The ecological importance of springs in semiarid regions is far greater than their small size and sparse distribution, yet little is known about the hydrologic functioning of these systems. During 2016–22, 261 springs were visited in the volcanic terrane of eastern Oregon and northern Nevada. When conditions were suitable, measurements of discharge, water temperature, and specific conductance were made, and samples for the analysis of carbon-14, tritium, and water stable isotopes (WSI) were collected. A subset of 60 springs was revisited during different seasons in the same year and during the dry season in multiple years to evaluate variability in discharge, chemistry, and groundwater age. Specific conductance and WSI varied considerably among springs across the study area but were unexpectedly stable across seasons and years at individual springs. Seasonal and interannual variability in spring discharge was related to the residence time of the discharging groundwater. Springs discharging older groundwater (103–104 years) had significantly less variability in their discharge compared to springs discharging younger groundwater (100–101 years). Variability among springs discharging younger groundwater included cessation of late-summer discharge at 18 % of the repeat-visit springs. A logistic regression model predicted the age of discharging spring water with 89 % accuracy using only the spring latitude, longitude, elevation, and δ2H value. This study framework provides a simple, inexpensive, and robust method to provisionally assess the hydrologic behavior of springs having little or no prior information in understudied, semiarid regions across the globe.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133922","usgsCitation":"Johnson, H.M., 2025, Hydrologic variability and groundwater age of springs in eastern Oregon and northern Nevada, USA: Journal of Hydrology, v. 662, no. Part A, 133922, 13 p., https://doi.org/10.1016/j.jhydrol.2025.133922.","productDescription":"133922, 13 p.","ipdsId":"IP-123085","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":493312,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133922","text":"Publisher Index Page"},{"id":492994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.31311680484953,\n 41.99539074875983\n ],\n [\n -120.0068581722988,\n 41.99391273807197\n ],\n [\n -119.90145747408332,\n 41.992434693061426\n ],\n [\n -119.84179670150823,\n 41.66048803137227\n ],\n [\n -118.9246520186846,\n 41.65959449142923\n ],\n [\n -118.93301194332504,\n 41.98445357532694\n ],\n [\n -117.02491929749873,\n 42.016929659002585\n ],\n [\n -117.01355889504242,\n 43.86708893750037\n ],\n [\n -116.91131527293696,\n 44.17343283492443\n ],\n [\n -117.20668573679785,\n 44.30365776197061\n ],\n [\n -117.26349474591721,\n 44.58751884415352\n ],\n [\n -117.18671855238352,\n 44.79442609102742\n ],\n [\n -117.77146876695777,\n 44.926186190521406\n ],\n [\n -117.91090405154984,\n 44.91839177439985\n ],\n [\n -117.97144831985975,\n 44.63186629043838\n ],\n [\n -118.6664325411721,\n 44.37656025661704\n ],\n [\n -119.868869617017,\n 44.396170474914186\n ],\n [\n -121.12677954373844,\n 44.318586844969104\n ],\n [\n -121.51042244069035,\n 42.944368334976076\n ],\n [\n -121.28368996303429,\n 42.40400912273424\n ],\n [\n -120.73802661060382,\n 42.42707264631977\n ],\n [\n -120.26821317970226,\n 41.99741467441126\n ],\n [\n -120.31311680484953,\n 41.99539074875983\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"662","issue":"Part A","noUsgsAuthors":false,"publicationDate":"2025-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Henry M. 0000-0002-7571-4994 hjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":869,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"hjohnson@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944189,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70269455,"text":"70269455 - 2025 - A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","interactions":[],"lastModifiedDate":"2025-07-23T14:18:18.596644","indexId":"70269455","displayToPublicDate":"2025-07-19T09:12:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation","docAbstract":"Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography published in the National Hydrography Dataset. Models were trained using 2,518 flow/no flow field observations collected in late summer 2019–2021 across headwaters of 129 sub-watersheds. The final model, the Western Oregon WeT DRy model, used Random Forest and 13 environmental covariates for classifying every 5-m stream sub-reach across 426 sub-watersheds. The most important covariates were annual precipitation and drainage area. Model output included probabilities of late summer surface flow presence and were subsequently categorized into three streamflow permanence classes—Wet, Dry, and Ambiguous. Ambiguous denoted model probabilities and associated prediction intervals that extended over the 50% classification threshold between wet and dry. Model accuracy was 0.83 for sub-watersheds that contained training data and decreased to 0.67 for sub-watersheds that did not have observations of late summer surface flow. The model identified where predictions extrapolated beyond the domain characterized by the training data. The combination of spatially continuous estimates of late summer streamflow status along with uncertainty and extrapolation estimates provide critical information for strategic project planning and designing additional field data collection.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025WR040478","usgsCitation":"Burnett, J., Jaeger, K.L., Johnson, S.L., Wondzell, S., Dunham, J., Barker, M., Heaston, E.D., Chelgren, N., Wing, M., Staab, B., and Brown, M., 2025, A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation: Water Resources Research, v. 61, no. 7, e2025WR040478, 29 p., https://doi.org/10.1029/2025WR040478.","productDescription":"e2025WR040478, 29 p.","ipdsId":"IP-166720","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496356,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025wr040478","text":"Publisher Index Page"},{"id":492763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Coast Range, Cascades, Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.57426256802401,\n 42.38410052088969\n ],\n [\n -121.21373758117394,\n 45.28963738462886\n ],\n [\n -121.54860532807825,\n 45.699012143249206\n ],\n [\n -122.42689354437806,\n 45.47540902005011\n ],\n [\n -123.13281971409793,\n 44.19046431828406\n ],\n [\n -122.79064395589202,\n 45.678368936712275\n ],\n [\n -123.17575442941168,\n 46.11430287596801\n ],\n [\n -123.98200543500289,\n 46.12677363777644\n ],\n [\n -124.52205720467518,\n 42.84974529742891\n ],\n [\n -124.19614743434411,\n 41.9512539365376\n ],\n [\n -121.59312670246439,\n 42.062457611874805\n ],\n [\n -121.47701396768437,\n 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0000-0002-4223-3465","orcid":"https://orcid.org/0000-0002-4223-3465","contributorId":192210,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":943797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wondzell, Steven M. 0000-0002-5182-5796","orcid":"https://orcid.org/0000-0002-5182-5796","contributorId":337143,"corporation":false,"usgs":false,"family":"Wondzell","given":"Steven M.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":943798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barker, Matthew Irwin 0000-0002-5286-4930","orcid":"https://orcid.org/0000-0002-5286-4930","contributorId":358465,"corporation":false,"usgs":true,"family":"Barker","given":"Matthew Irwin","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaston, Emily Dawn 0000-0002-3949-391X","orcid":"https://orcid.org/0000-0002-3949-391X","contributorId":290618,"corporation":false,"usgs":true,"family":"Heaston","given":"Emily","email":"","middleInitial":"Dawn","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943801,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":943802,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wing, Michael G.","contributorId":358467,"corporation":false,"usgs":false,"family":"Wing","given":"Michael G.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943803,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Staab, Brian","contributorId":358469,"corporation":false,"usgs":false,"family":"Staab","given":"Brian","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":943804,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brown, Michael E.","contributorId":358471,"corporation":false,"usgs":false,"family":"Brown","given":"Michael E.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":943805,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70268790,"text":"sir20255054 - 2025 - Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","interactions":[],"lastModifiedDate":"2026-02-03T14:29:12.653472","indexId":"sir20255054","displayToPublicDate":"2025-07-18T13:39:29","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5054","displayTitle":"Hydrogeologic Framework and Conceptual Model of the Red River Alluvial Aquifer East of Lake Texoma, Southeastern Oklahoma, 1980–2022","title":"Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022","docAbstract":"The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. At present (2025), the Oklahoma Water Resources Board has not established a maximum annual yield for the Red River alluvial aquifer east of Lake Texoma. To support the evaluation and determination of a maximum annual yield, a hydrogeologic framework and conceptual groundwater-flow model were developed to assess groundwater availability in the Red River alluvial aquifer east of Lake Texoma.
The scope of this hydrologic investigation is the alluvium and terrace containing the Red River alluvial aquifer in Oklahoma between Lake Texoma, the Texas State line, and the Arkansas State line, an extent referred to in this report as “the eastern part of the Red River alluvial aquifer.” Parts of the alluvium and terrace extent in Arkansas and Texas are included in some analyses to address hydrologic influences from outside the aquifer’s boundaries in Oklahoma.
The eastern part of the Red River alluvial aquifer in southeastern Oklahoma consists of approximately 401,280 acres of Quaternary alluvium and terrace deposits associated with the Red River and its major tributaries. Mean annual recharge to the aquifer for the 1980–2022 study period was estimated to be 8.62 inches per year, or 17.98 percent of the mean annual precipitation over the same period (47.94 inches). This mean annual recharge rate is equivalent to an inflow of approximately 288,250 acre-feet per year for the eastern part of the Red River alluvial aquifer. Recharge estimated using the Soil-Water-Balance code accounts for 98.7 percent of the conceptual-model inflows to the eastern part of the Red River alluvial aquifer. Saturated-zone evapotranspiration accounts for 11.9 percent and net streambed seepage accounts for 87.4 percent of the outflows in the conceptual model.
Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Contact Us- USGS Publications Warehouse
","tableOfContents":"The factors controlling the spatial distribution and temporal evolution of earthquake swarms in volcanic systems remain unclear. We leverage leading-edge deep learning algorithms and a detailed three-dimensional velocity model to construct a 15-year high-resolution earthquake catalog of the Yellowstone caldera region. More than half of the region’s earthquakes are clustered into swarm-like families characterized by episodes of hypocenter expansion and migration. Adjacent earthquake swarms, separated by long quiescent periods, are found to be a dominant feature. We suggest that these swarms are controlled by the interplay between slowly diffusing aqueous fluids and rapid episodic fluid injections, which may result from the breaking of permeability seals. Our analyses also indicate that clustered seismicity beneath the caldera occurs on relatively immature, rougher fault structures, compared to more planar faults outside. Our results provide additional context for understanding seismicity in hydrothermal systems, highlighting the key role played by long-term fluid diffusion processes in driving the occurrence of earthquake swarms.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adv6484","usgsCitation":"Florez, M., Li, B.Q., Shelly, D.R., Angulo, M., and Sanabria-Gomez, J., 2025, Long-term dynamics of earthquake swarms in the Yellowstone caldera: Science Advances, v. 11, no. 29, eadv6484, 10 p., https://doi.org/10.1126/sciadv.adv6484.","productDescription":"eadv6484, 10 p.","ipdsId":"IP-175431","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":495178,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adv6484","text":"Publisher Index Page"},{"id":495121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.2,\n 44.85\n ],\n [\n -111.2,\n 44.1\n ],\n [\n -110.2,\n 44.1\n ],\n [\n -110.2,\n 44.85\n ],\n [\n -111.2,\n 44.85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"29","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Florez, Manuel","contributorId":360774,"corporation":false,"usgs":false,"family":"Florez","given":"Manuel","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Bing Q.","contributorId":360823,"corporation":false,"usgs":false,"family":"Li","given":"Bing","middleInitial":"Q.","affiliations":[],"preferred":false,"id":947633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":947634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angulo, Mia","contributorId":360775,"corporation":false,"usgs":false,"family":"Angulo","given":"Mia","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanabria-Gomez, Jose","contributorId":360776,"corporation":false,"usgs":false,"family":"Sanabria-Gomez","given":"Jose","affiliations":[{"id":86102,"text":"Universidad Industrial de Santander, Colombia","active":true,"usgs":false}],"preferred":false,"id":947636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269434,"text":"70269434 - 2025 - Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","interactions":[],"lastModifiedDate":"2025-08-18T15:15:37.43118","indexId":"70269434","displayToPublicDate":"2025-07-18T09:35:07","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":"Tailwater residency patterns of Silver Carp at Kentucky Lock and Dam","docAbstract":"The management of invasive Silver Carp Hypophthalmichthys molitrix in the Tennessee River basin focuses on removal, and there is interest in extending removal efforts to the tailwater environments of high-head locks and dams along the Tennessee River, such as Kentucky Dam. We used acoustic telemetry data from Silver Carp to understand important ecological associations underlying their residence in the Kentucky Dam tailwater, measured by daily fish counts and mean residence time.
We used time-series-informed regression models, variance partitioning, and cross-correlation function analysis to associate six predictors, including lock and dam operations (total, spill gate, and turbine discharge and number of lockages), hydrology (tailwater elevation), and water temperature, with two measures of Silver Carp residency (daily counts and mean residence time).
We found that spill-induced hydrology (total discharge + spill discharge + tailwater elevation) was negatively associated with daily counts but not with residence time, whereas temperature was positively associated with counts and negatively associated with residence times. Variance partitioning indicated that nearly all the variance in counts and residence times was jointly explained by temporal effects, lock and dam operations (discharge, tailwater elevation, and lockages), and temperature. The cross-correlations indicated that the counts were lagged by all predictors, sometimes up to 5 d, whereas residence times were lagged by both total and spill discharge and number of lockages.
We found that discharge and water temperature were principally associated with residency of Silver Carp in the Kentucky Dam tailwater. However, these associations were entirely temporally constrained, which can affect how strongly and how quickly Silver Carp respond to changing environmental conditions across different time scales. Managers can leverage these associations to plan removal periods where daily tailwater conditions/dam operations are favorable to invasive carp residence (e.g., >10°C and <2,500 m3/s) and adjust fishing effort to optimize removal rates in response to changing conditions.
Perfluorodecanesulfonate (PFDS), a long-chain polyfluoroalkyl substance (PFAS), is widely detected in aquatic environments and increasingly recognized for its environmental persistence and bioaccumulative potential; however, its immunotoxicity remains poorly understood in aquatic biota. In this study, early life stage zebrafish (Danio rerio) were exposed to environmentally relevant concentrations of PFDS and PFOS for 120 h to better characterize the adverse effects of PFDS on aquatic organisms. Additionally, the toxicological differences between PFDS and PFOS at the same exposure concentrations were compared, as PFDS is a known substitute for PFOS. PFDS bioaccumulated in zebrafish larvae at environmentally relevant concentrations, which disrupted immune function by altering the number of macrophages and neutrophils, inducing oxidative stress, and dysregulating immune markers such as interleukins and immunoglobulins. Mechanistically, PFDS activated the nuclear factor kappa B (NF-κB) signaling pathway, driving pro-inflammatory cytokine expression and immune dysfunction. Furthermore, the use of a NF-κB morpholino knockdown confirmed the role of the NF-κB pathway in mediating PFDS-induced immunotoxicity. These findings provide the first comprehensive evidence of PFDS-induced immunotoxicity being mediated through NF-κB activation, offering novel insights into the ecological risks of long-chain perfluorosulfonic acids. Notably, PFDS exhibited a stronger immunotoxic response relative to PFOS, indicating that its adverse effects may be more severe. Overall, these findings provide valuable insights for the ecological risk assessment of PFDS and the toxic potential that unregulated PFAS can have to aquatic systems.
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The connection between inland fish, fisheries, and their ecosystems means that addressing the needs of fish directly offers opportunities to meet multiple global commitments and provide indicators of progress towards many global goals. In this perspective, we highlight opportunities to better integrate inland fish and fisheries into MEAs, specifically the Convention on Biological Diversity (CBD), Convention on Wetlands (commonly known as the Ramsar Convention), Convention on Conservation of Migratory Species (CMS), Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), and World Heritage Convention (WHC). Greater attention on inland fish and fisheries through MEAs could help ensure more holistic planning, investment, and conservation of these important fish and fisheries, their biodiversity, the essential resources they provision, and the environments they inhabit.
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niche of brown bears: Constraints on adaptive capacity in human-modified landscapes","docAbstract":"DDiel activity rhythms, representing the behavioral pattern of the sleep–wake cycle, may be adjusted by wildlife in response to changes in environmental conditions. An increase in nocturnality is typically recognized as an adaptive strategy to segregate from humans and mitigate heat stress. Numerous studies have investigated spatial patterns and habitat use of large carnivores in human-modified landscapes, but little research has examined their activity rhythms. We compiled Global Positioning System data (2004–2022) for 139 brown bears Ursus arctos from six populations across Europe, representing a human-modified landscape, and the Greater Yellowstone Ecosystem, U.S.A., representing a landscape with limited human impact, which we used to calculate hourly movement rates as an activity proxy. Using a Bayesian approach to model the temporal autocorrelation of activity data, we tested if the extent of nocturnality in brown bears is modulated by intensity of human encroachment, accounting for primary productivity and maximum ambient temperature. All bear populations exhibited a predominantly bimodal, crepuscular pattern of activity, although Yellowstone bears were proportionally more crepuscular and diurnal. Whereas the effect of primary productivity was variable, all European populations became more nocturnal in response to higher human encroachment and reduced diurnal and crepuscular activity at higher summer temperatures, decreasing overall diel activity levels. Yellowstone bears displayed the greatest shift towards nocturnality among all populations in response to increasing human encroachment, and increased nocturnal activity to compensate for lower diurnal and crepuscular activity at higher summer temperatures. Our research indicates that European bears in human-modified landscapes may be reaching a limit in the behavioral plasticity they can manifest in their activity patterns, being already constrained into increased nocturnality. Our findings enhance the understanding of brown bear adaptive capacity to accommodate future changes, such as urbanization and increasing temperatures, to the ecosystems they inhabit.
","language":"English","publisher":"Wiley","doi":"10.1002/ecog.07979","usgsCitation":"Donatelli, A., Ćirović, D., Haroldson, M.A., Huber, Đ., Kindberg, J., Kojola, I., Kusak, J., Mastrantonio, G., Ordiz, A., Reljić, S., Santini, L., van Manen, F.T., and Ciucci, P., 2025, The diel niche of brown bears: Constraints on adaptive capacity in human-modified landscapes: Ecography, v. 2025, no. 10, e07979, 15 p., https://doi.org/10.1002/ecog.07979.","productDescription":"e07979, 15 p.","ipdsId":"IP-174846","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":493787,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecog.07979","text":"Publisher Index Page"},{"id":492607,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Croatia, Finland, Italy, Russia, Serbia, Sweden, United States","geographicExtents":"{\n \"type\": 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Sapienza","active":true,"usgs":false}],"preferred":false,"id":943657,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":943658,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ciucci, P.","contributorId":358405,"corporation":false,"usgs":false,"family":"Ciucci","given":"P.","affiliations":[{"id":81866,"text":"University of Rome La Sapienza","active":true,"usgs":false}],"preferred":false,"id":943659,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70269707,"text":"70269707 - 2025 - Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","interactions":[],"lastModifiedDate":"2025-07-30T15:06:19.598148","indexId":"70269707","displayToPublicDate":"2025-07-18T07:58:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22155,"text":"Smart Agricultural Technology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions","docAbstract":"Cover crops play a critical role in providing agroecological services such as improving soil health, reducing erosion and nitrogen loss, and suppressing weeds, which are closely tied to their performance such as accumulated biomass. This study evaluated the Active Canopy Sensor (ACS) -214, an active proximal sensing device equipped with its own light-emitting red and near-infrared spectral reflectance sensors, a time-of-flight laser, and an ultrasonic sensor, for estimating winter cover crop biomass across 13 U.S. states from 2020 to 2024. We assessed 11 species from three functional groups – grasses (n = 797), legumes (n = 264), and brassicas (n = 181) – using Random Forest (RF) models and four cross-validation strategies. The ACS-214 showed moderate to strong prediction accuracy for grasses (R2 = 0.51 – 0.64) and legumes (R2 = 0.44 – 0.76), though performance declined in leave-one-region-out analyses (R2 = 0.06 – 0.46), indicating limited spatial generalizability. Brassica models had low prediction accuracy for all models (R2 < 0.30), likely due to flowering and patchy growth. Biomass prediction breakpoints were observed at ∼3000 kg ha−1 for legumes and ∼4000 kg ha−1 for grasses. We also evaluated the effectiveness of using ACS-214 data to train Sentinel-2 satellite imagery for estimating grass cover crop biomass using withheld, out of bag data from 2023 to 2024. Sentinel-2 RF models trained with ACS-214 data showed good agreement with field-sampled (R2 = 0.58 – 0.61) and ACS-214-estimated biomass (R2 = 0.70). While Sentinel-2 offers scalability, the ACS-214 enables finer-resolution biomass mapping and better accounts for within-field variability, making it an effective tool for localized management and monitoring. These findings support the integration of proximal and satellite sensing approaches to enhance cover crop biomass estimation and agroecological assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atech.2025.101201","usgsCitation":"Jennewein, J., Davis, B., Seehaver-Eagan, S., Nicolette, J., Pittman, J., Hively, W.D., Goldsmith, A., Hidalgo, C., Reberg-Horton, C., and Mirsky, S., 2025, Multi-sensor proximal remote sensing for cover crop biomass estimation at high and moderate spatial resolutions: Smart Agricultural Technology, v. 12, 101201, 22 p., https://doi.org/10.1016/j.atech.2025.101201.","productDescription":"101201, 22 p.","ipdsId":"IP-179201","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":493304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atech.2025.101201","text":"Publisher Index Page"},{"id":493188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Indiana, Iowa, Kansas, Maryland, Missouri, North Carolina, Ohio, New Hampshire, Vermont, Virginia, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.92714553560637,\n 43.58854319693313\n ],\n [\n -95.89232587289348,\n 37.62183341552925\n ],\n [\n -89.95992461869106,\n 37.07043638610585\n ],\n [\n -88.56407871751861,\n 30.53924077937387\n ],\n [\n -87.95786849494071,\n 30.079081766107564\n ],\n [\n -79.28622937957765,\n 30.005749406912585\n ],\n [\n -71.27060896702632,\n 45.07860396784778\n ],\n [\n -86.55806437204849,\n 45.188229262227445\n ],\n [\n -91.6664764308591,\n 46.72848518852835\n ],\n [\n -96.92714553560637,\n 43.58854319693313\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jennewein, Jyoti","contributorId":243442,"corporation":false,"usgs":false,"family":"Jennewein","given":"Jyoti","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":944485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Brian W. 0000-0003-0714-5133","orcid":"https://orcid.org/0000-0003-0714-5133","contributorId":358921,"corporation":false,"usgs":false,"family":"Davis","given":"Brian W.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seehaver-Eagan, S. 0009-0002-1048-9623","orcid":"https://orcid.org/0009-0002-1048-9623","contributorId":358924,"corporation":false,"usgs":false,"family":"Seehaver-Eagan","given":"S.","affiliations":[{"id":85715,"text":"North Carolina State University (NCSU)","active":true,"usgs":false}],"preferred":false,"id":944487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nicolette, J. 0000-0002-8904-2391","orcid":"https://orcid.org/0000-0002-8904-2391","contributorId":358925,"corporation":false,"usgs":false,"family":"Nicolette","given":"J.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":944488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pittman, J.","contributorId":358926,"corporation":false,"usgs":false,"family":"Pittman","given":"J.","affiliations":[{"id":85718,"text":"BAER","active":true,"usgs":false}],"preferred":false,"id":944489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hively, W. 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Special conditions identified from U.S. Geological Survey gaging records and basin characteristics included regulation and diversion, urbanization, indeterminate drainage areas, drainage areas less than the minimum used in regional analyses, glacial lake outburst floods, other outburst floods, and snowmelt floods. For peak flows that occurred during calendar years 1980–2019, an atmospheric river dataset was used to identify atmospheric river presence or absence on the dates peak flows occurred. Extreme floods (defined as peak flows exceeding the 1-percent annual exceedance probability flood magnitude or an empirical measure of relative magnitude using Creager’s coefficient C) were identified and associated with flood-generating mechanisms using the other inventoried special conditions and other information.
The gaging record contained glacial lake outburst floods at 15 streamgages and other types of outburst floods at 10 streamgages. Non-outburst peak flows in Alaska resulted from a mixture of rainfall and melt-based flood-generating mechanisms in all but the most rain-dominated seasonal flow regime. Melt-based flood-generating mechanisms included snowmelt, high-elevation snow and ice melt, or rain-on-snow events. Atmospheric rivers were common in Alaska and conterminous basins in Canada, occurring in that region on 67 percent of the days in the calendar year 1980–2019 period. Atmospheric rivers were more common on the days of peak flows and even more common on the days of non-outburst extreme floods. The percentage of days when an atmospheric river was present increased to 78 percent for the days of peak flows in that period and to 83 percent for the days of non-outburst extreme floods in that period. Of 149 extreme floods in the gaging record, 38 were generated by outburst floods. Of the non-outburst extreme floods, 72 percent were generated by rainfall and 26 percent were generated by melt-based processes or a combination of rainfall and melt-based processes. Flood-generating mechanisms could not be determined for the final 2 percent of the non-outburst extreme floods because the month and day of the peak flows were unknown and no other information was available. Secondary factors strongly associated with extreme floods included antecedent rain and streamflow conditions and warm storm conditions that produced rain instead of snow or generated snowmelt.
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Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska, 99508
Rapid warming could drastically alter host–parasite relationships, which is especially important for fisheries crucial to human nutrition and economic livelihoods, yet we lack a synthetic understanding of how warming influences parasite-induced mortality in these systems. We conducted a meta-analysis using 266 effect sizes from 52 empirical papers on harvested aquatic species and determined the relationship between parasite-induced host mortality and temperature and how this relationship was altered by host, parasite, and study design traits. Overall, higher temperatures increased parasite-induced host mortality; however, the magnitude of this relationship varied. Hosts from the order Salmoniformes experienced a greater increase in parasite-induced mortality with temperature than the average response to temperature across fish orders. Opportunistic parasites were associated with a greater increase in infected host mortality with temperature than the average across parasite strategies, while bacterial parasites were associated with lower infected host mortality as temperature increased than the average across parasite types. Thus, parasites will generally increase host mortality as the environment warms; however, this effect will vary among systems.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.70156","usgsCitation":"Tomamichel, M.M., Lowe, K.I., Arnold, K.M., Frischer, M.E., Irwin, B., Osenberg, C.W., Hall, R.J., and Byers, J.E., 2025, Warmer Is deadlier: A meta‐analysis reveals increasing temperatures accentuate disease effects on fisheries hosts: Ecological Letters, v. 28, no. 7, e70156, 14 p., https://doi.org/10.1111/ele.70156.","productDescription":"e70156, 14 p.","ipdsId":"IP-159658","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495041,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ele.70156","text":"External Repository"},{"id":494524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tomamichel, M. 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E.","contributorId":360392,"corporation":false,"usgs":false,"family":"Frischer","given":"M.","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947008,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irwin, Brian J. 0000-0002-0666-2641","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":280043,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":947009,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osenberg, C. W.","contributorId":360396,"corporation":false,"usgs":false,"family":"Osenberg","given":"C.","middleInitial":"W.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947010,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hall, R. J.","contributorId":360398,"corporation":false,"usgs":false,"family":"Hall","given":"R.","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947011,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byers, J. E.","contributorId":360402,"corporation":false,"usgs":false,"family":"Byers","given":"J.","middleInitial":"E.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":947012,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269321,"text":"70269321 - 2025 - Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation","interactions":[],"lastModifiedDate":"2025-11-18T16:58:07.522222","indexId":"70269321","displayToPublicDate":"2025-07-17T09:08:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation","docAbstract":"The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaf087","usgsCitation":"Weiss, M., Holland, A., D’Amato, A.W., Deegan, L.A., Farmer, W., Hoving, C., Karmalkar, A., Latzka, A.W., Magee, M., McIntyre, P.B., Morelli, T.L., Notaro, M., Olmstead, N., Palmer, R., Pau, N., Renfrew, R., Ribic, C., Sheppard, J., Staudinger, M., Zuckerberg, B., and Bradley, B.A., 2025, Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation: BioScience, v. 75, no. 10, p. 842-855, https://doi.org/10.1093/biosci/biaf087.","productDescription":"14 p.","startPage":"842","endPage":"855","ipdsId":"IP-169492","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":492532,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiss, Marissa","contributorId":167459,"corporation":false,"usgs":false,"family":"Weiss","given":"Marissa","email":"","affiliations":[{"id":24712,"text":"Harvard Forest","active":true,"usgs":false}],"preferred":false,"id":943442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, Addie Rose","contributorId":355367,"corporation":false,"usgs":false,"family":"Holland","given":"Addie Rose","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":943443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":943444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deegan, Linda A.","contributorId":34094,"corporation":false,"usgs":false,"family":"Deegan","given":"Linda","email":"","middleInitial":"A.","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. 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Mazama (Crater Lake), USA","interactions":[],"lastModifiedDate":"2025-07-28T14:58:44.447972","indexId":"70269608","displayToPublicDate":"2025-07-17T07:52:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"New insights into gas-driven phase segregation in andesitic enclaves from Mt. Mazama (Crater Lake), USA","docAbstract":"A key process in active magmatic systems is the “recharge” of deep-sourced mafic magma into cooler, more evolved, and crystal-rich shallow reservoirs; recharge may be the cause of, or response to, eruptive activity. Although compositional evidence for recharge has been extensively documented, physical models of recharge are limited, particularly processes that\nseparate exsolving volatiles and melts from rapidly growing crystals. To improve constraints on phase separation behaviors, we re-examine andesitic enclaves in silicic andesite lava flows of Mt. Mazama (Crater Lake), USA, that provided early evidence of gas-driven filter pressing (Bacon, 1986). 2D and 3D imaging shows that enclaves have a sample-spanning crystal\nframework that is disrupted by melt patches, indicating that initially deformable crystal networks were subject to early phase reorganization. Small enclaves are poorly vesicular and require early gas loss. Large enclaves have porous cores with angular (diktytaxitic) voids that are well-connected in 3D and denser rinds with isolated pores. Large enclave rinds have similar bulk\ncompositions to small enclaves but their less evolved cores require ~ 20% melt removal. In the large enclave, diktytaxitic core textures and gas fingering structures at the core–rind boundary suggest relatively slow late-stage outward gas migration. Both scaling arguments and evidence of outward gas/melt migration require a resistant rind. Rind formation is best explained by differential cooling and demonstrates the importance of thermal gradients for gas-driven filter pressing. A corollary is a limited time scale of recharge, enclave formation, and vesiculation to produce diktytaxitic textures, suggesting that recharge was (near) synchronous with eruption.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01855-8","usgsCitation":"Oppenheimer, J., Cashman, K., Rust, A.C., Bacon, C.R., Lindoo, A., and Dobson, K., 2025, New insights into gas-driven phase segregation in andesitic enclaves from Mt. Mazama (Crater Lake), USA: Bulletin of Volcanology, v. 87, no. 65, 65, 19 p., https://doi.org/10.1007/s00445-025-01855-8.","productDescription":"65, 19 p.","ipdsId":"IP-172926","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":494436,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01855-8","text":"Publisher Index Page"},{"id":493002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake, Mt. Mazama","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.18090601540398,\n 42.98586629991806\n ],\n [\n -122.18090601540398,\n 42.895897881682174\n ],\n [\n -122.0345881300828,\n 42.895897881682174\n ],\n [\n -122.0345881300828,\n 42.98586629991806\n ],\n [\n -122.18090601540398,\n 42.98586629991806\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","issue":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oppenheimer, Julie","contributorId":358795,"corporation":false,"usgs":false,"family":"Oppenheimer","given":"Julie","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":944172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Katharine V.","contributorId":40097,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine V.","affiliations":[],"preferred":false,"id":944173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rust, Alison C.","contributorId":196700,"corporation":false,"usgs":false,"family":"Rust","given":"Alison","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":944174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":944175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindoo, Amanda","contributorId":344833,"corporation":false,"usgs":false,"family":"Lindoo","given":"Amanda","email":"","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":944176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dobson, Katherine J.","contributorId":358798,"corporation":false,"usgs":false,"family":"Dobson","given":"Katherine J.","affiliations":[{"id":37954,"text":"University of Durham","active":true,"usgs":false}],"preferred":false,"id":944177,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271993,"text":"70271993 - 2025 - Global terrestrial nitrogen fixation and its modification by agriculture","interactions":[],"lastModifiedDate":"2025-09-30T15:37:10.058045","indexId":"70271993","displayToPublicDate":"2025-07-16T10:32:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Global terrestrial nitrogen fixation and its modification by agriculture","docAbstract":"Biological nitrogen fixation (BNF) is the largest natural source of new nitrogen (N) that supports terrestrial productivity1,2, yet estimates of global terrestrial BNF remain highly uncertain3,4. Here we show that this uncertainty is partly because of sampling bias, as field BNF measurements in natural terrestrial ecosystems occur where N fixers are 17 times more prevalent than their mean abundances worldwide. To correct this bias, we develop new estimates of global terrestrial BNF by upscaling field BNF measurements using spatially explicit abundances of all major biogeochemical N-fixing niches. We find that natural biomes sustain lower BNF, 65 (52–77) Tg N yr−1, than previous empirical bottom-up estimates3,4, with most BNF occurring in tropical forests and drylands. We also find high agricultural BNF in croplands and cultivated pastures, 56 (54–58) Tg N yr−1. Agricultural BNF has increased terrestrial BNF by 64% and total terrestrial N inputs from all sources by 60% over pre-industrial levels. Our results indicate that BNF may impose stronger constraints on the carbon sink in natural terrestrial biomes and represent a larger source of agricultural N than is generally considered in analyses of the global N cycle5,6, with implications for proposed safe operating limits for N use7,8.
","language":"English","publisher":"Nature","doi":"10.1038/s41586-025-09201-w","usgsCitation":"Reis Ely, C., Perakis, S.S., Cleveland, C., Menge, D., Reed, S.C., Taylor, B., Batterman, S., Clark, C.M., Crews, T., Dynarski, K.A., Gei, M., Gundale, M., Herridge, D., Jovan, S.E., Kou-Giesbrecht, S., Peoples, M., Piipponen, J., Rodriguez-Caballero, E., Salmon, V., Soper, F.M., Staccone, A., Weber, B., Williams, C., and Wurzburger, N., 2025, Global terrestrial nitrogen fixation and its modification by agriculture: Nature, v. 643, p. 705-711, https://doi.org/10.1038/s41586-025-09201-w.","productDescription":"7 p.","startPage":"705","endPage":"711","ipdsId":"IP-163219","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":496330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41586-025-09201-w","text":"Publisher Index 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system","interactions":[],"lastModifiedDate":"2025-12-12T16:23:39.187411","indexId":"70273007","displayToPublicDate":"2025-07-16T10:18:19","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}},"title":"Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system","docAbstract":"Predation establishes risk, which can indirectly influence prey behavior and ecology. We evaluated the influence of Mexican gray wolves (Canis lupus baileyi) on habitat selection and spatiotemporal predator avoidance strategies of elk (Cervus canadensis). We fit 866 adult female elk with GPS collars across areas of varying wolf densities within the Mexican wolf experimental population area of eastern Arizona and western New Mexico between 2019−2021. Using step-selection functions we examined relative intensity of elk use in relation to landscape attributes, estimated predator/prey diel activity, and measures of risk. Risk metrics included predicted wolf presence, habitat openness, and predicted risky places modeled from attributes of locations where wolves killed elk. Wolf activity varied across seasons and increased midday and night in fall and monsoon seasons. Relative use by elk was best explained by incorporating an interaction between diel period and predicted risky places across all seasons. Elk utilized risky places more in times of nutritional deficit associated with high energetic demands of the third trimester pregnancy and lactation and when forage quality was best, during spring and monsoon season. Particularly, use of risky places increased at less risky times in areas with more established wolf presence, suggesting use of risky places varied relative to exposure to Mexican wolves. These behaviors highlight the importance of temporal avoidance when predators and prey are highly mobile and largely overlap in space. Our research suggests temporally responding to predictable and relatively static environmental characteristics associated with encounter and kill rates may better balance energetic trade-offs than anticipating changes in wolf activity or spatially avoiding areas with higher wolf presence. Thus, elk appear to be more willing to take chances and mitigate cursorial predation risk with a more immediate, reactive approach and make proactive trade-offs during the seasons they can best increase fitness.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2025.1613904","usgsCitation":"Thompson, C.J., Tatman, N.M., Farley, Z.J., Boyle, S.T., Greenleaf, A.R., and Cain, J.W., 2025, Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system: Frontiers in Ecology and Evolution, v. 13, 1613904, 17 p., https://doi.org/10.3389/fevo.2025.1613904.","productDescription":"1613904, 17 p.","ipdsId":"IP-178445","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":497705,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2025.1613904","text":"Publisher Index Page"},{"id":497479,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.32284903489135,\n 35.0948138550403\n ],\n [\n -111.32284903489135,\n 32.96688100110357\n ],\n [\n -106.60492292551181,\n 32.96688100110357\n ],\n [\n -106.60492292551181,\n 35.0948138550403\n ],\n [\n -111.32284903489135,\n 35.0948138550403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Cara J.","contributorId":363878,"corporation":false,"usgs":false,"family":"Thompson","given":"Cara","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tatman, Nicole M.","contributorId":363881,"corporation":false,"usgs":false,"family":"Tatman","given":"Nicole","middleInitial":"M.","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":952086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farley, Zachary J.","contributorId":363884,"corporation":false,"usgs":false,"family":"Farley","given":"Zachary","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyle, Scott T.","contributorId":363887,"corporation":false,"usgs":false,"family":"Boyle","given":"Scott","middleInitial":"T.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":952088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greenleaf, Allison R.","contributorId":363890,"corporation":false,"usgs":false,"family":"Greenleaf","given":"Allison","middleInitial":"R.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":952089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cain, James W. 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There are three species of tegu lizards native to South America and available in the pet trade that have a high risk of invasion and deleterious impacts to native ecosystems in the United States (US). There are four populations of the black and white tegu (Salvator merianae) in Florida and sightings as far north as North Carolina and west as California. Red tegus (S. rufescens) have been observed in Florida, and there is an established population of gold tegus (Tupinambis teguixin) in Florida. We updated previous distribution models for the contiguous United States (CONUS) that used occurrence points from their native range in South America to evaluate potential changes given current and future climate scenarios (+2 °C and +4 °C warming). Under current climate conditions, one or more tegu species have the potential to occupy most ecoregions in the CONUS. Under a + 4 °C warming scenario, suitable habitat increases by 11 % for S. merianae, 31 % for S. rufescens. The proportion of suitable habitat for T. teguixin was small under all scenarios, but increased from 0.0003 to 0.0017. For S. merianae, parts of Florida become less suitable, while suitability increases in this region for the other two species. Additionally, much of the western US is projected to be suitable for S. rufescens. Our case study underscores the potential for climate change to compound invasion threats that could outpace effective managerial responses.
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forest habitat and insect richness","docAbstract":"While aquatic environmental DNA (eDNA) methods have reached relative maturity, terrestrial eDNA methods are nascent and have yet to reach widespread use. Field-ready applications require eDNA survey methods where samples are easy to collect by inexperienced practitioners, easy to transport between the field and lab, and easy to process thereafter. Here, we demonstrate methods that satisfy these requirements and show strong potential for characterizing diverse terrestrial eDNA samples collected from flower and leaf surfaces.
We used novel methods to collect and process 236 flower eDNA samples and 21 leaf surface eDNA samples, obtaining 2,228 Arthropoda eDNA detections spanning 175 families using amplicon sequencing of two genetic markers.
Detected taxa were diverse and included numerous groups of conservation concern, such as bees (Hymenoptera; Anthophila, 32 genera spanning 5 families) and Lepidoptera (209 genera from 21 families). Data reveal strong associations between insect community richness and remotely sensed measures of forest habitat, providing a quantitative perspective of relevance to insect conservation.
It is increasingly clear that a variety of organisms readily disperse eDNA throughout the environment, supporting the notion that eDNA will be a powerful tool for characterizing species distributions and monitoring at-risk species. However, we conclude that researchers seeking to characterize fine-scale habitat associations or plant-pollinator interactions using eDNA will need to carefully design studies with appropriate field controls, such as the leaf surface eDNA samples collected here.
This report synthesizes current (2024) science-based knowledge related to the impacts of climate change on big sagebrush vegetation in Western North America. This effort was conducted through the U.S. Geological Survey working with the Bureau of Land Management as part of multiple science syntheses to aid management agencies developing environmental impacts assessments in response to human-related or caused events. This report reviews the potential impacts climate change may have on sagebrush vegetation and related management decisions. The body of the synthesis introduces the diverse impacts of climate change across the region by first focusing directly on what climate change may entail in terms of altered temperature and precipitation patterns. The report then discusses how these changes could likely affect individual plant species based on experimental results and scale the impacts to species distributions and community composition. The synthesis section ends by surveying efforts to model potential future changes in habitat. The report goes on to link the synthesis conclusions to individual land uses or land management decisions, such as forage resources, restoration or fuel treatment. Finally, the report provides a section that discusses the pros and cons of available datasets that model the potential future of vegetation in the sagebrush region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255045","collaboration":"Prepared in cooperation with Yale School of the Environment and Bureau of Land Management","usgsCitation":"Carpenter, S.M., Holdrege, M.C., Schlaepfer, D.R., Phillips, J., Griffin, P., Lauenroth, W.K., and Bradford, J.B., 2025, Climate change impacts on plant communities in the sagebrush region—A science synthesis to inform Bureau of Land Management resource management: U.S. Geological Survey Scientific Investigations Report 2025–5045, 60 p., https://doi.org/10.3133/sir20255045.","productDescription":"x, 60 p.","onlineOnly":"Y","ipdsId":"IP-158152","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":492288,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5045/images"},{"id":492163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5045/sir20255045.pdf","text":"Report","size":"54.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5045"},{"id":492162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5045/coverthb.jpg"},{"id":492435,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255045/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5045"},{"id":492289,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5045/sir20255045.xml"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, 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 -108.47085655229651,\n 49.03087841335443\n ],\n [\n -109.36707098761016,\n 48.97533905613594\n ],\n [\n -108.59984126360919,\n 47.10350873556769\n ],\n [\n -111.17120403969128,\n 48.93205699878433\n ],\n [\n -110.72899206743233,\n 47.28774464917828\n ],\n [\n -114.81019931620497,\n 44.92767854204746\n ],\n [\n -118.26252607142581,\n 47.40161992530679\n ],\n [\n -120.96059041198399,\n 48.913826471813934\n ],\n [\n -121.51113648480029,\n 48.583049845013676\n ],\n [\n -122.22592814966379,\n 42.19558595467558\n ],\n [\n -120.23956000538604,\n 38.86950616483054\n ],\n [\n -115.16424378294235,\n 34.49668753215643\n ],\n [\n -114.66904039390542,\n 35.774420444698194\n ],\n [\n -111.91445748122553,\n 36.57404002586604\n ],\n [\n -111.08039807202803,\n 38.090459720027894\n ],\n [\n -109.66040807077158,\n 34.09264795999532\n ],\n [\n -105.49956098365757,\n 33.35306735179675\n ],\n [\n -105.1942616934904,\n 36.86164728405714\n ],\n [\n -104.46325968085759,\n 41.6756079905559\n ],\n [\n -103.67824727595544,\n 42.2158730516426\n ],\n [\n -104.8704368129265,\n 44.69923426792971\n ],\n [\n -103.37233643926561,\n 45.25198814864976\n ],\n [\n -102.99032903885458,\n 48.723152452506895\n ],\n [\n -103.77002889466604,\n 48.730618780629214\n ],\n [\n -105.59751217809955,\n 47.36393384939501\n ],\n [\n -105.88781115813256,\n 48.97431691272439\n ],\n [\n -108.47085655229651,\n 49.03087841335443\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Researchers and policymakers increasingly recognize the contribution of aquatic food systems, such as fisheries, to food security and nutrition. Yet governing fisheries for nutrition objectives is complicated by the multiple overlapping processes that shape availability and access to nutrients over time, including fishing sustainability, climate change, trade dynamics, and consumer preferences. Anticipating the effect of governance interventions to sustain or enhance nutritional benefits from fisheries entails accounting for these multiple interacting influences. We develop an analytical approach to link available data on aquatic foods production, nutrition, distribution, and potential climate impacts to evaluate the nutrition implications of fishery management and post-harvest allocation interventions. We demonstrate this approach using national and publicly available datasets for five case study countries: Peru, Chile, Indonesia, Sierra Leone, and Malawi. As examples, we evaluate the potential to enhance domestic supply of key nutrients to nutritionally-vulnerable populations by (a) dynamically adjusting fishing effort in response to climate impacts on fish stocks, and (b) retaining aquatic foods currently diverted via trade or foreign fishing. The results indicate substantial differences across countries in terms of anticipated climate change effects, with potential for substantially increased nutrition yield in Chile and Peru under adaptive management, vs more modest yield increases in Indonesia. The impacts of post-harvest allocation policies related to foreign fishing, exports, fishing sector, and subnational trade also vary, with exports weighing heavily on nutrient availability in Sierra Leone. This methodological approach represents a step toward operationalizing calls to manage fisheries as part of national food and nutrient supplies, in light of climate change risks.
","language":"English","publisher":"Purpose-Led Publishing","doi":"10.1088/2976-601x/add164","usgsCitation":"Bennett, A., Mason, J.G., Battista, W., Free, C.M., Gephart, J.A., Kleisner, K.M., Rice, E.D., Robinson, K.F., and Virdin, J., 2025, An analytical approach to explore prospects and limits of nutrition-sensitive fisheries governance under climate change: Environmental Research: Food Systems, v. 2, 035003, 25 p., https://doi.org/10.1088/2976-601x/add164.","productDescription":"035003, 25 p.","ipdsId":"IP-166669","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/2976-601x/add164","text":"Publisher Index Page"},{"id":494537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","noUsgsAuthors":false,"publicationDate":"2025-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Bennett, Abigail","contributorId":360346,"corporation":false,"usgs":false,"family":"Bennett","given":"Abigail","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mason, Julia G.","contributorId":360348,"corporation":false,"usgs":false,"family":"Mason","given":"Julia","middleInitial":"G.","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":946988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battista, Willow","contributorId":360351,"corporation":false,"usgs":false,"family":"Battista","given":"Willow","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":946989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Free, Christopher M.","contributorId":360354,"corporation":false,"usgs":false,"family":"Free","given":"Christopher","middleInitial":"M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":946990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gephart, Jessica A.","contributorId":360357,"corporation":false,"usgs":false,"family":"Gephart","given":"Jessica","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":946991,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kleisner, Kristin M.","contributorId":360360,"corporation":false,"usgs":false,"family":"Kleisner","given":"Kristin","middleInitial":"M.","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":946992,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rice, Emma D.","contributorId":360362,"corporation":false,"usgs":false,"family":"Rice","given":"Emma","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946993,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robinson, Kelly Filer 0000-0001-8109-9492","orcid":"https://orcid.org/0000-0001-8109-9492","contributorId":340631,"corporation":false,"usgs":true,"family":"Robinson","given":"Kelly","email":"","middleInitial":"Filer","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946994,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Virdin, John","contributorId":360366,"corporation":false,"usgs":false,"family":"Virdin","given":"John","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":946995,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70270414,"text":"70270414 - 2025 - Blueprints for riverine cod nest boxes draw from multiple design considerations","interactions":[],"lastModifiedDate":"2025-08-19T14:30:10.508448","indexId":"70270414","displayToPublicDate":"2025-07-15T09:29:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12812,"text":"Aquaculture, Fish and Fisheries","onlineIssn":"2693-8847","active":true,"publicationSubtype":{"id":10}},"title":"Blueprints for riverine cod nest boxes draw from multiple design considerations","docAbstract":"Designing aquatic nest boxes is rarely afforded detailed scientific account. Here we provide some historical context for nest boxes used in production of large-bodied fishes of the Australian freshwater cod genus Maccullochella. Our experience with eastern freshwater cod is used as a case study to: (a) convey aspects of the complexity of the nest box design process and to (b) demonstrate the importance of visual literacy in project communication across the variety of contributors to the eco-design process. Specifically, we describe a new, two-variant, triangular nest box design for application in rivers and modifications to a standard stainless steel nest box for hatchery-pond-based spawning of eastern freshwater cod M. ikei. We designed the boxes to test adult preference for single versus double entrance/exits to cavities in hatchery and field environments. An important consideration specific to hatchery production is harvesting demersal, adhesive eggs prior to hatching to minimise fungal infection of eggs and physical loss of larvae, in addition to providing critical first feeding of larvae. In contrast, field nest box design incorporated multiple factors and associated trade-offs related to both internal and external design, ranging from manufacturer capability, material types, cost, transportability, hydrological performance, biodegradability, retrievability, as well as biological and ecological function. Only preliminary findings from field nest box deployments are provided here, and we focus primarily on elements of visual language in the form of conceptual drawings, sketches and final schematics which have been central to our process. We emphasise the benefit of harnessing input from multiple fields of expertise and documenting and testing designs of nest boxes for cavity nesting fishes, under both controlled hatchery and more complex field conditions.
","language":"English","publisher":"Wiley","doi":"10.1002/aff2.70095","usgsCitation":"Ebner, B.C., Morris, S.S., St Vincent Welch, J., Ryan, P.C., Turner, M., Cameron, L.M., Poitras, N., Coonrod, B., Welsh, S.A., McLellan, M., Jess, L., Vidler, S., Ingram, B.A., Thurstan, S., Rowland, S.J., Blake, S., and Butler, G.L., 2025, Blueprints for riverine cod nest boxes draw from multiple design considerations: Aquaculture, Fish and Fisheries, v. 5, no. 4, e70095, 13 p., https://doi.org/10.1002/aff2.70095.","productDescription":"e70095, 13 p.","ipdsId":"IP-166252","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aff2.70095","text":"Publisher Index Page"},{"id":494307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ebner, Brendan C.","contributorId":359871,"corporation":false,"usgs":false,"family":"Ebner","given":"Brendan","middleInitial":"C.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Shaun S.","contributorId":359872,"corporation":false,"usgs":false,"family":"Morris","given":"Shaun","middleInitial":"S.","affiliations":[{"id":85930,"text":"North Coast Local Land Services","active":true,"usgs":false}],"preferred":false,"id":946362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"St Vincent Welch, John","contributorId":359873,"corporation":false,"usgs":false,"family":"St Vincent Welch","given":"John","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Paul C.","contributorId":359874,"corporation":false,"usgs":false,"family":"Ryan","given":"Paul","middleInitial":"C.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turner, Mitch","contributorId":359875,"corporation":false,"usgs":false,"family":"Turner","given":"Mitch","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional 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Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946368,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":946369,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McLellan, Matthew","contributorId":359879,"corporation":false,"usgs":false,"family":"McLellan","given":"Matthew","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946370,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jess, Lachie","contributorId":359880,"corporation":false,"usgs":false,"family":"Jess","given":"Lachie","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946371,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vidler, Stephen","contributorId":359881,"corporation":false,"usgs":false,"family":"Vidler","given":"Stephen","affiliations":[{"id":85931,"text":"Victorian Fisheries Authority","active":true,"usgs":false}],"preferred":false,"id":946372,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ingram, Brett A.","contributorId":359882,"corporation":false,"usgs":false,"family":"Ingram","given":"Brett","middleInitial":"A.","affiliations":[{"id":85931,"text":"Victorian Fisheries Authority","active":true,"usgs":false}],"preferred":false,"id":946373,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurstan, S.","contributorId":359883,"corporation":false,"usgs":false,"family":"Thurstan","given":"S.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946374,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rowland, S. J.","contributorId":359884,"corporation":false,"usgs":false,"family":"Rowland","given":"S.","middleInitial":"J.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946375,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Blake, S.","contributorId":359885,"corporation":false,"usgs":false,"family":"Blake","given":"S.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946376,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Butler, G. L.","contributorId":359886,"corporation":false,"usgs":false,"family":"Butler","given":"G.","middleInitial":"L.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946377,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70269228,"text":"70269228 - 2025 - Evaluation of rapid DNA extraction methods to better enable point-of-use environmental DNA detection","interactions":[],"lastModifiedDate":"2025-07-17T14:21:33.35311","indexId":"70269228","displayToPublicDate":"2025-07-15T09:18:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of rapid DNA extraction methods to better enable point-of-use environmental DNA detection","docAbstract":"Recent developments in molecular testing have created the opportunity for biologists and managers to detect environmental DNA (eDNA) of target species rapidly and without the requirement of a laboratory. These point-of-use protocols may be especially useful for early detection and rapid response for invasive species or surveillance for at-risk native species, where timely management decisions are critical. Point-of-use eDNA protocols also facilitate wider and less expensive implementation of eDNA methods. One of the key components to an effective point-of-use protocol is a rapid DNA extraction method. Several rapid extraction protocols are suitable for implementation in the field, but information regarding their relative effectiveness is lacking. We evaluated extraction efficiency of four DNA rapid extraction protocols using filters spiked with primary cultured grass carp (Ctenopharyngodon idella) gill cells. The extraction methods included two syringe-based column extractions, a lysis and extraction solution, and a divalent cation chelation resin (Chelex) extraction protocol alongside a laboratory-based control kit. We estimated DNA yield using a newly designed quantitative polymerase chain reaction (qPCR) assay targeting the grass carp nuclear genome. We evaluated two additional factors, filter type (mixed cellulose ester [MCE] and polyethersulfone [PES]) and background eDNA source (aquaculture or river). The lysis and extraction solution and Chelex extraction both had the highest overall yield, with MCE filters further increasing Chelex yield while the enzyme extraction yield was dependent on interaction with both filter and eDNA source. Our results indicate that rapid extraction protocols, such as solutions with short heating steps, are effective for DNA isolation and help to increase the overall accessibility of eDNA analyses.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.70159","usgsCitation":"Kozaczek, M., Spear, S.F., Untiedt, T., Albosta, P., Jungbluth, C., Homola, J.J., Barnhart, E.P., and Merkes, C.M., 2025, Evaluation of rapid DNA extraction methods to better enable point-of-use environmental DNA detection: Environmental DNA, v. 7, no. 4, e70159, 11 p., https://doi.org/10.1002/edn3.70159.","productDescription":"e70159, 11 p.","ipdsId":"IP-171289","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":492509,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.70159","text":"Publisher Index Page"},{"id":492416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozaczek, Melisa E. 0009-0001-9159-2739","orcid":"https://orcid.org/0009-0001-9159-2739","contributorId":358215,"corporation":false,"usgs":false,"family":"Kozaczek","given":"Melisa E.","affiliations":[{"id":81824,"text":"Contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":943247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spear, Stephen Frank 0000-0001-8351-9382","orcid":"https://orcid.org/0000-0001-8351-9382","contributorId":293162,"corporation":false,"usgs":true,"family":"Spear","given":"Stephen","email":"","middleInitial":"Frank","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943248,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Untiedt, Tyler J. 0009-0003-9366-2627","orcid":"https://orcid.org/0009-0003-9366-2627","contributorId":358216,"corporation":false,"usgs":false,"family":"Untiedt","given":"Tyler J.","affiliations":[{"id":81824,"text":"Contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":943249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albosta, Paul","contributorId":342642,"corporation":false,"usgs":false,"family":"Albosta","given":"Paul","email":"","affiliations":[{"id":81904,"text":"University of Wisconsin – Stevens Point,","active":true,"usgs":false}],"preferred":false,"id":943250,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jungbluth, Caden","contributorId":358218,"corporation":false,"usgs":false,"family":"Jungbluth","given":"Caden","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":943251,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Homola, Jared J.","contributorId":264547,"corporation":false,"usgs":false,"family":"Homola","given":"Jared","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":943252,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":943253,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":943254,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269490,"text":"70269490 - 2025 - Grand Canyon landslide-dam and paleolake triggered by the Meteor Crater impact at 56 ka","interactions":[],"lastModifiedDate":"2025-11-18T17:01:10.597342","indexId":"70269490","displayToPublicDate":"2025-07-15T09:03:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Grand Canyon landslide-dam and paleolake triggered by the Meteor Crater impact at 56 ka","docAbstract":"This paper hypothesizes that the Meteor Crater impact in Arizona, USA, 56,000 years ago triggered landslides in Grand Canyon that dammed the Colorado River and formed Nankoweap paleolake. This is compatible with shock and earthquake physics for the impact that infer a M5.4 seismic event, attenuated to an effective magnitude of M3.5 at Grand Canyon. Results that support the hypothesis include radiocarbon dating of driftwood and luminescence dating of associated slack-water lake sediments that are preserved in caves up to 60 m above the modern Colorado River. Radiocarbon ages from two locations, including Stanton’s Cave, date the driftwood as 55.25 ± 2.44 ka (n = 4). Sediments associated with the driftwood gave a luminescence age of 56.00 ± 6.39 ka (n = 2). These six Grand Canyon dates, and three published ages for the Meteor Crater impact, show statistically indistinguishable results that support the hypothesis for a geologically instantaneous series of events with a mean age of 55.60 ± 1.30 ka. This work highlights the value of radiocarbon dating near the limits of the technique, integration of multiple dating methods, and seismic and landslide hazards associated with meteorite impacts in regions of extreme topography like Grand Canyon.
Copper-based chemical treatments are commonly used to eradicate invasive mussels in small ponds and lakes, but their use in large rivers has been limited. In 2023, in response to a detection of invasive quagga mussels, a 10-km reach of the Snake River (Idaho, USA), was treated with an unprecedented 19,300 kg of chelated copper molluscicide to a target concentration of 1,000 µg/L for 10 days. We assessed the transport and fate of the copper and its exposure and effects on the nontarget benthic community downstream. Water samples were collected at seven locations throughout the treatment period, and sediment, periphyton, and benthic macroinvertebrates were collected pre- and posttreatment. Nearly half of the original mass of copper was removed from the water column via sedimentation, sorption to algae, or biological uptake within the 10-km treatment reach and the first 15 km downstream. Even so, dissolved copper concentrations exceeded the acute toxicity threshold at least as far as 28 km downstream for more than 2 weeks. Sediment copper increased by up to 8.3-fold, exceeding the consensus-based sediment quality threshold effect concentration at several sites. Effects on benthic macroinvertebrates varied by taxa. From 0–28 km downstream, invertebrate abundances decreased 52%–94%, with gastropods among the most affected. Of the unique taxa present at these sites pretreatment, 52%–64% were not found posttreatment but were replaced by other taxa, indicating a reorganization of the base of the food web. Additionally, from 0–15 km downstream, the percentage of individuals from tolerant taxa increased two to15-fold. Findings from this study can help watershed managers plan future invasive mussel responses while protecting culturally, economically, and ecologically important nontarget species in large rivers.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgaf119","usgsCitation":"Baldwin, A.K., Murray, E., Zinsser, L.M., King, T.V., Ducar, S.D., Southern, I., Thom, T., and Mebane, C.A., 2025, Fate and effects to the benthic community of a copper treatment to eradicate invasive mussels in a large western river, USA: Environmental Toxicology and Chemistry, v. 44, no. 8, p. 2166-2180, https://doi.org/10.1093/etojnl/vgaf119.","productDescription":"15 p.","startPage":"2166","endPage":"2180","ipdsId":"IP-173841","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":494190,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgaf119","text":"Publisher Index Page"},{"id":493934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.19538272232973,\n 43.32567469741488\n ],\n [\n -116.19538272232973,\n 42.22650789070423\n ],\n [\n -113.5905787354007,\n 42.22650789070423\n ],\n [\n -113.5905787354007,\n 43.32567469741488\n ],\n [\n -116.19538272232973,\n 43.32567469741488\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murray, Erin 0000-0002-5007-3449","orcid":"https://orcid.org/0000-0002-5007-3449","contributorId":205705,"corporation":false,"usgs":true,"family":"Murray","given":"Erin","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zinsser, Lauren M. 0000-0002-8582-066X","orcid":"https://orcid.org/0000-0002-8582-066X","contributorId":205756,"corporation":false,"usgs":true,"family":"Zinsser","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":292424,"corporation":false,"usgs":true,"family":"King","given":"Tyler","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ducar, Scott D. 0000-0003-0781-5598","orcid":"https://orcid.org/0000-0003-0781-5598","contributorId":297547,"corporation":false,"usgs":true,"family":"Ducar","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Southern, India","contributorId":359460,"corporation":false,"usgs":false,"family":"Southern","given":"India","affiliations":[{"id":6912,"text":"Idaho Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":945510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thom, Theresa","contributorId":224436,"corporation":false,"usgs":false,"family":"Thom","given":"Theresa","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":945511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":945512,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}