Fibropapillomatosis (FP) is a neoplastic disease most often found in green turtles (Chelonia mydas). Afflicted turtles are burdened with potentially debilitating tumors concentrated externally on the soft tissues, plastron, and eyes and internally on the lungs, kidneys, and the heart. Clinical signs occur at various levels, ranging from mild disease to severe debilitation. Tumors can both progress and regress in affected turtles, with outcomes ranging from death due to the disease to complete regression. Since its official description in the scientific literature in 1938, tumor growth rates have been rarely documented. In addition, FP tumors come in two very different morphologies; yet, to our knowledge, there have been no quantified differences in growth rates between tumor types. FP tumors are often rugose in texture, with a polypoid to papillomatous morphology, and may or may not be pedunculated. In other cases, tumors are smooth, with a skin-like surface texture and little to no papillose structures. In our study, we assessed growth-rate differences between rugose and smooth tumor morphologies in a rehabilitation setting. We measured average biweekly tumor growth over time in green turtles undergoing rehabilitation at the University of Florida Whitney Laboratory Sea Turtle Hospital in St. Augustine, Florida, and compared growth between rugose and smooth tumors. Our results demonstrate that both rugose and smooth tumors follow a similar active growth progression pattern, but rugose tumors grew at significantly faster rates (p = 0.013) than smooth ones. We also documented regression across several examined tumors, ranging from −0.19% up to −10.8% average biweekly negative growth. Our study offers a first-ever assessment of differential growth between tumor morphologies and an additional diagnostic feature that may lead to a more comprehensive understanding and treatment of the disease. We support the importance of tumor morphological categorization (rugose versus smooth) being documented in future FP hospital- and field-based health assessments.
","language":"English","publisher":"MDPI","doi":"10.3390/vetsci10070421","usgsCitation":"Manes, C., Herren, R., Page, A., Dunlap, F., Skibicki, C., Rollinson Ramia, D.R., Farrell, J.A., Capua, I., Carthy, R.R., and Duffy, D.J., 2023, Green turtle fibropapillomatosis: Tumor morphology and growth rate in a rehabilitation setting: Veterinary Sciences, v. 10, no. 7, 421, 12 p., https://doi.org/10.3390/vetsci10070421.","productDescription":"421, 12 p.","ipdsId":"IP-153769","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442907,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/vetsci10070421","text":"Publisher Index Page"},{"id":432044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Manes, Costanza","contributorId":340560,"corporation":false,"usgs":false,"family":"Manes","given":"Costanza","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herren, Richard M.","contributorId":340561,"corporation":false,"usgs":false,"family":"Herren","given":"Richard M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Page, Annie","contributorId":340563,"corporation":false,"usgs":false,"family":"Page","given":"Annie","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunlap, Faith","contributorId":340565,"corporation":false,"usgs":false,"family":"Dunlap","given":"Faith","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skibicki, Chris","contributorId":340567,"corporation":false,"usgs":false,"family":"Skibicki","given":"Chris","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rollinson Ramia, Devon R.","contributorId":340569,"corporation":false,"usgs":false,"family":"Rollinson Ramia","given":"Devon","email":"","middleInitial":"R.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Farrell, Jessica A.","contributorId":340572,"corporation":false,"usgs":false,"family":"Farrell","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":81632,"text":"Florida Atlantic University Harbor Branch Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":907369,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Capua, Ilaria","contributorId":340573,"corporation":false,"usgs":false,"family":"Capua","given":"Ilaria","email":"","affiliations":[{"id":37540,"text":"John Hopkins University","active":true,"usgs":false}],"preferred":false,"id":907370,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carthy, Raymond R. 0000-0001-8978-5083 rayc@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":3685,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","email":"rayc@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907371,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duffy, David J.","contributorId":340574,"corporation":false,"usgs":false,"family":"Duffy","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907372,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70245766,"text":"fs20233017 - 2023 - U.S. Geological Survey Rocky Mountain Region 2022 science exchange, showcasing interdisciplinary and state-of-the-art USGS science","interactions":[],"lastModifiedDate":"2023-06-29T10:52:05.845833","indexId":"fs20233017","displayToPublicDate":"2023-06-28T13:30:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3017","displayTitle":"U.S. Geological Survey Rocky Mountain Region 2022 Science Exchange, Showcasing Interdisciplinary and State-of-the-Art USGS Science","title":"U.S. Geological Survey Rocky Mountain Region 2022 science exchange, showcasing interdisciplinary and state-of-the-art USGS science","docAbstract":"The Rocky Mountains and the Colorado River Basin in the Western United States represent complex, interconnected systems that sustain a number of species, including tens of millions of humans. These systems face several challenges, including worsening drought, altered wildfire regimes, climate change, and the spread of invasive species. These factors can exacerbate one another, further contributing to habitat loss and affecting species of conservation concern. Characterizing and managing these challenges require interdisciplinary communities of scientists to develop information and decision-support tools that can inform holistic land and water management solutions. The U.S. Geological Survey (USGS) Rocky Mountain Region 2022 Science Exchange focused on the use of interdisciplinary and state-of-the-art science being conducted by USGS scientists in the region to address these complex problems.
The USGS Rocky Mountain Regional Office organized its first Science Exchange in 2017 to share scientific information between leaders and early career scientists throughout the region. Science Exchanges held in 2018 and 2020 focused on drought science relevant to the region and the Earth Monitoring, Analyses, and Prediction (EarthMAP) concept, which is designed to facilitate interdisciplinary, timely, and actionable science related to drought in the Colorado River Basin and other areas. Based on the emerging need for more holistic approaches to address increasingly complex natural resource issues that affect society, the Region hosted a virtual fourth Science Exchange for three days in April 2022. This event focused on barriers and bridges to interdisciplinary science and highlighted studies from the Region to inspire collaboration across disciplines. Presentations described recent and ongoing research that applied collaborative and state-of-the-art methods to address problems in the fields of geology, hydrology, ecology, and natural hazards. Science collaboration and outreach to all levels of stakeholders are vital elements needed for providing timely and actionable data, interpretations, analytical tools, and products. These presentations led to active online chats and panel discussions and showcased interdisciplinary science and advanced methods that may inform and lead to more effective, holistic management decisions as the Western United States adapts to ongoing and future changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233017","usgsCitation":"Peterson, D.E., French, K.L., Oden, J.H., Anderson, P.J., Titus, T.N., Dahm, K.G., Driscoll, J., Andrews, W.J., 2022, U.S. Geological Survey Rocky Mountain Region 2022 Science Exchange, Showcasing Interdisciplinary and State-of-the-Art USGS Science, U.S. Geological Survey Fact Sheet 2023-3017, 6 p., https://doi.org/10.3133/fs20233017.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-144708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":418590,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3017/images"},{"id":418591,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.xml"},{"id":418596,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233017/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3017"},{"id":418480,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3017/coverthb.jpg"},{"id":418481,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.pdf","text":"Report","size":"4.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3017"}],"contact":"Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS-911
Denver, CO 80225-0046
The open waters of large lakes can sometimes become so depleted in important metals that phytoplankton communities become either growth limited or limited in some metabolic function. Metals such as Fe, Ni, Mo, and Zn are used as co-factors for enzymes by phytoplankton in core metabolic functions, as well as metabolic pathways that allow phytoplankton to use less preferred forms of N and P (e.g. nitrates, urea, and organic phosphorus). In the Laurentian Great Lakes, metal limitation has been observed primarily in waters that are isolated from tributary inputs and sediment exchange. These are situations where the supply of metals is very low relative to demand. We hypothesized that another situation where metal limitation could occur is within algal blooms, where the demand for metals is high because preferred forms of N and P are often low or absent and the phytoplankton biomass is extremely high. As a preliminary test of this hypothesis, we performed seven laboratory incubation experiments on naturally occurring phytoplankton communities from two nearshore habitats that frequently experience blooms (Green Bay in Lake Michigan and Maumee Bay in Lake Erie). Metals and labile nutrients (inorganic N and P) were often present at low concentrations or below the method detection limit. Amendments of inorganic N (5 experiments) and P (1 one experiment) resulted in increased chlorophyll in laboratory incubations, but metal amendments alone never appeared to stimulate growth. Although we attempted to sample during conditions when we hypothesized metal limitation would be most likely, we cannot rule out the possibility that metal limitation is occurring at other times in these eutrophic nearshore areas. Further, metal availability could affect other aspects of the phytoplankton community, such as the production of cyanotoxins or the interactions between different phytoplankton taxa.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02705060.2023.2222747","usgsCitation":"Larson, J.H., Loftin, K.A., Stelzer, E., Costello, D.M., Bailey, S., Evans, M.A., Givens, C.E., and Fogarty, L., 2023, Role of trace metal co-limitation in cyanobacterial blooms of Maumee Bay (Lake Erie) and Green Bay (Lake Michigan): Journal of Freshwater Ecology, v. 38, no. 1, 2222747, 15 p., https://doi.org/10.1080/02705060.2023.2222747.","productDescription":"2222747, 15 p.","ipdsId":"IP-136002","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":442927,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2023.2222747","text":"Publisher Index Page"},{"id":435273,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IP79XZ","text":"USGS data release","linkHelpText":"Response of natural phytoplankton communities from Green Bay (Lake Michigan) and Maumee Bay (Lake Erie) to laboratory manipulations of nutrient and trace metal availability during late summer 2018"},{"id":424272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Ohio, Wisconsin","otherGeospatial":"Green Bay, Maumee Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.02458004719206,\n 44.51570563868941\n ],\n [\n -87.5884726794596,\n 44.7753240579504\n ],\n [\n -87.40156952185973,\n 44.88893583461942\n ],\n [\n -87.0277632066606,\n 45.29107496323033\n ],\n [\n -87.35706877005029,\n 45.447391559510095\n ],\n [\n -87.64187358163099,\n 44.989736059296405\n ],\n [\n -87.81097643850703,\n 44.93305770757982\n ],\n [\n -88.00677974646825,\n 44.68047649545244\n ],\n [\n -88.02458004719206,\n 44.51570563868941\n ]\n ]\n ],\n \"type\": 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Center","active":false,"usgs":true}],"preferred":true,"id":891838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Costello, David M. 0000-0002-1532-5399","orcid":"https://orcid.org/0000-0002-1532-5399","contributorId":255146,"corporation":false,"usgs":false,"family":"Costello","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":18142,"text":"Kent State University","active":true,"usgs":false}],"preferred":false,"id":891840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Sean 0000-0003-0361-7914 sbailey@usgs.gov","orcid":"https://orcid.org/0000-0003-0361-7914","contributorId":198515,"corporation":false,"usgs":true,"family":"Bailey","given":"Sean","email":"sbailey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":891841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":891842,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891843,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fogarty, Lisa R. 0000-0003-0329-3251","orcid":"https://orcid.org/0000-0003-0329-3251","contributorId":201646,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa R.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891844,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70255040,"text":"70255040 - 2023 - Tourism-supported working lands sustain a growing jaguar population in the Colombian Llanos","interactions":[],"lastModifiedDate":"2024-06-12T23:14:10.953527","indexId":"70255040","displayToPublicDate":"2023-06-27T18:08:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Tourism-supported working lands sustain a growing jaguar population in the Colombian Llanos","docAbstract":"Understanding large carnivore demography on human-dominated lands is a priority to inform conservation strategies, yet few studies examine long-term trends. Jaguars (Panthera onca) are one such species whose population trends and survival rates remain unknown across working lands. We integrated nine years of camera trap data and tourist photos to estimate jaguar density, survival, abundance, and probability of tourist sightings on a working ranch and tourism destination in Colombia. We found that abundance increased from five individuals in 2014 to 28 in 2022, and density increased from 1.88 ± 0.87 per 100 km2 in 2014 to 3.80 ± 1.08 jaguars per 100 km2 in 2022. The probability of a tourist viewing a jaguar increased from 0% in 2014 to 40% in 2020 before the Covid-19 pandemic. Our results are the first robust estimates of jaguar survival and abundance on working lands. Our findings highlight the importance of productive lands for jaguar conservation and suggest that a tourism destination and working ranch can host an abundant population of jaguars when accompanied by conservation agreements and conflict interventions. Our analytical model that combines conventional data collection with tourist sightings can be applied to other species that are observed during tourism activities.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-36935-2","usgsCitation":"Hyde, M., Payan, E., Barragan, J., Stasiukynas, D., Kendall, W.L., Rincon, S., Rodriguez, J., Crooks, K., Breck, S., and Boron, V., 2023, Tourism-supported working lands sustain a growing jaguar population in the Colombian Llanos: Scientific Reports, v. 13, 10408, 11 p., https://doi.org/10.1038/s41598-023-36935-2.","productDescription":"10408, 11 p.","ipdsId":"IP-151847","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442932,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-36935-2","text":"Publisher Index Page"},{"id":430051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2023-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hyde, Matthew","contributorId":338376,"corporation":false,"usgs":false,"family":"Hyde","given":"Matthew","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Payan, Esteban","contributorId":338377,"corporation":false,"usgs":false,"family":"Payan","given":"Esteban","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barragan, Jorge","contributorId":338378,"corporation":false,"usgs":false,"family":"Barragan","given":"Jorge","email":"","affiliations":[{"id":81123,"text":"Reserva Natural de la Sociedad Civil Hato La Aurora","active":true,"usgs":false}],"preferred":false,"id":903232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stasiukynas, Diana","contributorId":338379,"corporation":false,"usgs":false,"family":"Stasiukynas","given":"Diana","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rincon, Samantha","contributorId":338382,"corporation":false,"usgs":false,"family":"Rincon","given":"Samantha","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903235,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rodriguez, Jeronimo","contributorId":338383,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Jeronimo","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903236,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crooks, Kevin R.","contributorId":338384,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":903237,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Breck, Stewart W.","contributorId":338385,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart W.","affiliations":[{"id":81125,"text":"United States Department of Agriculture (USDA)-Wildlife Services","active":true,"usgs":false}],"preferred":false,"id":903238,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Boron, Valeria","contributorId":338386,"corporation":false,"usgs":false,"family":"Boron","given":"Valeria","email":"","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":903239,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70247957,"text":"70247957 - 2023 - Open water dreissenid mussel control projects: Lessons learned from a retrospective analysis","interactions":[],"lastModifiedDate":"2023-08-29T14:38:21.203695","indexId":"70247957","displayToPublicDate":"2023-06-27T09:35:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Open water dreissenid mussel control projects: Lessons learned from a retrospective analysis","docAbstract":"Dreissenid mussels are one of the most problematic aquatic invasive species (AIS) in North America, causing substantial ecological and economic effects. To date, dreissenid mussel control efforts in open water have included physical, biological, and chemical methods. The feasibility of successful dreissenid mussel management or eradication in lakes is relatively undocumented in the freshwater management literature. This review presents information on 33 open water dreissenid mussel control projects in 23 North America lakes. We reviewed data from past dreissenid mussel control projects and identified patterns and knowledge gaps to help inform adaptive management strategies. The three key lessons learned include (1) pre- and post-treatment survey methods that are designed to meet management objectives are beneficial, e.g., by sampling for all life stages and taking into account that no survey method is completely comprehensive; (2) defining the treatment area—particularly ensuring it is sufficiently large to capture all life stages present—is critical to meeting management objectives; and (3) control projects provide an opportunity to collect water chemistry, effects on non-target organisms, and other efficacy-related data that can inform safe and effective adaptive management.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-36522-5","usgsCitation":"Dahlberg, A.D., Waller, D.L., Hammond, D., Lund, K., and Phelps, N.B., 2023, Open water dreissenid mussel control projects: Lessons learned from a retrospective analysis: Scientific Reports, v. 13, 10410, 13 p., https://doi.org/10.1038/s41598-023-36522-5.","productDescription":"10410, 13 p.","ipdsId":"IP-145079","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":442935,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-36522-5","text":"Publisher Index Page"},{"id":420241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2023-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Dahlberg, Angelique D.","contributorId":328772,"corporation":false,"usgs":false,"family":"Dahlberg","given":"Angelique","email":"","middleInitial":"D.","affiliations":[{"id":78488,"text":"Minnesota Aquatic Invasive Species Research Center and Department of Fisheries, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":881241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":881242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammond, David","contributorId":328773,"corporation":false,"usgs":false,"family":"Hammond","given":"David","email":"","affiliations":[{"id":78489,"text":"Earth Science Laboratories, Inc.","active":true,"usgs":false}],"preferred":false,"id":881243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lund, Keegan","contributorId":328774,"corporation":false,"usgs":false,"family":"Lund","given":"Keegan","email":"","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":881244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phelps, Nicholas B. D.","contributorId":328775,"corporation":false,"usgs":false,"family":"Phelps","given":"Nicholas","email":"","middleInitial":"B. D.","affiliations":[{"id":78488,"text":"Minnesota Aquatic Invasive Species Research Center and Department of Fisheries, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":881245,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246270,"text":"70246270 - 2023 - Development and application of an Infragravity Wave (InWave) driver to simulate nearshore processes","interactions":[],"lastModifiedDate":"2023-06-29T11:48:32.232329","indexId":"70246270","displayToPublicDate":"2023-06-27T06:45:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5407,"text":"Journal of Advances in Modeling Earth Systems","active":true,"publicationSubtype":{"id":10}},"title":"Development and application of an Infragravity Wave (InWave) driver to simulate nearshore processes","docAbstract":"Infragravity waves are key components of the hydro-sedimentary processes in coastal areas, especially during extreme storms. Accurate modeling of coastal erosion and breaching requires consideration of the effects of infragravity waves. Here, we present InWave, a new infragravity wave driver of the Coupled Ocean-Atmopshere-Waves-Sediment Transport (COAWST) modeling system. InWave computes the spatial and temporal variation of wave energy at the wave group scale and the associated incoming bound infragravity wave. Wave group-varying forces drive free infragravity wave growth and propagation within the hydrodynamic model of the coupled modeling system, which is the Regional Ocean Modeling System (ROMS) in this work. Since ROMS is a three-dimensional model, this coupling allows for the combined formation of undertow currents and infragravity waves. We verified the coupled InWave-ROMS with one idealized test case, one laboratory experiment, and one field experiment. The coupled modeling system correctly reproduced the propagation of gravity wave energy with acceptable numerical dissipation. It also captured the transfer of energy from the gravity band to the infragravity band, and within the different infragravity bands in the surf zone, the measured three-dimensional flow structure, and dune morphological evolution satisfactorily. The idealized case demonstrated that the infragravity wave variance depends on the directional resolution and horizontal grid resolution, which are known challenges with the approach taken here. The addition of InWave to COAWST enables novel investigation of nearshore hydro-sedimentary dynamics driven by infragravity waves using the strengths of the other modeling components, namely the three-dimensional nature of ROMS and the sediment transport routines.
The VEI 6, Tierra Blanca Joven pyroclastic sequence (30–90 km3 DRE volume), erupted from Ilopango caldera, El Salvador, in 431 CE, is the product of one of the largest eruptions of the last two millennia. The eruption devastated Central America's Mayan civilization. The eruption began with a short-lived phase of ash and pumice fall deposition and transitioned to a ‘wet’ explosive phase during which pyroclastic density currents flowed >40 km from the caldera. Detailed field and sedimentological analyses are provided for the deposits of ash-aggregate-rich pyroclastic density currents generated during early phases of the eruption. The first phase of pyroclastic density current inundation incinerated forests and deposited up to 30 m of, non-welded, ash-rich ignimbrite in proximal regions, along with ash fall layers of co-ignimbrite origin. Following fallout of a thin layer of pumice and lithic lapilli, a second phase of pyroclastic density current inundation and co-ignimbrite ash fall commenced. A range of ash aggregate types is present in the pyroclastic density current deposits and interbedded co-ignimbrite ash fall layers. Whole and broken concentrically layered ash aggregates (accretionary lapilli) reach >50 vol% in some horizons within some beds in the pyroclastic density current deposits. The evidence indicates that the ash aggregates grew within overriding co-ignimbrite ash plumes and subsequently fell into ground-hugging currents. Our findings suggest that the aggregate-rich nature of the pyroclastic density current deposits originated through incorporation of lake water into eruptive plumes, which in turn triggered rapid, pervasive aggregation within ash clouds and co-ignimbrite plumes.
The Gulf of Mexico supports many seabird species, yet data gaps describing species composition and habitat use are prevalent. We used vessel-based observations from the Gulf of Mexico Marine Assessment Program for Protected Species to identify and characterize distinct seabird assemblages in the northern Gulf of Mexico (within the U.S. Exclusive Economic Zone; nGoM). Using cluster analysis of 17 seabird species, we identified assemblages based on seabird relative density. Vessel-based surveys documented the location, species, and number of seabirds across the nGoM between 2017–2019. For each assemblage, we identified the (co-)dominant species, spatial distribution, and areas of greater relative density. We also assessed the relationship of the total relative density within each assemblage with environmental, spatial, and temporal covariates. Of the species assessed, 76% (n = 13) breed predominantly outside the nGoM basin. We identified four seabird assemblages. Two assemblages, one dominated by black tern and the other co-dominated by northern gannet/laughing gull, occurred on the continental shelf. An assemblage dominated by sooty tern occurred along the continental slope into pelagic waters. The fourth assemblage had no dominant species, was broadly distributed, and was composed of observations with low relative density (‘singles’ assemblage). Differentiation of assemblages was linked to migratory patterns, residency, and breeding location. The spatial distributions and relationships of the black tern and northern gannet/laughing gull assemblages with environmental covariates indicate associations with river outflows and ports. The sooty tern assemblage overlapped an area prone to mesoscale feature formation. The singles assemblage may reflect commuting and dispersive behaviors. These findings highlight the importance of seasonal migrations and dynamic features across the seascape, shaping seabird assemblages. Considering the potential far-ranging effects of interactions with seabirds in the nGoM, awareness of these unique patterns and potential links with other fauna could inform future monitoring, research, restoration, offshore energy, and aquaculture development in this highly industrialized sea.
Drinking-water quality is a rising concern in the United States (US), emphasizing the need to broadly assess exposures and potential health effects at the point-of-use. Drinking-water exposures to per- and poly-fluoroalkyl substances (PFAS) are a national concern, however, there is limited information on PFAS in residential tapwater at the point-of-use, especially from private-wells. We conducted a national reconnaissance to compare human PFAS exposures in unregulated private-well and regulated public-supply tapwater. Tapwater from 716 locations (269 private-wells; 447 public supply) across the US was collected during 2016–2021 including three locations where temporal sampling was conducted. Concentrations of PFAS were assessed by three laboratories and compared with land-use and potential-source metrics to explore drivers of contamination. The number of individual PFAS observed ranged from 1 to 9 (median: 2) with corresponding cumulative concentrations (sum of detected PFAS) ranging from 0.348 to 346 ng/L. Seventeen PFAS were observed at least once with PFBS, PFHxS and PFOA observed most frequently in approximately 15% of the samples. Across the US, PFAS profiles and estimated median cumulative concentrations were similar among private wells and public-supply tapwater. We estimate that at least one PFAS could be detected in about 45% of US drinking-water samples. These detection probabilities varied spatially with limited temporal variation in concentrations/numbers of PFAS detected. Benchmark screening approaches indicated potential human exposure risk was dominated by PFOA and PFOS, when detected. Potential source and land-use information was related to cumulative PFAS concentrations, and the number of PFAS detected; however, corresponding relations with specific PFAS were limited likely due to low detection frequencies and higher detection limits. Information generated supports the need for further assessments of cumulative health risks of PFAS as a class and in combination with other co-occurring contaminants, particularly in unmonitored private-wells where information is limited or not available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2023.108033","usgsCitation":"Smalling, K., Romanok, K.M., Bradley, P.M., Morriss, M.C., Gray, J., Kanagy, L.K., Gordon, S.E., Williams, B., Breitmeyer, S.E., Jones, D.K., DeCicco, L.A., Eagles-Smith, C., and Wagner, T., 2023, Per- and polyfluoroalkyl substances (PFAS) in United States tapwater: Comparison of underserved private-well and public-supply exposures and associated health implications: Environment International, v. 178, 108033, 12 p., https://doi.org/10.1016/j.envint.2023.108033.","productDescription":"108033, 12 p.","ipdsId":"IP-137132","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science 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wildlife when direct sampling of animals is difficult. Although several faecal DNA extraction methods exist, their efficacy varies between species. Previous attempts to amplify mitochondrial DNA (mtDNA) markers from faeces of wild dugongs (Dugong dugon) have met with limited success and nuclear markers (microsatellites) have been unsuccessful. This study aimed to establish a tool for sampling both mtDNA and nuclear DNA (nDNA) from dugong faeces by modifying approaches used in studies of other large herbivores. First, a streamlined, cost-effective DNA extraction method that enabled the amplification of both mitochondrial and nuclear markers from large quantities of dugong faeces was developed. Faecal DNA extracted using a new ‘High Volume- Cetyltrimethyl Ammonium Bromide- Phenol-Chloroform-Isoamyl Alcohol’ (HV-CTAB-PCI) method was found to achieve comparable amplification results to extraction of DNA from dugong skin. As most prevailing practices advocate sampling from the outer surface of a stool to maximise capture of sloughed intestinal cells, this study compared amplification success of mtDNA between the outer and inner layers of faeces, but no difference in amplification was found. Assessment of the impacts of faecal age or degradation on extraction, however, demonstrated that fresher faeces with shorter duration of environmental (seawater) exposure amplified both markers better than eroded scats. Using the HV-CTAB-PCI method, nuclear markers were successfully amplified for the first time from dugong faeces. The successful amplification of single nucleotide polymorphism (SNP) markers represents a proof-of-concept showing that DNA from dugong faeces can potentially be utilised in population genetic studies. This novel DNA extraction protocol offers a new tool that will facilitate genetic studies of dugongs and other large and cryptic marine herbivores in remote locations.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0278792","usgsCitation":"Ooi, V., McMichael, L., Hunter, M., Takoukam Kamla, A., and Lanyon, J.M., 2023, A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong: PLoS ONE, v. 18, no. 6, e0278792, 29 p., https://doi.org/10.1371/journal.pone.0278792.","productDescription":"e0278792, 29 p.","ipdsId":"IP-147065","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0278792","text":"Publisher Index Page"},{"id":418217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","otherGeospatial":"Moreton Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.37192416070502,\n -27.859614592565208\n ],\n [\n 153.42962470601918,\n -27.687005800163497\n ],\n [\n 153.43511999604937,\n -27.504375776224627\n ],\n [\n 153.46534409121273,\n -27.406848872159316\n ],\n [\n 153.3939053208257,\n -27.204205934764204\n ],\n [\n 153.38566238578045,\n -27.050146132142267\n ],\n [\n 153.17134607461963,\n -27.050146132142267\n ],\n [\n 153.0422067589185,\n -27.106414779566876\n ],\n [\n 152.99824443867976,\n -27.194430673154535\n ],\n [\n 153.08891672417235,\n -27.23108348366104\n ],\n [\n 153.0202255988005,\n -27.297028138020522\n ],\n [\n 153.08616907915723,\n -27.362933646179656\n ],\n [\n 153.14661726948384,\n -27.38489343868985\n ],\n [\n 153.18233665467994,\n -27.492189631662583\n ],\n [\n 153.2345419099613,\n -27.51168681530772\n ],\n [\n 153.2867471652453,\n -27.601816322987915\n ],\n [\n 153.29224245527553,\n -27.711333458802045\n ],\n [\n 153.34994300058702,\n -27.786714713843168\n ],\n [\n 153.37192416070502,\n -27.859614592565208\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ooi, Vicky","contributorId":310440,"corporation":false,"usgs":false,"family":"Ooi","given":"Vicky","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMichael, Lee","contributorId":310441,"corporation":false,"usgs":false,"family":"McMichael","given":"Lee","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takoukam Kamla, Aristide","contributorId":204221,"corporation":false,"usgs":false,"family":"Takoukam Kamla","given":"Aristide","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lanyon, Janet M.","contributorId":204224,"corporation":false,"usgs":false,"family":"Lanyon","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875697,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245409,"text":"70245409 - 2023 - The Colorado River water crisis: Its origin and the future","interactions":[],"lastModifiedDate":"2023-11-07T15:04:05.989924","indexId":"70245409","displayToPublicDate":"2023-06-17T06:45:50","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"The Colorado River water crisis: Its origin and the future","docAbstract":"During much of the 21st century, natural runoff in the Colorado River basin has declined, while consumption has remained relatively constant, leading to historically low reservoir storage. Between January 2000 and April 2023, the amount of water stored in Lake Mead and Lake Powell, the two largest reservoirs in the United States, declined by 33.5 million acre feet (41.3 billion cubic meters). As of April 2023, total basin-wide storage was sufficient to support the 21st century average rate of basin-wide consumption for only 15 months. Runoff in spring 2023 is predicted to be large, providing a short-term reprieve. However, it will take four to five additional unusually wet years in succession to refill Lake Powell and Lake Mead if basin-wide water use remains unchanged. Increasing evapotranspiration and dry soils associated with global climate change makes such a scenario unlikely. To stabilize reservoir storage, basin-wide use needs to equal modern runoff. To recover reservoir storage, basin-wide use needs to decline even more. Based on 21st century average runoff, a 13%–20% decline in basin-wide use would allow for stabilization and some reservoir storage recovery. Future policy debate about reservoir operations will inevitably concern whether most, or all, reservoir storage should be in Lake Mead or in Lake Powell. The choice of one or the other will result in significantly different environmental and recreational outcomes for Glen Canyon and the Grand Canyon.
","language":"English","publisher":"Wiley Interdisciplinary Reviews","doi":"10.1002/wat2.1672","usgsCitation":"Schmidt, J.C., Yackulic, C., and Kuhn, E., 2023, The Colorado River water crisis: Its origin and the future: WIREs Water, v. 10, no. 6, e1672, 11 p., https://doi.org/10.1002/wat2.1672.","productDescription":"e1672, 11 p.","ipdsId":"IP-148177","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":443043,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wat2.1672","text":"Publisher Index Page"},{"id":418391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Baja California, California, Colorado, Nevada, New Mexico, Sonora, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.48421418796046,\n 31.35434215860566\n ],\n [\n -113.65259586662187,\n 32.23920414412936\n ],\n [\n -112.21089756604964,\n 31.90052568352887\n ],\n [\n -111.87558421754458,\n 32.20952085093056\n ],\n [\n -111.28541066018629,\n 32.11399667847604\n ],\n [\n -111.23279241837177,\n 31.437228609979257\n ],\n [\n -110.94817616136105,\n 30.97237021578711\n ],\n [\n -109.99614795253682,\n 31.0580658429583\n ],\n [\n -109.765123637271,\n 31.565815216207625\n ],\n [\n -109.2216186810205,\n 31.780902751508492\n ],\n [\n -108.70850128918396,\n 31.58004054549238\n ],\n [\n -107.23835863291889,\n 32.490078241661664\n ],\n [\n -106.730360119866,\n 34.66458922372419\n ],\n [\n -107.42958642929439,\n 35.07481907867975\n ],\n [\n -106.85826554201257,\n 35.61881061726045\n ],\n [\n -105.7061398095985,\n 37.33375003848154\n ],\n [\n -105.879787594186,\n 39.89096635274717\n ],\n [\n -106.74739533342402,\n 41.696412051333766\n ],\n [\n -106.68778798532564,\n 42.531437760880465\n ],\n [\n -108.38774334794128,\n 42.38607065176245\n ],\n [\n -110.40321867986886,\n 43.243504117137775\n ],\n [\n -111.01626499710237,\n 42.72084370600541\n ],\n [\n -111.07561236378847,\n 41.02050419347333\n ],\n [\n -112.02989616951957,\n 39.12042969242722\n ],\n [\n -113.30959508904654,\n 37.1563348714911\n ],\n [\n -114.37484829397191,\n 37.048946927772775\n ],\n [\n -114.7380747976792,\n 38.490173161398246\n ],\n [\n -116.45388765022786,\n 38.98493898775925\n ],\n [\n -116.41298707291212,\n 37.45745026322449\n ],\n [\n -115.37080488894956,\n 35.768178708278725\n ],\n [\n -115.16334164848244,\n 33.20321074731645\n ],\n [\n -116.48506247630979,\n 33.87016090096576\n ],\n [\n -116.22048705379954,\n 32.88635352395437\n ],\n [\n -115.44554171380956,\n 31.52088586510753\n ],\n [\n -114.48421418796046,\n 31.35434215860566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":876047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, Eric","contributorId":311212,"corporation":false,"usgs":false,"family":"Kuhn","given":"Eric","email":"","affiliations":[{"id":67359,"text":"General Manager, Colorado River Water Conservation District (retired) Glenwood Springs, CO","active":true,"usgs":false}],"preferred":false,"id":876049,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70245089,"text":"70245089 - 2023 - Pathology and infectious agents of unionid mussels: A primer for pathologists in disease surveillance and investigation of mortality events","interactions":[],"lastModifiedDate":"2023-09-06T16:11:31.128796","indexId":"70245089","displayToPublicDate":"2023-06-15T09:34:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3687,"text":"Veterinary Pathology","active":true,"publicationSubtype":{"id":10}},"title":"Pathology and infectious agents of unionid mussels: A primer for pathologists in disease surveillance and investigation of mortality events","docAbstract":"Freshwater mussels are one of the most imperiled groups of organisms in the world, and more than 30 species have gone extinct in the last century. While habitat alteration and destruction have contributed to the declines, the role of disease in mortality events is unclear. In an effort to involve veterinary pathologists in disease surveillance and the investigation of freshwater mussel mortality events, we provide information on the conservation status of unionids, sample collection and processing techniques, and unique and confounding anatomical and physiological differences. We review the published accounts of pathology and infectious agents described in freshwater mussels including neoplasms, viruses, bacteria, fungi, fungal-like agents, ciliated protists, Aspidogastrea, Digenea, Nematoda, Acari, Diptera, and Odonata. Of the identified infectious agents, a single viral disease, Hyriopsis cumingii plague disease, that occurs only in cultured mussels is known to cause high mortality. Parasites including ciliates, trematodes, nematodes, mites, and insects may decrease host fitness, but are not known to cause mortality. Many of the published reports identify infectious agents at the light or ultrastructural microscopy level with no lesion or molecular characterization. Although metagenomic analyses provide sequence information for infectious agents, studies often fail to link the agents to tissue changes at the light or ultrastructural level or confirm their role in disease. Pathologists can bridge this gap between identification of infectious agents and confirmation of disease, participate in disease surveillance to ensure successful propagation programs necessary to restore decimated populations, and investigate mussel mortality events to document pathology and identify causality.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/03009858231171666","usgsCitation":"Knowles, S., Dennis, M., McElwain, A., Leis, E., and Richard, J.C., 2023, Pathology and infectious agents of unionid mussels: A primer for pathologists in disease surveillance and investigation of mortality events: Veterinary Pathology, v. 60, no. 5, p. 510-528, https://doi.org/10.1177/03009858231171666.","productDescription":"19 p.","startPage":"510","endPage":"528","ipdsId":"IP-145112","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":418130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennis, Michelle 0000-0002-9075-2032","orcid":"https://orcid.org/0000-0002-9075-2032","contributorId":310343,"corporation":false,"usgs":false,"family":"Dennis","given":"Michelle","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":875429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McElwain, Andrew 0000-0001-8153-2196","orcid":"https://orcid.org/0000-0001-8153-2196","contributorId":310345,"corporation":false,"usgs":false,"family":"McElwain","given":"Andrew","email":"","affiliations":[{"id":67147,"text":"State University of New York Oswego","active":true,"usgs":false}],"preferred":false,"id":875430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leis, Eric","contributorId":179325,"corporation":false,"usgs":false,"family":"Leis","given":"Eric","affiliations":[],"preferred":false,"id":875431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richard, Jordan C. 0000-0002-9981-7832","orcid":"https://orcid.org/0000-0002-9981-7832","contributorId":270965,"corporation":false,"usgs":false,"family":"Richard","given":"Jordan","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":875432,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245102,"text":"70245102 - 2023 - Implications of tree expansion in shrubland ecosystems for two generalist avian predators","interactions":[],"lastModifiedDate":"2023-06-15T13:58:45.922001","indexId":"70245102","displayToPublicDate":"2023-06-15T08:50:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Implications of tree expansion in shrubland ecosystems for two generalist avian predators","docAbstract":"Shrublands globally have undergone structural changes due to plant invasions, including the expansion of native trees. Removal of native conifer trees, especially juniper (Juniperus spp.), is occurring across the Great Basin of the western U.S. to support declining sagebrush (Artemisia spp.) habitats and associated wildlife species, such as greater sage-grouse (Centrocercus urophasianus). One justification for conifer removal is that it may improve survival of sagebrush-associated wildlife by reducing the abundance of avian predators. However, the relationship between conifer expansion and predator distributions has not been explicitly evaluated. Further, although structural characteristics of habitat are important for generalist predators, overall prey abundance may also affect habitat use by predators. We examined habitat use of common ravens (Corvus corax) and red-tailed hawks (Buteo jamaicensis), two generalist predators whose populations are increasing in western North America, to variation in structural characteristics and prey distributions in sagebrush habitat that has experienced conifer expansion. Structural characteristics of habitat were important predictors of habitat use for both ravens and red-tailed hawks, whereas measures of prey abundance were unimportant for both species likely because generalist predators can use a wide variety of food resources. Ravens, but not red-tailed hawks, responded positively to increasing cover of juniper and the probability of habitat use was highest (> 0.95) where juniper cover within 100 m was > 20%. Habitat use by red-tailed hawks, but not ravens, was greater near cliffs but was not associated with juniper cover. Our study suggests that the removal of conifer in similar environments may lower the probability of habitat use for ravens, a common predator with significant impacts on many prey species. Therefore, we suggest conifer removal may improve sage-grouse reproductive success and survival depending on responses to conifer removal from other predators. Our results may be reflective of similar changes in rangeland ecosystems around the world undergoing expansion of conifer and other woody vegetation. Though species identities differ from sagebrush habitats, generalist avian predators in other habitats may have similar relationships with structural resources.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0286478","usgsCitation":"Young, A.C., Katzner, T., Shinneman, D.J., and Johnson, T.N., 2023, Implications of tree expansion in shrubland ecosystems for two generalist avian predators: PLoS ONE, v. 18, no. 6, e0286478, 19 p., https://doi.org/10.1371/journal.pone.0286478.","productDescription":"e0286478, 19 p.","ipdsId":"IP-138528","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":443070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0286478","text":"Publisher Index Page"},{"id":418128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.5173530797766,\n 42.071580753595896\n ],\n [\n -115.5173530797766,\n 43.20939209273595\n ],\n [\n -116.98604075296564,\n 43.20939209273595\n ],\n [\n -116.98604075296564,\n 42.071580753595896\n ],\n [\n -115.5173530797766,\n 42.071580753595896\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Young, Aaron C. 0000-0002-7577-4081","orcid":"https://orcid.org/0000-0002-7577-4081","contributorId":306196,"corporation":false,"usgs":false,"family":"Young","given":"Aaron","email":"","middleInitial":"C.","affiliations":[{"id":33345,"text":" University of Idaho","active":true,"usgs":false}],"preferred":false,"id":875476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":875477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":875478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Tracey N. 0000-0003-3480-8596","orcid":"https://orcid.org/0000-0003-3480-8596","contributorId":223735,"corporation":false,"usgs":false,"family":"Johnson","given":"Tracey","email":"","middleInitial":"N.","affiliations":[{"id":40761,"text":"Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID 83844","active":true,"usgs":false}],"preferred":false,"id":875479,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247521,"text":"70247521 - 2023 - Accounting for spatial habitat and management boundaries when estimating forest bird population distribution and density: Inferences from a soap film smoother","interactions":[],"lastModifiedDate":"2023-08-10T12:09:25.852819","indexId":"70247521","displayToPublicDate":"2023-06-14T07:06:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for spatial habitat and management boundaries when estimating forest bird population distribution and density: Inferences from a soap film smoother","docAbstract":"Birds are often obligate to specific habitats which can result in study areas with complex boundaries due to sudden changes in vegetation or other features. This can result in study areas with concave arcs or that include holes of unsuitable habitat such as lakes or agricultural fields. Spatial models used to produce species’ distribution and density estimates need to respect such boundaries to make informed decisions for species conservation and management. The soap film smoother is one model for complex study regions which controls the boundary behaviour, ensuring realistic values at the edges of the region. We apply the soap film smoother to account for boundary effects and compare it with thin plate regression spline (TPRS) smooth and design-based conventional distance sampling methods to produce abundance estimates from point-transect distance sampling collected data on Hawai‘i ‘Ākepa Loxops coccineus in the Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex, Hawai‘i Island, USA. The soap film smoother predicted zero or near zero densities in the northern part of the domain and two hotspots (in the southern and central parts of the domain). Along the boundary the soap film model predicted relatively high densities where ‘Ākepa occur in the adjacent forest and near zero elsewhere. The design-based and soap film abundance estimates were nearly identical. The width of the soap film confidence interval was 16.5% and 0.8% wider than the width of the TPRS smooth and design-based confidence intervals, respectively. The peaks in predicted densities along the boundary indicates leakage by the TPRS smooth. We provide a discussion of the statistical methods, biological findings and management implications of applying soap film smoothers to estimate forest bird population status.
We use a combination of proxy records from a high-resolution analysis of sediments from Searsville Lake and adjacent Upper Lake Marsh and historical records to document over one and a half centuries of vegetation and socio-ecological change—relating to logging, agricultural land use change, dam construction, chemical applications, recreation, and other drivers—on the San Francisco Peninsula. A relatively open vegetation with minimal oak (Quercus) and coast redwood (Sequoia sempervirens) in the late 1850s reflects widespread logging and grazing during the nineteenth century. Forest and woodland expansion occurred in the early twentieth century, with forests composed of coast redwood and oak, among other taxa, as both logging and grazing declined. Invasive species include those associated with pasturage (Rumex, Plantago), landscape disturbance (Urtica, Amaranthaceae), planting for wood production and wind barriers (Eucalyptus), and agriculture. Agricultural species, including wheat, rye, and corn, were more common in the early twentieth century than subsequently. Wetland and aquatic pollen and fungal spores document a complex hydrological history, often associated with fluctuating water levels, application of algaecides, raising of Searsville Dam, and construction of a levee. By pairing the paleoecological and historical records of both lakes, we have been able to reconstruct the previously undocumented impacts of socio-ecological influences on this drainage, all of which overprinted known climate changes. Recognizing the ecological manifestations of these impacts puts into perspective the extent to which people have interacted with and transformed the environment in the transition into the Anthropocene.
","language":"English","publisher":"Springer","doi":"10.1007/s10113-023-02056-9","usgsCitation":"Anderson, R., Stegner, M.A., La Selle, S., Sherrod, B.L., Barnosky, A.D., and Hadly, E.A., 2023, Witnessing history: Comparison of a century of sedimentary and written records in a California protected area: Regional Environmental Change, v. 23, 65, 18 p., https://doi.org/10.1007/s10113-023-02056-9.","productDescription":"65, 18 p.","ipdsId":"IP-147736","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10113-023-02056-9","text":"Publisher Index Page"},{"id":417945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Jasper Ridge Biological Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23418768300823,\n 37.3930404399613\n ],\n [\n -122.20397178645686,\n 37.40170883665597\n ],\n [\n -122.209679233583,\n 37.404509181302004\n ],\n [\n -122.21387588588198,\n 37.406109331254214\n ],\n [\n -122.21773680599699,\n 37.4091761898071\n ],\n [\n -122.21857613645665,\n 37.411576252406434\n ],\n [\n -122.22109412783595,\n 37.4118429212817\n ],\n [\n -122.22176559220381,\n 37.41424289844102\n ],\n [\n -122.24123805887044,\n 37.4121095892076\n ],\n [\n -122.2456025772612,\n 37.408376151853375\n ],\n [\n -122.2459383094448,\n 37.406776050314505\n ],\n [\n -122.24543471116908,\n 37.403842442069205\n ],\n [\n -122.24778483645659,\n 37.403842442069205\n ],\n [\n -122.24963136346803,\n 37.40264229649942\n ],\n [\n -122.2494634973759,\n 37.3998418820846\n ],\n [\n -122.23418768300823,\n 37.3930404399613\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, R. Scott","contributorId":6983,"corporation":false,"usgs":false,"family":"Anderson","given":"R. Scott","affiliations":[{"id":7034,"text":"School of Earth Sciences and Environmental Sustainability at Northern Arizona University, in Flagstaff","active":true,"usgs":false}],"preferred":false,"id":874942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stegner, M. Allison","contributorId":197658,"corporation":false,"usgs":false,"family":"Stegner","given":"M.","email":"","middleInitial":"Allison","affiliations":[],"preferred":false,"id":874943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":874944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":874945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnosky, Anthony D.","contributorId":197553,"corporation":false,"usgs":false,"family":"Barnosky","given":"Anthony","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":874946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hadly, Elizabeth A.","contributorId":197554,"corporation":false,"usgs":false,"family":"Hadly","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":874947,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70244268,"text":"70244268 - 2023 - Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors","interactions":[],"lastModifiedDate":"2023-06-12T11:31:14.028063","indexId":"70244268","displayToPublicDate":"2023-06-08T06:25:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors","docAbstract":"Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.
Understanding potential limiting factors affecting population growth of the endangered pallid sturgeon, Scaphirhynchus albus, is important in the upper (UMOR) and lower Missouri River (LMOR) basins. The UMOR is upstream of several reservoirs and generally has more natural habitat features, whereas the LMOR is downstream of these reservoirs and has been channelized to support navigation. In both sections, pallid sturgeon recruitment to age-1 is a concern, but hypothesized for different reasons. One hypothesis in the LMOR centers on food limitation for age-0 fish, which is not considered an issue in the UMOR, but evaluating this hypothesis is challenging given the rarity of age-0 pallid sturgeon. As a result, the related, more abundant shovelnose sturgeon (S. platorhynchus) has been considered as a potential surrogate to assess food-related hypotheses. Thus, the purpose of our study was to compare diets of age-0 sturgeon captured in 2016 from three reaches in the LMOR (Copeland, Langdon, and Lexington) with individuals captured from a reach in the UMOR (Williston) during the same year to provide additional context regarding potential food limitation in the LMOR. Consumption percentage (prey weight in the gut as a percentage of body weight) was similar among all reaches, but diet composition was different for the most downstream reach in the LMOR. Age-0 sturgeon in the UMOR reach as well as the two upstream LMOR reaches primarily consumed Diptera larvae along with Ephemeroptera nymphs. In contrast, age-0 sturgeon in the most downstream LMOR reach (Lexington) almost exclusively consumed Diptera larvae. These results may provide information on relative differences in prey availability between Lexington and the other upstream reaches but the similarity in consumption percentage values across all reaches provide further evidence that age-0 sturgeon are not food limited in the LMOR.
In an investigation of pharmaceutical contamination in the Lac du Flambeau Chain of Lakes (hereafter referred to as “the Chain”), few contaminants were detected; only eight pharmaceuticals and one pesticide were identified among the 110 pharmaceuticals and other organic contaminants monitored in surface water samples. This study, conducted in cooperation with the Lac du Flambeau Tribe’s Water Resource Program, investigated these organic contaminants and potential biological effects in channels connecting lakes throughout the Chain, including the Moss Lake Outlet site, adjacent to the wastewater treatment plant lagoon. Of the 6 sites monitored and 24 samples analyzed, sample concentrations and contaminant detection frequencies were greatest at the Moss Lake Outlet site; however, the concentrations and detection frequencies of this study were comparable to other pharmaceutical investigations in basins with similar characteristics. Because established water-quality benchmarks do not exist for the pharmaceuticals detected in this study, alternative screening-level water-quality benchmarks, developed using two U.S. Environmental Protection Agency toxicological resources (ToxCast database and ECOTOX knowledgebase), were used to estimate potential biological effects associated with the observed contaminant concentrations. Two contaminants (caffeine and thiabendazole) exceeded the prioritization threshold according to ToxCast alternative benchmarks, and four contaminants (acetaminophen, atrazine, caffeine, and carbamazepine) exceeded the prioritization threshold according to ECOTOX alternative benchmarks. Atrazine, an herbicide, was the most frequently detected contaminant (79% of samples), and it exhibited the strongest potential for biological effects due to its high estimated potency. Insufficient toxicological information within ToxCast and ECOTOX for gabapentin and methocarbamol (which had the two greatest concentrations in this study) precluded alternative benchmark development. This data gap presents unknown potential environmental impacts. Future research examining the biological effects elicited by these two contaminants as well as the others detected in this study would further elucidate the ecological relevance of the water chemistry results generated though this investigation.
The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California.
S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile 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 (1) survival and growth within each habitat unit and (2) movement of fish among habitat units.
The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or 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 timeseries 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 key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates.
Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability.
Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
One challenge in wildlife conservation is understanding how various threats and management actions may influence long-term population viability. This is particularly evident when there is considerable uncertainty regarding population structure and vital rates. Reassessment of current knowledge and population trends is necessary for listed species to improve management actions that benefit conservation. We present an updated population viability analysis for northern Great Plains piping plovers (Charadrius melodus circumcinctus) based on the latest scientific data on survival, fecundity, and connectivity. Further, we explore the consequences of potential management actions and the stochastic effects of global climate change on population viability through changes in survival and fecundity. Our results predict elevated risks of extinction after 50 years (0.088 – 0.373) compared to previous predictions (0.033) based on assumed conditions of low connectivity among four major breeding groups structured as a metapopulation. We explored eight scenarios based on empirically-derived, higher connectivity rates and found that the northern Great Plains population never had a mean predicted population growth rate greater than one (0.946 – 0.996). Two scenarios that simulated a reduction in adult survival showed higher extinction probabilities (0.267 – 0.373), whereas two other scenarios that simulated an increase in fecundity exhibited lower extinction probabilities (0.088 – 0.103). These results indicate that viability of the northern Great Plains population of piping plovers could be improved with management actions that increase fecundity as long as adult survival is not simultaneously reduced. Lastly, breeding groups appeared to function less independently when connectivity rates were higher, as the breeding population was divided evenly among breeding groups. This indicates that the presumed metapopulation structure of our study system may need to be re-evaluated, and that empirically-based estimates of connectivity are essential to assessing population viability of mobile species that exhibit a spatially structured distribution.
Factors such as soil type and precipitation vary across rangeland landscapes, and these factors affect restoration outcomes and ultimately mean that “one size fits all” management strategies are not effective across large, complex landscapes. Big sagebrush (Artemisia tridentata) is a foundational rangeland species that is important to wildlife habitat across the western U.S. On the Colorado Plateau, sagebrush is important browse for ungulates, such as mule deer and pronghorn, which motivates a great deal of restoration effort. However, most scientific knowledge of big sagebrush comes from the Great Basin, and we know much less about how to restore sagebrush on the Colorado Plateau, where soils and precipitation patterns are different and conditions are warmer and drier. This fact sheet describes research about establishing and restoring sagebrush seedlings on the Colorado Plateau.
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