Disease, alone or combined with other stressors such as habitat loss and contaminants, affects wildlife populations worldwide. However, interactions among stressors and how they affect demography and populations remain poorly understood. The amphibian chytrid fungus (Batrachochytrium dendrobatidis; Bd) is a sometimes-lethal pathogen linked with population declines and extirpations of amphibians globally. Laboratory evidence shows ubiquitous contaminants like methylmercury (MeHg) can reduce vigor and survival of amphibians, but population-level effects remain unclear. We used non-lethal sampling to assess how Bd and MeHg affected survival of juvenile and adult amphibians in 20 populations across the USA. Survival of several species declined with increasing Bd loads, including some species previously considered resistant to Bd (e.g., eastern newt [Notophthalmus viridescens]). Although our sampling for MeHg was less intensive than for Bd, we found MeHg can both directly reduce survival and synergistically magnify the effects of Bd infection. For a population of foothill yellow-legged frogs (Rana boylii), the estimated reduction in survival from MeHg exceeded that from Bd. Although effects varied widely among populations and species, our results help clarify the potential for synergistic effects of disease and contaminants and emphasize the complexity of identifying and quantifying the population-level effects of interactions among stressors.
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Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River","interactions":[],"lastModifiedDate":"2025-08-21T15:24:33.358166","indexId":"70270600","displayToPublicDate":"2025-05-19T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Protected from Pterygoplichthys? Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River","docAbstract":"Objective
Nonnative fishes can modify ecosystems and harm economies when they are introduced to new environments. Climate change is likely to assist the spread and establishment of some nonnative fishes (e.g., warmwater species), but spatiotemporal gaps in water temperature monitoring and modeling may prevent ecologists and managers from forecasting thermal habitat suitability for these taxa. The purpose of this study was to develop a predictive model of winter water temperatures and thermal habitat suitability for two priority nonnative armored catfish, Vermiculated Sailfin Catfish Pterygoplichthys disjunctivus and Orinoco Sailfin Catfish P. multiradiatus, in the Suwannee River, Florida and Georgia.
Methods
Precipitation- and groundwater-corrected air–water temperature models were developed and evaluated using a model selection procedure to predict water temperatures at four sites in the Suwannee River. These models were chosen because they blend the simplicity of air–water temperature models with the accuracy of hydrometeorological models to create an efficient, economical, management-relevant approach for analyzing and forecasting water temperature.
Results
Most of the top-performing water temperature models (92%) had precipitation or groundwater corrections to air–water temperature formulations. Projected mean and maximum water temperatures increased as simulated climate change intensified. All four Suwannee River sites studied were projected to be thermally hospitable to the survival of Vermiculated Sailfin Catfish. Lower river sites, noticeably warmer than upper river sites, were conducive to the survival of Orinoco Sailfin Catfish throughout the winter months. The upper river sites were too cold for Orinoco Sailfin Catfish survival in some climate-change scenarios, but the Suwannee River has an abundance of constant-temperature springs that are likely hospitable to Vermiculated Sailfin Catfish and Orinoco Sailfin Catfish throughout the year.
Conclusions
The findings suggest that winter water temperatures will likely not be a barrier to the survival of Pterygoplichthys catfish in the Suwannee River, amplifying the importance of conservation and management approaches to inhibit their spread and establishment. If the Pterygoplichthys population remains small and isolated and decision makers are able to devote required staff time and resources to managing these species, removal and eradication at local if not broader scales may be reasonable goals. This study provides a water temperature modeling approach that can aid ecologists and managers in prioritizing sites to prevent the introduction, slow the dispersal, eradicate, and control Pterygoplichthys catfish and other nonnative fishes in the Suwannee River and beyond.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnaf018","usgsCitation":"Carlson, A.K., 2025, Protected from Pterygoplichthys? Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River: Transactions of the American Fisheries Society, v. 154, no. 4, p. 398-413, https://doi.org/10.1093/tafafs/vnaf018.","productDescription":"16 p.","startPage":"398","endPage":"413","ipdsId":"IP-171826","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/tafafs/vnaf018","text":"Publisher Index Page"},{"id":494386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","otherGeospatial":"Suwannee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.76698997402998,\n 31.112972868570907\n ],\n [\n -83.18475784303796,\n 30.177311490235\n ],\n [\n -83.16967351009271,\n 29.211264445611363\n ],\n [\n -82.78703329930818,\n 29.017838843725343\n ],\n [\n -82.37936790717382,\n 30.074113688375725\n ],\n [\n -82.26360657954834,\n 31.112972868570907\n ],\n [\n -82.76698997402998,\n 31.112972868570907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"154","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946650,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70269986,"text":"70269986 - 2025 - Predator-induced injury of a neonatal pronghorn cues abandonment of current reproductive investment","interactions":[],"lastModifiedDate":"2025-08-07T15:29:06.180863","indexId":"70269986","displayToPublicDate":"2025-05-18T10:20:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predator-induced injury of a neonatal pronghorn cues abandonment of current reproductive investment","docAbstract":"Evolutionary theory predicts that parental care is favored when the fitness benefits outweigh the costs of providing care (Klug et al., 2012). In mammals, parental care is generally provided by females, who provide nourishment through lactation, protection from predators, aid in juvenile movement, or otherwise facilitate offspring survival (Balshine, 2012; Lent, 1974). However, in capital breeding species that rely on stored energy reserves for reproduction, increased investment can reduce the female's body condition and the number of offspring produced in subsequent years (Balme et al., 2017; Cook et al., 2013; Stephens et al., 2009). Unlike income breeders, which produce offspring from concurrent energy uptake, capital breeders deplete energy stores during reproduction, and lactation hinders the recovery of these stores (Clutton-Brock et al., 1983; Cook et al., 2013; Stephens et al., 2009). Consequently, iteroparous mammals face a trade-off between investing in current offspring and investing in maintenance or future offspring (Hamel et al., 2010; Stearns, 1989; Williams, 1966).
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.70111","usgsCitation":"Dart, M.M., Turnley, M.T., Rickels, C.M., Tanner, E.P., Colter Chitwood, M., DeYoung, R.W., Fairbanks, W.S., Hahn, D.P., Heffelfinger, L.J., Lonsinger, R.C., Wang, H.G., and Cherry, M.J., 2025, Predator-induced injury of a neonatal pronghorn cues abandonment of current reproductive investment: Ecology, v. 106, no. 5, e70111, 6 p., https://doi.org/10.1002/ecy.70111.","productDescription":"e70111, 6 p.","ipdsId":"IP-171928","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Dart, Marlin M.","contributorId":359315,"corporation":false,"usgs":false,"family":"Dart","given":"Marlin","middleInitial":"M.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turnley, Matthew T.","contributorId":359316,"corporation":false,"usgs":false,"family":"Turnley","given":"Matthew","middleInitial":"T.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":945142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rickels, Celine M.J.","contributorId":359317,"corporation":false,"usgs":false,"family":"Rickels","given":"Celine","middleInitial":"M.J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tanner, Evan P.","contributorId":359318,"corporation":false,"usgs":false,"family":"Tanner","given":"Evan","middleInitial":"P.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colter Chitwood, M.","contributorId":359319,"corporation":false,"usgs":false,"family":"Colter Chitwood","given":"M.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":945145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeYoung, Randy W.","contributorId":359322,"corporation":false,"usgs":false,"family":"DeYoung","given":"Randy","middleInitial":"W.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945146,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fairbanks, W. Sue","contributorId":359325,"corporation":false,"usgs":false,"family":"Fairbanks","given":"W.","middleInitial":"Sue","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":945147,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hahn, Derek P.","contributorId":359328,"corporation":false,"usgs":false,"family":"Hahn","given":"Derek","middleInitial":"P.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":945148,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Heffelfinger, Levi J.","contributorId":359331,"corporation":false,"usgs":false,"family":"Heffelfinger","given":"Levi","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945149,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":945150,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wang, H. George","contributorId":359338,"corporation":false,"usgs":false,"family":"Wang","given":"H.","middleInitial":"George","affiliations":[{"id":85772,"text":"East Central University","active":true,"usgs":false}],"preferred":false,"id":945151,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Cherry, Michael J.","contributorId":359341,"corporation":false,"usgs":false,"family":"Cherry","given":"Michael","middleInitial":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":945152,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70267371,"text":"70267371 - 2025 - A review of standardization in Mississippi’s multidecadal inland fisheries monitoring program","interactions":[],"lastModifiedDate":"2025-05-21T14:29:44.778022","indexId":"70267371","displayToPublicDate":"2025-05-18T09:27:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"A review of standardization in Mississippi’s multidecadal inland fisheries monitoring program","docAbstract":"Standardizing data collection, management, and analysis processes can improve the reliability and efficiency of fisheries monitoring programs, yet few studies have examined the operationalization of these tasks within agency settings. We reviewed the Mississippi Department of Wildlife, Fisheries, and Parks, Fisheries Bureau’s inland recreational fisheries monitoring program—a 30+-year effort to standardize field protocols, data handling procedures, and automated analyses through a custom-built computer application, the Fisheries Resources Analysis System (FRAS). Drawing on quantitative summaries of sampling trends and qualitative interviews with fisheries managers, we identified key benefits, challenges, and opportunities associated with the Bureau’s standardization efforts. Standardized procedures improved sampling consistency, data reliability, and operational efficiency, enabling the long-term tracking of fish population and angler metrics across more than 270 managed waterbodies. However, challenges related to analytical transparency and spatiotemporal comparisons persist. Simulations indicated that under current conditions, 5.8, 22.9, and 37.1 years would be required to sample (boat electrofishing) 50%, 75%, and 95% of the Bureau’s waterbodies at least once, respectively; these figures should translate to other agencies, assuming similar resource availability per waterbody. The monitoring program has reduced manual processing effort and enhanced staff capacity for waterbody-specific management, yet several opportunities remain to improve efficiency and utility. These include expanding FRAS functionalities for trend visualization, integrating mobile field data entry to reduce transcription errors, linking monitoring results with management objectives, and enhancing automated report generation for management support. Strengthening these elements could not only streamline workflows but better position agencies to apply standardized data in adaptive management embedded into the monitoring program.
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geophysics, and temperature for groundwater TDS in the San Ardo Oil Field, California, USA","interactions":[],"lastModifiedDate":"2025-05-28T14:15:05.548599","indexId":"70267512","displayToPublicDate":"2025-05-18T09:08:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A joint Gaussian process model of geochemistry, geophysics, and temperature for groundwater TDS in the San Ardo Oil Field, California, USA","docAbstract":"Although prevalent for the late Holocene, relative sea level (RSL) constraints during and immediately after the Last Glacial Maximum (LGM) are sparse. This scarcity of data is particularly pronounced along mid-latitude shelves such as central California, which lack post LGM RSL constraints older than 12 ka. In this study we collected 7 sediment cores and high-resolution seismic data from Estero Bay to constrain RSLs across the central California shelf between ∼9 and ∼16 ka. We reconstructed these RSLs using two sea-level indicators found within our sediment cores: the wave ravinement shell hash burial surface (WRSHBS) and the sedimentary contact between offshore mud facies and ripple cross-laminated sands. To determine the indicative meaning of these two sea-level indicators, we examined the relationship between the local wave regime, modern bathymetric profiles, and the depth of preservation of each sea-level indicator. After correcting for tectonic uplift, we estimated sea levels in central California to have been ∼39 ± 7.5 and 49 ± 7.5 m below present sea level between 9 and 12 ka, in agreement with previous RSL reconstructions along this coast. Between 13.8 and 15.9 ka, we estimate sea levels to have reached ∼86 ± 8–99 ± 8 m below present sea level. Our findings offer a Late Pleistocene RSL reconstruction for central California and develop new methodologies for estimating past RSLs on similar mid-latitude shelves.
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Gary","contributorId":357461,"corporation":false,"usgs":false,"family":"Greene","given":"H. 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Dozens of organizations from government agencies, nonprofits, and Tribal Nations have developed projects and monitoring programs to analyze and protect the water resources of the watershed and sound. The abundance of data and lack of an existing searchable index require a centralized metadata repository to allow users to find water resources data more efficiently. 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U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
The Long Island Sound watershed is home to nearly 9 million people in parts of Connecticut, Massachusetts, New Hampshire, New York, Rhode Island, Vermont, and Canada. Government agencies, nonprofits, and Tribal Nations have overseen numerous projects to monitor and protect the water resources of this watershed and the sound. Although there is an abundance of data, there is no easy way to search them or a central place to manage this information. To help, the U.S. Geological Survey, the U.S. Environmental Protection Agency, and the Long Island Sound Study have created an interactive map to help users find and understand data about the water resources of the Long Island Sound and its watershed.
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U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
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Email: 3DEP@usgs.gov
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U.S. Geological Survey
601 SW Second Avenue, Suite 1950
Portland, Oregon 97204
The terrestrial management plan for Palmyra Atoll includes large-scale removal of coconut (Cocos nucifera) as part of native forest restoration and contaminant remediation that will leave soils and vegetation communities profoundly altered. To inform those efforts and provide baseline data for restoration monitoring, woody stem crowns and vegetation communities at Palmyra Atoll were mapped using existing datasets and manual photointerpretation of high-resolution aerial imagery collected using uncrewed aerial systems. Coconut palm, grand devil's claws (Pisonia grandis), and numerous other species were delineated as either individual crowns, crown portions, or species patches. The extent of land area at high tide was also delineated based on vegetation patterns, topographic indicators, and deposition lines of vegetation litter and flotsam. Finally, in a novel “bottom-up” approach to vegetation community mapping, crown maps were used to delineate U.S. National Vegetation Classification System vegetation communities and other management areas. Of the more than 44,000 mapped crowns, coconut was by far the most abundant species, comprising nearly half of the mapped stems. By establishing a quantitative baseline for current habitat conditions, this project facilitates the integration of contaminant remediation recovery activities with habitat restoration planning, implementation, and monitoring at Palmyra Atoll. Results illustrate the appropriateness of the mapping approach for plant species-level censuses and cover estimation over relatively small areas to aid in inventory and monitoring and to facilitate management planning. The relatively simple mapping methods used in this study are appropriate for resource managers with limited human and computational resources to support automated mapping.
","language":"English","publisher":"University of Hawaii Press","doi":"10.2984/78.3.4","usgsCitation":"Struckhoff, M., 2025, Pre-restoration woody species crown and vegetation community mapping using high-resolution uncrewed aerial system imagery, Palmyra Atoll: Pacific Science, v. 78, no. 3, p. 279-293, https://doi.org/10.2984/78.3.4.","productDescription":"15 p.","startPage":"279","endPage":"293","ipdsId":"IP-167800","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":486215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Palmyra Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -162.11964162708554,\n 5.904086042937834\n ],\n [\n -162.11964162708554,\n 5.857794667611088\n ],\n [\n -162.03636083136453,\n 5.857794667611088\n ],\n [\n -162.03636083136453,\n 5.904086042937834\n ],\n [\n -162.11964162708554,\n 5.904086042937834\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"78","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Struckhoff, Matthew 0000-0002-4911-9956","orcid":"https://orcid.org/0000-0002-4911-9956","contributorId":201512,"corporation":false,"usgs":true,"family":"Struckhoff","given":"Matthew","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937678,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70269069,"text":"70269069 - 2025 - If you build it, will they come? Assessing the response of tiger populations to elevated conservation efforts in lowland Nepal","interactions":[],"lastModifiedDate":"2025-07-16T13:42:27.704339","indexId":"70269069","displayToPublicDate":"2025-05-16T08:35:30","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"If you build it, will they come? Assessing the response of tiger populations to elevated conservation efforts in lowland Nepal","docAbstract":"Thirteen countries within the distributional range of tigers adopted the St. Petersburg Declaration in 2010, committing to double their tiger populations by 2022. As a signatory to this document, Nepal elevated its tiger conservation efforts soon after the declaration was adopted. Using capture-mark-recapture (CMR) analyses of tiger survey data (2013–2022), we assessed the response of tiger populations to enhanced conservation measures in Banke and Bardia national parks (NP) in western lowland of Nepal. In Bardia NP, estimated tiger numbers increased from 49 in 2013 to 122 in 2022, and estimated population density increased from 3.39 in 2013 to 8.47 tigers/100 km2 in 2022). Female survival rate was consistently higher than male, with 87.06 % during 2013–2018 and 89.08 % during 2018–2022, compared to 72.9 % and 76.6 % for males in the respective periods. Additionally, the female population grew at a faster rate (6–7 % per year vs. ∼ 2 % per year for males). In Banke NP, tiger abundance increased from 3 to 22 between 2013 and 2022, and population density increased from 0.34 to 2.42/100 km2 over the same period. The remarkable 7-fold increase in tiger abundance within the Banke NP was facilitated by high male and female survival rates (≥ 90 % per year), as well as high recruitment rates (0.27 individual−1 year−1) from 2013 to 2018, leading to a robust (18–20 %) annual population growth rate. Tigers were recolonizing Banke NP at the beginning of this study, and the area offered ample space and a recovering prey base. This facilitated the recruitment of dispersers from the larger population in Bardia NP and allowed survival to be high by eliminating mortality due to density-dependent intra-specific aggression. Our results not only suggest that Nepal has met or exceeded its commitment to the St. Petersburg Declaration in Banke and Bardia NPs, but they highlight the ability of certain tiger populations to respond quickly and positively to enhanced conservation measures given suitable habitat and a healthy prey base.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03632","usgsCitation":"Lamichhane, S., Pathak, A., Karki, A., Khatiwada, A., Pokheral, C.P., Hines, J.E., Onorato, D.P., Stein, T., and Oli, M., 2025, If you build it, will they come? Assessing the response of tiger populations to elevated conservation efforts in lowland Nepal: Global Ecology and Conservation, v. 60, e03632, 14 p., https://doi.org/10.1016/j.gecco.2025.e03632.","productDescription":"e03632, 14 p.","ipdsId":"IP-172084","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":492499,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03632","text":"Publisher Index Page"},{"id":492341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","otherGeospatial":"Banke National Park, Bardia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 81.21243616640487,\n 28.814284168801763\n ],\n [\n 80.92541905887717,\n 28.44135810205067\n ],\n [\n 81.84220185865365,\n 27.8331018653778\n ],\n [\n 82.23232219898381,\n 28.00056066689831\n ],\n [\n 82.10971294916527,\n 28.27580010616687\n ],\n [\n 81.21243616640487,\n 28.814284168801763\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationDate":"2025-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamichhane, Saneer","contributorId":358054,"corporation":false,"usgs":false,"family":"Lamichhane","given":"Saneer","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":943205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pathak, Abhinaya","contributorId":358055,"corporation":false,"usgs":false,"family":"Pathak","given":"Abhinaya","affiliations":[{"id":85578,"text":"Department of National Parks & Wildlife Conservation, Babar Mahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":943206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karki, Ajay","contributorId":344545,"corporation":false,"usgs":false,"family":"Karki","given":"Ajay","email":"","affiliations":[{"id":82383,"text":"Department of National Parks and Wildlife Conservation, Babarmahal, Kathmandu","active":true,"usgs":false}],"preferred":false,"id":943207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khatiwada, Ambika P.","contributorId":358057,"corporation":false,"usgs":false,"family":"Khatiwada","given":"Ambika P.","affiliations":[{"id":85580,"text":"National Trust for Nature Conservation,","active":true,"usgs":false}],"preferred":false,"id":943208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pokheral, Chiranjibi Prasad","contributorId":201696,"corporation":false,"usgs":false,"family":"Pokheral","given":"Chiranjibi","email":"","middleInitial":"Prasad","affiliations":[{"id":36232,"text":"National Trust for Nature Conservation, Khumaltar, POB 3712, Lalitpur, Nepal","active":true,"usgs":false}],"preferred":false,"id":943209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":943210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Onorato, Dave P.","contributorId":171827,"corporation":false,"usgs":false,"family":"Onorato","given":"Dave","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":943211,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stein, Taylor V.","contributorId":358058,"corporation":false,"usgs":false,"family":"Stein","given":"Taylor V.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":943212,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oli, Madan K.","contributorId":352359,"corporation":false,"usgs":false,"family":"Oli","given":"Madan K.","affiliations":[{"id":84187,"text":"Department of Wildlife Ecology and Conservation, Newins-Zeigler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":943213,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70266505,"text":"70266505 - 2025 - Remote sensing of river discharge based on critical flow theory","interactions":[],"lastModifiedDate":"2025-05-09T15:35:03.88114","indexId":"70266505","displayToPublicDate":"2025-05-16T08:27:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of river discharge based on critical flow theory","docAbstract":"Critical flow theory provides a physical foundation for inferring discharge from measurements of wavelength and channel width made from images. In rivers with hydraulically steep local slopes greater than
∼0.01, flow velocities are high and the Froude number F r (ratio of inertial to gravitational forces) can approach 1.0 (critical flow) or greater. Under these conditions, undular hydraulic jumps (UHJ's) can form as standing wave trains at slope transitions or constrictions. The presence of UHJ's indicates that mean F r ≈ 1, implying that the velocity and depth of the flow and the spacing of the waves are uniquely related to one another. Discharges estimated from 82 Google Earth images agreed closely with discharges recorded at gaging stations (R2 = 0.98), with a mean bias of 1% ± 11%. This approach could provide reliable discharge information in many fluvial environments where critical flow occurs, which tend to be underrepresented in gage networks
Invasive Burmese pythons (Python bivittatus) are extremely cryptic animals. Although their conservation status in their native range is Vulnerable, in the Greater Everglades Ecosystem (Florida, USA) they have become a dominant destructive force and usually are immediately removed whenever found. This poses a paradox where removals are occurring, yet the study and understanding of python ecology is needed to inform removal methods. An important component of life history includes the nesting season, but little is known about python nest site selection, nest brooding, thermogenesis, or hatching success in the wild. Here, we present the first complete and most detailed report of oviposition and brooding for this biologically significant time period of a female Burmese python. We describe anthropogenic nest site selection, document the extent of shivering thermogenesis, describe brooding behaviors, and provide photo-documentation of complete hatching of the largest python clutch on record.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70271","usgsCitation":"Currylow, A.F., McBride, L.M., Anderson, G.E., Guzy, J.C., McCollister, M., Romagosa, C., Hart, K., and Yackel Adams, A.A., 2025, Wild Burmese python nest site selection, thermogenesis, and brooding behaviors in the Greater Everglades Ecosystem: Ecosphere, v. 16, no. 5, e70271, 8 p., https://doi.org/10.1002/ecs2.70271.","productDescription":"e70271, 8 p.","ipdsId":"IP-147379","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":492479,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70271","text":"Publisher Index Page"},{"id":492139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.26056296567494,\n 26.62944759399676\n ],\n [\n -82.26056296567494,\n 24.914081290199974\n ],\n [\n -79.89952282220611,\n 24.914081290199974\n ],\n [\n -79.89952282220611,\n 26.62944759399676\n ],\n [\n -82.26056296567494,\n 26.62944759399676\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Currylow, Andrea Faye 0000-0003-1631-8964","orcid":"https://orcid.org/0000-0003-1631-8964","contributorId":257055,"corporation":false,"usgs":true,"family":"Currylow","given":"Andrea","email":"","middleInitial":"Faye","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McBride, Lisa Marie 0000-0003-4558-5391","orcid":"https://orcid.org/0000-0003-4558-5391","contributorId":303824,"corporation":false,"usgs":true,"family":"McBride","given":"Lisa","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Gretchen Erika 0000-0002-5887-4961","orcid":"https://orcid.org/0000-0002-5887-4961","contributorId":271047,"corporation":false,"usgs":true,"family":"Anderson","given":"Gretchen","email":"","middleInitial":"Erika","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCollister, Matthew F.","contributorId":357875,"corporation":false,"usgs":false,"family":"McCollister","given":"Matthew F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":942727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romagosa, Christina M.","contributorId":357877,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":942728,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":218455,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":942729,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":942730,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266894,"text":"ofr20251007 - 2025 - Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery","interactions":[{"subject":{"id":70261584,"text":"70261584 - 2024 - Mapping eelgrass cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery","indexId":"70261584","publicationYear":"2024","noYear":false,"title":"Mapping eelgrass cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery"},"predicate":"SUPERSEDED_BY","object":{"id":70266894,"text":"ofr20251007 - 2025 - Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery","indexId":"ofr20251007","publicationYear":"2025","noYear":false,"title":"Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery"},"id":1}],"lastModifiedDate":"2025-05-20T13:49:59.506555","indexId":"ofr20251007","displayToPublicDate":"2025-05-16T07:54:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1007","displayTitle":"Mapping Eelgrass (Zostera marina) Cover and Biomass at Izembek Lagoon, Alaska, Using In-Situ Field Data and Sentinel-2 Satellite Imagery","title":"Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery","docAbstract":"The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass (Zostera marina) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251007","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Land Management Research Program","usgsCitation":"Douglas, D.C., Fleming, M.D., Patil, V.P., and Ward, D.H., 2025, Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery: U.S. Geological Survey Open-File Report 2025–1007, 30 p., https://doi.org/10.3133/ofr20251007. [Supersedes preprint https://doi.org/10.1101/2024.08.07.607047.]","productDescription":"Report: vii, 30 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169599","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":485960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1007/coverthb2.jpg"},{"id":485963,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1HLTAHD","text":"USGS data release","description":"USGS data release","linkHelpText":"Eelgrass (Zostera marina) maps from 2016 and 2020, at Izembek Lagoon, Alaska"},{"id":485961,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1007/ofr20251007.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1007"},{"id":485962,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1007"},{"id":485964,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1007/images"},{"id":485965,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1007/ofr20251007.XML"}],"country":"United States","state":"Alaska","otherGeospatial":"Izembek Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.098854980302,\n 55.171004418891414\n ],\n [\n -162.87580882559715,\n 55.150219377165826\n ],\n [\n -162.79513255687405,\n 55.2819754305454\n ],\n [\n -162.63219813180595,\n 55.3494888427272\n ],\n [\n -162.52937543637472,\n 55.342292888511395\n ],\n [\n -162.47875503247008,\n 55.40162041992025\n ],\n [\n -162.50248334680037,\n 55.47879257840398\n ],\n [\n -162.74767592913727,\n 55.39443394016618\n ],\n [\n -162.92959300566955,\n 55.31259575418295\n ],\n [\n -163.098854980302,\n 55.171004418891414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Highly pathogenic H5N1 influenza A virus (HP H5N1) cases in wild mammals have been increasing globally. Carnivora has been the most affected mammal order; however, the extent of morbidity and mortality in carnivores exposed to HP H5N1 remains undefined. We assessed the presence of antibodies to H5 and N1 in the sera of 16 live-captured bobcats (Lynx rufus) in New York State, USA; reported on postcapture outcomes of HP H5N1-exposed bobcats; and reported on a case of HP H5N1 infection in one bobcat. In 2024, 4/16 bobcats (25%) tested positive for antibodies to H5 and N1. Two bobcats were confirmed alive as of November 2024 according to GPS data; the other two were alive as of June 2024, when their GPS collars stopped communicating. Another bobcat, which was negative for HP H5N1 antibodies at capture, died from HP H5N1 infection within 5 wks of capture. Our results provide evidence of bobcats both surviving and succumbing to HP H5N1 infection and highlight the importance of focused health studies paired with monitoring data to better understand exposure, infection, and outcomes for novel pathogens and species.
","language":"English","publisher":"BioOne","doi":"10.7589/jwd-d-24-00137","usgsCitation":"Turner, H., Fuller, A.K., Twining, J., Hitchener, G., Fadden, M., Stallknecht, D., Poulson, R., Carter, D., Watson, M., Schuler, K., and Bloodgood, J., 2025, Highly pathogenic avian influenza virus exposure and infection in free-ranging bobcats (Lynx rufus) in New York, USA: Journal of Wildlife Diseases, v. 61, no. 2, p. 515-521, https://doi.org/10.7589/jwd-d-24-00137.","productDescription":"7 p.","startPage":"515","endPage":"521","ipdsId":"IP-171388","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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While conducting a controlled mesocosm study assessing the impacts of contaminants on crayfish growth, development, and reproductive status, we recorded an observation where New River Crayfish neonates clustered around the head of an untreated, reference maternal crayfish after molting. This neonate head-clustering behavior did not appear to impact the female during the 3-week period the behavior was observed. Further observations are needed to determine if this behavior occurs across other crayfish species, and if it is displayed outside of captive conditions.
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Arun","contributorId":359125,"corporation":false,"usgs":false,"family":"Oakley-Cogan","given":"Arun","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":944975,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Fisk, Aaron T.","contributorId":359126,"corporation":false,"usgs":false,"family":"Fisk","given":"Aaron","middleInitial":"T.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":944976,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Matley, Jordan K.","contributorId":359127,"corporation":false,"usgs":false,"family":"Matley","given":"Jordan","middleInitial":"K.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":944977,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70267435,"text":"70267435 - 2025 - Characterization of the long-distance dispersal kernel of white-tailed deer and evaluating its impact on chronic wasting disease spread in Wisconsin","interactions":[],"lastModifiedDate":"2025-05-23T15:29:29.683831","indexId":"70267435","displayToPublicDate":"2025-05-15T10:22:59","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1107,"text":"Bulletin of Mathematical Biology","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of the long-distance dispersal kernel of white-tailed deer and evaluating its impact on chronic wasting disease spread in Wisconsin","docAbstract":"Chronic wasting disease (CWD) is a fatal neurodegenerative disease infecting cervids. It is highly contagious and caused by misfolded prions that propagate via templated conformational conversion of the cervid’s normal prion protein. Prevalence of CWD in free-ranging deer in North America is mostly low, but in some regions local prevalence has reached 80%. CWD prions can be transmitted via direct contact with infected individuals or indirectly through the environment. Infected individuals shed prions through feces, urine, saliva or carcasses, and prions have long environmental persistence. Long-distance dispersal of infected deer poses a significant risk for CWD spread. We propose an integrodifference equation (IDE) model to capture CWD dynamics and the consequences of long-distance dispersal behavior in white-tailed deer (WTD, Odocoileus virginianus). A diffusion-settling model characterizes long-distance dispersal kernels, accommodating hypothetical dispersal behaviors through time-dependent settling rate functions. Three new closed-form dispersal kernels are approximated using Laplace’s method and parameterized with GPS location data collected from WTD in Wisconsin, USA. Settling rates reflecting ongoing sensitivity to stimuli which prompt deer to disperse from their natal home range give the most supported long-distance dispersal kernel. Impact of long-distance dispersal on CWD spread is quantified using the IDE model. At high population densities, long-distance dispersal can magnify CWD spread by a factor of four. At lower population densities single infected individuals cannot initiate an outbreak, but CWD may still spread due to the accumulation of environmental hazard from prions behind the wave of invasion, possibly presenting substantial management challenges.
","language":"English","publisher":"Springer","doi":"10.1007/s11538-024-01394-x","usgsCitation":"Mennatallah, G., Powell, J., McClure, J., Walsh, D.P., and Storm, D., 2025, Characterization of the long-distance dispersal kernel of white-tailed deer and evaluating its impact on chronic wasting disease spread in Wisconsin: Bulletin of Mathematical Biology, v. 87, 52, https://doi.org/10.1007/s11538-024-01394-x.","productDescription":"52","ipdsId":"IP-166201","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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dwalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":4758,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"dwalsh@usgs.gov","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":938193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storm, Daniel J.","contributorId":341059,"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":938194,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270717,"text":"70270717 - 2025 - Genetic analysis of Missouri’s Topeka Shiners with implications for the propagation of understudied small-bodied freshwater fishes","interactions":[],"lastModifiedDate":"2025-08-22T16:54:17.790275","indexId":"70270717","displayToPublicDate":"2025-05-15T09:48:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Genetic analysis of Missouri’s Topeka Shiners with implications for the propagation of understudied small-bodied freshwater fishes","docAbstract":"Objective
Best practices for conservation hatcheries to conserve genetic diversity and minimize adaptation to captivity have been established for decades, but how to apply them is not clear in every circumstance. As a growing number of aquatic species are propagated in captive settings, addressing the fit of these practices to each system will help managers operate optimally while conserving hatchery resources. Small-bodied freshwater fish present a unique set of traits compared with species that are typically considered for propagation (i.e., salmonids), including a patchy distribution within a watercourse. We examine the propagation and reintroduction program that supports the Topeka Shiner Miniellus topeka, an endangered minnow in the Midwestern USA.
Methods
We genotyped shiners from groups with different histories (two reintroduced, three captive, and two remnant populations) at 11 microsatellite loci and compared genetic diversity, genetic structure, effective population size, and evidence of population bottlenecks. We also looked at the breeding structure by genetically assigning hatchery-reared young (n = 148) to candidate parents.
Results
We documented high levels of genetic structure among the two natural populations in our study. We also noted lower diversity and evidence of bottlenecks in hatchery-reared groups. However, hatcheries may support sufficient (>50) effective population sizes with minimal space.
Conclusions
Hatcheries may avoid bottlenecks in other small-bodied freshwater fish by collecting wild fish from a broad area and frequently incorporating them into the captive population. Within the hatchery, we emphasize the need to reduce generational overlap by stocking all production fish and/or subdividing the captive populations.
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","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Shriver, L.C., 2025, Spring 2025: RAMPS Newsletter, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-179005","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":486211,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":486152,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/centers/southwest-biological-science-center/news/ramps-newsletter-spring-2025","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shriver, Laura Cecilia 0009-0008-5567-0868","orcid":"https://orcid.org/0009-0008-5567-0868","contributorId":334175,"corporation":false,"usgs":true,"family":"Shriver","given":"Laura","email":"","middleInitial":"Cecilia","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937641,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272049,"text":"70272049 - 2025 - Using peak geometry and shifts in the x-ray spectrum of carbon from electron probe microanalysis to determine thermal maturity of organic matter","interactions":[],"lastModifiedDate":"2025-11-14T16:17:17.657692","indexId":"70272049","displayToPublicDate":"2025-05-15T09:13:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"Using peak geometry and shifts in the x-ray spectrum of carbon from electron probe microanalysis to determine thermal maturity of organic matter","docAbstract":"During the burial of mudstones, the associated organic matter undergoes gradual thermal maturation, a key process that can influence the reactivity of organic matter during catagenesis, the formation of hydrocarbon deposits and the chemical weathering of mudstones. Conventional methods for assessing the thermal maturity of organic matter often fail to reflect the geochemical heterogeneity between individual organic phases in mudstone samples. Here, we report an alternative, non-destructive, surficial and micro-scale (analytical spot size of ~ 300 nm with about 4 μm diffusion depth for micrometre-size organic grains) method to evaluate the thermal maturity of organic matter in mudstones using the carbon Kα X-ray spectrum measured by field emission-electron probe microanalyser (FE-EPMA). Using this method, we observed correlations between parameter values derived from FE-EPMA spectra, including the peak position, the peak area and the intra-sample heterogeneity of these measurements, and independently measured vitrinite/solid bitumen reflectance for a suite of mudstones, representing different age, geological context and burial depth. With the increased values in peak area and position, we identified an increase in the carbon mass fraction of organic matter and the mean nominal oxidation state of carbon approaching zero. These trends, which are consistent with aromatisation and graphitisation, provide the rationale for using FE-EPMA to estimate the thermal maturity of organic matter. To explore some of these trends in more detail, we employed time-of-flight secondary ionisation mass spectrometry, X-ray photoelectron spectroscopy and optical reflectance measurements on a subset of samples.
","language":"English","publisher":"Wiley","doi":"10.1111/ggr.12611","usgsCitation":"Zhou, H., Costin, G., Birdwell, J.E., Hackley, P.C., Minisini, D., Terlier, T., and Torres, M.A., 2025, Using peak geometry and shifts in the x-ray spectrum of carbon from electron probe microanalysis to determine thermal maturity of organic matter: Geostandards and Geoanalytical Research, v. 49, no. 3, p. 591-605, https://doi.org/10.1111/ggr.12611.","productDescription":"15 p.","startPage":"591","endPage":"605","ipdsId":"IP-166529","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":496492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Haolin","contributorId":289963,"corporation":false,"usgs":false,"family":"Zhou","given":"Haolin","email":"","affiliations":[],"preferred":false,"id":949851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costin, Gelu 0000-0003-3054-7886","orcid":"https://orcid.org/0000-0003-3054-7886","contributorId":269538,"corporation":false,"usgs":false,"family":"Costin","given":"Gelu","email":"","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":949852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":949854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minisini, Daniel","contributorId":343398,"corporation":false,"usgs":false,"family":"Minisini","given":"Daniel","affiliations":[{"id":82083,"text":"ExxonMobil Technology and Engineering","active":true,"usgs":false}],"preferred":false,"id":949855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terlier, Tanguy","contributorId":343399,"corporation":false,"usgs":false,"family":"Terlier","given":"Tanguy","affiliations":[{"id":82085,"text":"SIMS Lab, Shared Equipment Authority, Rice University","active":true,"usgs":false}],"preferred":false,"id":949856,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Torres, Mark A.","contributorId":362032,"corporation":false,"usgs":false,"family":"Torres","given":"Mark","middleInitial":"A.","affiliations":[{"id":7173,"text":"Rice University","active":true,"usgs":false}],"preferred":false,"id":949857,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267457,"text":"70267457 - 2025 - Rapid recovery of an arctic lake ecosystem from a pulse disturbance caused by thermokarst failure","interactions":[],"lastModifiedDate":"2025-05-23T16:05:00.603621","indexId":"70267457","displayToPublicDate":"2025-05-15T09:00:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Rapid recovery of an arctic lake ecosystem from a pulse disturbance caused by thermokarst failure","docAbstract":"Due to rapid climate change, arctic ecosystems are experiencing an increase in disturbances including localized land-surface failures caused by melting ground ice (thermokarst failures). These failures result in the mass transport of sediment and organic materials into surface waters, with the potential to dramatically alter aquatic ecosystem function and biotic interactions. We coupled direct comparisons and long-term data of a suite of abiotic and biotic variables in a thermokarst-impacted lake and nearby reference lake to assess the impacts of thermokarst failure. After the thermokarst failure and relative to long-term averages, water transparency was substantially reduced. We hypothesized there would be subsequent changes to lower trophic levels and profound declines in fish foraging efficiency. However, these characteristics were within the range of natural variability and/or rapidly recovered to values within the range of long-term variability. In addition, although there was limited evidence of taxa-specific changes, we did not observe any strong changes in the total relative densities, growth rates, or composition of the bacterioplankton and zooplankton communities, benthic macroinvertebrates, or changes in fish diet, that could be attributed statistically to the thermokarst event. In sum, the thermokarst disturbance had substantial effects on water transparency and some lower trophic levels, which surprisingly were not manifested in higher trophic levels. Overall, the lake ecosystem appeared resistant to thermokarst disturbance with rapid recovery within two years after the disturbance.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00442-025-05681-9","collaboration":"Alaska Dept. of Fish and Game","usgsCitation":"Budy, P., Pennock, C., Messenger, S., Pehrson, H., Adler, E., Thiede, G., Christman, N.R., Crump, B.C., Giblin, A., and Kling, G., 2025, Rapid recovery of an arctic lake ecosystem from a pulse disturbance caused by thermokarst failure: Oecologia, v. 207, 82, 16 p., https://doi.org/10.1007/s00442-025-05681-9.","productDescription":"82, 16 p.","ipdsId":"IP-162860","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00442-025-05681-9","text":"Publisher Index Page"},{"id":486523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Toolik Lake","geographicExtents":"{\n \"type\": 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This deoxygenation can favor microbial methylation of mercury (Hg). To understand the dynamics of Hg under increasing deoxygenation, we simultaneously quantified both Hg and hypoxia (< 2 mg O2/L) lifetime chronologies in fishes. We used a novel combination of chemical biomarkers in ear stones and eye lenses. We compared these markers in two species with different life histories, benthic Round Goby (Neogobius melanostomus) and semi-demersal Yellow Perch (Perca flavescens), from two connected ecosystems with different levels of hypoxia: the Central Basin of Lake Erie and the less hypoxic but more polluted Western Basin. Overall, Central Basin Round Goby were exposed to hypoxia throughout their lifetime and exhibited significantly elevated eye lens Hg concentrations ([Hg]) compared to their Western Basin counterparts. In contrast, the Central Basin Yellow Perch were exposed to hypoxia only at their juvenile stage. Central Basin Yellow Perch exhibited significantly lower eye lens [Hg] compared to their Western Basin counterparts. Patterns revealed by eye lens [Hg] were not detectable in muscle tissue [Hg]. Findings show that exposure to hypoxia can alter fish lifetime Hg accumulation patterns, with species-specific outcomes.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0235","usgsCitation":"Miraly, H., Razavi, N.R., Kraus, R., Gorman, A., Duskey, E., Altenritter, M., and Limburg, K., 2025, Using complementary biomarkers to unravel fish lifetime exposure to hypoxia and mercury: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-12, https://doi.org/10.1139/cjfas-2024-0235.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-160319","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":502660,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":489693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"central and western basins of Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.89516329987413,\n 42.22922395564774\n ],\n [\n -80.31876949997724,\n 42.723196642933516\n ],\n [\n -80.56436204497173,\n 42.586172322716635\n ],\n [\n -80.85406530581916,\n 42.6475830324963\n ],\n [\n -81.23686023317622,\n 42.669037962594786\n ],\n [\n -81.54383543092807,\n 42.558792951461854\n ],\n [\n -81.79650715654992,\n 42.38566818477545\n ],\n [\n -81.83639227525022,\n 42.24548812681907\n ],\n [\n -82.03960905303965,\n 42.24430434515543\n ],\n [\n -82.22731055307747,\n 42.1856734329775\n ],\n [\n -82.45380024749375,\n 42.08677033038843\n ],\n [\n -82.50186424776832,\n 41.90146334011604\n ],\n [\n -82.65573447223925,\n 42.02901910499938\n ],\n [\n -82.89493872434342,\n 41.98357513899583\n ],\n [\n -83.13673924284132,\n 42.03102328099084\n ],\n [\n -83.33214738082043,\n 41.94305439608826\n ],\n [\n -83.41607606516274,\n 41.82723540573549\n ],\n [\n -83.42242836074821,\n 41.71141641538273\n ],\n [\n -82.5219858387644,\n 41.35739468311547\n ],\n [\n -81.99215115587265,\n 41.519201708215675\n ],\n [\n -81.83196193924863,\n 41.47224610549724\n ],\n [\n -81.70280327812782,\n 41.52988864684306\n ],\n [\n -81.2586233923877,\n 41.78108885460402\n ],\n [\n -80.42561938805427,\n 41.993498193411206\n ],\n [\n -79.89516329987413,\n 42.22922395564774\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Miraly, Hadis","contributorId":356364,"corporation":false,"usgs":false,"family":"Miraly","given":"Hadis","affiliations":[{"id":33387,"text":"SUNY-ESF","active":true,"usgs":false}],"preferred":false,"id":939202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Razavi, N. 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This principle, central to the pulse-reserve paradigm, has not been thoroughly evaluated in biological soil crusts (biocrusts), essential primary producers on dryland surfaces. We conducted two experiments to investigate carbon uptake in biocrusts under different precipitation regimes. In the first, we applied a gradient of watering amounts to biocrusts dominated by moss or cyanobacteria, hypothesising distinct pulse-response strategies. The second experiment extended watering treatments over three months, varying pulse size and frequency. Our results revealed distinct carbon uptake patterns: moss crusts exhibited increased CO2 uptake with larger, less frequent watering events, whereas cyanobacteria crusts maintained similar carbon uptake across all event sizes. These findings suggest divergent pulse-response strategies across biocrust types, with implications for modelling dryland carbon dynamics and informing land management under changing precipitation regimes.","language":"English","publisher":"Wiley","doi":"10.1111/ele.70125","usgsCitation":"Young, K., Sala, O.E., Darrouzet-Nardi, A., Tucker, C.L., Finger-Higgens, R.A., Starbuck, M., and Reed, S., 2025, Biocrust mosses and cyanobacteria exhibit distinct carbon uptake responses to variations in precipitation amount and frequency: Ecology Letters, v. 28, no. 5, e70125, 10 p., https://doi.org/10.1111/ele.70125.","productDescription":"e70125, 10 p.","ipdsId":"IP-171245","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":489080,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/2566615","text":"External Repository"},{"id":486154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau, southeastern Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.03847502985644,\n 38.34758364168215\n ],\n [\n -111.03847502985644,\n 37.01866208836557\n ],\n [\n -109.01970607796514,\n 37.01866208836557\n ],\n [\n -109.01970607796514,\n 38.34758364168215\n ],\n [\n -111.03847502985644,\n 38.34758364168215\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":937537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sala, Osvaldo E.","contributorId":139047,"corporation":false,"usgs":false,"family":"Sala","given":"Osvaldo","email":"","middleInitial":"E.","affiliations":[{"id":12629,"text":"Arizona State University, Tempe, AZ (DETAIL TO BE ADDED)","active":true,"usgs":false}],"preferred":false,"id":937538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Darrouzet-Nardi, Anthony adarrouzet-nardi@usgs.gov","contributorId":207292,"corporation":false,"usgs":false,"family":"Darrouzet-Nardi","given":"Anthony","email":"adarrouzet-nardi@usgs.gov","affiliations":[],"preferred":false,"id":937539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tucker, Colin L","contributorId":270737,"corporation":false,"usgs":false,"family":"Tucker","given":"Colin","email":"","middleInitial":"L","affiliations":[{"id":56205,"text":"U.S. National Forest Service, Northern Research Station, Houghton, MI 49931","active":true,"usgs":false}],"preferred":false,"id":937540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finger-Higgens, Rebecca A 0000-0002-7645-504X","orcid":"https://orcid.org/0000-0002-7645-504X","contributorId":290211,"corporation":false,"usgs":true,"family":"Finger-Higgens","given":"Rebecca","email":"","middleInitial":"A","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Starbuck, Megan Elyse 0000-0002-1363-6994","orcid":"https://orcid.org/0000-0002-1363-6994","contributorId":355528,"corporation":false,"usgs":true,"family":"Starbuck","given":"Megan Elyse","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937543,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266895,"text":"ofr20241070 - 2025 - Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18","interactions":[],"lastModifiedDate":"2025-05-16T14:44:27.229198","indexId":"ofr20241070","displayToPublicDate":"2025-05-15T07:39:36","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-1070","displayTitle":"Calibration of the Stream Salmonid Simulator (S3) Model to Estimate Annual Survival, Movement, and Food Consumption by Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in the Restoration Reach of the Trinity River, California, 2006–18","title":"Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18","docAbstract":"The Trinity River is managed in two sections: (1) from the upper 64-kilometer “restoration reach” downstream from Lewiston Dam to the confluence with the North Fork Trinity River, and (2) the 120-kilometer lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously applied to these reaches and the Klamath River. To estimate fish growth, past S3 calibration efforts in the Trinity and Klamath Rivers used maximum likelihood methods that considered only the abundance of juvenile Chinook salmon (Oncorhynchus tshawytscha) passing a fish trap to estimate survival and movement parameters, but not fish consumption. Previous calibrations did not estimate the average proportion of maximum consumption (Cy) when estimating survival (Sy) and movement (M0y) parameters across years (y) of data, but because no other information was available in the literature a fixed value of Cy=0.66 was assumed. Therefore, the goal of this report is to present an alternative approach that calibrates the S3 model to multivariate data (that is, abundance and size), enabling the estimation of the average proportion of maximum consumption, in conjunction with survival and movement parameters for a particular migration year. We fit the S3 model to individual years of weekly trap abundance estimates and mean fish sizes (fork length) at the Pear Tree Gulch (hereafter referred to as Pear Tree) fish trap representing the restoration reach. We used the Earth Mover’s Distance (EMD) as the objective value to be minimized in parameter optimization. This approach estimated survival, movement, and consumption parameters for each migration year. Because we had information on the abundance of natural and hatchery produced juvenile salmon at the fish traps, we estimated survival and movement for natural and hatchery fish.
S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile Chinook Salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units.
The physical template of the restoration reach of the Trinity River was classified into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity time series were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival.
We estimated movement, survival, and consumption parameters by calibrating the model to 12 years of weekly juvenile abundance estimates and fish sizes at the Pear Tree fish trap near the downstream end of the restoration reach. We estimated parameters for 12 years that included a wide range of female spawner abundances (1,414–11,494) and water year types (critically dry–extremely wet). We contrast the estimated parameters to the corresponding number of female spawners and the total annual volume of water discharged for the Trinity River (Trinity River Restoration Program; https://www.trrp.net/restoration/flows/summary/).
The calibration consisted of replicating historical conditions as closely as possible (for example, discharge; temperature; spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location from each brood year of adults and subsequent migration year of their juvenile progeny. Because density-dependent movement was favored in past evaluations, we estimated S3 parameters based on density-independent survival and density-dependent movement. Likewise, each year’s estimated survival parameter for natural (SNy) and hatchery (SHy) fish may be interpreted as the mean daily survival probability from emergence or hatchery release to the Pear Tree fish trap. Under density dependence, the estimated movement parameter for natural (M0Ny) and hatchery (M0Hy) fish represents the intercept of the Beverton-Holt model; the probability of remaining in a habitat at near-zero abundance.
We estimated Cy by using EMD and incorporating abundance and fish size into model calibration. Average daily proportions of maximum consumption, , across the years were generally high (=0.640; standard deviation (SD) SD=0.176), suggesting that fish were feeding at about two-thirds of expected maximum consumption rates. This average proportion of maximum consumption,is very similar to what has been assumed (=0.66) in previous Trinity and Klamath River S3 calibration and simulation efforts. In 2017, we estimated the lowest Cy, suggesting lower average consumption for juvenile salmon in high-discharge water years. When this high discharge year was excluded, there was no apparent trend in Cy with annual water volume. Estimates of survival showed little trend over the range in spawner abundances, but a trend towards higher natural and hatchery fish survival with higher annual volumes of water was apparent. Over the 12 years, the average survival of hatchery fish was =0.888 (SD=0.079) and the average survival natural fish was=0.969 (SD=0.01).
With respect to fish movement, we estimated higher M0Ny and M0Hy with higher annual volumes of water in the Trinity River. Higher MN0y or MH0y suggest greater probability of remaining in a habitat at low fish densities, with potential for density-dependent processes in movement to occur. The highest M0Ny = 0.676 was estimated during brood year 2012, and the overall average for natural fish was =0.276 (SD=0.188) and for hatchery fish was=0.467 (SD=0.235). Under the Beverton-Holt model, as M0Ny or M0Hy approach zero, there is less capacity for change in fish movement as fish density increases.
The S3 model was initialized with only the spatiotemporal distribution of spawners, so it performed well at capturing the essential outmigration features that are ultimately governed by rates of growth, movement, and mortality. We used a new optimization method that could accommodate multivariate data on abundance and fish size collected at the Pear Tree fish trap, enabling the calibration of S3 to estimate five parameters for 12 separate years of data. Incorporating weekly fish size data for each year in our parameter optimization process made the estimation of Cy possible and represents a step forward in the fitting of the S3 model to fish trap data for the purposes of parameter calibration and the estimation of growth parameters with respect to annual conditions. We identified lack of fit and adding important effects into the S3 model may improve the S3 estimation and simulation of water scenarios.
The Trinity River Restoration Program (TRRP) Science Advisory Board recommended that the TRRP focus on developing core elements of a decision support system (DSS; Buffington and others, 2014). Toward that end, the habitat and S3 models described in this report are both core elements of the DSS. The structure of S3 makes it a particularly useful fish production model for the DSS because population dynamics are sensitive to (1) water temperature, (2) daily discharge management, and (3) habitat quality and quantity. Each of these variables are key management parameters under consideration in the TRRP. As such, the S3 model may provide valuable insights into the potentially variable effects of different management decisions on the Trinity River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241070","collaboration":"Prepared in cooperation with U.S. Bureau of Reclamation","usgsCitation":"Plumb, J.M., Perry, R.W., and De Juilio, K., 2025, Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18: U.S. Geological Survey Open-File Report 2024–1070, 21 p., https://doi.org/10.3133/ofr20241070.","productDescription":"vii, 22 p.","onlineOnly":"Y","ipdsId":"IP-156648","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":485969,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1070/images"},{"id":485968,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241070/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1070"},{"id":485967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1070/ofr20241070.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1070"},{"id":485966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1070/coverthb.jpg"},{"id":485970,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1070/ofr20241070.XML"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.1406578585185,\n 40.785753827016435\n ],\n [\n -123.1406578585185,\n 40.69151845163566\n ],\n [\n -122.79146166523228,\n 40.69151845163566\n ],\n [\n -122.79146166523228,\n 40.785753827016435\n ],\n [\n -123.1406578585185,\n 40.785753827016435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016