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.
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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{\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 26.065014230773016,\n 66.4956143647446\n ],\n [\n 21.838974021425116,\n 61.559558551218515\n ],\n [\n 35.445586179009155,\n 62.062182578354594\n ],\n [\n 33.9840528412233,\n 66.40839952587402\n ],\n [\n 26.065014230773016,\n 66.4956143647446\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2025","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Donatelli, A.","contributorId":358394,"corporation":false,"usgs":false,"family":"Donatelli","given":"A.","affiliations":[{"id":81866,"text":"University of Rome La Sapienza","active":true,"usgs":false}],"preferred":false,"id":943647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ćirović, D.","contributorId":358396,"corporation":false,"usgs":false,"family":"Ćirović","given":"D.","affiliations":[{"id":85615,"text":"University of Belgrade","active":true,"usgs":false}],"preferred":false,"id":943648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":943649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huber, Đuro","contributorId":358406,"corporation":false,"usgs":false,"family":"Huber","given":"Đuro","affiliations":[],"preferred":false,"id":943650,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kindberg, J.","contributorId":358397,"corporation":false,"usgs":false,"family":"Kindberg","given":"J.","affiliations":[{"id":33046,"text":"Norwegian Institute for Nature Research","active":true,"usgs":false}],"preferred":false,"id":943651,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kojola, I.","contributorId":358398,"corporation":false,"usgs":false,"family":"Kojola","given":"I.","affiliations":[{"id":40380,"text":"Natural Resources Institute Finland","active":true,"usgs":false}],"preferred":false,"id":943652,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kusak, J.","contributorId":358399,"corporation":false,"usgs":false,"family":"Kusak","given":"J.","affiliations":[{"id":63829,"text":"University of Zagreb","active":true,"usgs":false}],"preferred":false,"id":943653,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mastrantonio, G.","contributorId":358400,"corporation":false,"usgs":false,"family":"Mastrantonio","given":"G.","affiliations":[{"id":85617,"text":"Department of Mathematics","active":true,"usgs":false}],"preferred":false,"id":943654,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ordiz, A.","contributorId":358401,"corporation":false,"usgs":false,"family":"Ordiz","given":"A.","affiliations":[{"id":85618,"text":"Departamento de Biodiversidad y Gestión Ambiental","active":true,"usgs":false}],"preferred":false,"id":943655,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reljić, S.","contributorId":358402,"corporation":false,"usgs":false,"family":"Reljić","given":"S.","affiliations":[{"id":63829,"text":"University of Zagreb","active":true,"usgs":false}],"preferred":false,"id":943656,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Santini, L.","contributorId":358403,"corporation":false,"usgs":false,"family":"Santini","given":"L.","affiliations":[{"id":81866,"text":"University of Rome La 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. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldsmith, Avi","contributorId":358927,"corporation":false,"usgs":false,"family":"Goldsmith","given":"Avi","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":944491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hidalgo, C. 0009-0007-2566-5198","orcid":"https://orcid.org/0009-0007-2566-5198","contributorId":358928,"corporation":false,"usgs":false,"family":"Hidalgo","given":"C.","affiliations":[{"id":13595,"text":"NCSU","active":true,"usgs":false}],"preferred":false,"id":944492,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reberg-Horton, C. 0000-0001-5002-106X","orcid":"https://orcid.org/0000-0001-5002-106X","contributorId":358929,"corporation":false,"usgs":false,"family":"Reberg-Horton","given":"C.","affiliations":[{"id":85719,"text":"NSCU","active":true,"usgs":false}],"preferred":false,"id":944493,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mirsky, S.B.","contributorId":357633,"corporation":false,"usgs":false,"family":"Mirsky","given":"S.B.","affiliations":[{"id":62785,"text":"USDA-ARS Sustainable Agricultural Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":944494,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70269608,"text":"70269608 - 2025 - New insights into gas-driven phase segregation in andesitic enclaves from Mt. 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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Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":949634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Cory C. 0000-0002-8804-4248","orcid":"https://orcid.org/0000-0002-8804-4248","contributorId":353556,"corporation":false,"usgs":false,"family":"Cleveland","given":"Cory C.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":949635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Menge, Duncan 0000-0003-4736-9844","orcid":"https://orcid.org/0000-0003-4736-9844","contributorId":241126,"corporation":false,"usgs":false,"family":"Menge","given":"Duncan","email":"","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":949636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 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0000-0002-8819-6786","orcid":"https://orcid.org/0000-0002-8819-6786","contributorId":353572,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher A.","affiliations":[{"id":24788,"text":"Clark University","active":true,"usgs":false}],"preferred":false,"id":949655,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wurzburger, Nina","contributorId":299676,"corporation":false,"usgs":false,"family":"Wurzburger","given":"Nina","email":"","affiliations":[{"id":27235,"text":"U Georgia","active":true,"usgs":false}],"preferred":false,"id":949656,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70273007,"text":"70273007 - 2025 - Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey 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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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.
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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 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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 Development","active":true,"usgs":false}],"preferred":false,"id":946365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cameron, Leo M.","contributorId":359876,"corporation":false,"usgs":false,"family":"Cameron","given":"Leo","middleInitial":"M.","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946366,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poitras, Natalie","contributorId":359877,"corporation":false,"usgs":false,"family":"Poitras","given":"Natalie","affiliations":[{"id":85927,"text":"New South Wales Department of Primary Industries and Regional Development","active":true,"usgs":false}],"preferred":false,"id":946367,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coonrod, Brooke","contributorId":359878,"corporation":false,"usgs":false,"family":"Coonrod","given":"Brooke","affiliations":[{"id":85927,"text":"New South Wales 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":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.
The geographic information system (GIS) community in Vermont has a long history of interdisciplinary and cooperative projects that have facilitated the leveraging of geospatial technology on myriad data acquisitions across the State. High-resolution elevation data are proving to be a resource of great economic value in dealing with many important issues in Vermont. Vermont attained statewide coverage of quality level 2 coverage of topographic light detection and ranging (lidar) data in 2019. Having access to elevation data that are exponentially more accurate than what was previously available is enabling GIS professionals to better support and empower decision makers in economically important efforts such as environmental protection, public safety, watershed management and water quality, geology, transportation planning, forest and wildlife management, local planning, and flood plain management. In addition, developing a consistent and seamless statewide topographic framework supplants the traditionally time consuming and costly approach of extensive field data collection by requiring less time and money, therefore adding economic benefits. Critical applications that meet the State’s management needs depend on lidar data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Vermont. The status of available and in-progress 3DEP baseline lidar data in Vermont is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $1.64 million in new benefits annually to the State. The top eight Vermont business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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\"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Somatic growth rate is a fundamental trait that influences metabolism, lifespan and reproductive maturity and is critical for understanding population dynamics and informing management actions. Brown Treesnakes (Boiga irregularis) introduced to Guam are highly invasive and can reproduce year-round without discrete cohorts. We compared snake size trajectories described by the conventionally used von Bertalanffy growth function versus the Gompertz model. Using quantile regression with a regularized effect for individual snakes we modeled growth rates of 270 marked, wild snakes as a function of size. The Gompertz model explained more of the variation in growth and rendered more realistic predictions of asymptotic sizes than did the von Bertalanffy model. With the Gompertz model, growth rates were 1.05–1.16× faster in males than in females. Females reached asymptotic sizes at shorter snout-vent lengths than males. Growth rate was positively correlated with amount of precipitation, and modeling wet-dry seasonality on Guam as a sinusoidal function identified a growth peak in September—October. Effects of seasonality and precipitation, however, were minor compared to individual and sex related differences in size-adjusted growth rates. We estimated that the 50th (and 5th, 95th) growth-rate percentile males in our study population become sexually mature at an age of 33 (∞, 15) months, while females mature at 41 (∞, 18) months, where ∞ indicates that the slowest growing snakes never reach maturity. However, 50% of the snakes mature at a size below the median, and age at maturity may be as low as 10.4 (males) and 13.7 (females) months for average-sized hatchlings that grow fast. Our results have implications for the timing of management options for this species and our approach can be broadly applied to animals where repeated growth data are obtained and age is unknown.
","language":"English","doi":"10.1002/ece3.71695","usgsCitation":"Lardner, B., Cade, B.S., Savidge, J.A., Rodda, G.H., Reed, R., and Yackel Adams, A.A., 2025, Growth rate variation in Brown Treesnakes (Boiga irregularis): An invasive species of conservation concern: Ecology and Evolution, v. 15, no. 7, e71695, 13 p., https://doi.org/10.1002/ece3.71695.","productDescription":"e71695, 13 p.","ipdsId":"IP-129633","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":492872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71695","text":"Publisher Index Page"},{"id":492628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.97370767089484,\n 13.602893910874045\n ],\n [\n 144.85437262594462,\n 13.66982861291649\n ],\n [\n 144.74819953448088,\n 13.502237780603025\n ],\n [\n 144.60561170503658,\n 13.462933343165659\n ],\n [\n 144.6200898538703,\n 13.238449316687053\n ],\n [\n 144.76311641509852,\n 13.23674118706542\n ],\n [\n 144.7977762259491,\n 13.410418069709003\n ],\n [\n 144.9383897623706,\n 13.516040821003134\n ],\n [\n 144.97370767089484,\n 13.602893910874045\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Lardner, Bjorn","contributorId":225066,"corporation":false,"usgs":false,"family":"Lardner","given":"Bjorn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":943626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":943627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Savidge, Julie A.","contributorId":175196,"corporation":false,"usgs":false,"family":"Savidge","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":943628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodda, Gordon H. 0000-0002-6696-7308 roddag@usgs.gov","orcid":"https://orcid.org/0000-0002-6696-7308","contributorId":210066,"corporation":false,"usgs":true,"family":"Rodda","given":"Gordon","email":"roddag@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":943629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":943630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":943631,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269427,"text":"70269427 - 2025 - Factors affecting short-term post-release survival probability of Lake Trout implanted with acoustic telemetry transmitters","interactions":[],"lastModifiedDate":"2025-07-22T14:19:41.956026","indexId":"70269427","displayToPublicDate":"2025-07-11T09:14:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting short-term post-release survival probability of Lake Trout implanted with acoustic telemetry transmitters","docAbstract":"The use of acoustic telemetry is steadily expanding to help answer questions related to habitat use, movement, and behavior of fishes. Significant time and resources are invested to start acoustic telemetry studies; therefore, careful planning is needed to limit post-release mortality of tagged individuals. Deep, cold-water species present additional challenges to acoustic tagging because of changes in temperature and pressure experienced during capture. The objective of our study was to determine if capture method, surface water temperature, water depth, or fish size influenced short-term post-release survival of a deep, cold-water species, Lake Trout Salvelinus namaycush. In 2023, 299 Lake Trout were captured with angling or gillnets across Lake Ontario (Laurentian Great Lake – U.S. & CAN) and surgically implanted with acoustic transmitters. We estimated 30-day post-release mortality and 24-h post-release distance traveled for tagged Lake Trout. We used Cox proportional hazards models to identify factors affecting survival probability and multiple linear regression to identify factors affecting post-release distance traveled. Thirty-day post-release mortality was minimal (9.03 %, 27/299 Lake Trout); however, mortality was 6.37 times more likely for Lake Trout captured in gillnets compare to angling (p = 0.003). Lake Trout length had a marginally significant effect on mortality (p = 0.052) but capture depth and temperature did not (p > 0.05). Lake Trout post-release distance traveled was not significantly influenced by capture gear, depth, temperature, or Lake Trout length (p = 0.61). Our results indicate that tagging-induced post-release mortality is minimal for Lake Trout tagged in the spring, but survival can be increased by avoiding use of gillnets.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107457","usgsCitation":"Gatch, A.J., Gorsky, D., Morton, K., Johnson, J., Farrell, C., Johnson, T., Bloomfield, E., Metcalfe, B., Goretzke, J., Connerton, M., Larocque, S., Midwood, J., O’Malley, B., Weidel, B., Cooke, S., and Furgal, S., 2025, Factors affecting short-term post-release survival probability of Lake Trout implanted with acoustic telemetry transmitters: Fisheries Research, v. 288, 107457, 9 p., https://doi.org/10.1016/j.fishres.2025.107457.","productDescription":"107457, 9 p.","ipdsId":"IP-178757","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":492876,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2025.107457","text":"Publisher Index Page"},{"id":492793,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P19H76DM","text":"USGS data 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Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.
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to USGS ERSOS Center","active":true,"usgs":false}],"preferred":false,"id":942813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":942814,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":199093,"corporation":false,"usgs":false,"family":"Friedrichs","given":"MacKenzie","affiliations":[],"preferred":false,"id":942815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yi, 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and Geodetic Engineering, Ohio State University","active":true,"usgs":false}],"preferred":false,"id":942824,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nelson, Jacob A.","contributorId":349155,"corporation":false,"usgs":false,"family":"Nelson","given":"Jacob A.","affiliations":[{"id":83446,"text":"Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Germany","active":true,"usgs":false}],"preferred":false,"id":942825,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Reed, David E.","contributorId":349160,"corporation":false,"usgs":false,"family":"Reed","given":"David E.","affiliations":[{"id":83451,"text":"School of the Environment, Yale University, New Haven","active":true,"usgs":false}],"preferred":false,"id":942826,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Tianxin","contributorId":333378,"corporation":false,"usgs":false,"family":"Wang","given":"Tianxin","email":"","affiliations":[{"id":79858,"text":"Unversity of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":942827,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Xiao, Xiangming","contributorId":150759,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","affiliations":[{"id":18095,"text":"Center for Spatial Analysis, U of OK, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":942828,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70268928,"text":"70268928 - 2025 - Chapter three - Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data","interactions":[],"lastModifiedDate":"2025-08-04T15:58:00.492236","indexId":"70268928","displayToPublicDate":"2025-07-11T08:36:28","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Chapter three - Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data","docAbstract":"AActual evapotranspiration (ETa) is an essential climate variable that can be used for drought monitoring and water availability assessment because of its close connection with vegetation, soil moisture, and the water cycle. An operational ETa using the Visible Infrared Imaging Radiometer Suite (VIIRS) and global weather datasets was developed through the Simplified Surface Energy Balance Model (SSEBop) model. An operational framework is established with the Famine Early Warning System Network (https://earlywarning.usgs.gov/fews) to generate and update global 1 km ETa at dekadal (∼10 day), monthly, and yearly time scales since February 2012. Modeled ETa at monthly and annual time scales was evaluated using 67 eddy covariance (EC) flux tower stations around the world and water balance-based ETa based on 810 United States eight-digit Hydrologic Unit Code (HUC8) and 18 Global Runoff Data Center (GRDC) basins. The correlation coefficient (r=0.68–0.94) shows relatively strong and consistent performance across the three datasets, capturing the spatiotemporal variability in HUC8 and GRDC basins and EC tower sites reliably. The bias (3%–15%) and root mean square error (RMSE: 13%–34%) showed relatively large errors and high variability among the three datasets. The evaluation results indicate the usefulness of the VIIRS ETa for drought monitoring and early warning applications without further adjustments, while bias-correction and calibration procedures may be required before using the VIIRS ETa data for localized water budget assessments. Availability of gridded actual ETa data from a combination of flux towers and basin-scale ETa is desired to establish bias-correction procedures to improve the absolute accuracy of remote-sensing ETa such as the SSEBop VIIRS operational products.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Evapotranspiration in agro-ecosystems and forestry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-443-21649-7.00004-3","usgsCitation":"Senay, G.B., Kagone, S., Khand, K., Parrish, G.E., Young, C., and Budde, M., 2025, Chapter three - Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data, chap. of Evapotranspiration in agro-ecosystems and forestry, p. 77-101, https://doi.org/10.1016/B978-0-443-21649-7.00004-3.","productDescription":"25 p.","startPage":"77","endPage":"101","ipdsId":"IP-175382","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":492123,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":942627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kagone, Stefanie 0000-0002-2979-4655","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":199091,"corporation":false,"usgs":false,"family":"Kagone","given":"Stefanie","affiliations":[],"preferred":false,"id":942628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khand, Kul Bikram 0000-0002-1593-1508","orcid":"https://orcid.org/0000-0002-1593-1508","contributorId":259185,"corporation":false,"usgs":false,"family":"Khand","given":"Kul Bikram","affiliations":[{"id":52326,"text":"AFDS, Contractor to USGS ERSOS Center","active":true,"usgs":false}],"preferred":false,"id":942629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parrish, Gabriel Edwin Lee 0000-0003-4078-3516","orcid":"https://orcid.org/0000-0003-4078-3516","contributorId":267751,"corporation":false,"usgs":false,"family":"Parrish","given":"Gabriel","email":"","middleInitial":"Edwin Lee","affiliations":[{"id":55490,"text":"Innovate! Inc., Contractor to the USGS EROS Center","active":true,"usgs":false}],"preferred":false,"id":942630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, Claudia 0000-0002-0859-7206","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":192646,"corporation":false,"usgs":false,"family":"Young","given":"Claudia","affiliations":[],"preferred":false,"id":942631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Budde, Michael 0000-0002-9098-2751 mbudde@usgs.gov","orcid":"https://orcid.org/0000-0002-9098-2751","contributorId":166756,"corporation":false,"usgs":true,"family":"Budde","given":"Michael","email":"mbudde@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":942632,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269347,"text":"70269347 - 2025 - ‘The fish that stop’: Drivers of historical decline for Pacific cod and implications for modern management in an era of rapidly changing climate","interactions":[],"lastModifiedDate":"2025-07-18T14:46:47.135868","indexId":"70269347","displayToPublicDate":"2025-07-10T09:42:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"‘The fish that stop’: Drivers of historical decline for Pacific cod and implications for modern management in an era of rapidly changing climate","docAbstract":"n the Gulf of Alaska, a series of marine heat waves depleted Pacific cod (Gadus macrocephalus) biomass to the lowest abundance ever recorded and led to the fishery’s closure in 2020. Although the fishery has been productive for decades, this collapse may have historical precedents. Traditional knowledge holders refer to cod as ‘the fish that stop’, and there is a suggested period of decline in the 1930s. Here we conduct a catch reconstruction of the early commercial fishery (1864–1950), confirming a rapid catch decline in the 1920s and 1930s. Next, we evaluate evidence for possible drivers. We document changes to demand and technology that contributed to declining catch. However, we also find both qualitative and quantitative evidence of depletion, suggesting catch declines were not driven entirely by social factors. Overfishing may have contributed to localized catch declines as evidenced by declining catch rates in heavily fished localities. We also find evidence for climate as a driver of regional decline, with the period of catch decline characterized by up to 2°C higher temperatures as compared to the earlier period of high fisheries production. Our analysis underscores the importance of understanding long-term drivers of fisheries productivity and the value of linking fisheries and climate histories.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rstb.2024.0278","usgsCitation":"McClenachan, L., Anderson, B., Addison, J.A., Barbeaux, S.J., Moore, K., Muir, K., Reedy, K., Spies, I.B., and West, C., 2025, ‘The fish that stop’: Drivers of historical decline for Pacific cod and implications for modern management in an era of rapidly changing climate: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 380, no. 1930, 20240278, 11 p., https://doi.org/10.1098/rstb.2024.0278.","productDescription":"20240278, 11 p.","ipdsId":"IP-168376","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":492865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2024.0278","text":"Publisher Index Page"},{"id":492537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -171.36734807808014,\n 60.34356991409652\n ],\n [\n -171.36734807808014,\n 49.72417629774134\n ],\n [\n -133.3953187776795,\n 49.72417629774134\n ],\n [\n -133.3953187776795,\n 60.34356991409652\n ],\n [\n -171.36734807808014,\n 60.34356991409652\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"380","issue":"1930","noUsgsAuthors":false,"publicationDate":"2025-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"McClenachan, Loren","contributorId":260606,"corporation":false,"usgs":false,"family":"McClenachan","given":"Loren","email":"","affiliations":[{"id":51887,"text":"Colby College","active":true,"usgs":false}],"preferred":false,"id":943491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Bruce T. 0000-0001-7006-5967","orcid":"https://orcid.org/0000-0001-7006-5967","contributorId":345835,"corporation":false,"usgs":false,"family":"Anderson","given":"Bruce T.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":943492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":943493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbeaux, Steven J.","contributorId":256680,"corporation":false,"usgs":false,"family":"Barbeaux","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":34572,"text":"NOAA, National Marine Fisheries Service, Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":943494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Karoline","contributorId":345836,"corporation":false,"usgs":false,"family":"Moore","given":"Karoline","affiliations":[{"id":82724,"text":"University of Victoria (Canada)","active":true,"usgs":false}],"preferred":false,"id":943495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muir, Kai","contributorId":345837,"corporation":false,"usgs":false,"family":"Muir","given":"Kai","affiliations":[{"id":82724,"text":"University of Victoria (Canada)","active":true,"usgs":false}],"preferred":false,"id":943496,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reedy, Katherine L.","contributorId":345838,"corporation":false,"usgs":false,"family":"Reedy","given":"Katherine L.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":943497,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spies, Ingrid B.","contributorId":256688,"corporation":false,"usgs":false,"family":"Spies","given":"Ingrid","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":943498,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"West, Catherine F. 0000-0001-5177-9235","orcid":"https://orcid.org/0000-0001-5177-9235","contributorId":345839,"corporation":false,"usgs":false,"family":"West","given":"Catherine F.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":943499,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70269643,"text":"70269643 - 2025 - Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae","interactions":[],"lastModifiedDate":"2025-09-22T15:54:20.408178","indexId":"70269643","displayToPublicDate":"2025-07-10T09:36:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9929,"text":"Limnology & Oceanography: Methods","active":true,"publicationSubtype":{"id":10}},"title":"Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae","docAbstract":"Measurements of chlorophyll concentration reported by fluorometers (fChl) are used in environmental research and monitoring, as inputs to models, and in the interpretation of remote sensing data. Researchers and managers benefit from understanding how to interpret and ensure the accuracy of fChl data collected by in situ fluorometers. Although fChl values produced by different manufacturers are often in agreement with discrete laboratory-derived Chlorophyll a (Chl a) concentration measurements, there are instances in which results significantly differ. Further, when measuring fChl side by side, different fluorometers may report values that differ significantly from each other, despite passing calibration checks prior to deployment. We compared environmental conditions and phytoplankton species composition associated with instances in which fChl measurements from three different fluorometers (EXO2 Total Algae Smart Sensor, YSI Inc./Xylem Inc., Yellow Springs, Ohio; FluoroProbe III, bbe Moldaenke GmbH, Kiel, Germany; WETStar, Sea-Bird Scientific, Bellevue, Washington) were significantly different from laboratory-derived Chl a concentrations. Results indicated that elevated primary productivity, as indicated by high pH, dissolved oxygen, and the ratio of Chl a to phaeophytin, were correlated with underestimated fChl values recorded by each sensor. After removing outliers, we determined unique correction guidance for each of the three sensors and demonstrated that after applying correction formulae, fChl measurements produced by each sensor became directly comparable.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lom3.10705","usgsCitation":"Richardson, E.T., Kraus, T.E., Sturgeon, C.L., O’Donnell, K., and Bergamaschi, B.A., 2025, Identifying conditions associated with outliers produced by three different chlorophyll fluorometers: A comparison of instrumentation and development of correction formulae: Limnology & Oceanography: Methods, v. 23, no. 9, p. 673-687, https://doi.org/10.1002/lom3.10705.","productDescription":"15 p.","startPage":"673","endPage":"687","ipdsId":"IP-168613","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":493096,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":493321,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lom3.10705","text":"Publisher Index Page"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.1569041318973,\n 38.781445775867496\n ],\n [\n -122.591638749212,\n 38.781445775867496\n ],\n [\n -122.41414092861007,\n 37.110093240321405\n ],\n [\n -121.1569041318973,\n 37.53901515220369\n ],\n [\n -121.1569041318973,\n 38.781445775867496\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturgeon, Crystal Lee 0000-0002-1799-9127","orcid":"https://orcid.org/0000-0002-1799-9127","contributorId":302710,"corporation":false,"usgs":true,"family":"Sturgeon","given":"Crystal","email":"","middleInitial":"Lee","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Katy 0000-0003-2323-8970 kodonnell@usgs.gov","orcid":"https://orcid.org/0000-0003-2323-8970","contributorId":5640,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Katy","email":"kodonnell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944257,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268887,"text":"tm5B13 - 2025 - Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution","interactions":[],"lastModifiedDate":"2026-02-03T14:25:36.603546","indexId":"tm5B13","displayToPublicDate":"2025-07-09T17:20:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"5-B13","displayTitle":"Determination of Per- and Polyfluoroalkyl Substances in Water by Direct Injection of Matrix-Modified Centrifuge Supernatant and Liquid Chromatography/Tandem Mass Spectrometry with Isotope Dilution","title":"Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution","docAbstract":"A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis.
Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]).
Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors.
Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm5B13","collaboration":"Strategic Laboratory Science Branch and National Water Quality Laboratory","usgsCitation":"Gray, J.L., Kanagy, L.K., Kanagy, C.J., and Anderson, C.A., 2025, Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution: U.S. Geological Survey Techniques and Methods, book 5, chap. B13, 121 p., https://doi.org/10.3133/tm5B13.","productDescription":"Report: xii, 121 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-144091","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":491919,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/05/b13/coverthb.jpg"},{"id":491984,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/05/b13/images"},{"id":491920,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/05/b13/tm5B13.pdf","text":"Report","size":"5.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 5-B13"},{"id":491921,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P3YPXG","text":"USGS data release","linkHelpText":"Concentrations of per- and polyfluoroalkyl substances (PFAS) from validation experiments and custom sample analysis by U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL) Laboratory Code 9660, December 2020 to March 2022"},{"id":491985,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/05/b13/tm5B13.xml"},{"id":492165,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm5B13/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"T and M 5-B13"}],"contact":"Chief, National Water Quality Laboratory
U.S. Geological Survey
Box 25046, Mail Stop 407
Denver, CO 80225-0585
Recent and ongoing collections of high-resolution elevation data in Louisiana are providing information that supports improved critical public safety modeling and enables the State to strengthen its efforts to fight the effects of land subsidence and sea-level rise. The availability of current and accurate three-dimensional (3D) elevation data supports numerous business activities, including flood risk management, infrastructure and construction management, coastal zone management, wildlife and habitat management, recreation, agriculture and precision farming, urban and regional planning, water supply and quality assessment, and natural resources conservation. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed 3D model of the Earth’s surface and aboveground features.
The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Louisiana. The status of available and in-progress 3DEP baseline lidar data in Louisiana is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $6.96 million in new benefits annually to the State. The top 10 Louisiana business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Beavers are ecosystem engineers and keystone species that protect freshwater resources and increase biodiversity. Beaver reintroductions are promoted for amphibian conservation, yet their impact on Batrachochytrium dendrobatidis (Bd), a pathogen linked with amphibian population declines worldwide, remains unclear. We investigated the abiotic and biotic drivers of Bd prevalence in Columbia spotted frogs (Rana luteiventris) and western toads (Anaxyrus boreas) in 20 beaver-modified and 23 non-beaver wetlands in Glacier National Park, USA. We found that beavers increased wetland hydroperiod, which was associated with higher Bd prevalence. However, beavers also reduced wetland canopy cover, which was associated with lower Bd prevalence. Our models also predicted higher Bd prevalence associated with higher adult density of both species of amphibians, although species’ densities were similar in beaver-modified and non-beaver wetlands. These results suggest that beavers have a cumulatively negligible net effect on Bd prevalence owing to their effects on both hydroperiod and canopy cover, which is encouraging for amphibian conservation. Our findings also suggest that decreasing canopy cover may be a potential management option to reduce Bd prevalence. In addition, these findings indicate that beaver-mimicking restoration projects may harm amphibian populations if they increase wetland hydroperiods without reducing canopy cover.
","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rsos.241169","usgsCitation":"Fischer, L.M., Luis, A.D., Hossack, B., McMahon, T.A., and Lowe, W.H., 2025, Ecosystem-engineered infections: Beaver-modified wetlands are associated with conflicting drivers of amphibian pathogen prevalence: Royal Society Open Science, v. 12, no. 7, 241169, 16 p., https://doi.org/10.1098/rsos.241169.","productDescription":"241169, 16 p.","ipdsId":"IP-159513","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":495745,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsos.241169","text":"Publisher Index Page"},{"id":495709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.86469041743416,\n 48.99734783362541\n ],\n [\n -113.86469041743416,\n 48.319004094254154\n ],\n [\n -113.210203320298,\n 48.319004094254154\n ],\n [\n -113.210203320298,\n 48.99734783362541\n ],\n [\n -113.86469041743416,\n 48.99734783362541\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Leah M","contributorId":361570,"corporation":false,"usgs":false,"family":"Fischer","given":"Leah","middleInitial":"M","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":948993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luis, Angela D","contributorId":361571,"corporation":false,"usgs":false,"family":"Luis","given":"Angela","middleInitial":"D","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":948994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":207343,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":948995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahon, Taegan A.","contributorId":361572,"corporation":false,"usgs":false,"family":"McMahon","given":"Taegan","middleInitial":"A.","affiliations":[{"id":78677,"text":"University of Tampa","active":true,"usgs":false}],"preferred":false,"id":948996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Winsor H","contributorId":361573,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","middleInitial":"H","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":948997,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269587,"text":"70269587 - 2025 - The breeding season and movement ecology of male white‐tailed deer in southwest Wisconsin","interactions":[],"lastModifiedDate":"2025-07-28T14:45:17.409277","indexId":"70269587","displayToPublicDate":"2025-07-09T09:38:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The breeding season and movement ecology of male white‐tailed deer in southwest Wisconsin","docAbstract":"White-tailed deer (Odocoileus virginianus; hereafter, deer) have been widely studied regarding their breeding ecology and responses to hunting pressures. However, variations in defining the breeding season—its duration and timing—across studies have created uncertainty about whether regional differences in deer breeding ecology stem from ecological factors or methodological inconsistencies. This study aims to clarify the peak breeding season timing and the movement patterns of males during this period, particularly in relation to hunting seasons. Understanding how age and the timing of hunting seasons impact movement and breeding behaviors is important for wildlife managers, as these factors can affect harvest success. This study took place in southwest Wisconsin, using GPS data collected from 188 collared male deer between 15 October and 1 December from 2017 to 2020. Based on generalized linear mixed models, 2-year-old males exhibited higher hourly movement rates than other ages, and the opening weekend of the firearm hunting season had no significant effect on movement rates. In contrast, the variance in daily movement rate differed significantly between yearlings and older ages, with males 3 years and older displaying the highest variance. This suggests that older males may alternate more frequently between high-movement mate searching and lower-movement mate tending, potentially enhancing reproductive success. Similarly, 2-year-old males had larger daily ranges than both older and younger ages. Changepoint analysis of daily movement rates determined that the peak breeding season occurred between 23 October and 12 November, with little variation among ages and alternative metrics. Our findings indicate that male movement rates and ranges can reflect deer reproductive efforts and vary by age, which has important implications for reproductive success and disease transmission risk.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71589","usgsCitation":"Hunsaker, M., Gilbertson, M., Storm, D., and Turner, W.C., 2025, The breeding season and movement ecology of male white‐tailed deer in southwest Wisconsin: Ecology and Evolution, v. 15, no. 7, e71589, 13 p., https://doi.org/10.1002/ece3.71589.","productDescription":"e71589, 13 p.","ipdsId":"IP-165270","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71589","text":"Publisher Index Page"},{"id":492997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.8,\n 43.25\n ],\n [\n -90.8,\n 42.95\n ],\n [\n -89.6,\n 42.95\n ],\n [\n -89.6,\n 43.25\n ],\n [\n -90.8,\n 43.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunsaker, Matthew","contributorId":358692,"corporation":false,"usgs":false,"family":"Hunsaker","given":"Matthew","affiliations":[{"id":83274,"text":"University of Wisconsin–Madison","active":true,"usgs":false}],"preferred":false,"id":944110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilbertson, Marie L.J.","contributorId":358694,"corporation":false,"usgs":false,"family":"Gilbertson","given":"Marie L.J.","affiliations":[{"id":83274,"text":"University of Wisconsin–Madison","active":true,"usgs":false}],"preferred":false,"id":944111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storm, Daniel J.","contributorId":358697,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel J.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":944112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":944113,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}