Agricultural land-use conversion has fragmented prairie wetland habitats in the Prairie Pothole Region (PPR), an area with one of the most wetland dense regions in the world. This fragmentation can lead to negative consequences for wetland obligate organisms, heightening risk of local extinction and reducing evolutionary potential for populations to adapt to changing environments.
This study models biotic connectivity of prairie-pothole wetlands using landscape genetic analyses of the northern leopard frog (Rana pipiens) to (1) identify population structure and (2) determine landscape factors driving genetic differentiation and possibly leading to population fragmentation.
Frogs from 22 sites in the James River and Lake Oahe river basins in North Dakota were genotyped using Best-RAD sequencing at 2868 bi-allelic single nucleotide polymorphisms (SNPs). Population structure was assessed using STRUCTURE, DAPC, and fineSTRUCTURE. Circuitscape was used to model resistance values for ten landscape variables that could affect habitat connectivity.
STRUCTURE results suggested a panmictic population, but other more sensitive clustering methods identified six spatially organized clusters. Circuit theory-based landscape resistance analysis suggested land use, including cultivated crop agriculture, and topography were the primary influences on genetic differentiation.
While the R. pipiens populations appear to have high gene flow, we found a difference in the patterns of connectivity between the eastern portion of our study area which was dominated by cultivated crop agriculture, versus the western portion where topographic roughness played a greater role. This information can help identify amphibian dispersal corridors and prioritize lands for conservation or restoration.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01515-8","usgsCitation":"Waraniak, J.M., Mushet, D., and Stockwell, C.A., 2022, Over the hills and through the farms: Land use and topography influence genetic connectivity of northern leopard frog (Rana pipiens) in the Prairie Pothole Region: Landscape Ecology, v. 37, p. 2877-2893, https://doi.org/10.1007/s10980-022-01515-8.","productDescription":"17 p.","startPage":"2877","endPage":"2893","ipdsId":"IP-137156","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":446618,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-022-01515-8","text":"Publisher Index Page"},{"id":406585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.39257812499999,\n 45.920587344733654\n ],\n [\n -96.85546875,\n 45.920587344733654\n ],\n [\n -96.85546875,\n 48.574789910928864\n ],\n [\n -102.39257812499999,\n 48.574789910928864\n ],\n [\n -102.39257812499999,\n 45.920587344733654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2022-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Waraniak, Justin M.","contributorId":211882,"corporation":false,"usgs":false,"family":"Waraniak","given":"Justin","email":"","middleInitial":"M.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":851527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":248468,"corporation":false,"usgs":true,"family":"Mushet","given":"David M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":851528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Craig A.","contributorId":194252,"corporation":false,"usgs":false,"family":"Stockwell","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":851529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70246958,"text":"70246958 - 2022 - Estimating the effect of tidal marsh restoration on housing prices: A hedonic analysis in the Nisqually National Wildlife Refuge, Washington, USA","interactions":[],"lastModifiedDate":"2023-07-20T11:42:22.401021","indexId":"70246958","displayToPublicDate":"2022-08-30T06:37:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the effect of tidal marsh restoration on housing prices: A hedonic analysis in the Nisqually National Wildlife Refuge, Washington, USA","docAbstract":"Streamflow drought is a recurring challenge, and understanding spatiotemporal patterns of past droughts is needed to manage future water resources. We examined regional patterns in streamflow drought metrics and compared these metrics to low flow timing and magnitude using long-term daily records for 555 minimally disturbed watersheds. For each streamgage, we calculated streamflow drought duration (number of days) and deficit (flow volume below a specified threshold) for each climate year (April 1–March 31). We identified drought using five thresholds (2%–30%) and two approaches: variable thresholds with unique values for each day of the year, and a fixed threshold based on all period-of-record flows. We then analyzed drought trends using the Mann-Kendall test with persistence adjustment for 1921–2020, 1951–2020, and 1981–2020, and computed correlations between annual streamflow drought metrics and climate metrics using values from a monthly water balance model. Spatial patterns in drought metrics were consistent between variable and fixed approaches, though fixed threshold durations were typically longer and variable threshold deficits larger. High interannual variability in drought duration emerged in the central, interior west, and southwestern U.S., with high deficit variability in the interior west. Drought metrics were weakly correlated with low flow magnitude and timing, providing unique information. Drought duration and deficit increased in the southern and western U.S. for both 1951–2020 and 1981–2020, particularly using fixed thresholds, and paralleled trends in aridity. Projections of continued aridification for the southern and western U.S. may increase drought durations and deficits and intensify water availability impacts.
The National Gap Analysis Project created species habitat distribution models for all terrestrial vertebrates in the United States to support conservation assessments and explore patterns of species richness. Those models link species to specific habitats throughout the range of each species. For most vertebrates, there are not enough occurrence data to drive inductive, range-wide species habitat distribution models at high spatial and thematic resolution. However, it is possible to use occurrence data for model evaluation. The combination of citizen science, formal species survey work, and digitized specimen archives are making millions of observations available to the scientific community. Our challenge is to combine the mostly unstructured data into metrics that help us characterize and understand patterns of biodiversity. In this work, we propose two model-evaluation metrics. The first, a buffer proportion assessment, is based on the proportion of habitat in the range relative to the mean proportion of habitat around each of the species’ occurrence records. The second is a measure of the sensitivity (proportion of true presence) to buffer distances around occurrence records. The buffer proportion is a modification of model prevalence versus point prevalence metric, whereby comparison to a null model allows us to determine if the model performs better or worse than random.
In this report, we describe the workflow used to compile and filter the species occurrence records from online resources (for example, the Global Biodiversity Information Facility) and show results for a single species, Desmognathus quadramaculatus (black-bellied salamander). For the salamander, 222 occurrence points met our criteria for inclusion in the evaluation. We found the model performed better than random with a buffer proportion index of 1.745, indicating about 5 times as much habitat was found adjacent to known occurrence records than would be expected from randomly located sites throughout the range. Sensitivity increased with larger buffer distances and leveled off to around 0.7 between 1,000- and 2,000-meter buffer distances, indicating the model is likely best suited for scales exceeding 1,000 meters. We plan to report the buffer proportion assessment and sensitivity metrics along with the full species model reports to increase understanding of the model’s performance and to use the metrics to help prioritize revisions to the models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm2A19","collaboration":"Prepared in cooperation with North Carolina State University, North Carolina Cooperative Fish and Wildlife Research Unit, Department of Applied Ecology","usgsCitation":"Rubino, M.J., McKerrow, A.J., Tarr, N.M., and Williams, S.G., 2022, Methods for evaluating Gap Analysis Project habitat distribution maps with species occurrence data: U.S. Geological Survey Techniques and Methods 2-A19, 13 p., https://doi.org/10.3133/tm2A19.","productDescription":"Report: vi, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124954","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":405205,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/02/a19/images"},{"id":405206,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/02/a19/tm2a19.xml"},{"id":405202,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/a19/tm2a19.pdf","text":"Report","size":"1.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 2A-19"},{"id":405201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/a19/coverthb.jpg"},{"id":405204,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H1308B","text":"USGS data release","linkHelpText":"Black-bellied Salamander (Desmognathus quadramaculatus) aBESAx_CONUS_2001v1 Habitat Map"}],"country":"United States","state":"Alabama, Georgia, North Carolina, Tennessee, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9580078125,\n 36.73888412439431\n ],\n [\n -82.41943359375,\n 36.73888412439431\n ],\n [\n -83.1884765625,\n 36.43896124085945\n ],\n [\n -84.04541015625,\n 36.13787471840729\n ],\n [\n -84.92431640625,\n 35.99578538642032\n ],\n [\n -85.7373046875,\n 35.38904996691167\n ],\n [\n -86.24267578125,\n 35.11990857099681\n ],\n [\n -86.220703125,\n 34.50655662164561\n ],\n [\n -85.58349609375,\n 34.361576287484176\n ],\n [\n -84.17724609375,\n 34.79576153473033\n ],\n [\n -82.81494140625,\n 35.02999636902566\n ],\n [\n -82.08984375,\n 35.28150065789119\n ],\n [\n -81.10107421874999,\n 35.44277092585766\n ],\n [\n -80.26611328125,\n 36.2265501474709\n ],\n [\n -80.068359375,\n 36.77409249464195\n ],\n [\n -79.7607421875,\n 37.37015718405753\n ],\n [\n -79.453125,\n 37.71859032558816\n ],\n [\n -79.2333984375,\n 38.09998264736481\n ],\n [\n -79.25537109375,\n 38.59970036588819\n ],\n [\n -79.65087890624999,\n 38.54816542304656\n ],\n [\n -80.04638671875,\n 38.42777351132902\n ],\n [\n -80.5517578125,\n 38.39333888832238\n ],\n [\n -80.83740234375,\n 37.996162679728116\n ],\n [\n -81.18896484375,\n 37.405073750176925\n ],\n [\n -81.49658203125,\n 36.914764288955936\n ],\n [\n -81.9580078125,\n 36.73888412439431\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Core Science Analytics and Synthesis
U.S. Geological Survey
Box 25046, Mail Stop 302
Denver, CO 80225
Unselective fishing involves activities that target the entire assemblage rather than specific fish species, size classes, or trophic levels. This common fishing approach has been in practice for decades in inland waters in China but its implications for biodiversity remain unclear. We addressed this issue by studying fish assemblages in freshwater lakes (five fishing lakes, one reference lake, and a total of 51 sampling sites) between pre- and post-fishing time-periods in Eastern China during 2017–2019. The effects of lake, fishing period, and their interactions on fish abundance, biomass, and diversity indices were assessed. Multivariate analysis was conducted to test for differences in fish assemblages among lakes and between fishing periods. After the implementation of fishing activities, significant reductions in fish species richness, abundance, biomass, and all three life-history strategies (opportunistic, equilibrium, and periodic) were observed in fishing lakes, whereas opposite trends were observed in the reference lake. Compositional similarity of fish assemblages among fishing lakes increased over the three-year monitoring period. Our results suggest that unselective fishing reduces fish diversity and homogenizes fish assemblage structure in lakes. These findings have important implications for protecting both biodiversity and fisheries in inland waters in China and are applicable to other countries or regions that rely on fish as a major food source.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watbs.2022.100055","usgsCitation":"Liu, H., Chen, Y., Gozlan, R., Qu, X., Xia, W., Cheng, F., Wang, L., Paukert, C.P., Olden, J., and Xie, S., 2022, Fish diversity reduction and assemblage structure homogenization in lakes: A case study on unselective fishing in China: Water Biology and Security, v. 1, 100055, 8 p., https://doi.org/10.1016/j.watbs.2022.100055.","productDescription":"100055, 8 p.","ipdsId":"IP-129830","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watbs.2022.100055","text":"Publisher Index Page"},{"id":433314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115,\n 37\n ],\n [\n 115,\n 32\n ],\n [\n 122,\n 32\n ],\n [\n 122,\n 37\n ],\n [\n 115,\n 37\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Han","contributorId":341500,"corporation":false,"usgs":false,"family":"Liu","given":"Han","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908513,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Yushun","contributorId":341501,"corporation":false,"usgs":false,"family":"Chen","given":"Yushun","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908514,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gozlan, Rodolphe E.","contributorId":341502,"corporation":false,"usgs":false,"family":"Gozlan","given":"Rodolphe E.","affiliations":[{"id":81747,"text":"Université de Montpellier","active":true,"usgs":false}],"preferred":false,"id":908515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qu, Xiao","contributorId":341503,"corporation":false,"usgs":false,"family":"Qu","given":"Xiao","email":"","affiliations":[{"id":27775,"text":"University of Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908516,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xia, Wentong","contributorId":341504,"corporation":false,"usgs":false,"family":"Xia","given":"Wentong","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheng, Fei","contributorId":341505,"corporation":false,"usgs":false,"family":"Cheng","given":"Fei","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908518,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Lizhu","contributorId":341506,"corporation":false,"usgs":false,"family":"Wang","given":"Lizhu","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":908519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":908520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olden, Julian D.","contributorId":341507,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":908521,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Xie, Songguang","contributorId":341508,"corporation":false,"usgs":false,"family":"Xie","given":"Songguang","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":908522,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70236305,"text":"70236305 - 2022 - Diminishing Arctic lakes","interactions":[],"lastModifiedDate":"2022-09-01T12:13:35.958674","indexId":"70236305","displayToPublicDate":"2022-08-29T07:12:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Diminishing Arctic lakes","docAbstract":"The Arctic is home to the largest surface water fraction of any terrestrial biome, containing thousands of low-lying lakes. Now, it appears that some Arctic lakes are drying due to rising air temperatures and autumn rains, causing permafrost to thaw and water bodies to drain.
Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data.
Features:
The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.
","language":"English","publisher":"Chapman and Hall/CRC","doi":"10.1201/9781351018784","usgsCitation":"Qian, S.S., Dufour, M.R., and Alameddine, I., 2022, Bayesian applications in environmental and ecological studies with R and Stan, 415 p., https://doi.org/10.1201/9781351018784.","productDescription":"415 p.","ipdsId":"IP-134860","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":407695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":842387,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":842388,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alameddine, Ibrahim","contributorId":244836,"corporation":false,"usgs":false,"family":"Alameddine","given":"Ibrahim","affiliations":[{"id":40455,"text":"American University of Beirut","active":true,"usgs":false}],"preferred":false,"id":842389,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236495,"text":"70236495 - 2022 - Geoelectric constraints on the Precambrian assembly and architecture of southern Laurentia","interactions":[],"lastModifiedDate":"2022-09-09T13:17:21.375872","indexId":"70236495","displayToPublicDate":"2022-08-27T08:10:01","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geoelectric constraints on the Precambrian assembly and architecture of southern Laurentia","docAbstract":"Using images from an updated and expanded three-dimensional electrical conductivity synthesis model for the contiguous United States (CONUS), we highlight the key continent-scale geoelectric structures that are associated with the Precambrian assembly of southern Laurentia. Conductivity anomalies are associated with the Trans-Hudson orogen, the Penokean suture, the ca. 1.8–1.7 Ga Cheyenne belt and Spirit Lake tectonic zone, and the Grenville suture zone; the geophysical characteristics of these structures indicate that the associated accretionary events involved the closure of ancient ocean basins along discrete, large-scale structures. In contrast, we observe no large-scale conductivity anomalies through the portion of southern Laurentia that is generally viewed as composed of late Paleoproterozoic–early Mesoproterozoic accretionary crust. The lack of through-going conductors places constraints on the structure, petrology, and geodynamic history of crustal growth in southern Laurentia during that time period. Overall, our model highlights the enigmatic nature of the concealed Precambrian basement of much of southern Laurentia, as it in some places supports and in other places challenges prevailing models of Laurentian assembly. The revised CONUS electrical conductivity model thus provides important constraints for testing new models of Precambrian tectonism in this region.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Laurentia: Turning points in the evolution of a continent","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.1220(13)","usgsCitation":"Murphy, B.S., Bedrosian, P.A., and Kelbert, A., 2022, Geoelectric constraints on the Precambrian assembly and architecture of southern Laurentia, chap. of Laurentia: Turning points in the evolution of a continent, v. 220, 18 p., https://doi.org/10.1130/2022.1220(13).","productDescription":"18 p.","ipdsId":"IP-131709","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":446629,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2022.1220(13)","text":"Publisher Index 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0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":851252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":851253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":851254,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70235983,"text":"ofr20221067 - 2022 - Updates for Wake Atoll biosecurity management, biological control, survey, and management, and integrated pest management plans","interactions":[],"lastModifiedDate":"2026-03-30T20:22:47.148148","indexId":"ofr20221067","displayToPublicDate":"2022-08-26T10:52:23","publicationYear":"2022","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":"2022-1067","displayTitle":"Updates for Wake Atoll Biosecurity Management, Biological Control, Survey, and Management, and Integrated Pest Management Plans","title":"Updates for Wake Atoll biosecurity management, biological control, survey, and management, and integrated pest management plans","docAbstract":"Pests and invasive species have been defined as any organism that can have real or perceived adverse effects on operations, or the well-being of personnel, native plants, animals, their environment and ecosystem processes; attack or damage real property, supplies, equipment, or are otherwise undesirable (paraphrased from many sources including 53 Federal Register [FR] 15975, May 4, 1988, as amended at 78 FR 13507, February 28, 2013). Biosecurity programs and pest management plans can be developed and implemented with the goals of preventing the arrival of or eradication or control of pests and invasive species to reduce the potential for adverse effects. Such plans have been developed for Wake Atoll (U.S. Air Force, unpub. data 2017). Periodic plan reviews are an integral step for evaluating plan efficacy and updating plans with new information for improving plan effectiveness. This report summarizes an evaluation of past, current, and potential biosecurity and pest management for Wake with the intent this information can be used for updating existing plans. This document was prepared in cooperation with the U.S. Air Force (USAF) and surveys were performed for the 611th Civil Engineer Squadron Natural Resources Program ACES PROJECT no. YGFZ17002 under agreement number F2MUAA7116GW01 between the USAF and the U.S. Geological Survey’s Western Ecological Research Center (USGS-WERC).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221067","collaboration":"Prepared in cooperation with the U.S. Air Force","programNote":"Ecosystems Mission Area—Land Management Research and Species Management Research Programs","usgsCitation":"Hathaway, S.A., Jacobi, J.D., Peck, R., and Fisher, R.N., 2022, Updates for Wake Atoll biosecurity management, biological control, survey, and management, and integrated pest management plans: U.S. Geological Survey Open-File Report 2022-1067, 56 p., https://doi.org/10.3133/ofr20221067.","productDescription":"viii, 56 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-136103","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":405629,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1067/ofr20221067.xml"},{"id":405628,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1067/ofr20221067.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":405627,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1067/covrthb.jpg"},{"id":501820,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113419.htm","linkFileType":{"id":5,"text":"html"}},{"id":405630,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1067/images"}],"contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Vampire bat transmitted rabies (VBR) is a continuing burden to public health and agricultural sectors in Latin America, despite decades-long efforts to control the disease by culling bat populations. Culling has been shown to disperse bats, leading to an increased spread of rabies. Thus, non-lethal strategies to control VBR, such as vaccination, are desired. Here, we evaluated the safety and efficacy of a viral-vectored recombinant mosaic glycoprotein rabies vaccine candidate (RCN-MoG) in vampire bats (Desmodus rotundus) of unknown history of rabies exposure captured in México and transported to the United States. Vaccination with RCN-MoG was demonstrated to be safe, even in pregnant females, as no evidence of lesions or adverse effects were observed. We detected rabies neutralizing antibodies in 28% (8/29) of seronegative bats post-vaccination. Survival proportions of adult bats after rabies virus (RABV) challenge ranged from 55–100% and were not significantly different among treatments, pre- or post-vaccination serostatus, and route of vaccination, while eight pups (1–2.5 months of age) used as naïve controls all succumbed to challenge (P<0.0001). Importantly, we found that vaccination with RCN-MoG appeared to block viral shedding, even when infection proved lethal. Using real-time PCR, we did not detect RABV nucleic acid in the saliva samples of 9/10 vaccinated bats that succumbed to rabies after challenge (one was inconclusive). In contrast, RABV nucleic acid was detected in saliva samples from 71% of unvaccinated bats (10/14 sampled, plus one inconclusive) that died of the disease, including pups. Low seroconversion rates post-vaccination and high survival of non-vaccinated bats, perhaps due to earlier natural exposure, limited our conclusions regarding vaccine efficacy. However, our findings suggest a potential transmission-blocking effect of vaccination with RCN-MoG that could provide a promising strategy for controlling VBR in Latin America beyond longstanding culling programs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pntd.0010699","usgsCitation":"Cardenas-Canales, E.M., Velasco-Villa, A., Ellison, J.A., Satheshkumar, P., Osario, J.E., and Rocke, T.E., 2022, A recombinant rabies vaccine that prevents viral shedding in rabid common vampire bats (Desmodus rotundus): PLoS Neglected Tropical Diseases, v. 16, no. 8, e0010699, 21 p., https://doi.org/10.1371/journal.pntd.0010699.","productDescription":"e0010699, 21 p.","ipdsId":"IP-142109","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":446632,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pntd.0010699","text":"Publisher Index Page"},{"id":435713,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KNHW1P","text":"USGS data release","linkHelpText":"Serology, survival, and detection of rabies data from vaccination trials in the common vampire bat (Desmodus rotundus) using a recombinant raccoon poxvirus-vectored mosaic rabies vaccine candidate"},{"id":406143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","city":"San Luis Potosi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.173095703125,\n 21.963424936844223\n ],\n [\n -100.799560546875,\n 21.963424936844223\n ],\n [\n -100.799560546875,\n 22.334833457530486\n ],\n [\n -101.173095703125,\n 22.334833457530486\n ],\n [\n -101.173095703125,\n 21.963424936844223\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Cardenas-Canales, Elsa M.","contributorId":192489,"corporation":false,"usgs":false,"family":"Cardenas-Canales","given":"Elsa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":850658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velasco-Villa, Andres","contributorId":174760,"corporation":false,"usgs":false,"family":"Velasco-Villa","given":"Andres","email":"","affiliations":[{"id":16974,"text":"US Centers for Disease Control and Prevention (CDC)","active":true,"usgs":false}],"preferred":false,"id":850659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellison, James A.","contributorId":197066,"corporation":false,"usgs":false,"family":"Ellison","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":850660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satheshkumar, Panayampalli S.","contributorId":296099,"corporation":false,"usgs":false,"family":"Satheshkumar","given":"Panayampalli S.","affiliations":[{"id":63980,"text":"Poxvirus and Rabies Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America","active":true,"usgs":false}],"preferred":false,"id":850661,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osario, Jorge E.","contributorId":296100,"corporation":false,"usgs":false,"family":"Osario","given":"Jorge","email":"","middleInitial":"E.","affiliations":[{"id":63982,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America","active":true,"usgs":false}],"preferred":false,"id":850662,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":850663,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236273,"text":"70236273 - 2022 - Confirmation that eagle fatalities can be reduced by automated curtailment of wind turbines","interactions":[],"lastModifiedDate":"2022-08-31T12:24:53.280063","indexId":"70236273","displayToPublicDate":"2022-08-26T07:24:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9977,"text":"Ecological Solutions and Evidence","active":true,"publicationSubtype":{"id":10}},"title":"Confirmation that eagle fatalities can be reduced by automated curtailment of wind turbines","docAbstract":"The biomagnification of toxic methylmercury (MeHg) and selenium (Se) through aquatic food webs using nitrogen stable isotopes (δ15N) varies among ecosystems but underlying mechanisms are yet unexplained. Given the strong links between MeHg and thiol-containing amino acids and proteins containing selenocysteine, our hypothesis was that cysteine content is a better predictor of MeHg and Se transfer through lake food webs than δ15N. Food web samples were collected from six lakes in Kejimkujik National Park, Nova Scotia, Canada, and the regression slopes of log MeHg or Se versus protein-bound cysteine or bulk δ15N were compared. Across all six lakes, MeHg varied by a factor of 10 among taxa and was significantly and positively related to both cysteine (R2 = 0.65–0.80, p < 0.001) and δ15N (R2 = 0.88–0.94, p < 0.001), with no among-system differences in these slopes. In contrast, total Se concentrations varied by less than a factor of 2 among taxa in four lakes and were significantly related to cysteine in only two food webs (R2 = 0.20 & 0.37, p = 0.014 & < 0.001); however, δ15N was not a predictor of Se in any lake (p = 0.052–0.777). Overall, these novel results indicate that cysteine content predicts MeHg, and sometimes Se, across trophic levels, providing a potential mechanism for among-system differences in their biomagnification.
In the United States, national chemical water quality criteria for the protection of aquatic life assume that aquatic ecosystems have sufficient resiliency to recover from criteria exceedences occurring up to once every 3 years. This resiliency assumption was critically reviewed through two approaches: 1) synthesis of case studies and 2) population modeling. The population modeling examined differences in recovery of species with widely different life histories. One invertebrate (Hyalella azteca) and four fish species were modeled (fathead minnow, brook trout, lake trout, and shortnose sturgeon) with various disturbance magnitudes and intervals. The synthesis of ecosystem case studies showed generally faster recoveries for insect communities rather than fish, and recoveries from pulse (acute) disturbances were often faster than recoveries from press (chronic) disturbances. When the recovery dataset excluded severe disturbances that seemed unrepresentative of common facility discharge upsets that might cause criteria exceedences, the median recovery time was 1 year, 81% of the cases were considered recovered within 3 years, and 95% were considered recovered within 10 years. The modeling projected that short-lived fish species with high recovery times could thrive despite enduring 50% mortality disturbances every other year. However, long-lived fish species had longer recovery times and declined under the 1 disturbance every 3 years scenario. Overall, the analyses did not refute the long-standing judgements that 3 years is generally sufficient for recovery from non-repetitive, moderate intensity disturbances of a magnitude up to 2X the chronic criteria in waters without other pollution sources or stresses. However, these constraints may not always be met and if long-lived fish species are a concern, longer return intervals such as 5 to 10 years could be indicated.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.5471","usgsCitation":"Mebane, C.A., 2022, The capacity of freshwater ecosystems to recover from exceedances of aquatic life criteria: Environmental Toxicology and Chemistry, v. 41, no. 12, p. 2887-2910, https://doi.org/10.1002/etc.5471.","productDescription":"24 p.","startPage":"2887","endPage":"2910","ipdsId":"IP-125552","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":446640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.5471","text":"Publisher Index Page"},{"id":406944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852244,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70235866,"text":"fs20223068 - 2022 - Database of biodiversity, habitat, and aquatic-resource quantification tools used in market-based conservation — 2022 update","interactions":[],"lastModifiedDate":"2022-09-27T13:31:01.57704","indexId":"fs20223068","displayToPublicDate":"2022-08-26T06:25:00","publicationYear":"2022","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":"2022-3068","displayTitle":"Database of Biodiversity, Habitat, and Aquatic-Resource Quantification Tools Used in Market-Based Conservation — 2022 Update","title":"Database of biodiversity, habitat, and aquatic-resource quantification tools used in market-based conservation — 2022 update","docAbstract":"Market-based conservation makes use of economic incentives to promote actions that avoid, minimize, or compensate for detrimental effects on natural resources and the environment. Examples of market-based conservation mechanisms include aquatic-resource (such as, streams, wetlands, and estuaries) compensatory mitigation, conservation banking, habitat exchanges, and payments for ecosystem services. A critical component in the operation of these market-based conservation mechanisms is the methods (hereafter referred to as “quantification tools”) used to assess existing (sometimes referred to as “baseline”) or potential site conditions. Quantification tools are used to assign values to the benefits provided by preservation, restoration, or enhancement actions, as well as the negative effects of human activities (for example, infrastructure development, energy extraction, and anthropogenic disasters).
In 2018, the U.S. Geological Survey (USGS) published a database describing the attributes of 69 quantification tools developed for United States conservation markets. The database focused on tools used for species-based mitigation, payments for ecosystem services, and ecolabel programs (Chiavacci and Pindilli, 2020). Recently, the USGS, in collaboration with the U.S. Environmental Protection Agency, revised the original database by updating the existing tool information, adding newly developed tools, and broadening the scope to include tools developed for compensatory mitigation under the Clean Water Act Section 404 Regulatory Program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223068","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Chiavacci, S.J., French, E.D., and Morgan, J.A., 2022, Database of biodiversity, habitat, and aquatic-resource quantification tools used in market-based conservation — 2022 update: U.S. Geological Survey Fact Sheet 2022–3068, 2 p., https://doi.org/10.3133/fs20223068.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-140564","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":405533,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223068/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2022-3068"},{"id":406471,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79G5M3X","text":"USGS data release","linkHelpText":"Database of Biodiversity, Habitat, and Aquatic Resource Quantification Tools Used for Market-based Conservation in the United States (ver. 2.0, June 2022)"},{"id":405535,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3068/fs20223068.XML"},{"id":405534,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3068/images/"},{"id":405509,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3068/fs20223068.pdf","text":"Report","size":"558 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3068"},{"id":405508,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3068/coverthb3.jpg"}],"contact":"Science and Decisions Center
12201 Sunrise Valley Drive
Reston, VA 20192
A radium industry existed between about 1914 and 1920 in Denver, Colorado, with operations located along the South Platte River. Sites associated with that industry were contaminated with radium and uranium processing residues and were incorporated into clean-up efforts as Operating Units (OUs) of the Denver Radium Superfund Site. Concentrations of uranium exceeding the U.S. Environmental Protection Agency maximum contaminant level of 0.03 milligrams per liter for drinking water are present in shallow groundwater at OU8. However, previous studies have shown concentrations of dissolved uranium can be naturally high in shallow groundwater of the South Platte River valley compared to other rivers of the world. This report compares dissolved uranium concentrations measured by the U.S. Geological Survey across the South Platte River valley to data collected at the OU8 of the Denver Radium Superfund Site. The U.S. Geological Survey data represent 5 distinct urban or agricultural geographic areas and included 230 sampling events at 114 wells during 1993 to 2013. The OU8 data represent 13 wells and groundwater discharge locations sampled during the years 2017 and 2018. Dissolved uranium concentrations were statistically significantly greater for both years of the OU8 data compared to three datasets from shallow groundwater beneath urban areas in the Denver metropolitan area. However, compared to OU8, concentrations were significantly greater in shallow groundwater from an agricultural area of the South Platte River valley distant from Denver. Additionally, each of the urban area datasets contained some individual dissolved uranium concentrations greater than the greatest concentrations from the two OU8 datasets. Thus, naturally occurring concentrations of dissolved uranium in shallow groundwater that are greater than those observed at OU8 are not uncommon in the South Platte River valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20225085","collaboration":"Prepared in cooperation the U.S. Environmental Protection Agency","usgsCitation":"Bern, C.R., 2022, Examination of dissolved uranium concentrations in regional shallow groundwater relative to Operable Unit 8 of the Denver Radium Superfund Site: U.S. Geological Survey Scientific Investigations Report 2022–5085, 16 p., https://doi.org/10.3133/sir20225085.","productDescription":"Report: vi, 16 p.; Database","onlineOnly":"Y","ipdsId":"IP-135030","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":405601,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"},{"id":405600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://semspub.epa.gov/work/08/100005517.pdf","text":"U.S. Environmental Protection Agency [EPA], 2018b—","linkHelpText":"Fifth five-year review report for Denver radium superfund site, Denver County, Colorado"},{"id":405596,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5085/coverthb.jpg"},{"id":405598,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5085/ofr20225085.pdf","text":"Report","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5085"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.07598876953125,\n 39.115144700901475\n ],\n [\n -103.75213623046875,\n 39.115144700901475\n ],\n [\n -103.75213623046875,\n 39.8992015115692\n ],\n [\n -105.07598876953125,\n 39.8992015115692\n ],\n [\n -105.07598876953125,\n 39.115144700901475\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
The Great Lakes Basin covers around 536,393 square kilometers, and the Great Lakes hold more than 5,400 cubic miles of water, accounting for more than 20 percent of the world’s fresh surface water supply. The Great Lakes provide a source of drinking water to tens of millions of people in Canada and the United States and support one of the most diverse ecosystems in the world. Increasing urbanization combined with aging infrastructure and more extreme storm events because of changing weather patterns creates stormwater management challenges for communities across the Great Lakes region. A variety of green infrastructure (GI) practices, designed to decrease runoff and improve water quality, have been implemented throughout the region in response to these challenges; however, implementation often remains limited to local efforts and with little coordination among various levels of government because of, at least in part, a lack of clear standards for stormwater, limited funding, and a general uncertainty in the type and expected performance of these practices. City planners, engineers, and political leaders often see GI investment as riskier than other alternatives despite studies that determined, in most cases, practices can either reduce or not affect costs.
This report summarizes selected published reports and data sources from studies done in Great Lakes states and compares the measured effects of various GI practices and their applicability in different settings around the Great Lakes. By summarizing selected published reports and data sources from studies done in Great Lakes states, this report provides foundational information for U.S. Geological Survey scientists and their local and national partners to assess the ability of GI to reduce stormwater runoff in Great Lakes urban areas. GI includes a variety of stormwater management techniques designed to mimic natural hydrologic processes like infiltration and evapotranspiration, which can decrease the volume of water running into sewers and streams. It can also improve water quality by trapping sediment, nutrients, and other contaminants. A variety of landscape practices can be incorporated into urban areas as GI, but the discussion here is limited to vegetated basins, vegetated channels, permeable pavement, urban tree canopy, and green roofs. Other types of GI, such as downspout disconnection, rainwater harvesting, and wet and dry detention basins were not included because hydrologic function and associated components are not widely monitored or evaluated in literature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1496","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Baker, N.T., Sullivan, D.J., Selbig, W.R., Haefner, R.J., Lampe, D.C., Bayless, R., and McHale, M.R., 2022, Green infrastructure in the Great Lakes—Assessment of performance, barriers, and unintended consequences: U.S. Geological Survey Circular 1496, 70 p., https://doi.org/10.3133/cir1496.","productDescription":"Report: ix, 70 p.; 1 Table","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-128488","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Although polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) subpopulation have commonly created maternal dens on sea ice in the past, maternal dens on land have become increasingly prevalent as sea ice declines. This trend creates conditions for increased human–bear interactions associated with local communities and industrial activity. Maternal denning is a vulnerable period in the polar bear life cycle, and den disturbance could lead to den abandonment, cub mortality, and negative population impacts. We used published long-term data to parameterize a Bayesian hierarchical model of annual land den abundance during 2000–2015, in 4 regions of northern Alaska, USA, with current or potential future oil and gas activity. We also estimated long-term (1982–2015) shifts in the spatial distribution of land dens within and among regions using kernel density estimation and assessed the influence of local and regional sea ice and snow conditions on den site selection using a random forest resource selection function. Our objectives were to quantify current den distribution and abundance, test for distributional shifts over time, and investigate if those shifts could be attributed to environmental variables related to den habitat. We estimated that between 2000 and 2015, the SBS contained a median 123 dens in a typical year, of which 68 occurred on land. The region between the Colville and Canning rivers, where most current oil and gas activity occurred, also contained the largest fraction of land dens. Overall, land dens were disproportionately concentrated on barrier islands and on land within 30 km of the coast. The probability of dens occurring on land varied from 1982–1999 to 2000–2015 in all regions, and the overall distribution of land dens shifted west between those periods. This regional-scale change in den distribution was predictable based on spatial and temporal heterogeneity in snow and sea ice conditions within 50 km of individual den locations. Land denning is likely to become increasingly common with continued sea ice loss, and our results and modeling framework could be used to design additional mitigation strategies for reducing the risk of incidental take due to den disturbance.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.22302","usgsCitation":"Patil, V.P., Durner, G.M., Douglas, D.C., and Atwood, T.C., 2022, Modeling the spatial and temporal dynamics of land-based polar bear denning in Alaska: Journal of Wildlife Management, v. 86, no. 8, e22302, 22 p., https://doi.org/10.1002/jwmg.22302.","productDescription":"e22302, 22 p.","ipdsId":"IP-134179","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":446643,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22302","text":"Publisher Index Page"},{"id":435714,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZNG8JT","text":"USGS data release","linkHelpText":"Code for analysis of polar bear maternal den abundance and distribution in four regions of northern Alaska and Canada within the Southern Beaufort Sea subpopulation boundary (1982-2015)"},{"id":406139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canadian, United States","state":"Alaska","otherGeospatial":"Southern Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -172.6171875,\n 67.7427590666639\n ],\n [\n -122.51953124999999,\n 67.7427590666639\n ],\n [\n -122.51953124999999,\n 77.5041191797399\n ],\n [\n -172.6171875,\n 77.5041191797399\n ],\n [\n -172.6171875,\n 67.7427590666639\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Patil, Vijay P. 0000-0002-9357-194X vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":850654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":850655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":850656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":850657,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236730,"text":"70236730 - 2022 - Can lava flow like water? Assessing applications of critical flow theory to channelized basaltic lava flows","interactions":[],"lastModifiedDate":"2022-09-16T14:39:42.900391","indexId":"70236730","displayToPublicDate":"2022-08-25T09:35:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Can lava flow like water? Assessing applications of critical flow theory to channelized basaltic lava flows","docAbstract":"Flowing lava and water have dramatically different physical properties but can form similar hydraulic structures, including undular hydraulic jumps, or standing wave trains. In water flows, undular hydraulic jumps are evidence of critical flow (Froude number ∼1) and open-channel hydraulic theory provides a powerful tool for estimating flow depth and velocity. Monitoring these parameters in an active lava channel is inherently challenging, but essential for calculating lava discharge (effusion rate), a primary control on the rate of flow front advance and ultimate flow runout distance. We analyze undular hydraulic jumps in both water and lava flows to assess the conditions under which they form and, by extension, the potential use of critical flow theory to estimate, in real time, lava flow velocity, depth, and discharge. Experimental data for water flows show that these structures mark the transition from supercritical to subcritical flow. Undular hydraulic jumps in the near-vent lava channel of the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi also reflect critical flow conditions; their wavelengths scale with flow depth and velocity, consistent with hydraulic theory. Calculated lava effusion rates are similar to estimates made using more traditional approaches (Jeffreys', 1925, https://doi.org/10.1080/14786442508634662, equation based on lava viscosity, density, and channel slope) and with lava volumes derived from topographic-change mapping. From this we conclude that critical flow phenomena show great potential to track flow dynamics and inform hazard assessment for a wide range of geophysical fluids.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JF006666","usgsCitation":"Dietterich, H., Grant, G., Fasth, B., Major, J., and Cashman, K., 2022, Can lava flow like water? Assessing applications of critical flow theory to channelized basaltic lava flows: Journal of Geophysical Research - Earth Surface, v. 127, no. 9, e2022JF006666, 26 p., https://doi.org/10.1029/2022JF006666.","productDescription":"e2022JF006666, 26 p.","ipdsId":"IP-138706","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":406841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":852036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, Gordon E.","contributorId":30881,"corporation":false,"usgs":false,"family":"Grant","given":"Gordon E.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":852037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fasth, Becky","contributorId":296636,"corporation":false,"usgs":false,"family":"Fasth","given":"Becky","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":852038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Major, J. J. 0000-0003-2449-4466","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":29461,"corporation":false,"usgs":true,"family":"Major","given":"J. J.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":852039,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cashman, Katharine V.","contributorId":40097,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine V.","affiliations":[],"preferred":false,"id":852040,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237816,"text":"70237816 - 2022 - Effects of formaldehyde (Parasite-S®) on biofilter nitrification from a cold- and a warm freshwater RAS","interactions":[],"lastModifiedDate":"2022-10-25T14:11:50.833419","indexId":"70237816","displayToPublicDate":"2022-08-25T09:08:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":857,"text":"Aquaculture Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of formaldehyde (Parasite-S®) on biofilter nitrification from a cold- and a warm freshwater RAS","docAbstract":"The effect of Parasite-S® (an aqueous formaldehyde solution) on the nitrification processes of biofilters was evaluated in two recirculating aquaculture systems (RASs). Rearing tanks in the warmwater RAS contained yellow perch (Perca flavescens) and grass carp (Ctenopharyngodon idella) with an initial weight of 166.8 kg and a mean density of 39.5 kg/m3. Rearing tanks in the coldwater RAS contained rainbow trout (Oncorhynchus mykiss) and lake trout (Salvelinus namaycush) with an initial weight of 1377.8 kg at a system density of 41.9 kg/m3. Parasite-S® was administered to the entire system on four consecutive days in both trials to achieve a nominal concentration of 14.8 mg/L formaldehyde (40 mg/L formalin) at the biofilter. Removal efficiencies for total ammonia nitrogen (TAN) and nitrite nitrogen were measured as indicators of biofilter nitrification processes. The active ingredient in Parasite-S®, formaldehyde, was measured until it was below the method detection limit of 0.8 mg/L. TAN volumetric removal rate was significantly decreased in both systems after formaldehyde addition and remained below pre-exposure efficiency in the coldwater RAS. Nitrite nitrogen volumetric removal rate was not significantly different, but the slope and intercepts were less after formaldehyde addition indicating an effect on the nitrifying bacteria. Although removal rates were decreased, no mortality occurred after four consecutive formaldehyde indefinite bath exposures in either system.
","language":"English","publisher":"Wiley","doi":"10.1111/are.16046","usgsCitation":"Fredricks, K.T., Schleis, S.M., Smerud, J.R., Gaikowski, M., Erickson, R.A., Hebert, J.L., Fischer, G.J., Holmes, K., and Hartleb, C.F., 2022, Effects of formaldehyde (Parasite-S®) on biofilter nitrification from a cold- and a warm freshwater RAS: Aquaculture Research, v. 53, no. 16, p. 5647-5655, https://doi.org/10.1111/are.16046.","productDescription":"9 p.","startPage":"5647","endPage":"5655","ipdsId":"IP-106180","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467166,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/55361","text":"External Repository"},{"id":408695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"16","noUsgsAuthors":false,"publicationDate":"2022-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":173994,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim","email":"kfredricks@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schleis, Susan M. 0000-0002-9396-7856","orcid":"https://orcid.org/0000-0002-9396-7856","contributorId":298489,"corporation":false,"usgs":false,"family":"Schleis","given":"Susan","email":"","middleInitial":"M.","affiliations":[{"id":64592,"text":"former UMESC employee (retired)","active":true,"usgs":false}],"preferred":false,"id":855734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":149357,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark P.","email":"mgaikowski@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erickson, Richard A. 0000-0001-8977-2127 rerickson@usgs.gov","orcid":"https://orcid.org/0000-0001-8977-2127","contributorId":298490,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hebert, Jillian Lee 0000-0003-4893-8287","orcid":"https://orcid.org/0000-0003-4893-8287","contributorId":289197,"corporation":false,"usgs":true,"family":"Hebert","given":"Jillian","email":"","middleInitial":"Lee","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":855781,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fischer, Gregory J.","contributorId":178010,"corporation":false,"usgs":false,"family":"Fischer","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":855739,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holmes, Kendall","contributorId":178011,"corporation":false,"usgs":false,"family":"Holmes","given":"Kendall","email":"","affiliations":[],"preferred":false,"id":855740,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hartleb, Christopher F","contributorId":298491,"corporation":false,"usgs":false,"family":"Hartleb","given":"Christopher","email":"","middleInitial":"F","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":855738,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70255104,"text":"70255104 - 2022 - Wildfire influences individual growth and breeding dispersal, but not survival and recruitment in a montane amphibian","interactions":[],"lastModifiedDate":"2024-06-17T14:07:46.883503","indexId":"70255104","displayToPublicDate":"2022-08-25T09:02:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire influences individual growth and breeding dispersal, but not survival and recruitment in a montane amphibian","docAbstract":"Global wildfire regimes are changing rapidly, with widespread increases in the size, frequency, duration, and severity of wildfires. Whereas the effects of wildfire on ecological state variables such as occupancy, abundance, and species diversity are relatively well documented, changes in population vital rates (e.g., survival, recruitment) and individual responses (e.g., growth, movement) to wildfire are more limited because of the detailed information needed on the same individuals both pre- and post-fire. We capitalized on the 2018 Roosevelt wildfire, which occurred during our 6-year (2015–2020) capture–mark–recapture study of boreal toads (Anaxyrus boreas boreas; n = 1415) in the Bridger-Teton National Forest, USA, to evaluate the responses of population vital rates and individual metrics to wildfire. We employed robust design capture–recapture models to compare the growth, dispersal, survival, and recruitment of adult boreal toads pre- and post-fire at burned versus unburned sites. At burned locations, growth increased 2 years post-fire compared with the year directly following wildfire and was higher 2 years post-fire than any other interval during our study period. Boreal toads dispersed to alternative breeding patches more at burned sites than unburned sites and dispersal increased 2 years post-fire compared with the year directly following wildfire. Annual survival and recruitment neither differed between pre- and post-fire years nor among pre-fire years, the year following wildfire, and 2 years post-fire. We demonstrate that, in certain contexts, dispersal can play a major role in changes to state variables (e.g., abundance) after wildfire, as opposed to other vital rates such as survival and recruitment. Our study represents an important step toward understanding the biological processes that underlie observed patterns in state variables following wildfire, which ultimately will be critical for the effective management of species in landscapes experiencing shifts in fire activity.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4212","usgsCitation":"Barrile, G., Chalfoun, A.D., Estes-Zumpf, W.A., and Walters, A.W., 2022, Wildfire influences individual growth and breeding dispersal, but not survival and recruitment in a montane amphibian: Ecosphere, v. 13, no. 8, e4212, 18 p., https://doi.org/10.1002/ecs2.4212.","productDescription":"e4212, 18 p.","ipdsId":"IP-134283","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":446650,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4212","text":"Publisher Index Page"},{"id":430272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.6,\n 43.32\n ],\n [\n -110.6,\n 42.9\n ],\n [\n -109.8,\n 42.9\n ],\n [\n -109.8,\n 43.32\n ],\n [\n -110.6,\n 43.32\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Barrile, Gabriel M.","contributorId":338642,"corporation":false,"usgs":false,"family":"Barrile","given":"Gabriel M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":903415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":903416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Estes-Zumpf, Wendy A.","contributorId":338643,"corporation":false,"usgs":false,"family":"Estes-Zumpf","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":903417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903414,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255280,"text":"70255280 - 2022 - Incorporating habitat suitability, landscape distance, and resistant kernels to estimate conservation units for an imperiled terrestrial snake","interactions":[],"lastModifiedDate":"2024-06-17T13:49:07.864148","indexId":"70255280","displayToPublicDate":"2022-08-25T08:43:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating habitat suitability, landscape distance, and resistant kernels to estimate conservation units for an imperiled terrestrial snake","docAbstract":"Wildlife distributions are often subdivided into discrete conservation units to aid in implementing management and conservation objectives. Habitat suitability models, resistance surfaces, and resistant kernels provide tools for delineating spatially explicit conservation units but guidelines for parameterizing resistant kernels are generally lacking.
We used the federally threatened eastern indigo snake (Drymarchon couperi) as a case study for calibrating resistant kernels using observed movement data and resistance surfaces to help delineate habitat-based conservation units.
We simulated eastern indigo snake movements under different resistance surface and resistant kernel parameterizations and selected the scenario that produced simulated movement distances that best approximated the maximum observed annual movement distance. We used our calibrated resistant kernel to model range-wide connectivity and compared delineated conservation units to Euclidean distance-based population units from the recent eastern indigo snake species status assessment (SSA).
We identified a total of 255 eastern indigo snake conservation units, with numerous large (2500–5000 ha of suitable habitat) conservation units across the eastern indigo snake distribution. There was substantial variation in the degree of overlap with the SSA population units likely reflecting the spatial heterogeneity in habitat suitability and landscape resistance.
Our calibration approach is widely applicable to other systems for parameterizing biologically meaningful resistant kernels. Our conservation units can be used to prioritize future eastern indigo snake conservation efforts, identify areas where more survey work is needed, or identify small, isolated populations with high extinction risks.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01510-z","usgsCitation":"Bauder, J.M., Chandler, H.C., Elmore, M., and Jenkins, C.L., 2022, Incorporating habitat suitability, landscape distance, and resistant kernels to estimate conservation units for an imperiled terrestrial snake: Landscape Ecology, v. 37, https://doi.org/10.1007/s10980-022-01510-z.","productDescription":"15 p.","startPage":"2533","ipdsId":"IP-137585","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467167,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/666095","text":"External Repository"},{"id":430270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.6589463070196,\n 30.27164925540076\n ],\n [\n -87.4471664851995,\n 30.273991912380097\n ],\n [\n -87.243062061103,\n 30.25688691395483\n ],\n [\n -86.504722900934,\n 30.288280599826876\n ],\n [\n -85.8821985085937,\n 30.127920150613292\n ],\n [\n -85.45848132490356,\n 29.678163497359677\n ],\n [\n -85.18012336836138,\n 29.52298729685313\n ],\n [\n -84.431494016169,\n 29.8435460527122\n ],\n [\n -84.27785036727468,\n 29.98120848065058\n ],\n [\n -83.89226362456542,\n 29.960791456317352\n ],\n [\n -83.47317674842255,\n 29.509171366635385\n ],\n [\n -83.08833538532544,\n 29.1434267271204\n ],\n [\n -82.82094989668451,\n 29.0956993019621\n ],\n [\n -82.67858009554807,\n 28.666898644234394\n ],\n [\n -82.84220852464915,\n 27.892907277971844\n ],\n [\n -81.9139493773393,\n 26.026944742093463\n ],\n [\n -81.3608497502143,\n 25.677695288573233\n ],\n [\n -81.20240783558897,\n 25.110332177132477\n ],\n [\n -80.5049186418957,\n 25.163605849744997\n ],\n [\n -81.39546331741505,\n 24.792875468134326\n ],\n [\n -81.84017458395616,\n 24.611130518564238\n ],\n [\n -81.49095266413781,\n 24.52625187147568\n ],\n [\n -80.30964454840066,\n 25.01219197845387\n ],\n [\n -80.28167788112444,\n 25.441483917895624\n ],\n [\n -80.07107634394508,\n 25.88314239044695\n ],\n [\n -80.01314206035136,\n 26.51492387439309\n ],\n [\n -80.110778674335,\n 27.072566624838785\n ],\n [\n -80.54296836001978,\n 28.439325701479135\n ],\n [\n -80.92465488637467,\n 29.033168269780845\n ],\n [\n -81.40440957377771,\n 30.780806652102896\n ],\n [\n -80.97885233616921,\n 32.04045515787071\n ],\n [\n -81.28694625263563,\n 32.58791480990446\n ],\n [\n -81.99407467041935,\n 32.551271523349655\n ],\n [\n -87.68936380825409,\n 31.462681042444245\n ],\n [\n -87.8537521440345,\n 31.229156643229587\n ],\n [\n -87.97481408751028,\n 30.53533344322976\n ],\n [\n -87.6589463070196,\n 30.27164925540076\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","edition":"2519","noUsgsAuthors":false,"publicationDate":"2022-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Bauder, Javan Mathias 0000-0002-2055-5324","orcid":"https://orcid.org/0000-0002-2055-5324","contributorId":337814,"corporation":false,"usgs":true,"family":"Bauder","given":"Javan","email":"","middleInitial":"Mathias","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":904088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, H. C.","contributorId":339318,"corporation":false,"usgs":false,"family":"Chandler","given":"H.","email":"","middleInitial":"C.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":904089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elmore, M.","contributorId":339320,"corporation":false,"usgs":false,"family":"Elmore","given":"M.","email":"","affiliations":[{"id":81289,"text":"Georgia Ecological Services","active":true,"usgs":false}],"preferred":false,"id":904090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jenkins, C. L.","contributorId":339321,"corporation":false,"usgs":false,"family":"Jenkins","given":"C.","email":"","middleInitial":"L.","affiliations":[{"id":13223,"text":"The Orianne Society","active":true,"usgs":false}],"preferred":false,"id":904091,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236759,"text":"70236759 - 2022 - The influence of submerged coastal structures on nearshore flows and wave runup","interactions":[],"lastModifiedDate":"2022-09-19T12:09:25.337399","indexId":"70236759","displayToPublicDate":"2022-08-25T07:07:03","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The influence of submerged coastal structures on nearshore flows and wave runup","docAbstract":"Engineered and natural submerged coastal structures (e.g., submerged breakwaters and reefs) modify incident wave fields and thus can alter hydrodynamic processes adjacent to coastlines. Although submerged structures are generally assumed to promote beach protection by dissipating waves offshore and creating sheltered conditions in their lee, their interaction with waves can result in mean wave-driven circulation patterns that may either promote shoreline accretion or erosion. Here, we analyse the mean flow patterns and shoreline water levels (wave runup) in the lee of idealised impermeable submerged structures with a phase-resolved nonhydrostatic numerical model. Waves propagating over submerged structures can drive either a 2-cell mean (wave-averaged) circulation, which is characterised by diverging flows behind the structure and at the shoreline, or 4-cell circulation, with converging flows at the shoreline and diverging flows in the immediate lee of the structure. The numerical results show that the mode of circulation can be predicted with a set of relationships depending on the incoming wave heights, the structure crest level, and distance to the shoreline (or structure depth). Qualitative agreement between the mean flow and proxies for the sediment transport using an energetics approach suggest that the mean flow can be a robust proxy for inferring sediment transport patterns. For the cases considered, the submerged structures had a minimal influence on shoreline wave setup and wave runup despite the wave energy dissipation by the structures due to alongshore wave energy fluxes in the lee. Consequently, these results suggest that the coastal protection provided by the range of impermeable submerged structures we modelled is primarily due to their capacity to promote beach accretion.
The fathead minnow (Pimephales promelas) is a model species for toxicological research. A high-quality genome reference sequence is available, and genomic methods are increasingly used in toxicological studies of the species. However, phylogenetic relationships within the genus remain incompletely known and little population-genomic data are available for fathead minnow despite the potential effects of genetic background on toxicological responses. On the other hand, a wealth of extant samples is stored in museum collections that in principle allow fine-scale analysis of contemporary and historical genetic variation.
Here we use short-read shotgun resequencing to investigate sequence variation among and within Pimephales species. At the genus level, our objectives were to resolve phylogenetic relationships and identify genes with signatures of positive diversifying selection. At the species level, our objective was to evaluate the utility of archived-sample resequencing for detecting selective sweeps within fathead minnow, applied to a population introduced to the San Juan River of the southwestern United States sometime prior to 1950.
We recovered well-supported but discordant phylogenetic topologies for nuclear and mitochondrial sequences that we hypothesize arose from mitochondrial transfer among species. The nuclear tree supported bluntnose minnow (P. notatus) as sister to fathead minnow, with the slim minnow (P. tenellus) and bullhead minnow (P. vigilax) more closely related to each other. Using multiple methods, we identified 11 genes that have diversified under positive selection within the genus. Within the San Juan River population, we identified selective-sweep regions overlapping several sets of related genes, including both genes that encode the giant sarcomere protein titin and the two genes encoding the MTORC1 complex, a key metabolic regulator. We also observed elevated polymorphism and reduced differentation among populations (FST) in genomic regions containing certain immune-gene clusters, similar to what has been reported in other taxa. Collectively, our data clarify evolutionary relationships and selective pressures within the genus and establish museum archives as a fruitful resource for characterizing genomic variation. We anticipate that large-scale resequencing will enable the detection of genetic variants associated with environmental toxicants such as heavy metals, high salinity, estrogens, and agrichemicals, which could be exploited as efficient biomarkers of exposure in natural populations.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.13954","usgsCitation":"Klymus, K.E., Hrabik, R.A., Thompson, N., and Cornman, R.S., 2022, Genome resequencing clarifies phylogeny and reveals patterns of selection in the toxicogenomics model Pimephales promelas: PeerJ, v. 10, e13954, 34 p., https://doi.org/10.7717/peerj.13954.","productDescription":"e13954, 34 p.","ipdsId":"IP-138759","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":446657,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.13954","text":"Publisher Index Page"},{"id":435715,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XXEUNR","text":"USGS data release","linkHelpText":"Genomic variation in the genus Pimephales: raw sequence data and single-nucleotide polymorphisms"},{"id":405677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":849724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Robert A.","contributorId":148008,"corporation":false,"usgs":false,"family":"Hrabik","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":849725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Nathan 0000-0002-1372-6340 nthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-1372-6340","contributorId":196133,"corporation":false,"usgs":true,"family":"Thompson","given":"Nathan","email":"nthompson@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":849726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":849727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236904,"text":"70236904 - 2022 - Aqueously altered igneous rocks sampled on the floor of Jezero crater, Mars","interactions":[],"lastModifiedDate":"2022-10-17T16:16:55.626611","indexId":"70236904","displayToPublicDate":"2022-08-25T06:59:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Aqueously altered igneous rocks sampled on the floor of Jezero crater, Mars","docAbstract":"Pollen accumulation rates (PAR, grains cm–2 year–1) have been shown to be a reliable but methodologically complex bioproxy for quantitative reconstruction of past tree abundance. In a prior study, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and the pollen group TC (Taxaceae and Cupressaceae families) – were robust and precise estimators of contemporary tree biomass. This paper expands our earlier work. Here, we more fully evaluate the errors associated with biomass reconstructions to identify weaknesses and recommend improvements in PAR-based reconstructions of forest biomass. We account for uncertainty in our biomass proxy in a formal, coherent fashion. The greatest error was introduced by the age models, underscoring the need for improved statistical approaches to age-depth modeling. Documenting the uncertainty in pollen vegetation models should be standard practice in paleoecology. We also share insights gained from the delineation of the relevant source area of pollen, advances in Bayesian 210Pb modeling, the importance of site selection, and the use of independent data to corroborate biomass estimates. Lastly, we demonstrate our workflow with a new dataset of reconstructed tree biomass between 1850 and 2018 AD from lakes in the Klamath Mountains, California. Our biomass records followed a broad trend of low mean biomass in the ∼1850s followed by large contemporary increases, consistent with expectations of forest densification due to twentieth century fire suppression policies in the American West. More recent reconstructed tree biomass estimates also corresponded with silviculture treatments occurring within the relevant source area of pollen of our lake sites.