],\n [\n -89.31231479627827,\n 48.18989928985803\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Iacaruso, Nicholas J. 0009-0004-0829-2252","orcid":"https://orcid.org/0009-0004-0829-2252","contributorId":366087,"corporation":false,"usgs":false,"family":"Iacaruso","given":"Nicholas","middleInitial":"J.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Myers, Jared Thomas 0009-0004-9362-8792","orcid":"https://orcid.org/0009-0004-9362-8792","contributorId":363104,"corporation":false,"usgs":true,"family":"Myers","given":"Jared","middleInitial":"Thomas","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":955228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seider, Michael J. 0000-0002-6500-4710","orcid":"https://orcid.org/0000-0002-6500-4710","contributorId":366088,"corporation":false,"usgs":false,"family":"Seider","given":"Michael","middleInitial":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":955229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Mark A. 0000-0001-9034-9430","orcid":"https://orcid.org/0000-0001-9034-9430","contributorId":366089,"corporation":false,"usgs":false,"family":"Davis","given":"Mark","middleInitial":"A.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":955230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272620,"text":"dr1217 - 2025 - Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","interactions":[],"lastModifiedDate":"2026-02-03T16:40:49.220576","indexId":"dr1217","displayToPublicDate":"2025-12-01T07:18:23","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1217","displayTitle":"Range-wide Population Trend Analysis for Greater Sage-Grouse (Centrocercus urophasianus)—Updated 1960–2024","title":"Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024","docAbstract":"Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are at the center of State and national land-use policies largely because of their unique life-history traits as an ecological indicator for the health of sagebrush ecosystems. This updated population trend analysis provides State and Federal land and wildlife managers with the best available science to help guide management and conservation plans aimed at benefiting sage-grouse populations and the ecosystems they inhabit. This analysis relied on previously published population trend modeling methodology from Coates and others (2021, 2022a) and incorporates population lek count data for 1960–2024. Included in this report are methodological updates to lek count data aggregation, state-space model forecasting, and targeted annual warning system signals, which are detailed under individual Modification sections. State-space models estimated a 2.9-percent average annual decline in sage-grouse populations between 1966 and 2021 (Period 1, six population oscillations) across their geographical range. The average annual decline among climate clusters for the same number of oscillations ranged between 2.2 and 3.4 percent. Cumulative declines were 41.2, 64.1, and 78.8 percent range-wide in Period 5 (19 years), Period 3 (35 years), and Period 1 (55 years), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1217","collaboration":"Prepared in cooperation with the Bureau of Land Management","programNote":"Ecosystems Mission Areas—Species Management Research Program and Land Management Research Program","usgsCitation":"Prochazka, B.G., Coates, P.S., Aldridge, C.L., O'Donnell, M.S., Edmunds, D.R., Monroe, A.P., Hanser, S.E., Wiechman, L.A., and Chenaille, M.P., 2025, Range-wide population trend analysis for greater sage-grouse (Centrocercus urophasianus)—Updated 1960–2024: U.S. Geological Survey Data Report 1217, 22 p., https://doi.org/10.3133/dr1217.","productDescription":"Report: viii, 22 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-182475","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496879,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.XML"},{"id":496877,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OQWGIV","text":"USGS data release","description":"USGS data release","linkHelpText":"Trends and a targeted annual warning system for greater sage-grouse in the western United States (ver. 4.0, November 2025)"},{"id":496878,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1217/images"},{"id":496874,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1217/coverthb.jpg"},{"id":496875,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1217/dr1217.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1217"},{"id":496876,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1217/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1217"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.02726904687307,\n 37.11378745198651\n ],\n [\n -107.91246282672654,\n 39.23148053932573\n ],\n [\n -104.18656479624082,\n 42.68923879351195\n ],\n [\n -104.09712675152082,\n 44.90768367632023\n ],\n [\n -103.10713250018665,\n 45.28903162099806\n ],\n [\n -103.07124138706033,\n 46.81624492709619\n ],\n [\n -105.38823344586734,\n 48.94676636341262\n ],\n [\n -120.30657593063506,\n 48.87342393238805\n ],\n [\n -120.60087183124688,\n 42.81488245718879\n ],\n [\n -120.58608571052426,\n 38.32426094909158\n ],\n [\n -117.42786260245566,\n 36.55795546064512\n ],\n [\n -113.02726904687307,\n 37.11378745198651\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
Knowledge of vital rates informs the conservation and management of threatened and endangered species. In the northern Great Plains, USA, the federally threatened Piping Plover Charadrius melodus uses a variety of nesting habitats including natural river sandbars and human-created sites in the lower Platte River system, Nebraska. In this area, off-river sandpit sites (i.e., active sand and gravel mines, transition sites, and lakeshore housing developments) are not managed to prioritize nesting and are often considered inferior habitat to sandbars. However, most Piping Plovers in the lower Platte River system nest off river, especially in years when sandbar habitat is limited. As the quantity of habitat provided at off-river sites is predicted to decline, evaluating vital rates among different off-river nesting habitats will inform future conservation efforts. We estimated annual survival and fidelity of adult (n = 165) and hatch-year (n = 671) Piping Plovers from 2008 to 2018 and within-season weekly survival of breeding adults (n = 271) from 2011 to 2024. Annual adult survival was 0.771 (95% CI = 0.733–0.804) and hatch-year survival was 0.394 (0.335–0.456). Fidelity to the study area was 0.737 (0.634–0.819) for adults and 0.261 (0.192–0.345) for hatch-years. Within-season apparent weekly survival was higher for Piping Plovers at lakeshore housing developments (0.946 [85% CI = 0.917–0.965]) than sand and gravel mines (0.909 [0.874–0.935]) and transition sites (0.881 [0.834–0.928]). Annual survival of adult and hatch-year birds were comparable to other studies and regions within the Northern Great Plains population, indicating no negative consequence of off-river nesting to survival. Considering that off-river habitats are important for the persistence of Piping Plovers in the lower Platte River system, continued monitoring of survival could help managers evaluate recovery implications under uncertain future habitat availability in the region.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00393","usgsCitation":"Forsberg, E., Powell, L., Swift, R.J., Jorgensen, J., and Vrtiska, M.P., 2025, Adult and hatch-year survival and fidelity of Piping Plovers Charadrius melodus in the lower Platte River system, Nebraska, USA: Wader Study, v. 132, no. 3, p. 210-222, https://doi.org/10.18194/ws.00393.","productDescription":"13 p.","startPage":"210","endPage":"222","ipdsId":"IP-175896","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"lower Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.53013643892548,\n 41.848160677437875\n ],\n [\n -97.53013643892548,\n 40.86001959632918\n ],\n [\n -95.95197180336409,\n 40.86001959632918\n ],\n [\n -95.95197180336409,\n 41.848160677437875\n ],\n [\n -97.53013643892548,\n 41.848160677437875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"132","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Forsberg, Elsa M.","contributorId":357514,"corporation":false,"usgs":false,"family":"Forsberg","given":"Elsa M.","affiliations":[{"id":16602,"text":"University of Nebraska, Lincoln","active":true,"usgs":false}],"preferred":false,"id":957558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Larkin A.","contributorId":352292,"corporation":false,"usgs":false,"family":"Powell","given":"Larkin A.","affiliations":[{"id":84162,"text":"School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska USA","active":true,"usgs":false}],"preferred":false,"id":957559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swift, Rose J. 0000-0001-7044-6196","orcid":"https://orcid.org/0000-0001-7044-6196","contributorId":212082,"corporation":false,"usgs":true,"family":"Swift","given":"Rose","email":"","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":957560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgensen, Joel G.","contributorId":169604,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Joel G.","affiliations":[{"id":25564,"text":"Nongame Bird Program, Nebraska Game and Parks Commission, Lincoln, NE 68503","active":true,"usgs":false}],"preferred":false,"id":957561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vrtiska, Mark P.","contributorId":201604,"corporation":false,"usgs":false,"family":"Vrtiska","given":"Mark","middleInitial":"P.","affiliations":[{"id":36216,"text":"NE Game & Parks","active":true,"usgs":false}],"preferred":false,"id":957562,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273001,"text":"70273001 - 2025 - A framework for analyzing wild turkey summer sighting data.","interactions":[],"lastModifiedDate":"2025-12-12T17:19:15.483358","indexId":"70273001","displayToPublicDate":"2025-11-30T10:04:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A framework for analyzing wild turkey summer sighting data.","docAbstract":"Wildlife agencies collect data on productivity (e.g., proportion of hens with poults and number of poults per hen) of wild turkey (Meleagris gallopavo) to monitor population status and trends. However, sampling protocols to collect productivity data rely on opportunistic observations reported by wildlife agency personnel and the public and have changed over time and differed among agencies. A protocol to standardize data collection was adopted by most state wildlife agencies in 2019, but long-term historical datasets exist that cannot be analyzed readily to make inferences about spatial and temporal patterns in wild turkey productivity. We developed statistical models to allow comparisons and model trends in productivity among and within states even though data collection protocols changed over time and differed among states. We found greater spatial variation in the proportion of hens with poults than the number of poults per brood, which may reflect how environmental factors influence wild turkey productivity. Our models can also provide inferences about productivity when data are limited or temporally discontinuous for some spatial units. Additionally, we found that temporal and spatial variation in data collection, even under the new protocol, can affect inferences about trends in productivity. The statistical models we developed address the uncontrolled nature of when and where data are collected and offer the ability to investigate long-term patterns of productivity in relation to factors such as changing climate or habitat conditions.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1623","usgsCitation":"Diefenbach, D.R., Buderman, F.E., Casalena, M.J., Dye, M., Gates, R., Gigliotti, L., Long, C., Martin, K., Muthersbaugh, M., Peters, M.L., Sloan, J., Stiller, J., and Wiley, M., 2025, A framework for analyzing wild turkey summer sighting data.: Wildlife Society Bulletin, v. 49, no. 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Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":951416,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":951417,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":951418,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sutfin, Nicholas A. 0000-0003-4429-7814","orcid":"https://orcid.org/0000-0003-4429-7814","contributorId":357883,"corporation":false,"usgs":true,"family":"Sutfin","given":"Nicholas","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951419,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70273803,"text":"70273803 - 2025 - Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","interactions":[],"lastModifiedDate":"2026-02-02T21:34:17.940337","indexId":"70273803","displayToPublicDate":"2025-11-27T15:29:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires","docAbstract":"Savannas depend on frequent, low-intensity fires that shape animal and plant communities. These fires alter animal populations, movement, and habitat use. Here, we report on how fires in a longleaf pine (Pinus palustris) savanna affected small mammal microhabitat use via changes in competition and predation. We monitored small mammal populations and vegetation subjected to biennial prescribed fires and compared microhabitat use of three small mammal populations [hispid cotton rats (Sigmodon hispidus), cotton mice (Peromyscus gossypinus) and oldfield mice (Peromyscus polionotus)] in the presence and absence of mesocarnivores while accounting for changes in density and movement of each small mammal species. Densities of cotton rats varied greatly across years but were similar between predator exclosures and controls. However, frequency of use was greater in exclosures than in controls irrespective of vegetation characteristics, suggesting predation risk altered cotton rat microhabitat use. Conversely, higher relative abundance of cotton rats was associated with lower cotton mouse and oldfield mouse use, suggesting spatial separation in niche and indicating that cotton mice expand their realized niche following predation-induced declines of cotton rats associated with prescribed burn events. Our results contribute to a better understanding of pyrodiversity and how interspecific interactions can moderate effects of vegetation changes following prescribed fires.","language":"English","publisher":"Springer","doi":"10.1038/s41598-025-26529-5","usgsCitation":"Shastry, V., Conner, L.M., Morris, G., Royle, A., Smith, L., and Morin, D., 2025, Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires: Scientific Reports, v. 15, no. 1, 42385, 12 p., https://doi.org/10.1038/s41598-025-26529-5.","productDescription":"42385, 12 p.","ipdsId":"IP-181552","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499616,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-26529-5","text":"Publisher Index Page"},{"id":499417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Baker County","otherGeospatial":"Jones Center at Ichauway","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shastry, Varsha","contributorId":365822,"corporation":false,"usgs":false,"family":"Shastry","given":"Varsha","affiliations":[{"id":87229,"text":"Mississippi State University; The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conner, L. Mike","contributorId":365823,"corporation":false,"usgs":false,"family":"Conner","given":"L.","middleInitial":"Mike","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Gail","contributorId":365824,"corporation":false,"usgs":false,"family":"Morris","given":"Gail","affiliations":[{"id":56171,"text":"The Jones Center at Ichauway","active":true,"usgs":false}],"preferred":false,"id":954878,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":954879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lora","contributorId":156438,"corporation":false,"usgs":false,"family":"Smith","given":"Lora","affiliations":[],"preferred":false,"id":954880,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morin, Dana","contributorId":264602,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":954881,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273268,"text":"70273268 - 2025 - Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","interactions":[],"lastModifiedDate":"2025-12-29T15:38:48.704275","indexId":"70273268","displayToPublicDate":"2025-11-27T09:31:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","title":"Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert","docAbstract":"Utility-scale solar energy (USSE) development is driving the projected growth in global renewable energy capacity but comes with environmental tradeoffs. New, alternative construction methods are promoted to minimize impacts to soils, vegetation, and hydrology; however, the disturbance created by these methods requires further investigation. We evaluated the population of a rare annual species, threecorner milkvetch (Astragalus geyeri var. triquetrus), at the Gemini Solar Project in the Mojave Desert, USA, two years after construction. Gemini was required to minimize disturbance in the threecorner milkvetch habitat, providing a unique opportunity to study the plant population and life history characteristics of a rare plant species under novel construction methods. Our objectives were to compare plant population characteristics of threecorner milkvetch inside and outside the Gemini footprint and in different photovoltaic (PV) panel microsites (interspace, panel dripline, under panel). We hypothesized that 1) threecorner milkvetch would have lower survival, reproduction, and growth, and a later phenology, inside compared to outside the facility, and 2) that these negative effects on plant demography and phenology would intensify with increasing proximity to photovoltaic panels in the solar array due to an increasing effect of disturbance and reduction of light and water availability. The results of this 1-year study during a favorable year of rainfall demonstrate the persistence of a rare Mojave annual plant species within an altered environment at a USSE facility. We found that threecorner milkvetch had an earlier phenology, grew larger, and had a higher fecundity at Gemini compared to plants off-site. Survivorship between the two populations, however, was not significantly different. Although growth and reproductive metrics were not correlated with distance to panel, minimal threecorner milkvetch emergence occurred directly under the PV panels and along their driplines, indicating a potential loss of suitable habitat if this pattern becomes more widespread in space or through time. Novel construction techniques for USSE could be considered moving forward to minimize impact on aboveground vegetation and maintain viable seed banks. The results of this study can assist land managers in making decisions about USSE development as the demand grows.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2025.1697878","usgsCitation":"Pereira, T.J., Karban, C.C., Kobelt, L., and Munson, S.M., 2025, Rare milkvetch (Astragalus) persistence at a utility-scale solar energy facility in the Mojave Desert: Frontiers in Ecology and Evolution, v. 13, 1697878, 12 p., https://doi.org/10.3389/fevo.2025.1697878.","productDescription":"1697878, 12 p.","ipdsId":"IP-182848","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2025.1697878","text":"Publisher Index Page"},{"id":498143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.87877698144997,\n 36.55309391567229\n ],\n [\n -114.87877698144997,\n 36.398061936746544\n ],\n [\n -114.70717521419876,\n 36.398061936746544\n ],\n [\n -114.70717521419876,\n 36.55309391567229\n ],\n [\n -114.87877698144997,\n 36.55309391567229\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Pereira, Tiffany J.","contributorId":364633,"corporation":false,"usgs":false,"family":"Pereira","given":"Tiffany","middleInitial":"J.","affiliations":[{"id":86877,"text":"Desert Research Institute [DRI] Conservation Ecology Lab, Division of Earth and Ecosystem Sciences, DRI, Las Vegas, NV, US","active":true,"usgs":false}],"preferred":false,"id":952964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karban, Claire C 0000-0002-6157-031X","orcid":"https://orcid.org/0000-0002-6157-031X","contributorId":344987,"corporation":false,"usgs":true,"family":"Karban","given":"Claire","email":"","middleInitial":"C","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kobelt, Lara A.","contributorId":350355,"corporation":false,"usgs":false,"family":"Kobelt","given":"Lara A.","affiliations":[{"id":83722,"text":"Bureau of Land Management, Southern Nevada District Office, 4701 North Torrey Pines Dr., Las Vegas, NV 89130","active":true,"usgs":false}],"preferred":false,"id":952966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272631,"text":"70272631 - 2025 - The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears","interactions":[],"lastModifiedDate":"2025-12-01T15:26:20.339626","indexId":"70272631","displayToPublicDate":"2025-11-27T09:18:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears","docAbstract":"Omnivores often face tradeoffs between selecting for spatially dispersed energy-dense vertebrate prey versus densely distributed herbivorous resources that have limited energetic value per unit intake. Arctic grizzly bears (Ursus arctos) are large omnivores within a resource-limited ecosystem that are known to exhibit smaller body masses and occur at lower densities than grizzly bears in other regions of North America. We evaluated the energy balance of Arctic grizzly bears during a portion of the fall hyperphagic period in two ecologically differing regions on Alaska’s northern Arctic coast by monitoring mass change, food intake, activity, and energy expenditure of 12 individuals over 17–22 days. Bears in coastal areas were more carnivorous than bears in the foothills that were predominantly herbivorous and frugivorous. Carnivory was associated with greater movement, body fat, and energy expenditure and two of four carnivorous bears lost mass. Overall, the mean body fat of the bears in this study was 34% lower than other grizzly bear populations in North America in the fall. Furthermore, the bears in this study exhibited relatively small changes in body mass (x̄= 3%, range =−2 to 11%) that were 60% lower than other grizzly bear populations which typically gain substantial mass in the fall in preparation for denning. Our results, while representing a snapshot from a small number of bears during the fall hyperphagic period, are consistent with previous studies and indicate limited availability of energy-dense food resources during this time for grizzly bears in this region of the Arctic.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00442-025-05830-0","usgsCitation":"Pagano, A.M., Rode, K.D., Nicholson, K.L., Leacock, W.B., Stricker, C.A., and Robbins, C.T., 2025, The effects of carnivory and herbivory on the energy balance of Arctic grizzly bears: Oecologia, v. 208, 2, 15 p., https://doi.org/10.1007/s00442-025-05830-0.","productDescription":"2, 15 p.","ipdsId":"IP-179627","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":496947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"North Slope","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -152,\n 70.5\n ],\n [\n -152,\n 69.5\n ],\n [\n -144,\n 69.5\n ],\n [\n -144,\n 70.5\n ],\n [\n -152,\n 70.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"208","noUsgsAuthors":false,"publicationDate":"2025-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":951049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":951050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nicholson, Kerry L.","contributorId":363061,"corporation":false,"usgs":false,"family":"Nicholson","given":"Kerry","middleInitial":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":951051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leacock, William B.","contributorId":363062,"corporation":false,"usgs":false,"family":"Leacock","given":"William","middleInitial":"B.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":951052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":951053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robbins, Charles T.","contributorId":363063,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","middleInitial":"T.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":951054,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70274577,"text":"70274577 - 2025 - From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia","interactions":[],"lastModifiedDate":"2026-04-06T15:48:16.485239","indexId":"70274577","displayToPublicDate":"2025-11-26T14:51:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia","docAbstract":"Poorly designed linear infrastructure can reduce habitat connectivity and be major barriers for migratory wildlife. An important start at effective mitigation is understanding how individuals respond when barriers are encountered. This can be done via comparison of fine- and broad-scale behavioural responses to various anthropogenic barrier types. We classified fine-scale responses of 62 Mongolian gazelles (Procapra gutturosa) across different barrier types, seasons and times of day. We also investigated interactions at a broader scale by measuring the length of linear infrastructure traced, interaction duration and crossing success rate. We learned that gazelle behaviour varied according to barrier permeability, and that fences were major obstacles. Gazelles exhibited similar bouncing behaviour when confronted with paved roads as with fences, suggesting paved roads can act as semi-permeable barriers during high traffic volume. Broad-scale movement patterns revealed gazelles travelled considerable distances along fences—averaging 40.2 km, and up to 211.6 km—before moving away or crossing. Long-distance tracing movements can help identify areas with the strongest barrier effect and guide mitigation measures for current and future linear infrastructure. Designing infrastructure and implementing conservation strategies for ungulates in steppe ecosystems will benefit from taking into account behavioural responses at both fine and broad scales.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2025.2093","usgsCitation":"Sévêque, A., Mendgen, P., Freeman, I., Bayarbaatar, B., Kauffman, M.J., Olsen, K., Usukhjargal, D., Uuganbayar, G., Xu, W., Mueller, T., and Dejid, N., 2025, From fences to roads: Changes in barrier behaviour of Mongolian gazelle across different types of linear infrastructure in Mongolia: Proceedings of the Royal Society B: Biological Sciences, v. 292, no. 2059, 20252093, https://doi.org/10.1098/rspb.2025.2093.","productDescription":"20252093","ipdsId":"IP-180143","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501972,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mongolia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 86.14815830860528,\n 52.011926051186464\n ],\n [\n 86.14815830860528,\n 41.82159331743961\n ],\n [\n 119.95403757641532,\n 41.82159331743961\n ],\n [\n 119.95403757641532,\n 52.011926051186464\n ],\n [\n 86.14815830860528,\n 52.011926051186464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"292","issue":"2059","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Sévêque, Anthony","contributorId":369043,"corporation":false,"usgs":false,"family":"Sévêque","given":"Anthony","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":958345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendgen, Philipp","contributorId":339036,"corporation":false,"usgs":false,"family":"Mendgen","given":"Philipp","email":"","affiliations":[{"id":81238,"text":"Goethe University","active":true,"usgs":false}],"preferred":false,"id":958346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Ian","contributorId":335506,"corporation":false,"usgs":false,"family":"Freeman","given":"Ian","email":"","affiliations":[],"preferred":false,"id":958347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bayarbaatar, Buuveibaatar","contributorId":287848,"corporation":false,"usgs":false,"family":"Bayarbaatar","given":"Buuveibaatar","affiliations":[{"id":61638,"text":"Wildlife Conservation Society, Mongolia Program, Ulaanbaatar, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":958349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olsen, Kirk","contributorId":369044,"corporation":false,"usgs":false,"family":"Olsen","given":"Kirk","affiliations":[{"id":87706,"text":"Wildlife Conservation Society, Mongolia Program","active":true,"usgs":false}],"preferred":false,"id":958350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Usukhjargal, Dorj","contributorId":287888,"corporation":false,"usgs":false,"family":"Usukhjargal","given":"Dorj","email":"","affiliations":[{"id":61645,"text":"Hustai National Park Trust, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Uuganbayar, Ganbold","contributorId":287889,"corporation":false,"usgs":false,"family":"Uuganbayar","given":"Ganbold","email":"","affiliations":[{"id":61645,"text":"Hustai National Park Trust, Mongolia","active":true,"usgs":false}],"preferred":false,"id":958352,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Xu, Wenjing","contributorId":285005,"corporation":false,"usgs":false,"family":"Xu","given":"Wenjing","email":"","affiliations":[],"preferred":false,"id":958353,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mueller, Thomas","contributorId":337677,"corporation":false,"usgs":false,"family":"Mueller","given":"Thomas","affiliations":[{"id":81034,"text":"Goethe-University Frankfurt and Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":958354,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dejid, Nandintsetseg","contributorId":287854,"corporation":false,"usgs":false,"family":"Dejid","given":"Nandintsetseg","affiliations":[{"id":61644,"text":"Senckenberg Biodiversity and Climate Research Centre, Frankfurt (Main), Germany","active":true,"usgs":false}],"preferred":false,"id":958355,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70272619,"text":"ofr20251054 - 2025 - Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques","interactions":[],"lastModifiedDate":"2026-02-03T16:40:03.569804","indexId":"ofr20251054","displayToPublicDate":"2025-11-26T12:05:00","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":"2025-1054","displayTitle":"Comparisons of Shoreline Positions from Satellite-Derived and Traditional Field- and Remote-Sensing Techniques","title":"Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques","docAbstract":"Satellite-derived shorelines (SDS) have the potential to help researchers answer critical coastal science questions and support work to predict coastal change by filling in the spatial and temporal gaps present in current field-based and remote-sensing data collection methods. The U.S. Geological Survey conducted comparison analyses of traditionally sourced shorelines and SDS in diverse coastal landscapes to determine how SDS could be used in ongoing and future work across varied coastal environments and provided some initial findings that could be used for implementation. Using CoastSeg, a browser-based program for SDS detection and mapping, SDS for the period 1984–2023 for multiple locations across the United States were compared to shoreline positions from traditionally sourced shoreline data. In this report, the authors present these comparisons alongside lessons learned and challenges encountered when building SDS workflows in different coastal locations. Results show that individual SDS have larger uncertainty and yet produced similar linear trends to sparser, traditionally sourced shoreline data; because SDS methods provide orders of magnitude more data than traditional shoreline-detection methods, they can be used to evaluate shoreline behaviors. Refining average scalar slopes used in tidal corrections did not result in substantial decreases in uncertainty. Using lessons from this work to outline needs for regional implementation, initial setup time would be considerable, being on the order of weeks. However, once complete, shoreline detections and analyses are fast (on the order of minutes to hours) and achievable using a desktop computer.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251054","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"O’Neill, A.C., Batiste, S.F., Buscombe, D.D., Burgess, J., Doran, K.S., Gibbs, A.E., Henderson, R.E., Heslin, J.L., Janda, C.N., Lundine, M.A., Terrano, J.F., Warrick, J.A., and Weber, K.M., 2025, Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques: U.S. Geological Survey Open-File Report 2025–1054, 41 p., https://doi.org/10.3133/ofr20251054.","productDescription":"viii, 41 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-177965","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":496871,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251054/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1054 HTML"},{"id":496869,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1054/coverthb.jpg"},{"id":496873,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1054/images/"},{"id":496872,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1054/ofr20251054.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1054 XML"},{"id":496870,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1054/ofr20251054.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1054 PDF"}],"country":"United States","state":"Alaska, Florida, Massachusetts, Washington","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.23262232723678,\n 42.09708901142952\n ],\n [\n -70.23262232723678,\n 41.7296953201367\n ],\n [\n -69.88869105489118,\n 41.7296953201367\n ],\n [\n -69.88869105489118,\n 42.09708901142952\n ],\n [\n -70.23262232723678,\n 42.09708901142952\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.8586476385848,\n 27.855837758503966\n ],\n [\n -82.8586476385848,\n 27.73142586709062\n ],\n [\n -82.70953873940795,\n 27.73142586709062\n ],\n [\n -82.70953873940795,\n 27.855837758503966\n ],\n [\n -82.8586476385848,\n 27.855837758503966\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.6354762817767,\n 48.15958852423637\n ],\n [\n -123.6354762817767,\n 48.07700409405399\n ],\n [\n -123.49731286568142,\n 48.07700409405399\n ],\n [\n -123.49731286568142,\n 48.15958852423637\n ],\n [\n -123.6354762817767,\n 48.15958852423637\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -143.75227424150037,\n 70.14885784620938\n ],\n [\n -143.75227424150037,\n 70.08259373043822\n ],\n [\n -143.56394337243916,\n 70.08259373043822\n ],\n [\n -143.56394337243916,\n 70.14885784620938\n ],\n [\n -143.75227424150037,\n 70.14885784620938\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.26663872487647,\n 18.348796644288143\n ],\n [\n -67.26663872487647,\n 18.327492880601937\n ],\n [\n -67.24442657044659,\n 18.327492880601937\n ],\n [\n -67.24442657044659,\n 18.348796644288143\n ],\n [\n -67.26663872487647,\n 18.348796644288143\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission Street
Santa Cruz, California 95060
Sudden habitat loss associated with environmental disturbance can trigger animals to move from affected to undisturbed areas, where increases in local density may occur. Although pathogen transmission is strongly related to local density, how crowding after habitat loss affects infection dynamics in wild populations remains unclear. Here we conceptualize the Disturbance-Density-Disease hypothesis, which posits that disturbance-induced habitat loss results in increased pathogen prevalence via increases in local density at adjacent, undisturbed patches. We then used data from before, during, and after flooding disturbance to test this hypothesis in boreal toads Anaxyrus boreas boreas co-occurring with the pathogenic fungus Batrachochytrium dendrobatidis (Bd). We collected Bd samples from captured individuals during a 5-year (2015–2019) mark-recapture study of boreal toads (n = 1295) that breed in beaver ponds in western Wyoming, USA. During spring of 2017, an extreme flooding event destroyed several beaver dams, resulting in the loss of breeding habitat. We compared host density and pathogen prevalence pre- and post-disturbance at sites affected versus unaffected by flooding. At affected sites, population density and Bd prevalence increased at adjacent, undisturbed ponds following the sudden loss of habitat. Moreover, neither host density nor Bd prevalence increased at control sites in areas unaffected by flooding. Taken together, our results support hypothesized links between disturbance, adjacent increases in density, and subsequent increases in pathogen prevalence. Our study contributes to a growing body of ecological research leveraging natural experiments to extract insights from extreme disturbance events. By doing so, we demonstrate an important consequence of disturbance beyond proximate habitat loss and introduce a clear conceptual approach (the Disturbance-Density-Disease hypothesis) to understanding how pathogen transmission can be affected by disturbance via alterations to local density.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70265","usgsCitation":"Barrile, G.M., Chalfoun, A.D., Walters, A.W., Merkle, J.A., 2025, Density as a mechanism linking habitat disturbance to increased pathogen prevalence: Evidence from a natural experiment: Ecology, v. 106, no. 11, e70265, 15 p., https://doi.org/10.1002/ecy.70265.","productDescription":"e70265, 15 p.","ipdsId":"IP-171436","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest, northern Wyoming Range, Wind River Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.9701288311253,\n 44.01466129417253\n ],\n [\n -110.9701288311253,\n 41.8640098196185\n ],\n [\n -108.35885871498692,\n 41.8640098196185\n ],\n [\n -108.35885871498692,\n 44.01466129417253\n ],\n [\n -110.9701288311253,\n 44.01466129417253\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"106","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Barrile, Gabriel M.","contributorId":366853,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":956316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merkle, Jerod A.","contributorId":366854,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":956319,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272658,"text":"70272658 - 2025 - The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics","interactions":[],"lastModifiedDate":"2025-12-03T17:19:25.259086","indexId":"70272658","displayToPublicDate":"2025-11-26T11:01:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics","docAbstract":"This paper introduces the use of acoustic Doppler current profiler (ADCP) measurements as input for the Acoustic Mapping Velocimetry (AMV) method, a technique for characterizing the dynamics of riverine bedforms. The performance of this new approach, ADCP-AMV, is compared with input from a multibeam echosounder through a field study conducted on the Mississippi River (USA). A virtual ADCP tool has been created to support the ADCP-AMV measurements with optimal data density predictions. To the authors’ knowledge, this is the first time ADCP measurements have been used in conjunction with the AMV dune-tracking method. Subsequently, the paper discusses the coupling of ADCP-AMV measurements with ancillary data extracted from the ADCP. These ancillary data are processed using previously developed protocols to characterize hydrodynamics and the suspended sediment distribution in the water column. This paper emphasizes the capability of ADCPs to characterize open-channel river hydromorphodynamic parameters with high spatiotemporal resolution. Recommendations to accurately and efficiently acquire these multi-variable measurements and derived datasets are discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2025.105180","usgsCitation":"Fleit, G., Muste, M., Baranya, S., Kim, D., Whaling, A., McAlpin, T., and You, H., 2025, The acoustic-Doppler current profiler (ADCP): A comprehensive tool for river-reach hydromorphodynamics: Advances in Water Resources, v. 206, 105180, 15 p., https://doi.org/10.1016/j.advwatres.2025.105180.","productDescription":"105180, 15 p.","ipdsId":"IP-177812","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":497092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2025.105180","text":"Publisher Index Page"},{"id":497018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","city":"Memphis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.08,\n 35.13\n ],\n [\n -90.08,\n 35.12\n ],\n [\n -90.07,\n 35.12\n ],\n [\n -90.07,\n 35.13\n ],\n [\n -90.08,\n 35.13\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"206","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fleit, Gábor","contributorId":363187,"corporation":false,"usgs":false,"family":"Fleit","given":"Gábor","affiliations":[{"id":86640,"text":"Research fellow at Budapest University of Technology and Economics","active":true,"usgs":false}],"preferred":false,"id":951233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muste, Marian 0000-0002-5975-462X","orcid":"https://orcid.org/0000-0002-5975-462X","contributorId":192136,"corporation":false,"usgs":false,"family":"Muste","given":"Marian","email":"","affiliations":[],"preferred":false,"id":951234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baranya, Sándor","contributorId":363188,"corporation":false,"usgs":false,"family":"Baranya","given":"Sándor","affiliations":[{"id":86642,"text":"Professor (Associate) at Budapest University of Technology and Economics","active":true,"usgs":false}],"preferred":false,"id":951235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kim, Dongsu","contributorId":363189,"corporation":false,"usgs":false,"family":"Kim","given":"Dongsu","affiliations":[{"id":86643,"text":"Professor at Dankook University","active":true,"usgs":false}],"preferred":false,"id":951236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whaling, Amanda 0000-0003-1375-8323","orcid":"https://orcid.org/0000-0003-1375-8323","contributorId":213953,"corporation":false,"usgs":true,"family":"Whaling","given":"Amanda","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":951237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McAlpin, Tate","contributorId":363190,"corporation":false,"usgs":false,"family":"McAlpin","given":"Tate","affiliations":[{"id":86644,"text":"Coastal and Hydraulics Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, USA.","active":true,"usgs":false}],"preferred":false,"id":951238,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"You, Hojun","contributorId":363191,"corporation":false,"usgs":false,"family":"You","given":"Hojun","affiliations":[{"id":86646,"text":"Senior Researcher at K-water Research Institute","active":true,"usgs":false}],"preferred":false,"id":951239,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272640,"text":"70272640 - 2025 - Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","interactions":[],"lastModifiedDate":"2025-12-02T16:25:40.80763","indexId":"70272640","displayToPublicDate":"2025-11-26T10:21:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Potential thiamine deficiency of phytoplankton across a productivity gradient and seasons in Ohio lakes","docAbstract":"The depth level at which porphyry Cu–forming magmas fractionated and exsolved mineralizing fluids is actively debated. In the classic model, extensive magma fractionation occurs in large, upper crustal magma chambers, and concomitant fluid exsolution leads to forceful expulsion of residual magmas in the form of porphyry dikes, stocks, and breccia pipes, which subsequently serve as pathways for the mineralizing fluids. In contrast, some recent studies highlighting the role of deep crustal magma fractionation in the production of fertile magmas essentially deny the existence of upper crustal magma chambers at the time of mineralization. To address this, we conducted a detailed thermobarometric investigation of 13 intermediate to felsic, porphyritic intrusive rocks related to porphyry-skarn Cu mineralization at Santa Rita and Hanover-Fierro, New Mexico, United States, representing two premineralization magmas (61–60 Ma), seven synmineralization magmas (60–58 Ma), and four late- to postmineralization magmas (58–57 Ma).
For each sample, the pressure of last magma crystallization before final magma ascent to the current exposure level was reconstructed based on Al-in-hornblende barometry of small hornblende inclusions trapped within quartz phenocrysts and through titanium-in-quartz (TitaniQ) thermobarometry of the host quartz phenocrysts themselves. Since quartz is one of the last crystallizing magmatic minerals, and no significant phenocryst growth could have occurred in small dikes and stocks after final magma emplacement, quartz phenocrysts and their contained hornblende inclusions record the depth of last magma crystallization before final magma ascent. When present, hornblende phenocrysts and hornblende inclusions within other major phenocrysts were also analyzed. Both quartz and hornblende barometers return consistent average pressures of 3.2 ± 0.4 kbar for the entire suite of pre- to postmineralization magmas, corresponding to depths of 11 to 14 km. The synmineralization magmas return even more consistent average pressures of 3.1 ± 0.2 kbar, corresponding to a depth of 12 ± 1 km.
The volume of the mineralizing porphyry dikes and stocks at the emplacement level is far too small to have provided all the fluids and metals required to form the observed ore deposits. Therefore, the majority of the ore-forming fluids must have originated from the magmas that crystallized at 12 ± 1 km depth. The ore deposits, conversely, formed at ~5-km paleodepth. This implies that most of the mineralizing fluids traveled an average vertical distance of ~7 km from their magmatic source to the eventual site of ore precipitation. The relatively unaltered nature and low veining degree of deeper parts of mineralized porphyry dikes and stocks suggest that the fluid transport through these intrusive bodies occurred mostly at near-solidus conditions by means of fluid percolation along grain boundaries.
In summary, our results suggest that (1) a large, upper crustal pluton exists ~7 km beneath the Santa Rita and Hanover-Fierro deposits; (2) abundant phenocryst crystallization occurred at this depth level; and (3) this pluton was the main source for the exsolution of ore-forming fluids. However, the investigated rocks have elevated whole-rock Sr/Y ratios, indicating magma fractionation at deep crustal levels. As a result, our preferred model is a combination of the two end-member models introduced above, with most magma fractionation having occurred in the deep crust and with residual, intermediate to felsic melts having ascended and accumulated at 11 to 14 km paleodepth, where they continued to crystallize with comparatively little crystal-liquid separation, before some of these magmas ascended further to shallow levels and quenched to porphyries.
","language":"English","publisher":"Society of Economic Geology","doi":"10.5382/econgeo.5197","usgsCitation":"Audétat, A., Chang, J., and Gaynor, S.P., 2025, Depth of magma crystallization and fluid exsolution beneath the porphyry-skarn Cu deposits at Santa Rita and Hanover-Fierro, New Mexico, USA: Economic Geology, v. 120, no. 7, p. 1679-1699, https://doi.org/10.5382/econgeo.5197.","productDescription":"21 p.","startPage":"1679","endPage":"1699","ipdsId":"IP-174016","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":496982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Hanover-Fierro deposit, Santa Rita mine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108,\n 32.875\n ],\n [\n -108.1667,\n 32.875\n ],\n [\n -108.1667,\n 32.75\n ],\n [\n -108,\n 32.75\n ],\n [\n -108,\n 32.875\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Audétat, Andreas","contributorId":363151,"corporation":false,"usgs":false,"family":"Audétat","given":"Andreas","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Jia","contributorId":363152,"corporation":false,"usgs":false,"family":"Chang","given":"Jia","affiliations":[{"id":83309,"text":"Bavarian Geoinstitute, University of Bayreuth","active":true,"usgs":false}],"preferred":false,"id":951174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaynor, Sean Patrick 0000-0002-8353-511X","orcid":"https://orcid.org/0000-0002-8353-511X","contributorId":346264,"corporation":false,"usgs":true,"family":"Gaynor","given":"Sean","email":"","middleInitial":"Patrick","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}