Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep (Ovis canadensis nelsoni) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation.
Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000–2018 and captured bighorn in 2010–2016 to deploy GPS collars and test for disease. From 2011–2015, we non-invasively collected fecal samples and genotyped them at 9–16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capture-recapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model.
Results and discussion: From 2010–2018, 3,176 sightings of bighorn were reported, with sightings of 56–145 bighorn annually on formal surveys. From 2012–2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae, a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011–2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure (FST 0.022–0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536–552 (95% CrI range 451–647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2024.1377214","usgsCitation":"Epps, C.W., Holton, P.B., Monello, R.J., Crowhurst, R.S., Gaulke, S.M., Janousek, W.M., Creech, T.G., and Graves, T., 2024, Population and spatial dynamics of desert bighorn sheep in Grand Canyon during an outbreak of respiratory pneumonia: Frontiers in Ecology and Evolution, v. 12, 1377214, 22 p., https://doi.org/10.3389/fevo.2024.1377214.","productDescription":"1377214, 22 p.","ipdsId":"IP-137271","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":439348,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/fevo.2024.1377214","text":"Publisher Index Page"},{"id":434937,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K89AA3","text":"USGS data release","linkHelpText":"Desert bighorn sheep (Ovis canadensis nelsoni) datasets from Grand Canyon National Park, 2010-2016"},{"id":430966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.5504498659519,\n 36.84244671894457\n ],\n [\n -114.04234802909026,\n 36.84244671894457\n ],\n [\n -114.04234802909026,\n 35.72909582502355\n ],\n [\n -111.5504498659519,\n 35.72909582502355\n ],\n [\n -111.5504498659519,\n 36.84244671894457\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Epps, Clinton W.","contributorId":198148,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":906239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holton, P. Brandon","contributorId":340119,"corporation":false,"usgs":false,"family":"Holton","given":"P.","email":"","middleInitial":"Brandon","affiliations":[],"preferred":false,"id":906240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monello, Ryan J.","contributorId":184143,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":906241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":906242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaulke, Sarah Mccrimmon 0000-0002-2657-5844","orcid":"https://orcid.org/0000-0002-2657-5844","contributorId":225564,"corporation":false,"usgs":true,"family":"Gaulke","given":"Sarah","email":"","middleInitial":"Mccrimmon","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Creech, Tyler G.","contributorId":198152,"corporation":false,"usgs":false,"family":"Creech","given":"Tyler","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":906245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906246,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70255668,"text":"70255668 - 2024 - Application of normalized radar backscatter and hyperspectral data to augment rangeland vegetation fractional classification","interactions":[],"lastModifiedDate":"2024-06-28T11:44:29.88845","indexId":"70255668","displayToPublicDate":"2024-06-25T06:36:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Application of normalized radar backscatter and hyperspectral data to augment rangeland vegetation fractional classification","docAbstract":"Enhancing detection of cryptic snakes is critical for the development of conservation and management strategies; yet, finding methods that provide adequate detection remains challenging. Issues with detecting snakes can be particularly problematic for some species, like the invasive Burmese python (Python bivittatus) in the Florida Everglades.
Using multiple survey methods, we predicted that our ability to detect pythons, larger snakes and all other snakes would be enhanced with the use of live mammalian lures (domesticated rabbits; Oryctolagus cuniculus). Specifically, we used visual surveys, python detection dogs, and time-lapse game cameras to determine if domesticated rabbits were an effective lure.
Time-lapse game cameras detected almost 40 times more snakes (n = 375, treatment = 245, control = 130) than visual surveys (n = 10). We recorded 21 independent detections of pythons at treatment pens (with lures) and one detection at a control pen (without lures). In addition, we found larger snakes, and all other snakes were 165% and 74% more likely to be detected at treatment pens compared to control pens, respectively. Time-lapse cameras detected almost 40 times more snakes than visual surveys; we did not detect any pythons with python detection dogs.
Our study presents compelling evidence that the detection of snakes is improved by coupling live mammalian lures with time-lapse game cameras. Although the identification of smaller snake species was limited, this was due to pixel resolution, which could be improved by changing the camera focal length. For larger snakes with individually distinctive patterns, this method could potentially be used to identify unique individuals and thus allow researchers to estimate population dynamics.
","language":"English","publisher":"PeerJ, Inc.","doi":"10.7717/peerj.17577","usgsCitation":"McCampbell, M.E., Spencer, M.M., Hart, K., Link, G., Watson, A.J., and McCleery, R.A., 2024, Mammalian lures monitored with time-lapse cameras increase detection of pythons and other snakes: PeerJ, v. 12, e17577, 21 p., https://doi.org/10.7717/peerj.17577.","productDescription":"e17577, 21 p.","ipdsId":"IP-154422","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":439354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.17577","text":"Publisher Index Page"},{"id":430963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.06716804534993,\n 26.337274298622603\n ],\n [\n -81.34055052477085,\n 26.337274298622603\n ],\n [\n -81.34055052477085,\n 25.103410837459833\n ],\n [\n -80.06716804534993,\n 25.103410837459833\n ],\n [\n -80.06716804534993,\n 26.337274298622603\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"McCampbell, Marina E.","contributorId":331286,"corporation":false,"usgs":false,"family":"McCampbell","given":"Marina","email":"","middleInitial":"E.","affiliations":[{"id":40348,"text":"Department of Wildlife Ecology and Conservation, University of Florida","active":true,"usgs":false}],"preferred":false,"id":906086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spencer, McKayla M.","contributorId":301071,"corporation":false,"usgs":false,"family":"Spencer","given":"McKayla","email":"","middleInitial":"M.","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":906087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":222407,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":906088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Link, Gabrielle","contributorId":340076,"corporation":false,"usgs":false,"family":"Link","given":"Gabrielle","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":906089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Watson, Andrew J.","contributorId":176461,"corporation":false,"usgs":false,"family":"Watson","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":906090,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCleery, Robert A.","contributorId":139849,"corporation":false,"usgs":false,"family":"McCleery","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":906091,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70255572,"text":"70255572 - 2024 - A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA","interactions":[],"lastModifiedDate":"2024-06-24T14:17:47.470372","indexId":"70255572","displayToPublicDate":"2024-06-23T06:39:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA","docAbstract":"Spatial machine learning models can be developed from observations with substantial unexplainable variability, sometimes called ‘noise’. Traditional point-scale metrics (e.g., R2) alone can be misleading when evaluating these models. We present a multi-scale performance evaluation (MPE) using two additional scales (distributional and geostatistical). We apply the MPE framework to predictions of depth to bedrock (DTB) in the Delaware River Basin. Geostatistical analysis shows that approximately one third of the DTB variance is at spatial scale smaller than 2 km. Hence, we interpret our point-scale R2 of 0.3 (testing data) to be sufficient for regional-scale modelling. Bias-correction methods improve performance at two of the three MPE scales: point-scale change is negligible, while distributional and geostatistical performance improves. In contrast, bias correction applied to a global DTB model does not improve MPE performance. This work encourages scale-appropriate performance evaluations to enable effective model intercomparison.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106124","usgsCitation":"Goodling, P.J., Belitz, K., Stackelberg, P.E., and Fleming, B.J., 2024, A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA: Environmental Modelling & Software, v. 179, 106124, 12 p., https://doi.org/10.1016/j.envsoft.2024.106124.","productDescription":"106124, 12 p.","ipdsId":"IP-160581","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":439361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106124","text":"Publisher Index Page"},{"id":430446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.88099946089724,\n 38.58741180591247\n ],\n [\n -74.71321333503417,\n 39.379784628066616\n ],\n [\n -74.91854009408658,\n 39.623906471535875\n ],\n [\n -74.56682974019151,\n 39.83490997578861\n ],\n [\n -74.83087158557463,\n 40.43445755432647\n ],\n [\n -74.69462804413362,\n 42.31099383658801\n ],\n [\n -75.89851464683143,\n 42.243461978517985\n ],\n [\n -76.67474108243883,\n 40.45538711590305\n ],\n [\n -76.4341425039691,\n 39.732367924983954\n ],\n [\n -75.81256791410406,\n 39.70992285882126\n ],\n [\n -75.68892404289328,\n 38.72600697054469\n ],\n [\n -74.88099946089724,\n 38.58741180591247\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"179","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":904792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":904793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":904794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":904795,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255527,"text":"sir20245029 - 2024 - Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","interactions":[],"lastModifiedDate":"2024-06-21T16:00:45.438369","indexId":"sir20245029","displayToPublicDate":"2024-06-21T06:46:09","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5029","displayTitle":"Dissolved Arsenic Concentrations in Surface Waters Within the Upper Portions of the Klamath River Basin, Oregon and California","title":"Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","docAbstract":"Arsenic toxicity is an environmental health problem. Levels of arsenic in surface waters at some locations in the Klamath River Basin in southern Oregon and northern California can exceed the U.S. Environmental Protection Agency (EPA) standard for drinking water. There are both anthropogenic and natural sources of arsenic. The Klamath River Basin consists primarily of volcanic deposits and contains an underground geothermal system with hot springs and warm water wells, all known natural sources of arsenic. Anthropogenic sources of arsenic are related to the agricultural use of herbicides, fungicides, and insecticides. Surface water arsenic levels can also be affected by fertilizer amendments, evaporative concentration, oxygen-level depletion, and various geochemical transformations that can increase arsenic mobilization.
In this study by the U.S. Geological Survey and the Bureau of Reclamation, dissolved concentrations of arsenic, copper, and lead were measured in surface waters at 39 unique sites within the upper portions of the Klamath River Basin between 2018 and 2022. In every year, except 2022, sites were sampled four times between April and November. Surface-water arsenic concentrations varied up to four-orders of magnitude among sites. Median arsenic concentration was lowest at Cherry Creek (0.03 micrograms per liter [μg/L]) and highest at Wood Kimball Spring (36.7 μg/L), two sites located north of Upper Klamath Lake. The highest arsenic concentrations (17.4±4.9 μg/L, n=3) were found in drain sites (defined here as a waterbody returning used irrigation water) while the lowest arsenic concentrations were found in an artesian well (0.8 μg/L, n=1). The elevated arsenic concentrations of the drain sites suggest that arsenic might be concentrated or mobilized by agricultural activities, water re-use practices, and (or) by geochemical processes occurring around water stored in drains (that is, in the water column and across sediment water boundaries). A source of arsenic in drain water in the Klamath Strait Drain area includes water used for irrigation originating from Ady Canal. Other potential sources include groundwater, geothermal water, and local soils and sediments.
Seasonal differences in surface-water arsenic concentrations were detected at 13 sites, 10 of which had higher arsenic concentrations in summer than in either spring or fall. The sites sampled around Upper Klamath Lake, the impounded rivers, one of the two canal sites, and 5 of the 14 river sites had higher surface-water arsenic concentrations in the summer than in either spring or fall. Surface-water arsenic concentrations from groundwater sources (that is, springs and in the artesian well) did not vary significantly among seasons (p-values greater than 0.1).
Median surface-water concentrations of copper and lead ranged from 0.03 to 3.7 μg/L, and from 0.013 to 0.175 μg/L (n=2–18), respectively. Dissolved concentrations of both metals were below acute toxicity endpoints reported by the EPA for freshwater animals. Surface-water arsenic concentrations varied independently from corresponding changes in surface-water lead or copper concentrations. However, arsenic concentrations measured in bed-sediment samples collected from a subset of sites located north of Upper Klamath Lake correlated strongly and significantly with the corresponding sedimentary lead concentrations (p=0.015).
Aqueous arsenic speciation measured in a subset of sites in 2019 and 2022 showed that all the arsenic existed as arsenic (V), the most oxidized arsenic species, and presumably, the least toxic. The highest proportions of arsenite (As(III)), the presumably most toxic arsenic species, relative to total arsenic concentrations were found at drain sites.
Our assessment of dissolved arsenic concentrations in various surface-water bodies in the Upper Klamath River Basin reveals geographical areas of consistently low (below 2.1 μg/L), moderate (below 10 μg/L) and high (above 10 μg/L) surface-water arsenic concentrations. South of Upper Klamath Lake, surface-water arsenic concentrations were consistently higher than 20 μg/L at two drain sites located in an area of predominant agricultural land use with extensive water re-use practices. North of Upper Klamath Lake, surface-water arsenic concentrations greater than 20 μg/L were consistently measured at sites with limited nearby agricultural activities, suggesting a geogenic source. The consistently high arsenic levels from the Wood River at Jackson F. Kimball State Park, Fort Creek, and Crooked Creek, which are sites located at or near headwater spring sources, suggest a natural background source of arsenic. Water flowing downstream from this area could be a potential source of arsenic to Upper Klamath Lake and the Upper Klamath River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245029","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Croteau, M.N., Topping, B.R., and Carlson, R.A., 2024, Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2024–5029, 42 p., https://doi.org/10.3133/sir20245029.","productDescription":"Report: viii, 38 p.; Data Release","ipdsId":"IP-149938","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":430399,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P943CWH1","text":"USGS Data Release","description":"Hill, K.L., Croteau, M.N., Topping, B.R., Caro, D.A., Parris, J.L., Zierdt Smith, E.L., and Baesman, S.M., 2021, Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P943CWH1.","linkHelpText":"Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023)"},{"id":430404,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245029/full"},{"id":430403,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5029/images"},{"id":430402,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.xml"},{"id":430401,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":430400,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5029/covrthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.44639737545533,\n 43\n ],\n [\n -122.44639737545533,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 43\n ],\n [\n -122.44639737545533,\n 43\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
The purpose of this report is to provide the Marine Corps with an annual summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (Vireo bellii pusillus) at Marine Corps Base Camp Pendleton (MCBCP, or Base). Surveys for the Least Bell's Vireo were conducted at MCBCP, California, between April 1 and July 10, 2020. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed 3–4 times. We detected 669 territorial male vireos and 16 transient vireos in core survey areas. An additional 156 territorial male vireos were detected in non-core survey areas. Territorial vireos were detected on all 10 drainages/sites surveyed (core and non-core areas). Of the vireo territories in core areas, 88 percent were on the 4 most populated drainages, with the Santa Margarita River containing 69 percent of all territories. In core areas, 79 percent of male vireos were confirmed as paired; 83 percent of male vireos in non-core areas were confirmed as paired.
The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP (669) increased 39 percent from 2019 to 2020. The number of territories in all core survey area drainages increased by one or more between 2019 and 2020. The substantial increase in vireo numbers on MCBCP (39 percent) was consistent with population changes in surrounding areas, including the lower San Luis Rey River (26 percent), Marine Corps Air Station, Camp Pendleton (58 percent), and the middle San Luis Rey River (7 percent).
Most core-area vireo territories (69 percent of males) occurred in willow (Salix spp.) riparian habitat. An additional 4 percent of birds occupied willow habitat co-dominated by Western sycamores (Platanus racemosa) or Fremont cottonwoods (Populus fremontii). Eighteen percent of territories were found in riparian scrub dominated by mule fat (Baccharis salicifolia) or sandbar willow (S. exigua). Upland scrub was used by 7 percent or fewer vireos; 1 percent of territories occurred in non-native vegetation, and less than 1 percent of vireo territories occurred in habitat co-dominated by coast live oak (Quercus agrifolia) and sycamore.
In 2019, MCBCP began operating an artificial seep along the Santa Margarita River. The artificial seep pumped water to the surface from March through August each year during daylight hours and was designed to increase the amount of surface water present to enhance Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited the seep and proposed seep areas within the past several years. Therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents preliminary analyses of vireo and vegetation response to the existing artificial seep.
We sampled vegetation in the Seep site and three Reference sites to determine the effects of a new water diversion dam that was completed in 2019 and a surface water enhancement seep pump installed along the Santa Margarita River. We found minor differences in non-native vegetation cover between Reference sites and the Seep site. However, soil moisture was higher at the Reference sites compared to the Seep site. The effect of the seep pump may have been masked by high precipitation in the bio-year (July 1‒June 30) before 2020, limited time for the water diversion to have an effect, well-draining soil, and the non-operation of two to three of the six seep outlets.
We color banded and resighted color banded Least Bell’s Vireos to evaluate adult site fidelity, between-year movement, and the effect of surface water enhancement on vireo site fidelity and between-year movement. We banded 146 Least Bell's Vireos for the first time during the 2020 season. Birds banded included 27 adult vireos and 119 juvenile vireos. All adult vireos were banded with unique color combinations. The juvenile vireos (all nestlings) were banded with a single gold numbered federal band on the left leg.
We resighted and identified 85 Least Bell's Vireos banded before the 2020 breeding season on Base in 2020. Of the 85, 13 vireos were originally banded on the San Luis Rey River, 2 were banded in Baja California Sur, 1 was banded at Marine Corps Air Station, Camp Pendleton, and the remaining birds were banded at MCBCP. Adult birds of known age ranged from 1 to 8 years old.
Most returning adult vireos showed strong between-year site fidelity. Of the adults present in 2019 and 2020, 74 percent, (79 percent of males; 40 percent of females) returned to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.3 plus or minus (±) 0.8 kilometer (km). The average movement of first-year vireos detected in 2020 that fledged from a known nest on MCBCP in 2019 was 4.7±7.0 km. One first-year vireo that originated at MCBCP moved off Base and was detected at Murrieta Creek, 23.0 km from his natal territory.
We monitored Least Bell's Vireo pairs to evaluate the effects of surface water enhancement on nest success and breeding productivity. Vireos were monitored at one Seep site and three Reference sites. Base personnel plan to install a second seep pump at one of the Reference sites in the future, at which time the status of the monitoring site will change from Reference to Seep.
Nesting activity was monitored between March 31 and July 28 in 52 territories within the Seep and Reference sites (12 at the Seep site and 40 at Reference sites). All territories were occupied by pairs, and all but one territory was fully monitored, meaning all nesting attempts were monitored at these territories. One vireo territory within a Reference site was partially monitored. During the monitoring period, 94 nests (25 in the Seep site and 69 in Reference sites) were monitored.
Breeding productivity was similar at the Seep site and Reference sites (3.7 and 2.9 young per pair, respectively), with 75 percent of Seep pairs and 79 percent of Reference pairs successfully fledging at least 1 young in 2020. Compared to Reference sites, the Seep site had a higher proportion of all eggs that hatched and also a higher proportion of nests with eggs that hatched. Conversely, a lower proportion of hatchlings and nests that had hatchlings fledged at the Seep site than at Reference sites. According to the best model, nest survival in 2020 was not affected by treatment (Seep versus Reference), although the second best model that included treatment was also well supported.
Completed nests at the Seep site were likely to be as successful as nests at Reference sites in 2020 (57 percent and 59 percent, respectively). Predation was believed to be the primary source of nest failure at both sites. Predation accounted for 90 percent and 73 percent of nest failures at Seep and Reference sites, respectively. Failure of the remaining eight nests was attributed to the collapse of the nesting substrate, exposure to rain and flooding, and other unknown reasons.
Fourteen plant species were used as hosts for vireo nests in 2020. In 2020, we found that at the Seep site, successful nests were placed in taller host plants and further from the edge of host plants (closer to the center) than unsuccessful nests. We found no difference in nest placement between the Seep site and the Reference sites.
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Standing dead trees (snags) are recognized for their influence on methane (CH4) cycling in coastal wetlands, yet the biogeochemical processes that control the magnitude and direction of fluxes across the snag-atmosphere interface are not fully elucidated. Herein, we analyzed microbial communities and fluxes at one height from ten snags in a ghost forest wetland. Snag-atmosphere CH4 fluxes were highly variable (− 0.11–0.51 mg CH4 m−2 h−1). CH4 production was measured in three out of ten snags; whereas, CH4 consumption was measured in two out of ten snags. Potential CH4 production and oxidation in one core from each snag was assayed in vitro. A single core produced CH4 under anoxic and oxic conditions, at measured rates of 0.7 and 0.6 ng CH4 g−1 h−1, respectively. Four cores oxidized CH4 under oxic conditions, with an average rate of − 1.13 ± 0.31 ng CH4 g−1 h−1. Illumina sequencing of the V3/V4 region of the 16S rRNA gene sequence revealed diverse microbial communities and indicated oxidative decomposition of deadwood. Methanogens were present in 20% of the snags, with a mean relative abundance of < 0.0001%. Methanotrophs were identified in all snags, with a mean relative abundance of 2% and represented the sole CH4-cycling communities in 80% of the snags. These data indicate potential for microbial attenuation of CH4 emissions across the snag-atmosphere interface in ghost forests. A better understanding of the environmental drivers of snag-associated microbial communities is necessary to forecast the response of CH4 cycling in coastal ghost forest wetlands to a shifting coastal landscape.
Understanding controls on solute export to streams is challenging because heterogeneous catchments can respond uniquely to drivers of environmental change. To understand general solute export patterns, we used a large-scale inductive approach to evaluate concentration–discharge (C–Q) metrics across catchments spanning a broad range of catchment attributes and hydroclimatic drivers. We leveraged paired C–Q data for 11 solutes from CAMELS-Chem, a database built upon an existing dataset of catchment and hydroclimatic attributes from relatively undisturbed catchments across the contiguous USA. Because C–Q relationships with Q thresholds reflect a shift in solute export dynamics and are poorly characterized across solutes and diverse catchments, we analysed C–Q relationships using Bayesian segmented regression to quantify Q thresholds in the C–Q relationship. Threshold responses were rare, representing only 12% of C–Q relationships, 56% of which occurred for solutes predominantly sourced from bedrock. Further, solutes were dominated by one or two C–Q patterns that reflected vertical solute–source distributions. Specifically, solutes predominantly sourced from bedrock had diluting C–Q responses in 43%–70% of catchments, and solutes predominantly sourced from soils had more enrichment responses in 35%–51% of catchments. We also linked C–Q relationships to catchment and hydroclimatic attributes to understand controls on export patterns. The relationships were generally weak despite the diversity of solutes and attribute types considered. However, catchment and hydroclimatic attributes in the central USA typically drove the most divergent export behaviour for solutes. Further, we illustrate how our inductive approach generated new hypotheses that can be tested at discrete, representative catchments using deductive approaches to better understand the processes underlying solute export patterns. Finally, given these long-term C–Q relationships are from minimally disturbed catchments, our findings can be used as benchmarks for change in more disturbed catchments.
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0000-0003-3008-3057","orcid":"https://orcid.org/0000-0003-3008-3057","contributorId":340200,"corporation":false,"usgs":false,"family":"Underwood","given":"Kristen","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":906557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamshaw, Scott Douglas 0000-0002-0583-4237","orcid":"https://orcid.org/0000-0002-0583-4237","contributorId":305601,"corporation":false,"usgs":true,"family":"Hamshaw","given":"Scott","email":"","middleInitial":"Douglas","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":906558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, L.","contributorId":152225,"corporation":false,"usgs":false,"family":"Li","given":"L.","affiliations":[],"preferred":false,"id":906559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seybold, Erin C. 0000-0002-0365-2333","orcid":"https://orcid.org/0000-0002-0365-2333","contributorId":340201,"corporation":false,"usgs":false,"family":"Seybold","given":"Erin","email":"","middleInitial":"C.","affiliations":[{"id":35641,"text":"Kansas Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Bryn 0000-0002-3199-0129","orcid":"https://orcid.org/0000-0002-3199-0129","contributorId":340202,"corporation":false,"usgs":false,"family":"Stewart","given":"Bryn","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":906561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rizzo, Donna M.","contributorId":171679,"corporation":false,"usgs":false,"family":"Rizzo","given":"Donna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":906562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ul Haq, Ijaz","contributorId":340203,"corporation":false,"usgs":false,"family":"Ul Haq","given":"Ijaz","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":906563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Perdrial, Julia N.","contributorId":177340,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":906564,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260116,"text":"70260116 - 2024 - Did steam boost the height and growth rate of the giant Hunga eruption plume?","interactions":[],"lastModifiedDate":"2024-10-29T11:35:41.156932","indexId":"70260116","displayToPublicDate":"2024-06-17T06:34:38","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Did steam boost the height and growth rate of the giant Hunga eruption plume?","docAbstract":"The eruption of Hunga volcano on 15 January 2022 produced a higher plume and faster-growing umbrella cloud than has ever been previously recorded. The plume height exceeded 58 km, and the umbrella grew to 450 km in diameter within 50 min. Assuming an umbrella thickness of 10 km, this growth rate implied an average volume injection rate into the umbrella of 330–500 km3 s−1. Conventional relationships between plume height, umbrella-growth rate, and mass eruption rate suggest that this period of activity should have injected a few to several cubic kilometers of rock particles (tephra) into the plume. Yet tephra fall deposits on neighboring islands are only a few centimeters thick and can be reproduced using ash transport simulations with only 0.1–0.2 km3 erupted volume (dense-rock equivalent). How could such a powerful eruption contain so little tephra? Here, we propose that seawater mixing at the vent boosted the plume height and umbrella growth rate. Using the one-dimensional (1-D) steady plume model Plumeria, we find that a plume fed by ~90% water vapor at a temperature of 100 °C (referred to here as steam) could have exceeded 50 km height while keeping the injection rate of solids low enough to be consistent with Hunga’s modest tephra-fall deposit volume. Steam is envisaged to rise from intense phreatomagmatic jets or pyroclastic density currents entering the ocean. Overall, the height and expansion rate of Hunga’s giant plume is consistent with the total mass of fall deposits plus underwater density current deposits, even though most of the erupted mass decoupled from the high plume. This example represents a class of high (> 10 km), ash-poor, steam-driven plumes, that also includes Kīlauea (2020) and Fukutoku-oka-no-ba (2021). Their height is driven by heat flux following well-established relations; however, most of the heat is contained in steam rather than particles. As a result, the heights of these water-rich plumes do not follow well-known relations with the mass eruption rate of tephra.
Understanding genetic structure and diversity among remnant populations of rare species can inform conservation and recovery actions. We used a population genetic framework to spatially delineate gene pools and estimate gene flow and effective population sizes for the endangered California Freshwater Shrimp Syncaris pacifica. Tissues of 101 individuals were collected from 11 sites in 5 watersheds, using non-lethal tissue sampling. Single Nucleotide Polymorphism markers were developed de novo using ddRAD-seq methods, resulting in 433 unlinked loci scored with high confidence and low missing data. We found evidence for strong genetic structure across the species range. Two hierarchical levels of significant differentiation were observed: (i) five clusters (regional gene pools, FST = 0.38–0.75) isolated by low gene flow were associated with watershed limits and (ii) modest local structure among tributaries within a watershed that are not connected through direct downstream flow (local gene pools, FST = 0.06–0.10). Sampling sites connected with direct upstream-to-downstream water flow were not differentiated. Our analyses suggest that regional watersheds are isolated from one another, with very limited (possibly no) gene flow over recent generations. This isolation is paired with small effective population sizes across regional gene pools (Ne = 62.4–147.1). Genetic diversity was variable across sites and watersheds (He = 0.09–0.22). Those with the highest diversity may have been refugia and are now potential sources of genetic diversity for other populations. These findings highlight which portions of the species range may be most vulnerable to future habitat fragmentation and provide management consideration for maintaining local effective population sizes and genetic connectivity.
Sleeper populations are established populations of introduced species whose population growth is limited by one or more abiotic or biotic conditions. Sleeper populations pose an invasion risk if a change in those limiting conditions, such as climate change, enables population growth and invasion. With thousands of established introduced species, it is critical that we identify and prioritize potential sleepers. Here, we identified introduced plants established in the northeastern United States with high impacts and the potential to expand with climate change. Of 1795 introduced plants established in one or more northeastern states, we focused on 118 taxa regulated by one or more states outside the Northeast plus 61 taxa recorded as invasive globally and under consideration for regulation in the Northeast. We used the environmental impact classification for alien taxa framework to quantify negative ecological and socioeconomic impacts reported in the scientific literature for these 169 taxa. We compared mean minimum winter temperature and annual precipitation where the species were abundant with current and future climate in the Northeast to evaluate whether climate change could increase risk. We identified 49 plants with ecological impacts linked to loss of native diversity and 94 plants with socioeconomic impacts. 81 species showed an increase in climatic suitability for abundant populations with climate change. Using ecological impact, increased climate suitability, and presence in fewer than 20 Northeastern counties, we highlight 18 species as high priorities for potential management in the Northeast. This approach can inform climate-smart, proactive management of sleeper populations before they become invasive.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-024-03351-0","usgsCitation":"O'Uhuru, A., Morelli, T.L., Evans, A.E., Salva, J., and Bradley, B., 2024, Identifying new invasive plants in the face of climate change: A focus on sleeper species: Biological Invasions, v. 26, p. 2989-3001, https://doi.org/10.1007/s10530-024-03351-0.","productDescription":"13 p.","startPage":"2989","endPage":"3001","ipdsId":"IP-159571","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":486085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2024-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Uhuru, A.C.","contributorId":355408,"corporation":false,"usgs":false,"family":"O'Uhuru","given":"A.C.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":937245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Annette E. 0000-0001-6439-4908","orcid":"https://orcid.org/0000-0001-6439-4908","contributorId":328976,"corporation":false,"usgs":false,"family":"Evans","given":"Annette","email":"","middleInitial":"E.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salva, J.D.","contributorId":355409,"corporation":false,"usgs":false,"family":"Salva","given":"J.D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, B.A.","contributorId":355410,"corporation":false,"usgs":false,"family":"Bradley","given":"B.A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":937248,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70257495,"text":"70257495 - 2024 - Widespread occupancy of the endangered northern myotis on northeastern Atlantic Coastal Plain islands","interactions":[],"lastModifiedDate":"2024-09-09T20:52:56.957874","indexId":"70257495","displayToPublicDate":"2024-06-13T09:16:32","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Widespread occupancy of the endangered northern myotis on northeastern Atlantic Coastal Plain islands","docAbstract":"Northern myotis Myotis septentrionalis are one of the bat species most affected by white-nose syndrome (WNS), and disease-induced declines may cause compounding effects when combined with other threats such as habitat loss and fragmentation. Recent evidence suggests that peripheral populations are persisting in post-WNS years; however, the environmental factors that influence the occurrence of this species along the Atlantic Coastal Plain are virtually unknown. We conducted a large-scale acoustic survey on 3 islands: Long Island, New York, and Martha’s Vineyard and Nantucket, Massachusetts, USA, and used a multi-scale occupancy modeling approach to determine the landscape and abiotic factors affecting the distribution of northern myotis. Our estimates of occupancy and detection probability suggest widespread presence across the islands. At the local (200 m) scale, we identified strong negative effects of development on Long Island and Nantucket and a strong positive effect of forest habitat on Martha’s Vineyard. None of the variables we measured sufficiently explained the landscape (1 km2 ) occupancy of this species, which was very high (ψ = 0.81–0.97), representing an outlier for this species in the post-WNS landscape. The lack of association at the landscape scale suggests that general differences in land cover are not a driving factor of higher occupancy of peripheral northern myotis populations, while local site- specific conditions may be supporting critical foraging or roosting habitat. Because islands are particularly vulnerable to human-driven habitat alteration due to the constraint of limited space, and development pressure is expected to increase, this study provides a baseline to enable managers to assess the effects of future environmental disturbances and monitor population trends to support long-term survival of northern myotis.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01335","usgsCitation":"Hoff, S., Mosher, B., Watson, M., Johnson, L., Olson, E., O’Dell, D., Pendergast, C.J., Bogan, D.A., Herzog, C.J., and Turner, W.C., 2024, Widespread occupancy of the endangered northern myotis on northeastern Atlantic Coastal Plain islands: Endangered Species Research, v. 54, p. 141-153, https://doi.org/10.3354/esr01335.","productDescription":"13 p.","startPage":"141","endPage":"153","ipdsId":"IP-158096","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439405,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01335","text":"Publisher Index Page"},{"id":433568,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New York","otherGeospatial":"Long Island, Martha's Vineyard, Nantucket","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.72456524610662,\n 41.44291621427166\n ],\n [\n -73.72456524610662,\n 40.57243247892035\n ],\n [\n -69.85737774610656,\n 40.57243247892035\n ],\n [\n -69.85737774610656,\n 41.44291621427166\n ],\n [\n -73.72456524610662,\n 41.44291621427166\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","noUsgsAuthors":false,"publicationDate":"2024-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoff, Samantha","contributorId":342962,"corporation":false,"usgs":false,"family":"Hoff","given":"Samantha","email":"","affiliations":[{"id":81956,"text":"University at Albany","active":true,"usgs":false}],"preferred":false,"id":910538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mosher, Brittany A.","contributorId":342963,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany A.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":910539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watson, Mandy","contributorId":342964,"corporation":false,"usgs":false,"family":"Watson","given":"Mandy","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Luanne","contributorId":342965,"corporation":false,"usgs":false,"family":"Johnson","given":"Luanne","affiliations":[{"id":81959,"text":"BiodiversityWorks","active":true,"usgs":false}],"preferred":false,"id":910541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olson, Elizabeth","contributorId":342966,"corporation":false,"usgs":false,"family":"Olson","given":"Elizabeth","email":"","affiliations":[{"id":81959,"text":"BiodiversityWorks","active":true,"usgs":false}],"preferred":false,"id":910542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Dell, Danielle","contributorId":342967,"corporation":false,"usgs":false,"family":"O’Dell","given":"Danielle","email":"","affiliations":[{"id":81960,"text":"Nantucket Conservation Foundation","active":true,"usgs":false}],"preferred":false,"id":910543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pendergast, Casey J.","contributorId":342968,"corporation":false,"usgs":false,"family":"Pendergast","given":"Casey","email":"","middleInitial":"J.","affiliations":[{"id":81956,"text":"University at Albany","active":true,"usgs":false}],"preferred":false,"id":910544,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bogan, Daniel A.","contributorId":342969,"corporation":false,"usgs":false,"family":"Bogan","given":"Daniel","email":"","middleInitial":"A.","affiliations":[{"id":81961,"text":"Siena College","active":true,"usgs":false}],"preferred":false,"id":910545,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Herzog, Carl J.","contributorId":342970,"corporation":false,"usgs":false,"family":"Herzog","given":"Carl","email":"","middleInitial":"J.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":910546,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910547,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70267341,"text":"70267341 - 2024 - Validation of a real-time quaking-induced conversion (RT-QuIC) assay protocol to detect chronic wasting disease using rectal mucosa of naturally infected, pre-clinical white-tailed deer (Odocoileus virginianus)","interactions":[],"lastModifiedDate":"2025-05-20T17:09:01.401428","indexId":"70267341","displayToPublicDate":"2024-06-13T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a real-time quaking-induced conversion (RT-QuIC) assay protocol to detect chronic wasting disease using rectal mucosa of naturally infected, pre-clinical white-tailed deer (Odocoileus virginianus)","docAbstract":"Chronic wasting disease (CWD) is a fatal prion disease of cervids spreading across North America. More effective mitigation efforts may require expansion of the available toolkit to include new methods that provide earlier antemortem detection, higher throughput, and less expense than current immunohistochemistry (IHC) methods. The rectal mucosa near the rectoanal junction is a site of early accumulation of CWD prions and is safely sampled in living animals by pinch biopsy. A fluorescence-based, 96-well format, protein-aggregation assay-the real-time quaking-induced conversion (RT-QuIC) assay-is capable of ultra-sensitive detection of CWD prions. Notably, the recombinant protein substrate is crucial to the assay's performance and is now commercially available. In this blinded independent study, the preclinical diagnostic performance of a standardized RT-QuIC protocol using a commercially sourced substrate (MNPROtein) and a laboratory-produced substrate was studied using mock biopsy samples of the rectal mucosa from 284 white-tailed deer (Odocoileus virginianus). The samples were from a frozen archive of intact rectoanal junctions collected at depopulations of farmed herds positive for CWD in the United States. All deer were pre-clinical at the time of depopulation and infection status was established from the regulatory record, which evaluated the medial retropharyngeal lymph nodes (MRPLNs) and obex by CWD-IHC. A pre-analytic sample precipitation step was found to enhance the protocol's detection limit. Performance metrics were influenced by the choice of RT-QuIC diagnostic cut points (minimum number of positive wells and assay time) and by deer attributes (preclinical infection stage and prion protein genotype). The peak overall diagnostic sensitivities of the protocol were similar for both substrates (MNPROtein, 76.8%; laboratory-produced, 73.2%), though each was achieved at different cut points. Preclinical infection stage and prion protein genotype at codon 96 (G = glycine, S = serine) were primary predictors of sensitivity. The diagnostic sensitivities in late preclinical infections (CWD-IHC positive MPRLNs and obex) were similar, ranging from 96% in GG96 deer to 80% in xS96 deer (x = G or S). In early preclinical infections (CWD-IHC positive MRPLNs only), the diagnostic sensitivity was 64-71% in GG96 deer but only 25% in xS96 deer. These results demonstrate that this standardized RT-QuIC protocol for rectal biopsy samples using a commercial source of substrate produced stratified diagnostic sensitivities similar to or greater than those reported for CWD-IHC but in less than 30 hours of assay time and in a 96-well format. Notably, the RT-QuIC protocol used herein represents a standardization of protocols from several previous studies. Alignment of the sensitivities across these studies suggests the diagnostic performance of the assay is robust given quality reagents, optimized diagnostic criteria, and experienced staff.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0303037","usgsCitation":"Piel III, R., Veneziano, S., Nicholson, E., Walsh, D.P., Lomax, A., Nichols, T., Seabury, C., and Schneider, D., 2024, Validation of a real-time quaking-induced conversion (RT-QuIC) assay protocol to detect chronic wasting disease using rectal mucosa of naturally infected, pre-clinical white-tailed deer (Odocoileus virginianus): PLoS ONE, v. 19, no. 6, e0303037, 18 p., https://doi.org/10.1371/journal.pone.0303037.","productDescription":"e0303037, 18 p.","ipdsId":"IP-160665","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490139,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0303037","text":"Publisher Index Page"},{"id":486236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n 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Afghanistan","docAbstract":"Drought is one of the key drivers of food insecurity in Afghanistan, which is among the most food insecure countries in the world. In this study, we build on previous research and seek to answer the central question: “What is the influence of El Niño-Southern Oscillation (ENSO) on drought outlooks and agricultural yield outcome in Afghanistan, and how do these influences vary spatially?” We do so by utilizing multiple indicators of droughts and available wheat yield reports. We find a clear distinction in the probability of drought (defined as being in the lower tercile) in Afghanistan during La Niña compared to El Niño events since 1981. The probability of drought in Afghanistan increased during La Niña, particularly in the North, Northeast, and West regions. La Niña events are related to an increase in the probability of snow drought, particularly in parts of the Amu Darya basin. It is found that relative to El Niño events, snow water equivalent [total runoff] during La Niña events January–March (March–July total runoff) decreases between 9% and 30% (28%–42%) for the five major basins in the country. The probability of agricultural drought during La Niña events is found to be higher than 70% in the rainfed and irrigated areas of the Northeast, North, and West regions. This result is at least partly supported by reported wheat yield composites related to La Niña events that tend to be lower than for El Niño events across all regions in the case of rainfed wheat (statistically significant in Northeast, West, and South regions) and in some cases for irrigated wheat. The results of this study have direct implications for improving early warning of worsening food insecurity in Afghanistan during La Niña events, given that we now have long-lead and skillful forecasts of ENSO up to 18–24 months in advance, which could potentially be used to provide earlier warning of worsening food insecurity in Afghanistan
","language":"English","publisher":"Elsevier","doi":"10.1016/j.wace.2024.100697","usgsCitation":"Shukla, S., Zaheer, F., Hoell, A., Anderson, W., Jayanthi, H., Husak, G., Lee, D., Barker, B., Pervez, S., Slinski, K., Justice, C., Rowland, J., McNally, A., Budde, M., and Verdin, J., 2024, ENSO-based outlook of droughts and agricultural outcomes in Afghanistan: Weather and Climate Extremes, v. 45, 100697, 16 p., https://doi.org/10.1016/j.wace.2024.100697.","productDescription":"100697, 16 p.","ipdsId":"IP-155371","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":493783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.wace.2024.100697","text":"Publisher Index 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Effects of MHWs on some seabirds (e.g. mass die-offs) are well documented, but mechanisms by which seabirds respond to MHWs remain poorly understood. Following from a symposium at the 3rd World Seabird Conference, this Theme Section presents recent research to address this knowledge gap. Studies included here spanned one or more MHW event, at spatial scales from individual seabird colonies to large marine ecosystems in subtropical, temperate, and polar oceans, and over timespans from months to decades. The findings summarized herein indicate that MHWs can affect seabirds directly by creating physiological heat stress that affects behavior or survival, or indirectly by disrupting seabird food webs, largely by altering metabolic rates in ectothermic prey species, leading to effects on their associated predators and prey. Four main mechanisms by which MHWs affect seabirds are (1) habitat modification, (2) physiological forcing, (3) behavioral responses, and (4) ecological processes or species interactions. Most seabird species have experienced limited effects from MHWs to date, owing to ecological and behavioral adaptations that buffer MHW effects. However, the intensity and frequency of MHWs is increasing due to global warming, and more seabird species may have difficulty coping with future heatwave events. Also, MHW impacts can persist for years after a MHW ends, so consequences of recent or future MHWs could continue to unfold over time for many long-lived seabird species.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14625","usgsCitation":"Piatt, J., Arimitsu, M.L., Thompson, S.A., Suryan, R., Wilson, R., Elliott, K., and Sydeman, W., 2024, Mechanisms by which marine heatwaves impact seabirds: MEPS, v. 737, p. 1-8, https://doi.org/10.3354/meps14625.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-164926","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":439441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14625","text":"Publisher Index Page"},{"id":429575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"737","noUsgsAuthors":false,"publicationDate":"2024-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Piatt, John F. 0000-0002-4417-5748","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":244053,"corporation":false,"usgs":true,"family":"Piatt","given":"John F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":902231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":902232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Sarah Ann","contributorId":198394,"corporation":false,"usgs":false,"family":"Thompson","given":"Sarah","email":"","middleInitial":"Ann","affiliations":[],"preferred":false,"id":902233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suryan, Rob","contributorId":258845,"corporation":false,"usgs":false,"family":"Suryan","given":"Rob","affiliations":[{"id":52314,"text":"NOAA NMFS Auke Bay Lab","active":true,"usgs":false}],"preferred":false,"id":902234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Rory","contributorId":337246,"corporation":false,"usgs":false,"family":"Wilson","given":"Rory","email":"","affiliations":[{"id":81000,"text":"Seaswan University","active":true,"usgs":false}],"preferred":false,"id":902235,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Kyle","contributorId":95347,"corporation":false,"usgs":true,"family":"Elliott","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":902236,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sydeman, W.J.","contributorId":95831,"corporation":false,"usgs":true,"family":"Sydeman","given":"W.J.","email":"","affiliations":[],"preferred":false,"id":902237,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256147,"text":"70256147 - 2024 - A decade-long study demonstrates that a population of invasive sea lamprey (Petromyzon marinus) can be controlled by introducing sterilized males","interactions":[],"lastModifiedDate":"2024-07-25T11:45:45.924333","indexId":"70256147","displayToPublicDate":"2024-06-03T06:42:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"A decade-long study demonstrates that a population of invasive sea lamprey (Petromyzon marinus) can be controlled by introducing sterilized males","docAbstract":"The release of sterilized insects to control pest populations has been used successfully during the past 6 decades, but application of the method in vertebrates has largely been overlooked or met with failure. Here, we demonstrate for the first time in fish, that a small population of sea lamprey (Petromyzon marinus; Class Agnatha), arguably one of the most impactful invasive fish in the world, can be controlled by the release of sterilized males. Specifically, the release of high numbers of sterile males (~ 1000's) into a geographically isolated population of adult sea lamprey resulted in the first multiyear delay in pesticide treatment since treatments began during 1966. Estimates of percent reduction in recruitment of age-1 sea lamprey due to sterile male release ranged from 7 to 99.9% with the precision of the estimate being low because of substantial year-to-year variability in larval density and distribution. Additional monitoring that accounts for recruitment variability in time and space would reduce uncertainty in the degree to which sterile male release reduces recruitment rates. The results are relevant to vertebrate pest control programs worldwide, especially as technical opportunities to sterilize vertebrates and manipulate sex ratios expand.
Wildlife telemetry data may be used to answer a diverse range of questions relevant to wildlife ecology and management. One challenge to modeling telemetry data is that animal movement often varies greatly in pattern over time, and current continuous-time modeling approaches to handle such nonstationarity require bespoke and often complex models that may pose barriers to practitioner implementation. We demonstrate a novel application of treed Gaussian process (TGP) modeling, a Bayesian machine learning approach that automatically captures the nonstationarity and abrupt transitions present in animal movement. The machine learning formulation of TGPs enables modeling to be nearly automated, while their Bayesian formulation allows for the derivation of movement descriptors with associated uncertainty measures. We demonstrate the use of an existing R package to implement TGPs using the familiar Markov chain Monte Carlo algorithm. We then use estimated movement trajectories to derive movement descriptors that can be compared across individuals and populations. We applied the TGP model to a case study of lesser prairie-chickens (Tympanuchus pallidicinctus) to demonstrate the benefits of TGP modeling and compared distance traveled and residence times across lesser prairie-chicken individuals and populations. For broad usability, we outline all steps necessary for practitioners to specify relevant movement descriptors (e.g., turn angles, speed, contact points) and apply TGP modeling and trajectory comparison to their own telemetry datasets. Combining the predictive power of machine learning and the statistical inference of Bayesian methods to model movement trajectories allows for the estimation of statistically comparable movement descriptors from telemetry studies. Our use of an accessible R package allows practitioners to model trajectories and estimate movement descriptors, facilitating the use of telemetry data to answer applied management questions.
Previous work found that numerous genes positively selected within the hoary bat (Lasiurus cinereus) lineage are physically clustered in regions of conserved synteny. Here I further validate and expand on those finding utilizing an updated L. cinereus genome assembly and additional bat species as well as other tetrapod outgroups.
A chromosome-level assembly was generated by chromatin-contact mapping and made available by DNAZoo (www.dnazoo.org). The genomic organization of orthologous genes was extracted from annotation data for multiple additional bat species as well as other tetrapod clades for which chromosome-level assemblies were available from the National Center for Biotechnology Information (NCBI). Tests of branch-specific positive selection were performed for L. cinereus using PAML as well as with the HyPhy package for comparison.
Twelve genes exhibiting significant diversifying selection in the L. cinereus lineage were clustered within a 12-Mb genomic window; one of these (Trpc4) also exhibited diversifying selection in bats generally. Ten of the 12 genes are landmarks of two distinct blocks of ancient synteny that are not linked in other tetrapod clades. Bats are further distinguished by frequent structural rearrangements within these synteny blocks, which are rarely observed in other Tetrapoda. Patterns of gene order and orientation among bat taxa are incompatible with phylogeny as presently understood, implying parallel evolution or subsequent reversals. Inferences of positive selection were found to be robust to alternative phylogenetic topologies as well as a strong shift in background nucleotide composition in some taxa.
This study confirms and further localizes a genomic hotspot of protein-coding divergence in the hoary bat, one that also exhibits an increased tempo of structural change in bats compared with other mammals. Most genes in the two synteny blocks have elevated expression in brain tissue in humans and model organisms, and genetic studies implicate the selected genes in cranial and neurological development, among other functions.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.17482","usgsCitation":"Cornman, R.S., 2024, A genomic hotspot of diversifying selection and structural change in the hoary bat (Lasiurus cinereus): PeerJ, v. 12, e17482, 32 p., https://doi.org/10.7717/peerj.17482.","productDescription":"e17482, 32 p.","ipdsId":"IP-159824","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":439470,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.17482","text":"Publisher Index Page"},{"id":434952,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1YKF5BJ","text":"USGS data release","linkHelpText":"DNA sequences used to analyze evolutionary rates of genes in bats"},{"id":429444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2024-05-31","publicationStatus":"PW","contributors":{"authors":[{"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":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":901903,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256585,"text":"70256585 - 2024 - Broad-scale changes in lesser prairie-chicken habitat","interactions":[],"lastModifiedDate":"2025-02-07T17:39:47.826731","indexId":"70256585","displayToPublicDate":"2024-05-31T06:51:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Broad-scale changes in lesser prairie-chicken habitat","docAbstract":"Lesser prairie-chicken (Tympanuchus pallidicinctus) populations of in the Sand Sagebrush Prairie Ecoregion of southwest Kansas and southeast Colorado, USA, have declined sharply since the mid-1980s. Decreased quality and availability of habitat are believed to be the main drivers of declines. Our objective was to reconstruct broad-scale change in the ecoregion since 1985 as a potential factor in population declines. We assessed temporal change from 1985–2015 in landcover types and calculated landscape metrics using Land Change Monitoring, Assessment, and Projection imagery layers. We also documented presence of anthropogenic structures including oil wells and electrical transmission lines. Landcover type composition changed little since 1990 across the Sand Sagebrush Prairie Ecoregion. However, anthropogenic structures (i.e., oil/gas wells, cell towers, wind farms, and transmission lines) notably increased, potentially causing functional habitat loss at a broad scale. Increased anthropogenic structures may have decreased habitat availability as well as the quality of existing habitat for lesser prairie-chickens, possibly contributing to recent population declines throughout the Sand Sagebrush Prairie Ecoregion.
There are two species of free-roaming feral equids in North America: horses (Equus caballus) and donkeys or “burros” (E. asinus). Both species were introduced as domestic animals to North America in the early 1500s and currently inhabit rangelands across the western United States, Canada, and all continents except Antarctica. Despite their global distribution, little is known about their fine scale spatial ecology. Contemporary research tools to assess space use include global positioning system (GPS) tracking collars, but older models were problematic due to stiff collar belting causing poor fit. We tested modern designs of GPS collars on n = 105 horses and n = 60 burros for 4 years in five populations (3 horse, 2 burro) across the western United States, to assess whether collars posed welfare risks to horses or burros. We found no difference in survival of collared versus uncollared mares and jennies, and no difference in survival of their foals. In 4036 of 4307 observations for horses (93.7%) and 2115 of 2258 observations for burros (93.6%), collars were observed symmetrical, maintaining proper fit on the neck. Fur effects from collars (sweaty neck, indented fur, broken fur) were seen in 3% of horse observations and 25% of burro observations. Superficial effects (chafes and marks on skin surface) were seen in 2% of horse observations and 11% of burro observations; no severe effects from collars were seen. Body condition was not affected by collars; mean body condition of collared horses was 4.70 ± 0.54 (mean ± s.d) and 4.71 ± 0.65 for collared burros. Behavior results indicated minimal effects; collared horses stood slightly more than uncollared, and collared burros stood and foraged more in one population, but not in the other. For 6.3% of observations of horses and 6.4% of observations of burros, we found an effect of time wearing a collar on the cumulative sum of fur effects which increased over time (burros: rs = 0.87, P = <0.0001; horses: rs = 0.31, P = 0.002). Burros also showed an increase over time in the number of superficial effects, but horses did not. Collars occasionally moved into the wrong position, shifting forward over the ears; we observed this on 19 horses and 1 burro. Of those, most collars went over the ears in summer (n = 12). All collars were equipped with a remote release mechanism as well as a timed-release mechanism for redundancy, thus removed when observed in wrong position to avoid rubbing or discomfort. Our finding of no consequential physical effects in 98% of horse observations, and 89% of burro observations suggests the consequences of collars on free-roaming equid welfare and survival is biologically insignificant, although collars should be monitored regularly and continue to be equipped with a remote release mechanism to remove a collar if needed. With frequent welfare-driven, visual monitoring, collaring of free-roaming equids can be a safe and useful tool to increase our understanding of their spatial ecology, demography, habitat use, behavior, and interactions with other wildlife.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0303312","usgsCitation":"Schoenecker, K., King, S., Hennig, J.D., Cole, M., Scasta, J., and Beck, J., 2024, Effects of telemetry collars on two free-roaming feral equid species: PLoS ONE, v. 19, no. 5, e0303312, 25 p., https://doi.org/10.1371/journal.pone.0303312.","productDescription":"e0303312, 25 p.","ipdsId":"IP-153889","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":492801,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZSTSU","text":"USGS data release","linkHelpText":"Data Describing Effects of Telemetry Collars on Horses and Burros Between 2016 and 2020"},{"id":492486,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0303312","text":"Publisher Index Page"},{"id":492200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.06222303379008,\n 41.072757505190026\n ],\n [\n -107.36220051733886,\n 41.115245664294946\n ],\n [\n -107.40026474431968,\n 42.06499507596479\n ],\n [\n -110.54265920350724,\n 42.13895203896956\n ],\n [\n -113.98376776007635,\n 39.63181029788828\n ],\n [\n -113.82085343427966,\n 33.356188610084644\n ],\n [\n -109.78674675994066,\n 33.290579751792464\n ],\n [\n -109.06222303379008,\n 41.072757505190026\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sarah","contributorId":357927,"corporation":false,"usgs":false,"family":"King","given":"Sarah","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":942885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hennig, Jacob D.","contributorId":177569,"corporation":false,"usgs":false,"family":"Hennig","given":"Jacob","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":942886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Mary C.","contributorId":357931,"corporation":false,"usgs":false,"family":"Cole","given":"Mary C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":942887,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scasta, J. Derek","contributorId":357933,"corporation":false,"usgs":false,"family":"Scasta","given":"J. Derek","affiliations":[{"id":85567,"text":"University of WY","active":true,"usgs":false}],"preferred":false,"id":942888,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beck, Jeffrey L.","contributorId":357934,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey L.","affiliations":[{"id":85567,"text":"University of WY","active":true,"usgs":false}],"preferred":false,"id":942889,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254582,"text":"70254582 - 2024 - Temporally dense monitoring of pathogen occurrence at four drinking-water well sites – Insights and Implications","interactions":[],"lastModifiedDate":"2024-06-03T12:02:06.269876","indexId":"70254582","displayToPublicDate":"2024-05-29T06:59:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Temporally dense monitoring of pathogen occurrence at four drinking-water well sites – Insights and Implications","docAbstract":"Yearlong, event based, microbiological and chemical sampling was conducted at four public water supply well sites spanning a range of geologic settings and well depths to look for correlation between precipitation events and microbial occurrence. Near-continuous monitoring using autosamplers occurred just before, during, and after 5–7 sampling events triggered by rainfall and/or snowmelt. Microbial genetic material was noted at all four locations during all but one sampling event, but was exceedingly variable in time, where one sample would have no detections and the next sample could be a relatively high concentration. The highest microbial sums (microbial concentrations summed over an event) were observed during months in which precipitation exceeded historical averages. Extended wet conditions through the spring thaw resulted in the highest percentage of microbial positive samples, though at relatively low concentrations. Sampling events that followed drier than normal periods showed longer lag times between the onset of precipitation and microbial occurrence, as well as lower microbial detection rates. Although a general lag time pattern was observed at each site, the largest offset in time was observed at the site with the greatest depth to water. The study's temporally dense representation of drinking water pathogen characterization suggests that single event or infrequent periodic sampling of a drinking water supply cannot provide a representative characterization of the probability that pathogens are present, which likely has ramifications for calculating health risk assessments.
In machine learning or scientific computing, model performance is measured with an objective function. But why choose one objective over another? According to the information-theoretic paradigm, the “best” objective function is whichever minimizes information loss. To evaluate different objectives, transform them into likelihoods. The ratios of these likelihoods represent how strongly we should prefer one objective versus another, and the log of that ratio represents the relative information loss (or gain) from one objective to another. In plain terms, minimizing information loss is equivalent to minimizing uncertainty, as well as maximizing probability and general utility. We argue that this paradigm is well-suited to models that have many uses and no definite utility like the complex Earth system models used to understand the effects of climate change. Furthermore, the benefits of “maximizing information and general utility” extend beyond model accuracy to other important considerations including how efficiently the model calibrates, how well it generalizes, and how well it compresses data.