Human populations have utilized heavy metals and persistent organic pollutants for their physiochemical properties in industrial, agricultural, and consumer goods for decades. Limited knowledge on their persistence and toxicological effects has resulted in organisms being exposed to some of the most problematic compounds ever generated by humans. Although overlap in exposure paradigms exists for historical and emerging contaminants, the different physiochemical properties, sources into the environment, and bioactivity of contaminants of emerging concern (CECs) have highlighted the importance of characterizing their risk to aquatic wildlife under chronic low-dose exposure scenarios. This chapter defines the fundamental terminology associated with characterizing the exposure paradigm in ecological risk assessment. The different sources and fate, routes of exposure, and biotransformation of common contaminants are covered using model chemicals to emphasize important factors that affect their partitioning among different environmental matrices. Finally, this chapter concludes with a discussion about bioaccumulation models and an example of how two similar CECs demonstrate different clearance rates and bioaccumulation potentials in fish.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Aquatic ecotoxicology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-53130-9_8","usgsCitation":"Saari, G.N., Siddiqui, S., and Brander, S.M., 2024, Partitioning of chemicals in aquatic organisms, chap. of Aquatic ecotoxicology, p. 115-130, https://doi.org/10.1007/978-3-031-53130-9_8.","productDescription":"16 p.","startPage":"115","endPage":"130","ipdsId":"IP-146203","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":433696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-19","publicationStatus":"PW","contributors":{"editors":[{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912940,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912941,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Saari, Gavin N. 0000-0002-3593-5127 gsaari@usgs.gov","orcid":"https://orcid.org/0000-0002-3593-5127","contributorId":289203,"corporation":false,"usgs":true,"family":"Saari","given":"Gavin","email":"gsaari@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":912888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siddiqui, Samreen","contributorId":298402,"corporation":false,"usgs":false,"family":"Siddiqui","given":"Samreen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":912889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brander, Susanne M.","contributorId":187546,"corporation":false,"usgs":false,"family":"Brander","given":"Susanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":912890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70253020,"text":"70253020 - 2024 - Invasive-dominated grasslands in Hawaiʻi are resilient to disturbance","interactions":[],"lastModifiedDate":"2024-04-17T12:12:10.505348","indexId":"70253020","displayToPublicDate":"2024-03-19T07:10:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Invasive-dominated grasslands in Hawaiʻi are resilient to disturbance","docAbstract":"Non-native-dominated landscapes may arise from invasion by competitive plant species, disturbance and invasion of early-colonizing species, or some combination of these. Without knowing site history, however, it is difficult to predict how native or non-native communities will reassemble after disturbance events. Given increasing disturbance levels across anthropogenically impacted landscapes, predictive understanding of these patterns is important. We asked how disturbance affected community assembly in six invaded habitat types common in dryland, grazed landscapes on Island of Hawai‘i. We mechanically disturbed 100 m2 plots in six vegetation types dominated by one of four invasive perennial grasses (Cenchrus ciliaris, Cenchrus clandestinus, Cenchrus setaceus, or Melinis repens), a native shrub (Dodonaea viscosa), or a native perennial bunchgrass (Eragrostis atropioides). We censused vegetation before disturbance and monitored woody plant colonization and herbaceous cover for 21 months following the disturbance, categorizing species as competitors, colonizers, or a combination, based on recovery patterns. In addition, we planted individuals of the native shrub and bunchgrass and monitored survival to overcome dispersal limitation of native species when exploring these patterns. We found that the dominant vegetation types showed variation in post-disturbance syndrome, and that the variation in colonizer versus competitor syndrome occurred both between species, but also within species among different vegetation types. Although there were flushes of native shrub seedlings, these did not survive to 21 months within invaded habitats, probably due to regrowth by competitive invasive grasses. Similarly, survival of planted native individuals was related to the rate of regrowth by dominant species. Regardless of colonization/competitor syndrome, however, all dominant vegetation types were relatively resilient to change. Our results highlight that the altered post-agricultural, invaded grassland landscapes in Hawaiʻi are stable states. More generally, they point to the importance of resident communities and their effects on species interactions and seed availability in shaping plant community response to disturbance.
Watershed nutrient management often focuses on actions that reduce the movement of nitrogen (N) and phosphorus (P) from agricultural lands into streams. One area of management focus is the buffer of land adjacent to streams. Wetlands and forests in this buffer can intercept and retain N and P from the landscape. In addition to directly intercepting agricultural nutrients, natural habitats in the buffer can alter stream geomorphology and influence the in-stream processing and transformation of N and P to less labile and mobile forms. Here, we assess the influence of buffer land cover on in-stream processing of N and P. We measured nutrient dynamics in the water column and sediments of agricultural streams in the Fox River and Duck Creek watersheds (WI, USA) during the growing season. In these streams, water column processing was low, possibly due to a lack of primary producers in the water column. Water column P processing was weakly associated with wetland land cover in the buffer, but buffer land cover had no clear effect on inorganic N processing. On the other hand, sediments were almost always a source of inorganic P and a sink for inorganic N. Sediment P release was higher in streams with more agricultural land cover in the buffer. Sediments in streams with agricultural land cover in the buffer also removed more nitrate, even after accounting for the greater availability of nitrate in those streams. The buffer land cover conditions we quantified occupy a very small portion of the overall watershed (100 m wide, for 1 km upstream of the study site) but nevertheless appear to influence in-stream cycling of N and P. For P management, reducing agricultural land cover in buffers is already a priority due to the ability of wetlands and forests to intercept nutrients, but this study suggests there may be some additional benefit due to changes in in-stream P processing.
The U.S. Geological Survey (USGS) collected data on the vertical distribution of hydraulic head, specific capacity, and water quality using aquifer-interval-isolation tests and other vertical profiling methods in 15 boreholes completed in fractured sedimentary bedrock in Northampton, Warminster, and Warwick Townships, Bucks County, Pennsylvania during 2018–19. This work was done, in cooperation with the U.S. Navy, to support detailed investigations at and near the former Naval Air Warfare Center (NAWC) Warminster, where groundwater contamination with per- and polyfluoroalkyl substances (PFAS) had become a concern since 2014. Two PFAS compounds, perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), have been measured in groundwater samples from supply and monitoring wells at or near NAWC Warminster in concentrations above U.S. Environmental Protection Agency health advisory levels for drinking water. The area is underlain by the Triassic Stockton Formation, which predominantly consists of sandstone interbedded with shale and siltstone beds and forms a layered fractured-rock aquifer used for private, industrial, and public drinking water supply.
The vertical distribution of aquifer properties and water quality was assessed through hydraulic tests and sampling of aquifer intervals using a straddle-packer system (13 boreholes) or depth-discrete point sampling under known borehole-flow conditions (2 boreholes). Geophysical and video logs collected by USGS during 2017–19 were used to identify potential water-bearing fractures in 15 boreholes, which ranged in depth from 210 to 604 feet (ft) and included 6 boreholes drilled in 2018 and 9 existing wells on or near the former NAWC Warminster. Measured borehole flow was predominantly downward in most of the deepest boreholes (greater than 400 ft), which were commonly located at the highest land-surface elevations, with inflow from fractures at relatively shallow depths and outflow through fractures near or below depths of 500 ft below land surface. Hydraulic head differences measured during packer tests were up to about 60 ft between shallow and deep intervals. Borehole flow was predominantly upward in most boreholes less than 400 ft in depth and farther from, and at lower land-surface elevations than, the former NAWC Warminster. Total borehole specific capacity ranged from about 0.07 to 41 gallons per minute per foot [(gal/min)/ft]. Specific-capacity values for individual intervals ranged from 0.02 to 40.0 (gal/min)/ft, with a median of 1.14 (gal/min)/ft and a large range in values at most depths.
Differences in water quality of samples as indicated by field properties (pH, dissolved oxygen, and specific conductance) and concentrations of dissolved major ions, PFOA, and PFOS were apparent among isolated intervals in the boreholes. Summed concentrations of PFOA and PFOS ranged from about 11 to 10,780 nanograms per liter (ng/L) and were greater than the 2016 U.S. Environmental Protection Agency health advisory of 70 ng/L for summed PFOA and PFOS concentrations in 62 of 104 intervals and discrete depths tested. The mass ratio of PFOS to PFOA was generally higher than 1.0 in samples with summed PFOA and PFOS concentrations greater than 70 ng/L, with ratio values as high as 8.7. In many boreholes, summed concentrations of PFOA and PFOS were positively related to chloride concentrations, which were elevated above natural-background values [less than 10 milligrams per liter] in most samples and as high as 717 milligrams per liter. Sources of the elevated chloride other than, or in addition to, common rock salt (sodium chloride) were indicated by chloride to sodium molar ratios greater than 1.0. Water-quality data indicated that sampled water from some intervals with lower hydraulic heads may be affected by water from intervals with higher hydraulic heads because of vertical flow in open boreholes; samples from these intervals with lower hydraulic heads may not be fully representative due to some component of cross contamination and should be interpreted with caution.
Through a preliminary correlation of natural gamma and resistivity logs of boreholes drilled at and near the former NAWC Warminster, 11 lithologic units were identified and interpreted to strike northeast and dip to the northwest. Hydraulic heads were generally highest in isolated intervals that intercepted beds which, when projected up dip, crop out at the highest land-surface elevation on the former NAWC Warminster, indicating that the dipping-bed structure and topography are factors affecting the distribution of hydraulic head in the aquifer. The hydrogeologic framework in conjunction with the vertical distribution of hydraulic heads and water quality may assist in evaluating the locations of various PFAS sources and potential migration pathways of PFAS in groundwater at and near NAWC Warminster.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241007","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Senior, L.A., and Fiore, A.R., 2024, Results of 2018–19 water-quality and hydraulic characterization of aquifer intervals using packer tests and preliminary geophysical-log correlations for selected boreholes at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania (ver. 1.1, January 2025): U.S. Geological Survey Open-File Report 2024–1007, 136 p., https://doi.org/10.3133/ofr20241007.","productDescription":"Report: xv, 136 p.; 5 Plates; Data Release","numberOfPages":"136","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138405","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":426405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1007 HTML"},{"id":426406,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.XML","description":"OFR 2024-1007 XML"},{"id":426407,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1007/images/"},{"id":426403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1007/coverthb2.jpg"},{"id":426404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007.pdf","text":"Report","size":"9.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1007 PDF"},{"id":426408,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TC92B5","text":"USGS data release","linkHelpText":"Water-level data and selected field notes for aquifer-interval-isolation tests at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania, 2018–19 (ver. 2.0, January 2024)"},{"id":426409,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_plates.pdf","text":"Plates 1–5","size":"921 KB"},{"id":481558,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2024/1007/ofr20241007_versionHist.txt","size":"949 B","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Naval Air Warfare Center Warminster","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.21874919403015,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.12697956762551\n ],\n [\n -74.97075997042653,\n 40.292862181975266\n ],\n [\n -75.21874919403015,\n 40.292862181975266\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 2024; Version 1.1 January 2025","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
This report is an update to the presentation by Schulz (1989) introducing potential users to the creepmeter data collected between the publication of Schulz’s report and mid-2020. The creepmeter network monitors aseismic, surface slip at various locations on the Hayward, Calaveras, and San Andreas Faults in northern and central California. There are different designs of creepmeters and these are briefly described. For a majority of the creepmeters, these data are automatically sent to the U.S. Geological Survey (USGS) offices where they are stored and processed. In addition, for most of the creepmeters, occasional manual measurements are made and these are compared with digitally recorded data. For some sites, the comparisons indicated degradation of the electronic sensor and consequently corrections are made to the digital data. The largest transient deformation is that which followed the 2004, M6, Parkfield earthquake. Various functions found in the literature that have been used to model postseismic slip were tested with the observed postseismic behavior seen on the creepmeters in the vicinity of Parkfield, California. No single function adequately fit all the data from these Parkfield instruments. This report is a discussion and analysis of data from creepmeters deployed by the USGS. The discussion primarily focuses on instruments that are currently operating in 2020 or have operated quite recently but are no longer in service.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241011","usgsCitation":"Langbein, J., Bilham, R.G., Snyder, H.A., and Ericksen, T., 2024, Summary of Creepmeter Data from 1980 to 2020—Measurements Spanning the Hayward, Calaveras, and San Andreas Faults in Northern and Central California: U.S. Geological Survey Report 2024–1011, 110 p., https://doi.org/10.3133/ofr20241011.","productDescription":"vi, 110 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-143918","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499206,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116172.htm","linkFileType":{"id":5,"text":"html"}},{"id":426750,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1011/ofr20241011.pdf","text":"Report","size":"60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1011/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.83784784258054,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 34.52234572819374\n ],\n [\n -119.36616815508066,\n 37.99394764431494\n ],\n [\n -122.83784784258054,\n 37.99394764431494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Rd.
Moffett Field, CA 94035
A massive bloom of the raphidophyte Heterosigma akashiwo occurred in summer 2022 in San Francisco Bay, causing widespread ecological impacts including events of low dissolved oxygen and mass fish kills. The rapidly evolving bloom required equally rapid management response, leading to the use of near-real-time image analysis of chlorophyll from the Ocean and Land Colour Instrument (OLCI) aboard Sentinel-3. Standard algorithms failed to adequately capture the bloom, signifying a need to refine a two-band algorithm developed for coastal and inland waters that relates the red-edge part of the remote sensing reflectance spectrum to chlorophyll. While the bloom was the initial motivation for optimizing this algorithm, an extensive dataset of in-water validation measurements from both bloom and non-bloom periods was used to evaluate performance over a range of concentrations and community composition. The modified red-edge algorithm with a simplified atmospheric correction scheme outperformed existing standard products across diverse conditions, and given the modest computational requirements, was found suitable for operational use and near-real-time product generation. The final version of the algorithm successfully minimizes error for non-bloom periods when chlorophyll a is typically <30 mg m−3, while also capturing bloom periods of >100 mg m−3 chlorophyll a.
","language":"English","publisher":"MDPI","doi":"10.3390/rs16061103","usgsCitation":"Kudela, R.M., Senn, D.B., Richardson, E.T., Bouma-Gregson, K., Bergamaschi, B.A., and Sim, L., 2024, Evaluation and refinement of chlorophyll-a algorithms for high-biomass blooms in San Francisco Bay (USA): Remote Sensing, v. 16, no. 6, 1103, 15 p., https://doi.org/10.3390/rs16061103.","productDescription":"1103, 15 p.","ipdsId":"IP-160723","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":440089,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16061103","text":"Publisher Index Page"},{"id":435018,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GXJHZ3","text":"USGS data release","linkHelpText":"Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the San Francisco Bay, California: 2021-2022 High-resolution mapping surveys"},{"id":427314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.07594813067364,\n 37.409521554962424\n ],\n [\n -122.01459141030173,\n 37.543473010939294\n ],\n [\n -122.3138751078345,\n 37.9439399615851\n ],\n [\n -122.2371288097209,\n 38.076947981745235\n ],\n [\n -122.4289707157553,\n 38.1493978144897\n ],\n [\n -122.49802549540809,\n 38.08298835733879\n ],\n [\n -122.5286656402067,\n 37.93788689033987\n ],\n [\n -122.4673236665621,\n 37.792501512759955\n ],\n [\n -122.35216906140471,\n 37.610380642182776\n ],\n [\n -122.07594813067364,\n 37.409521554962424\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kudela, Raphael M.","contributorId":205181,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":897798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senn, David B.","contributorId":205182,"corporation":false,"usgs":false,"family":"Senn","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Emily T. 0000-0003-2696-8266","orcid":"https://orcid.org/0000-0003-2696-8266","contributorId":304430,"corporation":false,"usgs":true,"family":"Richardson","given":"Emily","email":"","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouma-Gregson, Keith 0000-0002-0304-6034","orcid":"https://orcid.org/0000-0002-0304-6034","contributorId":311235,"corporation":false,"usgs":true,"family":"Bouma-Gregson","given":"Keith","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":897802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sim, Lawrence","contributorId":168731,"corporation":false,"usgs":false,"family":"Sim","given":"Lawrence","email":"","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":897803,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252559,"text":"70252559 - 2024 - All tidal wetlands are blue carbon ecosystems","interactions":[],"lastModifiedDate":"2024-03-28T11:57:06.250175","indexId":"70252559","displayToPublicDate":"2024-03-18T06:55:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"All tidal wetlands are blue carbon ecosystems","docAbstract":"Managing coastal wetlands is one of the most promising activities to reduce atmospheric greenhouse gases, and it also contributes to meeting the United Nations Sustainable Development Goals. One of the options is through blue carbon projects, in which mangroves, saltmarshes, and seagrass are managed to increase carbon sequestration and reduce greenhouse gas emissions. However, other tidal wetlands align with the characteristics of blue carbon. These wetlands are called tidal freshwater wetlands in the United States, supratidal wetlands in Australia, transitional forests in Southeast Asia, and estuarine forests in South Africa. They have similar or larger potential for atmospheric carbon sequestration and emission reductions than the currently considered blue carbon ecosystems and have been highly exploited. In the present article, we suggest that all wetlands directly or indirectly influenced by tides should be considered blue carbon. Their protection and restoration through carbon offsets could reduce emissions while providing multiple cobenefits, including biodiversity.
","language":"English","publisher":"American Institute of Biological Sciences","doi":"10.1093/biosci/biae007","usgsCitation":"Adame, M.F., Kelleway, J., Krauss, K., Lovelock, C.E., Adams, J.B., Trevathan-Tackett, S.M., Noe, G.E., Jeffrey, L., Ronan, M., Zann, M., Carnell, P.E., Iram, N., Maher, D.T., Murdiyarso, D., Sasmito, S.D., Tran, D.B., Dargusch, P., Kauffman, J.B., and Brophy, L.S., 2024, All tidal wetlands are blue carbon ecosystems: BioScience, biae007, 16 p., https://doi.org/10.1093/biosci/biae007.","productDescription":"biae007, 16 p.","ipdsId":"IP-152962","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":440093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biae007","text":"Publisher Index Page"},{"id":427204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Adame, Maria Fernanda","contributorId":242984,"corporation":false,"usgs":false,"family":"Adame","given":"Maria","email":"","middleInitial":"Fernanda","affiliations":[{"id":48596,"text":"Australian Rivers Institute, Griffith University","active":true,"usgs":false}],"preferred":false,"id":897548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleway, Jeffrey","contributorId":149007,"corporation":false,"usgs":false,"family":"Kelleway","given":"Jeffrey","email":"","affiliations":[{"id":17618,"text":"Plant Functional Biology and Climate Change Cluster, University of Technology, Sydney, Broadway, NSW, Australia","active":true,"usgs":false}],"preferred":false,"id":897549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":222384,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":897550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lovelock, Catherine E.","contributorId":215562,"corporation":false,"usgs":false,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":39280,"text":"School of Biological Sciences, The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":897551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Janine B.","contributorId":303863,"corporation":false,"usgs":false,"family":"Adams","given":"Janine","email":"","middleInitial":"B.","affiliations":[{"id":65919,"text":"Nelson Mandela University (South Africa)","active":true,"usgs":false}],"preferred":false,"id":897552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trevathan-Tackett, Stacey M.","contributorId":335151,"corporation":false,"usgs":false,"family":"Trevathan-Tackett","given":"Stacey","email":"","middleInitial":"M.","affiliations":[{"id":68587,"text":"Deakin University, Australia","active":true,"usgs":false}],"preferred":false,"id":897553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - 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Boone","contributorId":243963,"corporation":false,"usgs":false,"family":"Kauffman","given":"J.","email":"","middleInitial":"Boone","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":897565,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Brophy, Laura S.","contributorId":47266,"corporation":false,"usgs":false,"family":"Brophy","given":"Laura","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":897566,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70252241,"text":"70252241 - 2024 - Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river","interactions":[],"lastModifiedDate":"2024-03-21T11:57:22.485186","indexId":"70252241","displayToPublicDate":"2024-03-18T06:53:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river","docAbstract":"Predicting how increasing temperatures interact with other global change drivers to influence the structure and dynamics of Earth's ecosystems is a primary challenge in ecology. Our study made use of multiple simultaneous “natural experiments” to examine how rapid warming, declining nutrients, invasive consumers, and riparian invasive species management interact to influence leaf decomposition in a large and regulated river. Specifically, we compared the breakdown of cottonwood (Populus fremontii), willow (Salix exigua), and saltcedar (Tamarix sp.) leaf litter in 2022 to a previous experiment from 1998 that occurred under much cooler water temperatures, and had higher water phosphorus concentrations, low numbers of invasive New Zealand mudsnails (Potamopyrgus antipodarum), and unaltered litter chemistry from the herbivory of saltcedar leaf beetles (Diorhabda carinulata). We found that the effects of up to 10°C warmer temperatures on leaf decomposition were mediated by the establishment and management of invasive species and declining water nutrient concentrations arising from upstream reservoir lowering. Such interactions led to accelerated breakdown of saltcedar, but relatively minor effects of warming on the rate of cottonwood and willow decomposition. Additionally, our results demonstrate the potential for favorable invasive species management outcomes in the terrestrial environment to produce unintended responses in adjacent freshwater ecosystems. As temperatures continue to rise, it is critical that future studies consider how warming interacts with multiple stressors and environmental factors to influence processes such as decomposition in freshwater ecosystems.
Two earthquake sequences occurred a year apart at the Mendocino Triple Junction in northern California: first the 20 December 2021 �w 6.1 and 6.0 Petrolia sequence, then the 20 December 2022 �w 6.4 Ferndale sequence. To delineate active faults and understand the relationship between these sequences, we applied an automated deep‐learning workflow to create enhanced and relocated earthquake catalogs for both the sequences. The enhanced catalog newly identified more than 14,000 M 0–2 earthquakes and also found 852 of 860 already cataloged events. We found that deep‐learning and template‐matching approaches complement each other to improve catalog completeness because deep learning finds more M 0–2 background seismicity, whereas template‐matching finds the smallest M < 0 events near already known events. The enhanced catalog revealed that the 2021 Petrolia and 2022 Ferndale sequences were distinct in space and time, but adjacent in space. Though both the sequences happened in the downgoing Gorda slab, the shallower Ferndale sequence ruptured within the uppermost slab near the subduction interface, while the onshore Petrolia sequence occurred deeper in the mantle. Deep‐learning‐enhanced earthquake catalogs could help monitor evolving earthquake sequences, identify detailed seismogenic fault structures, and understand space–time variations in earthquake rupture and sequence behavior in a complex tectonic setting.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230053","usgsCitation":"Yoon, C., and Shelly, D.R., 2024, Distinct yet adjacent earthquake sequences near the Mendocino Triple Junction: 20 December 2021 Mw 6.1 and 6.0 Petrolia, and 20 December 2022 Mw 6.4 Ferndale: The Seismic Record, v. 4, no. 1, p. 81-92, https://doi.org/10.1785/0320230053.","productDescription":"12 p.","startPage":"81","endPage":"92","ipdsId":"IP-160618","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":440099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230053","text":"Publisher Index Page"},{"id":426825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.13993753734817,\n 41.452141149959374\n ],\n [\n -125.13993753734817,\n 39.78442225223091\n ],\n [\n -123.11845316234829,\n 39.78442225223091\n ],\n [\n -123.11845316234829,\n 41.452141149959374\n ],\n [\n -125.13993753734817,\n 41.452141149959374\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":896979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":896980,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252931,"text":"70252931 - 2024 - Analysis of mitochondrial DNA sequence data demonstrates that monophyly of myotis occultus is complicated by greater sampling of myotis lucifugus","interactions":[],"lastModifiedDate":"2024-04-11T11:48:04.087404","indexId":"70252931","displayToPublicDate":"2024-03-18T06:45:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of mitochondrial DNA sequence data demonstrates that monophyly of myotis occultus is complicated by greater sampling of myotis lucifugus","docAbstract":"The validity of Myotis occultus as a species unique from Myotis lucifugus has been a source of debate. Most recently, many authorities treat M. occultus as a distinct species, at least in part because a previous study showed that M. occultus and M. l. carissima (the subspecies that occurs in closest geographic proximity to M. occultus) form separate monophyletic clades based on sequences of two mitochondrial genes (cytochrome-b [cytb] and cytochrome oxidase subunit II [COII]). We re-evaluated the phylogenetic relationship between M. occultus and M. lucifugus based on mitochondrial sequences using an expanded dataset of cytb and COII sequences that originated from more genetically diverse specimens of M. lucifugus collected across a broader geographic area. Based on a phylogenetic analysis, we found that M. occultus sublineages embedded within a well-supported clade that included some specimens of M. lucifugus. These results indicate that the previous genetic analysis demonstrating that M. occultus and M. lucifugus form distinct monophyletic groups is unsupported by our larger dataset. Future research will likely need to focus on genetic work involving whole-genome sequencing of nuclear DNA to better resolve the true taxonomic relationship between M. occultus and M. lucifugus.
La valides de Myotis occultus como una especie distinta a Myotis lucifugus ha sido fuente de debate. Recientemente, muchas autoridades han considerado M. occultus como una especie diferente, en parte porque un estudio anterior mostró que M. occultus y M. l. carissima (la subespecie con la mayor proximidad geográfica a M. occultus) forman clados monofiléticos separados basados en secuencias de dos genes mitocondriales (el citocromo-b [cytb] y la subunidad II de citocromo oxidasa [COII]). Nosotros hemos reevaluado la relación filogenética entre M. occultus y M. lucifugus usando una ampliada colección de datos que contiene secuencias de los genes mitocondriales cytb y COII de especímenes de M. lucifugus genéticamente más diversos que fueron muestreados en un área geográfica más extensa. Nuestro análisis filogenético muestra que los sublinajes de M. occultus están incrustados dentro de un clado bien respaldado que incluye algunos especímenes de M. lucifugus. Estos resultados indican que el análisis genético anterior que demostró que M. occultus y M. lucifugus forman grupos monofiléticos distintos no está respaldado por nuestra más amplia colección de datos. Es probable que para resolver mejor la verdadera relación taxonómica entre M. occultus y M. lucifugus sea necesario el uso de secuenciación del genoma completo del ADN nuclear.
Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator–prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator–prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.11149","usgsCitation":"Clipp, H.L., Pesi, S.M., Miller, M.L., Gigliotti, L., Skelly, B.P., and Rota, C., 2024, White-tailed deer detection rates increase when coyotes are present: Ecology and Evolution, v. 14, no. 3, e11149, 13 pp., https://doi.org/10.1002/ece3.11149.","productDescription":"e11149, 13 pp.","ipdsId":"IP-157302","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":440105,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.11149","text":"Publisher Index Page"},{"id":433571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.4877790212181,\n 39.94978819373756\n ],\n [\n -82.01878727948417,\n 39.01317775882444\n ],\n [\n -82.58830516880357,\n 38.2047845680037\n ],\n [\n -79.5468825034643,\n 37.66652638635898\n ],\n [\n -77.96682473836029,\n 39.5141262945331\n ],\n [\n -76.37907636338417,\n 40.11338027059526\n ],\n [\n -77.28462588707731,\n 41.09189702989761\n ],\n [\n -80.4877790212181,\n 39.94978819373756\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Clipp, Hannah L.","contributorId":342785,"corporation":false,"usgs":false,"family":"Clipp","given":"Hannah","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pesi, Sarah M.","contributorId":342786,"corporation":false,"usgs":false,"family":"Pesi","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Madison L.","contributorId":342787,"corporation":false,"usgs":false,"family":"Miller","given":"Madison","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gigliotti, Laura C. 0000-0002-6390-4133","orcid":"https://orcid.org/0000-0002-6390-4133","contributorId":200327,"corporation":false,"usgs":false,"family":"Gigliotti","given":"Laura C.","affiliations":[],"preferred":false,"id":910395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skelly, Brett P.","contributorId":342789,"corporation":false,"usgs":false,"family":"Skelly","given":"Brett","email":"","middleInitial":"P.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910396,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rota, Christopher T.","contributorId":342791,"corporation":false,"usgs":false,"family":"Rota","given":"Christopher T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":910397,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70252441,"text":"70252441 - 2024 - Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","interactions":[],"lastModifiedDate":"2024-05-07T14:35:47.184916","indexId":"70252441","displayToPublicDate":"2024-03-17T08:31:39","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models","docAbstract":"Model development in the Next Generation Attenuation-East (NGA-East) project included two components developed concurrently and independently: (1) earthquake ground-motion models (GMMs) that predict the median and aleatory variability of various intensity measures conditioned on magnitude and distance, derived for a reference hard-rock site condition with an average shear-wave velocity in the upper 30 m (VS30) = 3000 m/s; and (2) a site amplification model that modifies intensity measures for softer site conditions. We investigate whether these models, when used in tandem, are compatible with ground-motion recordings in central and eastern North America (CENA) using an expanded version of the NGA-East database that includes new events from November 2011 (end date of NGA-East data curation) to April 2022. Following this expansion, the data set has 187 events, 2096 sites, and 16,272 three-component recordings, although the magnitude range remains limited (∼4 to 5.8). We compute residuals using 17 NGA-East GMMs and three data selection criteria that reflect within-CENA regional variations in ground-motion attributes. Mixed-effects regression of the residuals reveals a persistent pattern in which ground motions are overpredicted at short periods (0.01–0.6 s, including peak ground acceleration (PGA)) and underpredicted at longer periods. These misfits are regionally variable, with the Texas–Oklahoma–Kansas region having larger absolute misfits than other parts of CENA. Two factors potentially influencing these misfits are (1) differences in the site amplification models used to adjust the data to the reference condition during NGA-East GMM development relative to CENA amplification models applied since the 2018 National Seismic Hazard Model (NSHM), and (2) potential bias in simulation-based factors used to adjust ground motions from the hard-rock reference condition to a VS30 = 760 m/s condition. We provide adjustment factors and their epistemic uncertainties and discuss implications for applications.
","language":"English","publisher":"Sage Journals","doi":"10.1177/87552930241231825","usgsCitation":"Ramos-Sepulveda, M.E., Stewart, J.P., Parker, G.A., Moschetti, M.P., Thompson, E.M., Brandenberg, S.J., Hashash, Y.M., and Rathje, E., 2024, Data-driven adjustments for combined use of NGA-East hard-rock ground motion and site amplification models: Earthquake Spectra, v. 40, no. 2, p. 1132-1157, https://doi.org/10.1177/87552930241231825.","productDescription":"26 p.","startPage":"1132","endPage":"1157","ipdsId":"IP-153071","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":440108,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/87552930241231825","text":"Publisher Index 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s\":{\"name\":\"Kansas\",\"nation\":\"USA \"}}]}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-03-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos-Sepulveda, Maria E.","contributorId":294748,"corporation":false,"usgs":false,"family":"Ramos-Sepulveda","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":897170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":897171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":897172,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":897174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandenberg, Scott J.","contributorId":303895,"corporation":false,"usgs":false,"family":"Brandenberg","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":897175,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hashash, Youssef M A","contributorId":146595,"corporation":false,"usgs":false,"family":"Hashash","given":"Youssef","email":"","middleInitial":"M A","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":897176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rathje, Ellen 0000-0002-4169-7153","orcid":"https://orcid.org/0000-0002-4169-7153","contributorId":197024,"corporation":false,"usgs":false,"family":"Rathje","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":897177,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70252201,"text":"70252201 - 2024 - Vulnerability to sea-level rise varies among estuaries and habitat types: Lessons learned from a network of surface elevation tables in Puget Sound","interactions":[],"lastModifiedDate":"2024-08-26T14:32:10.591453","indexId":"70252201","displayToPublicDate":"2024-03-17T06:41:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Vulnerability to sea-level rise varies among estuaries and habitat types: Lessons learned from a network of surface elevation tables in Puget Sound","docAbstract":"Estuarine systems that provide valuable ecosystem services to society and important foraging and rearing habitat for fish and wildlife species continue to undergo degradation. In Puget Sound, WA, as much as 70–80% of historic estuarine habitat has been lost to anthropogenic development, and continued losses are expected through the end of the twenty-first century due to rising sea levels. To evaluate whether Puget Sound’s estuarine habitats will keep pace with current and projected sea-level rise (SLR), we assessed vertical rates of elevation change from a regional network of surface elevation tables and marker horizons (SET-MH). Over the past two decades, SET-MH equipment has been installed throughout a variety of habitats in five Puget Sound estuaries: the Nisqually, Snohomish, Stillaguamish, and Skagit River estuaries, and Padilla Bay. These data provide a unique opportunity to assess elevation change and habitat resilience across a spatiotemporal and environmental gradient. We observed different rates of surface elevation change among estuaries and habitats (Nisqually = 4.64 ± 2.81 mm/year, Snohomish = 5.71 ± 5.83 mm/year, Stillaguamish = 12.82 ± 10.29 mm/year, Skagit = 16.13 ± 7.57 mm/year, Padilla = − 1.25 ± 1.58 mm/year). The highest rates were found at restoring sites with regular sediment input in the Stillaguamish and Skagit estuaries, whereas rates were consistently negative at low elevation sites in sediment starved Padilla Bay. Many sites in Puget Sound appear to be keeping pace with current rates of relative SLR, and some areas are on track to exceed projected rates through the end of the century. These findings indicate that Puget Sound’s estuarine habitats can be resilient to rising tidal levels—as long as sediment delivery is maintained.
The number of large, high-severity wildfires has been increasing across the western United States over the last several decades. It is not fully understood how changes in the frequency of large, severe wildfires may impact the resilience of conifer forests, due to alterations in regeneration success or failure. Our research investigates 30 years of conifer recovery patterns within 34 high-severity wildfire complexes (1988–1991) of the Northern Rocky Mountains. We evaluate the capability of snow-cover Landsat to characterize conifer tree recolonization of high-severity burn patches. Snow-cover images isolate conifer-specific vegetation signals by diminishing spectral contributions from soil and deciduous vegetation. The presence of conifer regeneration was successfully classified by snow-cover Landsat at >10% canopy cover at 98% accuracy and modeled at 3-year intervals post-fire. Spectral detectability of regenerating conifer vegetation began 11–19 years post-fire, varying across forest types. Thirty years post-fire, 65% of the total high-severity burn area had been recolonized by conifer trees, with differences observed between forest types: 72% of lodgepole pine, 77% of Douglas-fir, and 44% of fir-spruce severely burned areas containing conifer regeneration. Projected recovery timelines to pre-fire conifer vegetation also differed between lodgepole pine (29.5 years), Douglas-fir (36.9 years), and fir-spruce forests (48.7 years), as estimated from snow-cover NDVI trends. Although we generally documented patterns of conifer resilience, we also identified reduced likelihoods of recovery within high-severity burn patches exhibiting greater area-to-perimeter ratios, aridity, south-facing aspects, slopes, and elevation. Snow-cover Landsat imagery was shown to improve the characterization of post-fire forest recovery and may be applied to support forest restoration decision-making following high-severity wildfire.
Predation can play an important role in structuring ecological communities, and predator–prey dynamics can be altered following the introduction of new species. An unauthorized introduction of redside shiner (Richardsonius balteatus) into reservoirs in the Upper Skagit River, Washington, USA created concern that a consequent shift in predator–prey dynamics in the reservoirs could reduce recruitment and production of native salmonids in the basin. We estimated predation mortality in Ross Lake on nonnative redside shiner and juvenile native salmonids to evaluate the potential role of predation in regulating these populations and limiting survival of native species of concern. We used bioenergetics modelling and stable isotope analysis combined with directed field measurements of growth, seasonal diet and thermal experience of piscivorous salmonids to quantify their consumption demand on prey fishes to evaluate the relative magnitude of predation mortality on invasive redside shiners and native salmonids. While redside shiner are the dominant prey fish species in Ross Lake, the modest biomass of native salmonids consumed could translate into substantial mortality, the magnitude of which depended on the timing and size at which prey fishes were eaten. This information provides important context for how nonnative species may indirectly impact native species through shared predation (apparent competition) and can inform conservation decisions surrounding nonnative species control, sustainability of native salmonids and introductions of anadromous fishes.
Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents.
The intent of a case definition is to provide scientifically based criteria for determining (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to electrocution and applies to all avian species.
Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents.
The intent of a case definition is to provide scientifically based criteria for determining (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to Ophidiomycosis (snake fungal disease) and applies to all snakes.
Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents.
The intent of a case definition is to provide scientifically based criteria for determining (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to avian botulism and applies to all avian species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm19E1","collaboration":"Prepared in cooperation with the Canadian Wildlife Health Cooperative","usgsCitation":"Lankton, J.S., and Stevens, B., 2024, Avian botulism case definition for wildlife: U.S. Geological Survey Techniques and Methods, book 19, chap. E1, 8 p., https://doi.org/10.3133/tm19E1.","productDescription":"v, 6 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-140737","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":426258,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/19/e1/tm19e1.pdf","text":"Report","size":"3.8 MB","description":"TM 19–E1"},{"id":426257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/19/e1/coverthb.jpg"},{"id":426259,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/19/e1/tm19e1.XML"},{"id":426260,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/19/e1/images/"},{"id":426261,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm19E1/full"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents. The intent of a case definition is to provide scientifically based criteria for determining (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition template can be used for any disease/pathogen for any species. An editable version of this template is available for download at https://doi.org/10.3133/tm19A1.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm19A1","collaboration":"Prepared in cooperation with the Canadian Wildlife Health Cooperative","usgsCitation":"Miller, K.J.G., Parmley, E.J., Ballmann, A., Buckner, J., Jones, M., Lankton, J.S., Zimmer, M., and Lankau, E., 2024, [Disease/condition] case definition [template] for wildlife: U.S. Geological Survey Techniques and Methods, book 19, chap. A1, 8 p., https://doi.org/10.3133/tm19A1.","productDescription":"Report: vi, 8 p.; Editable Template","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140735","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":426150,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/tm/19/a1/downloads/","text":"Editable template","size":"122 kB","linkHelpText":"—[Disease/Condition] Case Definition [Template] for Wildlife"},{"id":426151,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm19A1/full"},{"id":426146,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/19/a1/coverthb.jpg"},{"id":426148,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/19/a1/tm19a1.XML"},{"id":426149,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/19/a1/images/"},{"id":426147,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/19/a1/tm19a1.pdf","text":"Report","size":"7.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 19–A1"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
Welcome to the first manual of “Case Definitions for Wildlife Diseases,” a “living” electronic publication. The plan is to add and update this manual’s case definitions periodically as warranted; thus, this manual will never be completed, and readers should download the latest versions of specific chapters (that is, definitions) when available. Constructive suggestions from readers are welcome and will help guide adjustments as this project progresses.
The purpose of this manual is to provide case definitions for selected diseases of importance to wildlife in Canada and the United States. Case definitions provide standard sets of criteria for classifying the degree of certainty of a particular diagnosis and help improve surveillance data quality and comparability. Better data and standardization allow for improved data sharing, which increases geographic and species surveillance coverage and permits more robust analyses.
The definitions included in this manual have been developed by veterinary pathologists, epidemiologists, and wildlife biologists primarily from the U.S. Geological Survey National Wildlife Health Center (NWHC) and Canadian Wildlife Health Cooperative (CWHC). Pathologists from each organization reviewed and finalized the definitions. Each case definition has been peer reviewed by two scientific experts before publication.
This manual begins with the case definition template. This generic template includes four sections: “Individual, Place, and Time Criteria for Diagnosis and Testing,” “Field Criteria for Diagnosis,” “Laboratory Criteria for Diagnosis,” and “Epidemiological Linkage Criteria for Diagnosis” and can be used to guide development of new case definitions. Information in each section is then combined to provide an overall case classification. Disease diagnoses are classified as “Confirmed,” “Presumptive,” or “Suspected;” and evidence of a pathogen or toxin is classified as “Exposed” or “Present/Detected.” Each subsequent chapter is then a case definition for a specific disease of wildlife, and infectious and non-infectious diseases are included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm19","collaboration":"Prepared in cooperation with the Canadian Wildlife Health Cooperative","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":426174,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/19/tm19.pdf","size":"0.98 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":426173,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/19/coverthb2.jpg"},{"id":426538,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/19/downloads/","text":"Editable template","size":"121 kB","linkHelpText":"—[Disease/Condition] Case Definition [Template] for Wildlife"}],"contact":"Director, National Wildlife Health Center
U.S. Geological Survey
6006 Schroeder Road
Madison, WI 53711
The United States Geological Survey (USGS) has continuously monitored the Mohawk River between Lock 7 and Lock 9 of the New York State Barge Canal since 2011. There was a brief period, from 1914 to 1919, when a streamgage was operated at Vischer Ferry Dam (Lock 7), however, frequent damage to the gage from ice-jam related flooding in 1914 (figure 1) and 1916 resulted in establishing the Mohawk River streamgage at Cohoes, NY (USGS station ID 01357500) in 1917 and discontinuing the Vischer Ferry streamgage in 1919. The current monitoring network includes measurements of gage height (water level) and water temperature at various points within the reach, streamflow at Freeman’s Bridge, and realtime imagery from multiple pan-tilt-zoom web cameras, all of which provide situational awareness to the public, emergency managers, and other stakeholders during periods of ice-jam flooding. The USGS operates and maintains these stations in cooperation with the New York Power Authority, New York State Department of Environmental Conservation, Union College, and Brookfield Renewable Power.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2024 Mohawk Watershed Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Union College","usgsCitation":"Gazoorian, C.L., 2024, United States Geological Survey ice jam monitoring network on the Mohawk River in Schenectady, NY, in Proceedings of the 2024 Mohawk Watershed Symposium, v. 14, p. 27-28.","productDescription":"2 p.","startPage":"27","endPage":"28","ipdsId":"IP-162726","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":501500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501499,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://minerva.union.edu/garverj/mws/2024/symposium.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","city":"Schenectady","otherGeospatial":"Mohawk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.92518238681888,\n 42.83580687077557\n ],\n [\n -73.97515733707353,\n 42.83580687077557\n ],\n [\n -73.97515733707353,\n 42.81032004405722\n ],\n [\n -73.92518238681888,\n 42.81032004405722\n ],\n [\n -73.92518238681888,\n 42.83580687077557\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894589,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70252191,"text":"70252191 - 2024 - Flood of October 31 to November 3, 2019, East Canada Creek, West Canada Creek, and Sacandaga River Basins","interactions":[],"lastModifiedDate":"2024-03-19T13:23:25.892201","indexId":"70252191","displayToPublicDate":"2024-03-15T08:21:38","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Flood of October 31 to November 3, 2019, East Canada Creek, West Canada Creek, and Sacandaga River Basins","docAbstract":"Between October 31 and November 3, 2019, historic flooding in parts of the Mohawk Valley and southern Adirondack region resulted in one fatality, an estimated $33 million in damages, and the declaration of a state of emergency for 13 New York counties. Flooding resulted from high-intensity rainfall within a 24-hour period between October 31 and November 1, 2019, at the end of an October that had much higher rainfall than normal. In that 24-hour period, rainfall amounts in the most heavily affected parts of the region largely ranged from about 2 to 5 inches, but a maximum rainfall amount of 7.00 inches was recorded in Speculator, NY in Hamilton County. In this location, a rainfall of 7.00 inches in a 24-hour period is estimated to have between a 200- and 500-year recurrence interval or between a 0.5- and 0.2-percent chance of happening or being exceeded in any given year.\n\nThe most severe flooding from October 31 to November 3, 2019, was mainly in the East and West Canada Creek basins, which are within the Mohawk River basin, and the Sacandaga River basin, which is within the upper Hudson River basin. Flooding resulted in new peak streamflow records at eight of nine selected U.S. Geological Survey streamgages from the region, including at three streamgages that have been in operation for about 100 years. At East Canada Creek at East Creek, NY (01348000), flooding resulted in the second highest peak streamflow in its 71-year period of record. National Weather Service major flood stages were exceeded at the three streamgages in the region where National Weather Service flood stages have been established and were exceeded at Hinckley Reservoir at Hinckley, NY (01343600). Hinckley Reservoir has a drainage area of 372 square miles and regulates West Canada Creek streamflow about 31 miles upstream of West Canada Creek at Kast Bridge (01346000) and 3 miles downstream of West Canada Creek near Wilmurt, NY (01343060). \n\nIn West Canada Creek, downstream of Hinckley Reservoir, a distinct double peak of streamflow happened during the 2019 flood and was recorded at West Canada Creek at Kast Bridge, NY (01346000). A similar, but less distinct, double peak was recorded at Mohawk River near Little Falls, NY (01347000), which is located 14.8 miles downstream of West Canada Creek at Kast Bridge, NY (01346000). The first peak of the double peak was likely caused by inflows to West Canada Creek from unregulated tributaries downstream of Hinckley Reservoir, such as Cincinnati Creek, which drains a relatively large area of 48.5 square miles in the northwest corner of the West Canada Creek watershed. Cincinnati Creek was ungaged at the time, but in response to the flood, the U.S. Geological Survey, in cooperation with the New York State Canal Corporation, installed a gage at Cincinnati Creek at Barneveld, NY (01344795) that has been in operation since November 2022. The second peak of the double peak, which happened about a day after the first peak, likely resulted from regulated streamflow that passed through Hinckley Reservoir. At the other streamgages upstream of Hinckley Reservoir, single peak streamflows were recorded during the flood. More details on the nature of the flood of October 31 to November 3, 2019, including the historic context of the flood, and the results from flood-frequency analysis of six selected streamgages in the Mohawk Valley and southern Adirondack region, are discussed in Graziano and others (2024).","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2024 Mohawk Watershed Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Mohawk Watershed Symposium","conferenceDate":"March 15, 2024","conferenceLocation":"Schenectady, NY","language":"English","publisher":"Union College","collaboration":"New York State Department of Environmental Conservation","usgsCitation":"Graziano, A.P., Smith, T.L., and Lilienthal, A.G., 2024, Flood of October 31 to November 3, 2019, East Canada Creek, West Canada Creek, and Sacandaga River Basins, in Proceedings of the 2024 Mohawk Watershed Symposium, v. 14, Schenectady, NY, March 15, 2024, p. 35-40.","productDescription":"6 p.","startPage":"35","endPage":"40","ipdsId":"IP-162519","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":426768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":426765,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://minerva.union.edu/garverj/mws/2024/symposium.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"East Canada Creek, West Canada Creek, and Sacandaga River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.26955336733255,\n 43.83029414607452\n ],\n [\n -75.24342943210101,\n 43.48996180099857\n ],\n [\n -75.21373328157367,\n 43.29245297551128\n ],\n [\n -74.29992522793536,\n 43.507816029663445\n ],\n [\n -74.26955336733255,\n 43.83029414607452\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graziano, Alexander P. 0000-0003-1978-0986","orcid":"https://orcid.org/0000-0003-1978-0986","contributorId":211607,"corporation":false,"usgs":true,"family":"Graziano","given":"Alexander","email":"","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":896878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Travis L. 0000-0002-3448-2787 tlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-2787","contributorId":297400,"corporation":false,"usgs":true,"family":"Smith","given":"Travis","email":"tlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":896879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lilienthal, Arthur G. III 0000-0002-2906-6375","orcid":"https://orcid.org/0000-0002-2906-6375","contributorId":211366,"corporation":false,"usgs":true,"family":"Lilienthal","given":"Arthur","suffix":"III","email":"","middleInitial":"G.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":896880,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70252538,"text":"70252538 - 2024 - Yosemite toad (Anaxyrus canorus) transcriptome reveals interplay between speciation genes and adaptive introgression","interactions":[],"lastModifiedDate":"2024-04-10T16:06:54.454973","indexId":"70252538","displayToPublicDate":"2024-03-15T06:50:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Yosemite toad (Anaxyrus canorus) transcriptome reveals interplay between speciation genes and adaptive introgression","title":"Yosemite toad (Anaxyrus canorus) transcriptome reveals interplay between speciation genes and adaptive introgression","docAbstract":"Genomes are heterogeneous during the early stages of speciation, with small ‘islands’ of DNA appearing to reflect strong adaptive differences, surrounded by vast seas of relative homogeneity. As species diverge, secondary contact zones between them can act as an interface and selectively filter through advantageous alleles of hybrid origin. Such introgression is another important adaptive process, one that allows beneficial mosaics of recombinant DNA (‘rivers’) to flow from one species into another. Although genomic islands of divergence appear to be associated with reproductive isolation, and genomic rivers form by adaptive introgression, it is unknown whether islands and rivers tend to be the same or different loci. We examined three replicate secondary contact zones for the Yosemite toad (Anaxyrus canorus) using two genomic data sets and a morphometric data set to answer the questions: (1) How predictably different are islands and rivers, both in terms of genomic location and gene function? (2) Are the adaptive genetic trait loci underlying tadpole growth and development reliably islands, rivers or neither? We found that island and river loci have significant overlap within a contact zone, suggesting that some loci are first islands, and later are predictably converted into rivers. However, gene ontology enrichment analysis showed strong overlap in gene function unique to all island loci, suggesting predictability in overall gene pathways for islands. Genome-wide association study outliers for tadpole development included LPIN3, a lipid metabolism gene potentially involved in climate change adaptation, that is island-like for all three contact zones, but also appears to be introgressing (as a river) across one zone. Taken together, our results suggest that adaptive divergence and introgression may be more complementary forces than currently appreciated.
Per- and polyfluoroalkyl substances (PFAS) are ubiquitous in the environment but sources are not well defined for temporal and spatial aspects within an urban environment, and especially for an arid urban environment subject to seasonal short term high-intensity precipitation events. A focused diel sampling was conducted in the summer of 2021 to assess the temporal and spatial variability of PFAS in the Rio Grande near Albuquerque, New Mexico and showed an order of magnitude increase of PFAS as it flows through the Albuquerque urban area. Discrete samples were collected at two different locations on the Rio Grande in addition to wastewater treatment plant (WWTP) effluent that discharges directly to the Rio Grande between the sampling locations. Short-term high-intensity precipitation events occurred during the study period and mobilized PFAS from urban runoff. Dissolved organic matter composed of tryptophan-like organic substances and refined fuel and fuel byproducts, characteristic of an urban signature, were also related to the precipitation events. The PFAS in discharge from the WWTP was consistent over a 24-h period with slight differences in some compounds. Wastewater presence on the Rio Grande downstream of the WWTP was evidenced by a gadolinium anomaly as well as increases in several other trace elements, total dissolved nitrogen, and fluorescence indicators, in addition to PFAS. PFAS varied depending on source contribution, where urban runoff was associated with PFOA, PFOS, and PFBA, whereas PFHxA and PFPeA were associated with wastewater effluent. In addition, passive polar organic chemical integrative samplers (POCIS) using hydrophilic-lipid balance (HLB) sorption media were deployed for a month at two locations on the Rio Grande to assess longer term PFAS concentrations. The POCIS results show some compounds (PFPeA and PFHpA) were greater than the average concentration from discrete samples, whereas other compounds (PFHxA, PFOA, PFDA, and PFNA) were lower in the POCIS, and PFOS was very similar between the two. The POCIS did not detect PFBA, which may be related to the HLB media not performing well for short chain PFAS compounds. The results show promise for integrative samplers utilizing sorbent media. More detailed investigation of the spatial and temporal variability of water chemistry on the Rio Grande as it flows through Albuquerque could provide information applicable to urban areas worldwide.