The creation and expansion of protected areas, coupled with wildlife reintroductions, are increasingly used as conservation measures to combat wildlife declines worldwide. Although these types of restoration efforts are expected be beneficial to wildlife populations, variable species management and interactions among species within complex food webs have the potential to lead to unintended species-specific responses to reserve expansion which can counteract the anticipated positive effects. We used a multi-season camera trap study to investigate community-wide responses of wildlife to a reserve expansion and associated wildlife releases in South Africa. We analyzed the camera trap data using community occupancy and N-mixture models to assess how the occupancy and intensity of use of individual species changed in the four seasons following reserve expansion. We found species-specific responses to reserve expansion, although responses were generally positive in occupancy and intensity of use but un-sustained. The apex predator, the lion (Panthera leo) and the majority of managed herbivores exhibited sustained or delayed positive responses, whereas most subordinate predators and unmanaged herbivores had short-lived, fluctuating, or neutral responses. Interactive effects of top-down suppression, competitive pressure, and increased space and food resources likely resulted in the temporally-variable responses of most species. Although no species responded negatively to reserve expansion and mammal reintroductions, the lack of sustained positive responses for most species indicates the complexities of implementing conservation actions to benefit multiple wildlife species. Our results highlight the importance of monitoring the entire wildlife community following management actions such as reserve expansion or wildlife reintroductions.
Finding solutions for the remediation and restoration of abandoned mining areas is of great environmental importance as they pose a risk to ecosystem health. In this study, our aim was to determine how remediation strategies with (i) compost amendment, (ii) planting a metal-tolerant grass Bouteloua curtipendula, and (iii) its inoculation with beneficial endophytes influenced the microbiome of metal-contaminated tailings originating from the abandoned Blue Nose Mine, SE Arizona, near Patagonia (USA). We conducted an indoor microcosm experiment followed by a metataxonomic analysis of the mine tailings, compost, and root samples. Our results showed that each remediation strategy promoted a distinct pattern of microbial community structure in the mine tailings, which correlated with changes in their chemical properties. The combination of compost amendment and endophyte inoculation led to the highest prokaryotic diversity and total nitrogen and organic carbon, but also induced shifts in microbial community structure that significantly correlated with an enhanced potential for mobilization of Cu and Sb. Our findings show that soil health metrics (total nitrogen, organic carbon and pH) improved, and microbial community changed, due to organic matter input and endophyte inoculation, which enhanced metal leaching from the mine waste and potentially increased environmental risks posed by Cu and Sb. We further emphasize that because the initial choice of remediation strategy can significantly impact trace element mobility via modulation of both soil chemistry and microbial communities, site specific, bench-scale preliminary tests, as reported here, can help determine the potential risk of a chosen strategy.
Existing analyses of salt marsh carbon budgets rarely quantify carbon loss as CO2 through the air–water interface in inundated marshes. This study estimates the variability of partial pressure of CO2 (pCO2) and air–water CO2 fluxes over summer and fall of 2014 and 2015 using high-frequency measurements of tidal water pCO2 in a salt marsh of the U.S. northeast region. Monthly mean CO2 effluxes varied in the range of 5.4–25.6 mmol m−2 marsh d−1 (monthly median: 4.8–24.7 mmol m−2 marsh d−1) during July to November from the tidal creek and tidally-inundated vegetated platform. The source of CO2 effluxes was partitioned between the marsh and estuary using a mixing model. The monthly mean marsh-contributed CO2 effluxes accounted for a dominant portion (69%) of total CO2 effluxes in the inundated marsh, which was 3–23% (mean 13%) of the corresponding lateral flux rate of dissolved inorganic carbon (DIC) from marsh to estuary. Photosynthesis in tidal water substantially reduced the CO2 evasion, accounting for 1–86% (mean 31%) of potential CO2 evasion and 2–26% (mean 11%) of corresponding lateral transport DIC fluxes, indicating the important role of photosynthesis in controlling the air–water CO2 evasion in the inundated salt marsh. This study demonstrates that CO2 evasion from inundated salt marshes is a significant loss term for carbon that is fixed within marshes.
","language":"English","publisher":"Wiley","doi":"10.1002/lno.12409","usgsCitation":"Song, S., Wang, Z., Kroeger, K.D., Eagle, M.J., Chu, S.N., and Ge, J., 2023, High-frequency variability of carbon dioxide fluxes in tidal water over a temperate salt marsh: Limnology & Oceanography, v. 68, no. 9, p. 2108-2125, https://doi.org/10.1002/lno.12409.","productDescription":"18 p.","startPage":"2108","endPage":"2125","ipdsId":"IP-147876","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441932,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.12409","text":"Publisher Index Page"},{"id":421745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Waquoit Bay","otherGeospatial":"Sage Lot Pond","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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2021","title":"Bathymetric contour maps, surface area and capacity tables, and bathymetric change maps for selected water-supply lakes in northeastern Missouri, 2021","docAbstract":"Bathymetric data were collected at 12 water-supply lakes in northeastern Missouri by the U.S. Geological Survey (USGS) in cooperation with the Missouri Department of Natural Resources (MoDNR) and various local agencies, as part of a multiyear effort to establish or update the surface area and capacity tables for the surveyed lakes. The lakes were surveyed in March through May 2021. Ten of the lakes had been surveyed previously by the USGS, and the recent surveys were compared to the earlier surveys to document the changes in the bathymetric surface and capacity of the lakes.
Bathymetric data were collected using a high-resolution multibeam mapping system mounted on a boat. Supplemental depth data at five of the lakes were collected in shallow areas with an acoustic Doppler current profiler on a remote-controlled boat. Data points from the various sources were exported at a gridded data resolution appropriate to each lake, either 0.82 foot, 1.64 feet, or 3.28 feet. Data outside the multibeam survey extent and greater than the surveyed water-surface elevation were obtained from data collected using aerial light detection and ranging (lidar) point cloud data. A linear enforcement technique was used to add points to the dataset in areas of sparse data (the upper ends of coves where the water was shallow or aquatic vegetation precluded data acquisition) based on surrounding multibeam and upland data values. The various point datasets were used to produce a three-dimensional triangulated irregular network surface of the lake-bottom elevations for each lake. A surface area and capacity table was produced from the three-dimensional surface for each lake showing surface area and capacity at specified lake water-surface elevations. Various quality-assurance tests were conducted to ensure quality data were collected with the multibeam, including beam angle checks and patch tests. Additional quality-assurance tests were conducted on the gridded bathymetric data from the survey, the bathymetric surface created from the gridded data, and the contours created from the bathymetric survey.
If there were data from a previous bathymetric survey for a given lake, a bathymetric change map was generated from the elevation difference between the previous survey and the 2021 bathymetric survey data points. After reconciling any vertical datum disagreement between the previous survey data and the 2021 survey datum, coincident points between the surveys were identified, and a bathymetric change map was generated using the coincident point data.
The mean elevation change between all repeat surveys at most lakes was positive, indicating sedimentation. Relative to previous surveys, the change in capacity at the primary spillway elevation ranged from a 7.7-percent decrease at Memphis Reservoir to a 3.9-percent increase at Old Lake (Bowling Green West). The mean bathymetric change ranged from 0.03 foot at Hazel Creek and 0.07 foot at Shelbina Lake and Bowling Green Reservoir (Jack Floyd Memorial Lake) to 0.63 at Memphis Lake (Lake Showme) and 0.88 at Memphis Reservoir. The time-averaged mean bathymetric change ranged from 0.002 foot per year at Hazel Creek Lake to 0.044 foot per year at Memphis Reservoir. The computed volumetric sedimentation rate generally ranged from 0.14 to 6.80 acre-feet per year at Shelbina Lake and Memphis Lake (Lake Showme), respectively; however, Forest Lake had a substantially larger sedimentation rate of 17.0 acre-feet per year. Some changes observed in some bathymetric change maps are believed to result from the difference in data collection equipment and techniques between the previous and present bathymetric surveys, whereas other erosional features around the perimeter of certain lakes may be the result of wave action during low-water years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235108","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Rivers, B.C., Huizinga, R.J., Richards, J.M., and Waite, G.J., 2023, Bathymetric contour maps, surface area and capacity tables, and bathymetric change maps for selected water-supply lakes in northeastern Missouri, 2021: U.S. Geological Survey Scientific Investigations Report 2023–5108, 63 p., https://doi.org/10.3133/sir20235108.","productDescription":"Report: vii, 63 p.; 12 Plates: 24.00 × 24.00 inches or smaller; Data Release","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-137682","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501152,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115452.htm","linkFileType":{"id":5,"text":"html"}},{"id":421680,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2023/5108/downloads/","text":"Plates 1–12","linkFileType":{"id":1,"text":"pdf"}},{"id":421677,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5108/sir20235108.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5108"},{"id":421676,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5108/coverthb.jpg"},{"id":421681,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YJJQB4","text":"USGS data release","linkHelpText":"Bathymetric and supporting data for 12 water supply lakes in northeastern Missouri, 2021"},{"id":421679,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5108/images/"},{"id":421678,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5108/sir20235108.XML","linkFileType":{"id":8,"text":"xml"}}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.1618646084552,\n 40.60163096352804\n ],\n [\n -93.1618646084552,\n 38.998035265560674\n ],\n [\n -90.92065367095553,\n 38.998035265560674\n ],\n [\n -90.92065367095553,\n 40.60163096352804\n ],\n [\n -93.1618646084552,\n 40.60163096352804\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
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Rivers integrate processes occurring throughout their watersheds and are therefore sentinels of change across broad spatial scales. River chemistry also regulates ecosystem function across Earth’s land–ocean continuum, exerting control from the micro- (for example, local food web) to the macro- (for example, global carbon cycle) scale. In the rapidly warming Arctic, a wide range of processes—from permafrost thaw to biological uptake and transformation—might reasonably alter river water chemistry. Here we use data from major rivers that collectively drain two-thirds of the Arctic Ocean watershed to assess widespread change in biogeochemical function within the pan-Arctic basin from 2003 to 2019. While the oceanward flux of alkalinity and associated ions increased markedly over this time frame, nitrate and other inorganic nutrient fluxes declined. Fluxes of dissolved organic carbon showed no overall trend. This divergence in response indicates the perturbation of multiple processes on land, with implications for biogeochemical cycling in the coastal ocean. We anticipate that these findings will facilitate refinement of conceptual and numerical models of current and future functioning of Arctic coastal ecosystems and spur research on scale-dependent change across the river-integrated Arctic domain.
","language":"English","publisher":"Springer","doi":"10.1038/s41561-023-01247-7","usgsCitation":"Tank, S.E., McClelland, J., Spencer, R., Shiklomanov, A.I., Suslova, A., Moatar, F., Amon, R., Cooper, L.W., Elias, G., Gordeev, V., Guay, C., Gurtovaya, T., Kosmenko, L., Mutter, E., Peterson, B., Peucker-Ehrenbrink, B., Raymond, P., Schuster, P., Scott, L., Staples, R., Striegl, R.G., Tretiakov, M., Zhulidov, A.V., Zimov, N., Zimov, S., and Holmes, R.M., 2023, Long-term trends in Arctic riverine chemistry signal multi-faceted northern change: Nature Geoscience, v. 16, p. 789-796, https://doi.org/10.1038/s41561-023-01247-7.","productDescription":"17 p.","startPage":"789","endPage":"796","ipdsId":"IP-149200","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":441937,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.inrae.fr/hal-04198078","text":"External Repository"},{"id":421736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Finland, Kazakhstan, Norway, Russia, United States","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -342.3952371271182,\n 69.74468714335444\n ],\n [\n -329.1823633126795,\n 64.20545061647516\n ],\n [\n -318.0022393158466,\n 58.36516107875457\n ],\n [\n -296.658366230984,\n 51.99850510364584\n ],\n [\n -243.80687097322883,\n 54.13546363643496\n ],\n [\n -218.9056857075558,\n 59.41534474728698\n ],\n [\n -184.34893880825422,\n 64.20545061647516\n ],\n [\n -161.48050336018719,\n 67.52498621568131\n ],\n [\n -146.23487972814243,\n 64.86095895630618\n ],\n [\n -128.95650627849164,\n 57.82803046594279\n ],\n [\n -120.31731955366638,\n 50.40664276656898\n ],\n [\n -105.57988337602299,\n 51.049992898892185\n ],\n [\n -88.80969738077384,\n 65.0759803966236\n ],\n [\n -90.33425974397825,\n 72.98441077895814\n ],\n [\n -75.0886361119335,\n 78.83695010199563\n ],\n [\n -59.84301247988874,\n 82.6291688543401\n ],\n [\n -28.84357776139734,\n 83.87916304216341\n ],\n [\n -1.4014552237165958,\n 83.60217287649235\n ],\n [\n -0.8932677693154574,\n 85.00709506615163\n ],\n [\n -283.5519238077401,\n 85.00709506615163\n ],\n [\n -351.1408552431386,\n 80.80646270429665\n ],\n [\n -342.3952371271182,\n 69.74468714335444\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2023-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Tank, Suzanne E. 0000-0002-5371-6577","orcid":"https://orcid.org/0000-0002-5371-6577","contributorId":238026,"corporation":false,"usgs":false,"family":"Tank","given":"Suzanne","email":"","middleInitial":"E.","affiliations":[{"id":47684,"text":"Department of Biological Sciences, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":885640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClelland, James W.","contributorId":255074,"corporation":false,"usgs":false,"family":"McClelland","given":"James W.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":885641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spencer, Robert G. 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Russia","active":true,"usgs":false}],"preferred":false,"id":885652,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mutter, Edda A.","contributorId":238034,"corporation":false,"usgs":false,"family":"Mutter","given":"Edda A.","affiliations":[{"id":47690,"text":"˚Yukon River Inter-Tribal Watershed Council, Anchorage, Alaska","active":true,"usgs":false}],"preferred":false,"id":885653,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Peterson, Bruce","contributorId":330711,"corporation":false,"usgs":false,"family":"Peterson","given":"Bruce","affiliations":[{"id":78981,"text":"Marine Biological Laboratory, Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":885654,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Peucker-Ehrenbrink, Bernhard","contributorId":247622,"corporation":false,"usgs":false,"family":"Peucker-Ehrenbrink","given":"Bernhard","affiliations":[{"id":49599,"text":"Woods Hole Oceanographic Institution, Woods Hole, USA","active":true,"usgs":false}],"preferred":false,"id":885655,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Raymond, Peter","contributorId":330174,"corporation":false,"usgs":false,"family":"Raymond","given":"Peter","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":885656,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schuster, Paul","contributorId":330712,"corporation":false,"usgs":false,"family":"Schuster","given":"Paul","affiliations":[{"id":78982,"text":"U. S. Geological Survey, Earth System Processes Division, Boulder, CO, USA (deceased)","active":true,"usgs":false}],"preferred":false,"id":885657,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Scott, Lindsay","contributorId":330713,"corporation":false,"usgs":false,"family":"Scott","given":"Lindsay","email":"","affiliations":[{"id":78983,"text":"Woodwell Climate Research Center, Falmouth, MA, USA","active":true,"usgs":false}],"preferred":false,"id":885658,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Staples, Robin","contributorId":330714,"corporation":false,"usgs":false,"family":"Staples","given":"Robin","email":"","affiliations":[{"id":78984,"text":"Water Resources Division, Government of the Northwest Territories, Yellowknife, NT, Canada","active":true,"usgs":false}],"preferred":false,"id":885659,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":885660,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Tretiakov, Mikhail","contributorId":330715,"corporation":false,"usgs":false,"family":"Tretiakov","given":"Mikhail","email":"","affiliations":[{"id":78985,"text":"River Estuaries and Water Resources Department, Arctic and Antarctic Research Institute, Saint Petersburg, Russia","active":true,"usgs":false}],"preferred":false,"id":885661,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zhulidov, Alexander V.","contributorId":238030,"corporation":false,"usgs":false,"family":"Zhulidov","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":47688,"text":"South Russia Centre for Preparation and Implementation of International Projects, Rostov-on-Don, Russia","active":true,"usgs":false}],"preferred":false,"id":885662,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Zimov, Nikita","contributorId":238032,"corporation":false,"usgs":false,"family":"Zimov","given":"Nikita","email":"","affiliations":[{"id":47689,"text":"Northeast Science Station, Far Eastern Branch of Russian Academy of Science, Chersky, Russia","active":true,"usgs":false}],"preferred":false,"id":885663,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Zimov, Sergey","contributorId":238033,"corporation":false,"usgs":false,"family":"Zimov","given":"Sergey","email":"","affiliations":[{"id":47689,"text":"Northeast Science Station, Far Eastern Branch of Russian Academy of Science, Chersky, Russia","active":true,"usgs":false}],"preferred":false,"id":885664,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Holmes, Robert M.","contributorId":178901,"corporation":false,"usgs":false,"family":"Holmes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":885665,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70249296,"text":"fs20233034 - 2023 - Flood damage costs beyond buildings—A Lake Champlain case study","interactions":[],"lastModifiedDate":"2026-02-09T17:41:48.972867","indexId":"fs20233034","displayToPublicDate":"2023-10-05T13:20:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3034","displayTitle":"Flood Damage Costs Beyond Buildings—A Lake Champlain Case Study","title":"Flood damage costs beyond buildings—A Lake Champlain case study","docAbstract":"Floods account for more than 75 percent of Federal disaster declarations and lead other natural disasters in economic costs. Early-warning systems have lowered flood-related fatalities, but costs continue to rise as flood-prone areas continue to be urbanized (U.S. Geological Survey, 2006). A Lake Champlain case study shows that at moderate flood heights, the economic costs of non-structural damages or losses—such as temporary lodging, residential debris removal, commercial revenue losses, and road repair—can be greater than economic damages to buildings. For unprecedented flood heights, non-structural damages can still total more than 10 percent of structural damage costs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233034","usgsCitation":"Rhodes, C., 2023, Flood damage costs beyond buildings—A Lake Champlain case study: U.S. Geological Survey Fact Sheet 2023–3034, 6p., https://doi.org/10.3133/fs20233034.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146142","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":421549,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XWERGY","text":"USGS data release","linkHelpText":"U.S.-Side Principal Economic Indicators For the International Joint Commission Lake Champlain Richelieu River Study Project (2022)"},{"id":421545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3034/fs20233034.pdf","text":"Report","size":"1.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3034"},{"id":421544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3034/coverthb.jpg"},{"id":421546,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233034/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3034"},{"id":421547,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3034/images/"},{"id":421548,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3034/fs20233034.XML"},{"id":499692,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115451.htm","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.74618031431513,\n 43.36987616984206\n ],\n [\n -72.8562877361902,\n 43.36987616984206\n ],\n [\n -72.8562877361902,\n 45.31812414639214\n ],\n [\n -73.74618031431513,\n 45.31812414639214\n ],\n [\n -73.74618031431513,\n 43.36987616984206\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Dr.
Mail Stop 310
Reston, VA 20192
For endangered species persisting in a few populations, reintroductions to unoccupied habitat are a popular conservation action to increase viability in the long term. Identifying the reintroduction strategy that is most likely to result in viable founder and donor populations is essential to optimally use resources available for conservation. The San Francisco gartersnake (Thamnophis sirtalis tetrataenia) is an endangered sub-species that persists in a small number of populations in a highly urbanized region of California. Most of the extant populations of San Francisco gartersnakes have low adult abundance and effective population size, heightening the need for establishment of more populations for insurance against the risk of extinction. We used simulations from demographic models to project the probability of quasi-extinction for reintroduced populations of San Francisco gartersnakes based on the release of neonate, juvenile, adult, or mixed-age propagules. Our simulation results indicated that the release of head-started juveniles resulted in the greatest viability of reintroduced populations, and that releases would need to continue for at least 15 years to ensure a low probability of quasi-extinction. Releasing captive-bred juvenile snakes would also have less effect on the viability of the donor population, compared to strategies that require more adult snakes to be removed from the donor population for translocation. Our models focus on snake demography, but the genetic makeup of donor, captive, and reintroduced populations will also be a major concern for any proposed reintroduction plan. This study demonstrates how modeling can be used to inform reintroduction strategies for highly imperiled species.
It has long been challenging for researchers to track the crustal thickness and mode(s) of crustal modification in ancient convergent margins, limiting evaluation of the tectonic styles and processes that modify continental crust during orogenesis. We present trace element igneous geochemical crustal thickness proxies that quantitatively track the crustal thickness evolution of the long-lived Proterozoic active margin in the southwestern U.S.A. We integrate these results with geobarometric data to constrain the mode of crustal modification. The data indicate a complex record of crustal thickness change in space and time and evolving orogenic styles. Geochemical proxies at 1.84–1.72 Ga are consistent with 20–40 km thick magmatic arcs that were locally thickened to ∼50 km during ∼1.75 Ga tectonism. During the Yavapai orogeny, 1.72–1.69 Ga, a ∼200-km-wide belt of 50-60 km thick crust extended from southern California to northern Colorado and was rapidly thinned and exhumed by ∼1.68 Ga. Crustal thickening and thinning during the Yavapai orogeny largely occurred by shortening and exhumation, respectively, in the upper 25 km of the crust. Subsequent 1.68–1.60 Ga tectonism involved crustal growth, local crustal thickening, and low-P, high-T metamorphism, consistent with extensional accretionary orogenesis. The 1.47–1.37 Ga Picuris orogeny was associated with 50–60 km thick crust across much of the Southwest and involved crustal shortening with ∼10 km of magmatic underplating. Advective heat from the emplacement of ferroan granites in the mid-crust likely contributed to elevated geothermal gradients and rheologically weakened the crust. Our results suggest evolving orogenic styles in the Southwest from 1.75–1.69 Ga short-lived crustal thickening associated with terrane accretion to 1.69–1.60 Ga largely extensional accretionary orogenesis, and regional, long-lived crustal thickening at 1.47–1.37 Ga involving extensive basaltic underplating. Contrasting with some recent hypotheses, our data document a complex middle Proterozoic record for the Southwest that was not orogenically quiescent or tectonically stagnant but involved complex mountain building styles.
Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
MS 926A
Reston, VA 20192
Many geoscientific problems require us to exploit synergies of experimental and numerical approaches, which in turn lead to questions regarding the significance of experimental details for validation of numerical codes. We report results of an interlaboratory comparison regarding experimental determination of mechanical and hydraulic properties of samples from five rock types, three sandstone varieties with porosities ranging from 5% to 20%, a marble, and a granite. The objective of this study was to build confidence in the participating laboratories’ testing approaches and to establish tractable standards for several physical properties of rocks. We addressed the issue of sample-to-sample variability by investigating the variability of basic physical properties of samples of a particular rock type and by performing repeat tests. Compressive strength of the different rock types spans an order of magnitude and shows close agreement between the laboratories. However, differences among stress–strain relations indicate that the external measurement of axial displacement and the determination of system stiffness require special attention, apparently more so than the external load measurement. Furthermore, post-failure behavior seems to exhibit some machine-dependence. The different methods used for the determination of hydraulic permeability, covering six orders of magnitude for the sample suite, yield differences in absolute values and pressure dependence for some rocks but not for others. The origin of the differences in permeability, in no case exceeding an order of magnitude, correlate with the compressive strength and potentially reflect a convolution of end plug–sample interaction, sample-to-sample variability, heterogeneity on sample scale, and/or anisotropy, the last two aspects are notably not accounted for by the applied evaluation procedures. Our study provides an extensive data set apt for “benchmarking” considerations, be it regarding new laboratory equipment or numerical modeling approaches.
","language":"English","publisher":"Springer","doi":"10.1007/s12665-023-11173-x","usgsCitation":"Cheng, Y., Lockner, D., Duda, M., Morrow, C., Saffer, D., Song, I., and Renner, J., 2023, Interlaboratory comparison of testing hydraulic, elastic, and failure properties in compression: Lessons learned: Environmental Earth Sciences, v. 82, 509, 20 p., https://doi.org/10.1007/s12665-023-11173-x.","productDescription":"509, 20 p.","ipdsId":"IP-118956","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":487585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1007/s12665-023-11173-x","text":"Publisher Index Page"},{"id":482640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","noUsgsAuthors":false,"publicationDate":"2023-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cheng, Yang","contributorId":211352,"corporation":false,"usgs":false,"family":"Cheng","given":"Yang","email":"","affiliations":[],"preferred":false,"id":929146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":257574,"corporation":false,"usgs":true,"family":"Lockner","given":"David A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":929147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Mandy","contributorId":351625,"corporation":false,"usgs":false,"family":"Duda","given":"Mandy","affiliations":[{"id":84018,"text":"Ruhr-Universitat Bochum, Germany","active":true,"usgs":false}],"preferred":false,"id":929148,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morrow, Carolyn A.","contributorId":328522,"corporation":false,"usgs":false,"family":"Morrow","given":"Carolyn A.","affiliations":[{"id":37196,"text":"Retired USGS employee","active":true,"usgs":false}],"preferred":false,"id":929149,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saffer, Demian","contributorId":351626,"corporation":false,"usgs":false,"family":"Saffer","given":"Demian","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":929150,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Song, Insun","contributorId":351627,"corporation":false,"usgs":false,"family":"Song","given":"Insun","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":929151,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Renner, Joerg","contributorId":351628,"corporation":false,"usgs":false,"family":"Renner","given":"Joerg","affiliations":[{"id":84018,"text":"Ruhr-Universitat Bochum, Germany","active":true,"usgs":false}],"preferred":false,"id":929152,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70256518,"text":"70256518 - 2023 - Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin","interactions":[],"lastModifiedDate":"2024-09-09T15:52:04.867925","indexId":"70256518","displayToPublicDate":"2023-10-03T10:49:10","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-153-2023","title":"Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin","docAbstract":"We investigated the spatial and temporal distribution of Bighead Carp and Silver Carp (hereafter Carp) in the lower Red River basin of Arkansas. Our study objectives were: 1) determine the spatial and temporal extent of Bighead and Silver Carp in the Red River basin of Arkansas; 2) determine habitat associations of large river fish assemblages; and 3) summarize the demographics of Bighead and Silver Carp. We sampled 67 reaches in the lower Red River and its major tributaries for juvenile Carp and other small-bodied fishes (24 of the reaches were in the Arkansas portion of the Red River). We conducted repeated surveys in these reaches where the reaches were sampled 2-3 times over approximately 2 years representing 242 surveys (95 surveys in Arkansas). We completed adult Carp and native fish assemblage sampling across 61 reaches (22 reaches in Arkansas) where we also repeated surveys at these locations (245 total surveys, 100 surveys completed in Arkansas during the reporting period). We captured the most large-bodied fishes (including Carp) using gillnets and electrofishing, whereas fyke nets and seine hauls collected mainly smaller-bodied fishes. Hoop nets captured fewer fishes when compared to other gear types. We sampled 120,072 fishes, comprising 70 species and 41 genera, from the mainstem Red River in Arkansas. We used data associated with the entire catchment (including OK and TX data) to model the occupancy of adult fishes including both carp species. Carp tended to occupy reaches with the presence of slackwater habitat, that were deeper and narrower (lower habitat complexity), with higher discharge conditions, and were positively associated with chlorophyll-a concentrations. Adult and juvenile assemblage structure varied with reach scale attributes with notable differences among some taxonomically similar species. No carp under the age of 3 were sampled in the catchment. Bighead Carp and Silver Carp in the Red River catchment appear to live longer and grow larger than other populations. Silver Carp and Bighead Carp in the lower Red River had a theoretical maximum length (L_∞) of 920 and 1348-mm TL, respectively. The oldest sampled Silver Carp and Bighead Carp were age 14 and 17, respectively. Bighead Carp growth was positively associated with warmer air temperatures and negatively associated with discharge variability. Similarly, Silver Carp growth was positively associated with the warm air temperature and negatively associated with discharge variability. However, Silver Carp growth was also positively related to high discharge conditions and the variability of air temperature. Silver Carp annual mortality was relatively low and recruitment into the population appeared steady. It appears that Carp are likely coming from another catchment, have only limited or periodic successful reproduction in the study area, or spawn downriver in LA. Continued monitoring for reproductive success would be helpful. Moreover, if the goal is to greatly reduce or eliminate carp, then strategies to prevent further immigration would be ideal before reproduction occurs or becomes more successful. Targeted removal may then be useful for reducing numbers already in the catchment; however, there are also oxbow lakes that contain carp but appear only connected to the river during major floods (i.e., possible source locations).
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Brewer, S.K., Dattilo, J., Ramsey, P., and Birdsall, B., 2023, Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin: Cooperator Science Series FWS/CSS-153-2023, ii, 193 p.","productDescription":"ii, 193 p.","ipdsId":"IP-154807","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431854,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/evaluating-spatial-and-temporal-distribution-and-ecology-bighead-and-silver-carp-and-native"},{"id":433628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dattilo, John","contributorId":341000,"corporation":false,"usgs":false,"family":"Dattilo","given":"John","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":907784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Paul","contributorId":341001,"corporation":false,"usgs":false,"family":"Ramsey","given":"Paul","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":907785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdsall, Ben","contributorId":341002,"corporation":false,"usgs":false,"family":"Birdsall","given":"Ben","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":907786,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256477,"text":"70256477 - 2023 - Striped bass exploitation in tailwater habitats of east-central Oklahoma","interactions":[],"lastModifiedDate":"2024-09-09T15:47:17.424251","indexId":"70256477","displayToPublicDate":"2023-10-03T10:41:23","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-152-2023","title":"Striped bass exploitation in tailwater habitats of east-central Oklahoma","docAbstract":"Striped Bass (Morone saxatilis) is naturally anadromous, but a few land-locked populations have been documented that are self-sustaining, including fish in the Arkansas River, Oklahoma. This rare population is the source of brood stock for the Oklahoma Department of Wildlife Conservation hatcheries and is an important sportfish stock. Striped Bass often congregate in tailwater habitats, where anecdotal observations indicate anglers can harvest numerous fish daily. This suggests the need to evaluate the sustainability of harvest in these locations. It is unknown what portion of fish from the Arkansas River population use tailwater habitats or the timing and duration of use. The objectives of this study were to: 1) determine size structure , abundance, and total mortality rate of Striped Bass in the tailwaters of Tenkiller Lake and Lake Eufaula; 2) determine the extent and timing of immigration and emigration of Striped Bass in tailwater habitats to determine the potential for overharvest when they congregate in tailwater areas; 3) estimate delayed hooking mortality of Striped Bass in spring and summer; and 4) using the above data and modeling simulations, determine the potential for growth overfishing of Striped Bass in the tailwater reaches. We sampled 2,730 Striped Bass using boat electrofishing and tagged with passive integrated transponder (PIT) tags to estimate demographic data using a capture-recapture model. A subset of these Striped Bass was tagged with angler reward tags (internal anchor tags, n = 681) and dual technology acoustic-radio telemetry tags (n = 111) to estimate exploitation and track movements, respectively. Anglers returned 116 tags from 2020 to 2022; and our angler reporting rate was estimated to be 14.3%. Annual harvest mortality is minimally 7% (unadjusted for reporting rate) but could be as high as 42% (i.e., adjusting for compliance; but this exceeds the measured total mortality rate (34.3%) so true exploitation is probably 7–34.3%). Our abundance estimates for Striped Bass varied seasonally (ranging from 782 to 38,597 seasonally) and had a high level of uncertainty likely due to relatively low recapture rates. Additionally, our results indicated that Striped Bass exhibited a strong fidelity to their respective habitats within seasons, with fidelity probabilities ranging from 0.98 to 1.00. Movement among segments was common among seasons, indicating these localized populations mix with a larger population annually. Striped Bass were primarily in tailwater habitats during summer. Delayed hooking mortality data were collected in summer 2022. Due to habitat conditions that year, angling catch rates were low. Twenty-nine Striped Bass were tagged, and only eight Striped Bass remained tagged long enough to be tracked at least one day. The total time tracked for these eight fish was between one and three days. There were no confirmed mortalities, treatment, or control. Because of the low sample size, literature values for delayed hooking mortality were also used to supplement field data in the models. The yield-per-recruit model indicated exploitation at 30% or higher leads to recruitment overfishing. A 600 mm minimum TL regulation and 25–30% exploitation rate achieve maximum yield (954 kg/1,000 recruits). Maximum yield related to an average size at harvest of 718-mm TL; thus, growth overfishing occurs for any regulation where average size of harvest is smaller than 718 mm (which the model predicted would occur for any minimum length < 600, and for minimum length = 600 if exploitation was > 30%, it never occurred with minimum length requirements > 650). Increasing the minimum length regulation improves size structure, but a maximum length regulation had minimal effect unless it was implemented at a sufficiently small size (i.e., < 700 mm). Although catch-and-release mortality can be relatively high at times in the literature, according to our model, it appears to have a small effect on size structure, except when exploitation rates are > 50% and a restrictive maximum size regulation (< 800 mm) is used. The current population appears sustainable, especially considering the annual mixing dynamics and apparently large population (though we see a lot of uncertainty in the population estimates). However, modeling indicates that if enhancing size structure is an agency priority, then implementing more restrictive regulations could be advantageous.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Vaisvil, A., Shoup, D., and Brewer, S.K., 2023, Striped bass exploitation in tailwater habitats of east-central Oklahoma: Cooperator Science Series FWS/CSS-152-2023, ii, 67 p.","productDescription":"ii, 67 p.","ipdsId":"IP-155654","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431818,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/striped-bass-exploitation-tailwater-habitats-east-central-oklahoma"},{"id":433626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.68089573693297,\n 35.1807887620315\n ],\n [\n -94.68089573693297,\n 35.735103019942684\n ],\n [\n -95.40145518290683,\n 35.735103019942684\n ],\n [\n -95.40145518290683,\n 35.1807887620315\n ],\n [\n -94.68089573693297,\n 35.1807887620315\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Vaisvil, Alex","contributorId":340784,"corporation":false,"usgs":false,"family":"Vaisvil","given":"Alex","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoup, Daniel","contributorId":340785,"corporation":false,"usgs":false,"family":"Shoup","given":"Daniel","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907555,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270685,"text":"70270685 - 2023 - Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin","interactions":[],"lastModifiedDate":"2025-08-22T15:14:39.937639","indexId":"70270685","displayToPublicDate":"2023-10-03T10:05:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-153-2023","title":"Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin","docAbstract":"We investigated the spatial and temporal distribution of Bighead Carp and Silver Carp (hereafter Carp) in the lower Red River basin of Arkansas. Our study objectives were: 1) determine the spatial and temporal extent of Bighead and Silver Carp in the Red River basin of Arkansas; 2) determine habitat associations of large river fish assemblages; and 3) summarize the demographics of Bighead and Silver Carp. We sampled 67 reaches in the lower Red River and its major tributaries for juvenile Carp and other small-bodied fishes (24 of the reaches were in the Arkansas portion of the Red River). We conducted repeated surveys in these reaches where the reaches were sampled 2-3 times over approximately 2 years representing 242 surveys (95 surveys in Arkansas). We completed adult Carp and native fish assemblage sampling across 61 reaches (22 reaches in Arkansas) where we also repeated surveys at these locations (245 total surveys, 100 surveys completed in Arkansas during the reporting period). We captured the most large-bodied fishes (including Carp) using gillnets and electrofishing, whereas fyke nets and seine hauls collected mainly smaller-bodied fishes. Hoop nets captured fewer fishes when compared to other gear types. We sampled 120,072 fishes, comprising 70 species and 41 genera, from the mainstem Red River in Arkansas. We used data associated with the entire catchment (including OK and TX data) to model the occupancy of adult fishes including both carp species. Carp tended to occupy reaches with the presence of slackwater habitat, that were deeper and narrower (lower habitat complexity), with higher discharge conditions, and were positively associated with chlorophyll-a concentrations. Adult and juvenile assemblage structure varied with reach scale attributes with notable differences among some taxonomically similar species. No carp under the age of 3 were sampled in the catchment. Bighead Carp and Silver Carp in the Red River catchment appear to live longer and grow larger than other populations. Silver Carp and Bighead Carp in the lower Red River had a theoretical maximum length (\uD835\uDC3F∞) of 920 and 1,348-mm TL, respectively. The oldest sampled Silver Carp and Bighead Carp were age 14 and 17, respectively. Bighead Carp growth was positively associated with warmer air temperatures and negatively associated with discharge variability. Similarly, Silver Carp growth was positively associated with warm air temperature and negatively associated with discharge variability. However, Silver Carp growth was also positively related to high discharge conditions and the variability of air temperature. Silver Carp annual mortality was relatively low and recruitment into the population appeared steady. It appears that Carp are likely coming from another catchment, have only limited or periodic successful reproduction in the study area, or spawn downriver in LA. Continued monitoring for reproductive success would be helpful. Moreover, if the goal is to greatly reduce or eliminate carp, then strategies that prevent further immigration before reproduction occurs or becomes more successful would be ideal. Targeted removal may then be useful for reducing numbers already in the catchment; however, there are also oxbow lakes that contain carp but appear only connected to the river during major floods (i.e., possible source locations).
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css88134777","usgsCitation":"Brewer, S., Dattilo, J., Ramsey, P., and Birdsall, B., 2023, Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin: Cooperator Science Series CSS-153-2023, ii, 193 p., https://doi.org/10.3996/css88134777.","productDescription":"ii, 193 p.","ipdsId":"IP-177588","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3996/css88134777","text":"Publisher Index Page"},{"id":494522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Oklahoma, Texas","otherGeospatial":"lower Red River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.79873940117595,\n 34.31284035073031\n ],\n [\n -96.79873940117595,\n 33.02263338338369\n ],\n [\n -93.57412593043699,\n 33.02263338338369\n ],\n [\n -93.57412593043699,\n 34.31284035073031\n ],\n [\n -96.79873940117595,\n 34.31284035073031\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dattilo, John","contributorId":341000,"corporation":false,"usgs":false,"family":"Dattilo","given":"John","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Paul","contributorId":341001,"corporation":false,"usgs":false,"family":"Ramsey","given":"Paul","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdsall, Ben","contributorId":341002,"corporation":false,"usgs":false,"family":"Birdsall","given":"Ben","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250109,"text":"70250109 - 2023 - Effects of vehicle traffic on space use and road crossings of caribou in the Arctic","interactions":[],"lastModifiedDate":"2023-12-04T17:27:48.321119","indexId":"70250109","displayToPublicDate":"2023-10-03T09:30:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of vehicle traffic on space use and road crossings of caribou in the Arctic","docAbstract":"Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated with respect to the footprint of infrastructure, even though human activity can strongly mediate development impacts. In Arctic Alaska, there is substantial interest in expanding energy development, raising concerns about the potential effects on barren-ground caribou (Rangifer tarandus granti). While caribou generally avoid industrial infrastructure, little is known about the role of human activity in moderating their responses, and whether managing activity levels could minimize development effects. To address this uncertainty, we examined the influence of traffic volume on caribou summer space use and road crossings in the Central Arctic Herd within the Kuparuk and Milne Point oil fields on the North Slope of Alaska. We first modeled spatiotemporal variation in hourly traffic volumes across the road system from traffic counter data using gradient-boosted regression trees. We then used generalized additive models to estimate nonlinear step selection functions and road-crossing probabilities from collared female caribou during the post-calving and insect harassment seasons, when they primarily interact with roads. Step selection analyses revealed that caribou selected areas further from roads (~1–3 km) during the post-calving and mosquito seasons and selected areas with lower traffic volumes during all seasons, with selection probabilities peaking when traffic was <5 vehicles/h. Using road-crossing models, we found that caribou were less likely to cross roads during the insect seasons as traffic increased, but that response dissipated as insect harassment became more severe. Past studies suggested that caribou exhibit behavioral responses when traffic exceeds 15 vehicles/h, but our results demonstrate behavioral responses at much lower traffic levels. Our results illustrate that vehicle activity mediates caribou responses to road infrastructure, information that can be used in future land-use planning to minimize the behavioral responses of caribou to industrial development in sensitive Arctic landscapes.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2923","usgsCitation":"Severson, J.P., Johnson, H.E., and Vosburgh, T.C., 2023, Effects of vehicle traffic on space use and road crossings of caribou in the Arctic: Ecological Applications, v. 33, no. 8, e2923, 21 p., https://doi.org/10.1002/eap.2923.","productDescription":"e2923, 21 p.","ipdsId":"IP-145608","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":504068,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1NZMCND","text":"USGS data release","linkHelpText":"GPS Tracking Metadata for Caribou (Rangifer tarandus) from the Central Arctic Herd, Alaska, 2015-2021"},{"id":441958,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2923","text":"Publisher Index Page"},{"id":435163,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HXW3N5","text":"USGS data release","linkHelpText":"Hourly Vehicle Traffic Data Associated with Industrial Activity on the North Slope of Alaska During Summers 2019-2020"},{"id":422728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.86133804316822,\n 70.5106570028494\n ],\n [\n -150.1022371487244,\n 70.43506564845134\n ],\n [\n -150.2251448556409,\n 70.43341923336993\n ],\n [\n -150.57911905156016,\n 70.3773618530881\n ],\n [\n -150.74135722468978,\n 70.32611628176022\n ],\n [\n -150.84459969849965,\n 70.2448529934669\n ],\n [\n -150.83476708194632,\n 70.20992730257379\n ],\n [\n -150.71677568330648,\n 70.143238146334\n ],\n [\n -151.12482927026898,\n 69.73513298795481\n ],\n [\n -150.58895166811348,\n 69.72322531382761\n ],\n [\n -150.42671349498383,\n 69.76237009655026\n ],\n [\n -150.24972639702415,\n 69.86563513788099\n ],\n [\n -150.16123284804445,\n 69.94084273688509\n ],\n [\n -149.85642173489157,\n 69.9705480654984\n ],\n [\n -149.4606589186207,\n 70.04604045538369\n ],\n [\n -149.24679950858615,\n 70.08973159573645\n ],\n [\n -148.97640255337,\n 70.26312377942679\n ],\n [\n -149.04031456096658,\n 70.34927534019323\n ],\n [\n -148.91740685405023,\n 70.41529987953601\n ],\n [\n -149.0501471775199,\n 70.48111126247821\n ],\n [\n -149.46311707275905,\n 70.52213540068598\n ],\n [\n -149.649936787272,\n 70.5106570028494\n ],\n [\n -149.86133804316822,\n 70.5106570028494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Severson, John P. 0000-0002-1754-6689","orcid":"https://orcid.org/0000-0002-1754-6689","contributorId":213469,"corporation":false,"usgs":true,"family":"Severson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":888389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":888390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vosburgh, Timothy C.","contributorId":331661,"corporation":false,"usgs":false,"family":"Vosburgh","given":"Timothy","email":"","middleInitial":"C.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":888391,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70259334,"text":"70259334 - 2023 - Lateral edifice collapse and volcanic debris avalanches: A post-1980 Mount St. Helens perspective","interactions":[],"lastModifiedDate":"2024-10-04T12:22:29.122277","indexId":"70259334","displayToPublicDate":"2023-10-03T07:19:21","publicationYear":"2023","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":"Lateral edifice collapse and volcanic debris avalanches: A post-1980 Mount St. Helens perspective","docAbstract":"The 1980 eruption of Mount St. Helens was instrumental in advancing understanding of how volcanoes work. Lateral edifice collapses and the generation of volcanic debris avalanches were not widely recognized prior to that eruption, making assessment of their hazards and risks challenging. The proliferation of studies since 1980 on resulting deposits and evaluation of processes leading to their generation has built on the insights from the 1980 eruption. Volcano-related destabilizing phenomena, such as strength reduction by hydrothermal alteration, deformation and structural modifications from shallow magma intrusion, and thermal pressurization of pore fluids supplement those factors also affecting nonvolcanic slopes and can lead to larger failures. Remote and ground-based monitoring techniques can aid in detecting potentially destabilizing dynamic processes and in forecasting the size and location of future large lateral collapses, although forecasting remains a topic of investigation. More than a thousand large lateral collapse events likely ≥ 0.01 km3 in volume have now been identified from deposits or inferred from source area morphology, leading to a recognition of their importance in the evolution of volcanoes and the hazards they pose. Criteria for recognition of debris-avalanche deposits include morphological factors and textural characteristics from outcrop to microscopic scale, allowing discrimination from other volcaniclastic deposits. Lateral edifice failure impacts a broad spectrum of volcanic structures in diverse tectonic settings and can occur multiple times during the evolution of individual volcanoes. Globally, collapses ≥ 0.1 km3 in volume have been documented 5–6 times per century since 1500 CE, with about one per century having a volume ≥ 1 km3. Smaller events < 0.1 km3 are underrepresented in the earlier record but also have high hazard impact.
It is important to understand species-habitat relationships to implement effective adaptive management for rare species. However, it can be challenging to assess habitat associations and their relationships to abiotic stressors in dynamic habitats without the insights that can be gained from long-term monitoring. We report results from the first six years of extensive track tube monitoring of the largest two of three remaining extant populations of federally endangered Pacific pocket mouse (Perognathus longimembris pacificus) in a coastal Mediterranean-type ecosystem on Marine Corps Base, Camp Pendleton in southern California, USA. We used dynamic occupancy and structural equation modeling to assess potential drivers of population trends that included habitat, fire history, rainfall, disturbance, and the presence of other small mammals. We found that the variables that best predicted mouse occupancy were moderate to high forb and perennial herb cover (40–80%), and moderate to high open ground (20–70%) and low non-native grass cover (<20%), Non-native grass cover (>20%) was also a strong predictor of lower PPM colonization and increased extinction probabilities, with the extent of non-native grass cover being strongly influenced by annual rainfall and recency of fire. Our study adds to the growing literature on effects of invasive annual grasses on native species in Mediterranean-type ecosystems. We suggest that habitat management could be based upon promotion of open forb and perennial herb dominated habitats with reduction of non-native grasses by prescribed fire and other methods. These types of spatial and temporal monitoring programs can support land managers by creating a monitoring and management feedback loop. They can reveal landscape and environmental variables associated with species persistence, inform habitat management goals, and help managers to assess the success of management actions on populations of conservation concern.
We present the transverse coherence minimization method (TCM)—an approach to estimate the back-azimuth of infrasound signals that are recorded on an infrasound microphone and a colocated three-component seismometer. Accurate back-azimuth information is important for a variety of monitoring efforts, but it is currently only available for infrasound arrays and for seismoacoustic sensor pairs separated by 10 s of meters. Our TCM method allows for the analysis of colocated sensor pairs, sensors located within a few meters of each other, which may extend the capabilities of existing seismoacoustic networks and supplement operating infrasound arrays. This approach minimizes the coherence of the transverse component of seismic displacement with the infrasound wave to estimate the infrasound back-azimuth. After developing an analytical model, we investigate seismoacoustic signals from the August 2012 Humming Roadrunner experiment and the 26 May 2021 eruption of Great Sitkin Volcano, Alaska, U.S.A., at the ranges of 6.5–185 km from the source. We discuss back-azimuth estimates and potential sources of deviation (1°–15°), such as local terrain effects or deviation from common analytical models. This practical method complements existing seismoacoustic tools and may be suitable for routine application to signals of interest.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320230023","usgsCitation":"Bishop, J., Haney, M.M., Fee, D., Matoza, R., McKee, K., and Lyons, J.J., 2023, Back-azimuth estimation of air-to-ground coupled infrasound from transverse coherence minimization: The Seismic Record, v. 3, no. 4, p. 249-258, https://doi.org/10.1785/0320230023.","productDescription":"10 p.","startPage":"249","endPage":"258","ipdsId":"IP-155599","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467088,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320230023","text":"Publisher Index Page"},{"id":463340,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Bishop, Jordan","contributorId":345610,"corporation":false,"usgs":false,"family":"Bishop","given":"Jordan","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":917095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David","contributorId":345611,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":82656,"text":"Alaska Volcano Observatory/UAFGI","active":true,"usgs":false}],"preferred":false,"id":917097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matoza, Robin","contributorId":345612,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":917098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKee, Kathleen","contributorId":345613,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","affiliations":[{"id":36656,"text":"Vanderbilt University","active":true,"usgs":false}],"preferred":false,"id":917099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917100,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249323,"text":"70249323 - 2023 - Differing field methods and site conditions lead to varying bias in suspended sediment concentrations in the Lower Mississippi and Atchafalaya Rivers","interactions":[],"lastModifiedDate":"2023-10-06T13:51:06.518544","indexId":"70249323","displayToPublicDate":"2023-10-02T07:22:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Differing field methods and site conditions lead to varying bias in suspended sediment concentrations in the Lower Mississippi and Atchafalaya Rivers","docAbstract":"At sites that have been sampled for decades, changes in field and laboratory methods happen over time as instrumentation and protocols improve. Here, we compare the influence of depth- and point-integrated sampling on total, fine (< 0.0625 mm), and coarse (≥ 0.0625 mm) suspended sediment (SS) concentrations in the Lower Mississippi and Atchafalaya Rivers. Using historical field method information, we identified seven sites to test such differences. We found SS samples collected using point-integration tended to have higher concentrations than those collected using depth-integration. However, the presence and magnitude of the bias were inconsistent across sites. Bias was present at the site with less-than-ideal conditions (i.e., non-trapezoidal channel, non-uniform flow) and non-existent at the ideal site location, indicating the bias between sampling methods depends on site sampling conditions. When present, the bias is greater at higher concentrations and at moderate to high flows. At the less-than-ideal site, point-integrated samples can have 16% (total) and 34% (coarse) higher concentrations than depth-integrated samples. When flow effects are removed, this translates to a bias of 19, 9, and 8 mg per liter for total, fine, and coarse SS. When a change in field methods occurs, comparison samples and a rigorous evaluation of those samples are warranted to determine the proper course of action for a particular site. Often, the effect and solution will not be known until several years of comparison samples have been collected under a variety of hydrologic conditions.
Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer (Cervus elaphus) and 14 elk (Cervus canadensis) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16769","usgsCitation":"Mumme, S., Middleton, A.D., Ciucci, P., De Groeve, J., Corradini, A., Ossi, F., Atwood, P., Balkenhol, N., Cole, E., Debeffe, L., Dewey, S., Fischer, C., Gude, J., Heurich, M., Hurley, M.A., Jarnemo, A., Kauffman, M., Licoppe, A., van Loon, E., McWhirter, D., Mong, T., Pedrotti, L., Morellet, N., Mysterud, A., Peters, W., Proffitt, K., Saïd, S., Signer, J., Sunde, P., Stary, M., and Cagnacci, F., 2023, Wherever I may roam—Human activity alters movements of red deer (Cervus elaphus) and elk (Cervus canadensis) across two continents: Global Change Biology, v. 29, no. 20, p. 5788-5801, https://doi.org/10.1111/gcb.16769.","productDescription":"14 p.","startPage":"5788","endPage":"5801","ipdsId":"IP-148524","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441980,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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USA)","interactions":[],"lastModifiedDate":"2024-04-04T16:55:59.02534","indexId":"70252750","displayToPublicDate":"2023-10-01T11:47:31","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA)","docAbstract":"J.N. “Ding” Darling National Wildlife Refuge (DDNWR) is located on Sanibel Island along the southwestern coast of Florida, USA. Sanibel Island is heavily developed, but DDNWR provides protection for a large mangrove area that supports biodiversity and recreational opportunity. However, nitrogen (N) and phosphorus (P) eutrophication attributed to agriculture discharge along the Caloosahatchee River has affected the area’s aquatic habitat with algal blooms and may be causing untimely degradation of Sanibel’s mangrove forests. We launched a series of studies to understand how additional nutrient loading to the levels expected in the future might affect DDNWR’s mangrove resource. We experimentally fertilized selected mangrove forest areas with N fertilizer (+N; NH4) and P fertilizer (+P; P2O5) for three years, and monitored soil surface elevation change, soil and pneumatophore CO2 fluxes from respiration, mangrove tree sap flow from two species (Avicennia germinans, Rhizophora mangle), and individual tree and stand water use, from which we developed carbon (C) budgets for +N and +P vs. control simulations as applied to DDNWR’s 1112 ha mangrove area. Many of the measured response variables provided hints of subtle changes in response to +P rather than +N, which were compounded when scaled. From this, we found that additional P loading is expected to stimulate CO2 uptake via net ecosystem exchange of C, likely pressing the system beyond metabolic capacity and leading to a projected 41% increase in lateral C export to the estuary. Additional lateral C export is concomitant to a reduction in vertical soil surface elevation with +P. Furthermore, an inability of DDNWR’s mangroves to bury additional P and a release of P-bound ions to lateral export may exacerbate estuarine eutrophication. We also modelled the effect of sea-level rise influences on DDNWR’s mangroves through 2100 using a soil cohort model (WARMER-Mangroves) and found that the mangroves may be resilient to current rates of sea-level rise into the future but may also be susceptible to moderate accelerations. Greater eutrophication could create additional vulnerabilities to mangrove submergence, especially to basin mangroves where P concentrations are high and already reducing soil surface elevations in some mangroves. Our results suggest that amelioration of current P concentrations and avoidance of additional P loading to Sanibel Island’s mangroves are management options to consider.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Krauss, K., Conrad, J.R., Duberstein, J., Ward, E., Drexler, J.Z., Buffington, K., Thorne, K., Benscoter, B.W., Miller, H., Faron, N.T., Merino, S., From, A., Peneva-Reed, E., and Zhu, Z., 2023, Mangrove habitat persistence and carbon vulnerability associated with increased nutrient loading and sea-level rise at Ding Darling National Wildlife Refuge (Sanibel Island, Florida, USA), 46 p.","productDescription":"46 p.","ipdsId":"IP-156801","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":427403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427371,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/mangrove-ecosystem-services/"}],"country":"United States","state":"Florida","otherGeospatial":"Ding Darling National Wildlife Refuge, Sanibel Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.09257743948284,\n 26.43591715803987\n ],\n [\n -82.04970400948879,\n 26.44673081335216\n ],\n [\n -82.05393096737532,\n 26.472138907162602\n ],\n [\n -82.08170811920239,\n 26.469976734538434\n ],\n [\n -82.09016203497596,\n 26.461327637778552\n ],\n [\n -82.1227699958168,\n 26.475922611484222\n ],\n [\n -82.15718951003726,\n 26.494839266177138\n ],\n [\n -82.17107808595081,\n 26.49916263597524\n ],\n [\n -82.17590889496402,\n 26.515914157596868\n ],\n [\n -82.18315510848416,\n 26.521857658684468\n ],\n [\n -82.18557051299105,\n 26.487272977733056\n ],\n [\n -82.14330093412373,\n 26.455381006749434\n ],\n [\n -82.10163520638315,\n 26.43916136120143\n ],\n [\n -82.09257743948284,\n 26.43591715803987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, Jeremy R.","contributorId":149347,"corporation":false,"usgs":false,"family":"Conrad","given":"Jeremy","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":898086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":898087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":217389,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - 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2023 - Lake Ontario April prey fish survey results and Alewife assessment, 2023","interactions":[],"lastModifiedDate":"2025-08-26T14:29:06.466685","indexId":"70249606","displayToPublicDate":"2023-10-01T10:08:53","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Lake Ontario April prey fish survey results and Alewife assessment, 2023","docAbstract":"The April bottom trawl survey and Alewife Alosa pseudoharengus population assessment provides science to inform Lake Ontario fisheries management. The 2023 survey included 215 trawls in the main lake and embayments, and sampled depths from 6.5 to 252 m (21-833 ft). The survey captured 1,012,178 fish from 32 species with a total weight of 12,136 kg (26,700 lbs.). Alewife were 92% of the catch by number while Rainbow Smelt, Osmerus mordax, Deepwater Sculpin, Myoxocephalus thompsonii, and Round Goby, Neogobius melanostomus, comprised 3%, 3%, and 1% of the catch, respectively. To improve the accuracy of prey fish biomass and density estimates we reanalyzed trawl sensor data from each of three participating survey vessels and created vessel-specific relationships predicting how bottom trawl bottom contact time, wing width, and area-swept varies with depth.
Total Alewife biomass increased in 2023 due to growth and survival of the abundant 2020 year class (now age-3) and an abundant 2022 year class (age-1). The 2023 mean Alewife biomass (81.1 kg·ha-1) was the largest since whole lake sampling began in 2016 and was the ninth largest value observed in the modern time series (1997-2023, maximum value in 2000 = 91.8 kg·ha-1). The 2023 Alewife density (6795 n·ha-1) was the greatest density observed in the modern time series. These high biomass and density values are due to above average Alewife reproductive success in 2020 and 2022. Simulation modeling suggests the 2024 and 2025 Alewife biomass index may be substantially higher than the 2023 observations.
In 2023, the Rainbow Smelt biomass index increased relative to the 2022 index, as did the biomass index for Cisco, Coregonus artedi. In contrast, Emerald Shiner Notropis atherinoides and Threespine Stickleback Gasterosteus aculeatus, biomass values continue to be low (< 0.01 kg·ha-1). Three Bloater Coregonus hoyi, were captured during the 2023 survey. Hydroacoustic sampling conducted during the bottom trawl survey estimated prey fish densities in pelagic habitats not sampled by the bottom trawl (3 m below the surface to 3 m above the lake bottom) and these densities were hundreds to thousands of times lower than bottom trawl-based densities. These results support the idea that, in April, when the warmest water is on the lake bottom, Alewife and most other pelagic prey fish are near the lake bottom and can be effectively sampled with bottom trawling.
","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Weidel, B., Goretzke, J., Holden, J., Mitchinson, O.M., and Minihkeim, S.P., 2023, Lake Ontario April prey fish survey results and Alewife assessment, 2023, 16 p.","productDescription":"16 p.","ipdsId":"IP-156780","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":422004,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421986,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"http://www.glfc.org/","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.925537109375,\n 43.265206318396025\n ],\n [\n -79.8101806640625,\n 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Jeremy","contributorId":168905,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":886438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchinson, Olivia Margaret 0009-0002-7999-1160","orcid":"https://orcid.org/0009-0002-7999-1160","contributorId":339869,"corporation":false,"usgs":true,"family":"Mitchinson","given":"Olivia","email":"","middleInitial":"Margaret","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Minihkeim, Scott P. 0000-0003-4958-2462","orcid":"https://orcid.org/0000-0003-4958-2462","contributorId":265808,"corporation":false,"usgs":true,"family":"Minihkeim","given":"Scott","email":"","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886440,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266470,"text":"70266470 - 2023 - Spatially and temporally variable production pathways support the Lake Erie central basin food web","interactions":[],"lastModifiedDate":"2025-05-07T18:47:53.830989","indexId":"70266470","displayToPublicDate":"2023-09-30T13:43:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatially and temporally variable production pathways support the Lake Erie central basin food web","docAbstract":"In large freshwater systems, the dominant production pathways supporting food webs are often spatiotemporally variable. We used stable isotope analysis and analysis of covariance (ANCOVA) models to investigate spatial and interannual variation in the dominant production pathways supporting fish consumers within the central basin of Lake Erie. We examined C and N stable isotope ratios of zooplankton, benthic invertebrates, and four species of fish common to nearshore areas of the central basin (yellow perch, Perca flavescens; white perch, Morone americana; rainbow smelt, Osmerus mordax; and round goby, Neogobius melanostomus) using tissue samples collected in 2017 and 2019. δ 13C values varied by location consistent with expected baseline differences in nutrient loading (13C was more enriched in the southern region) in two of six ANCOVA models. Furthermore, δ 15N values varied with individual fish size and by location in a manner consistent with spatial patterns of nutrient loading from surrounding agricultural landscapes (15N was more enriched in the northern region) and a longitudinal gradient of eutrophication, decreasing from west to east. These patterns were not exhibited by all species and did not necessarily persist across years, suggesting that additional factors (e.g., regional diet differences, river plume dynamics) also contributed to observed δ 13C and δ 15N variation. We suggest that spatiotemporal variation of stable isotope ratios should be accounted for in studies of trophic basis of production and food web structure in Lake Erie.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.07.006","usgsCitation":"Tellier, J., Höök, T., Kraus, R., and Collingsworth, P., 2023, Spatially and temporally variable production pathways support the Lake Erie central basin food web: Journal of Great Lakes Research, v. 49, no. 5, p. 1137-1149, https://doi.org/10.1016/j.jglr.2023.07.006.","productDescription":"13 p.","startPage":"1137","endPage":"1149","ipdsId":"IP-144710","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488148,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.jglr.2023.07.006","text":"Publisher Index Page"},{"id":485518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"central Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.89113891431519,\n 42.642087429833964\n ],\n [\n -81.54918796649198,\n 42.5518853383298\n ],\n [\n -82.00732338256428,\n 42.28154650023495\n ],\n [\n -82.41825696788968,\n 42.08990823363946\n ],\n [\n -82.65704269990312,\n 41.35456309813142\n ],\n [\n -81.71855924152474,\n 41.51441245425303\n ],\n [\n -80.95777679301685,\n 41.82391066009919\n ],\n [\n -80.89113891431519,\n 42.642087429833964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Tellier, Joshua M.","contributorId":354641,"corporation":false,"usgs":false,"family":"Tellier","given":"Joshua M.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":936058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Höök, Tomas O.","contributorId":354642,"corporation":false,"usgs":false,"family":"Höök","given":"Tomas O.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":936059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936060,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collingsworth, Paris D.","contributorId":354643,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris D.","affiliations":[{"id":84645,"text":"Illinois-Indiana SeaGrant","active":true,"usgs":false}],"preferred":false,"id":936061,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249643,"text":"70249643 - 2023 - Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06","interactions":[],"lastModifiedDate":"2023-10-23T13:39:48.181636","indexId":"70249643","displayToPublicDate":"2023-09-30T08:29:02","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17063,"text":"DWH MDBC Cruise Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CR-23-03","title":"Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06","docAbstract":"Between 9 August and 1 September, 2022, the Mesophotic and Deep Benthic (MDBC) Habitat Assessment and Evaluation (HAE) and Mapping, Ground-truthing, and Predictive Habitat Modeling (MGM) projects implemented remotely operated vehicle (ROV) dives, multibeam surveys, and conductivity, temperature, depth (CTD) operations at deep-sea sites in the northern Gulf of Mexico. The primary sites selected are a region of known deep-sea coral habitats, including Deepwater Horizon (DWH) injured and reference sites at depths of 1,100–2,000 m.
The cruise includes objectives from MGM and HAE projects. Habitat characterization and analysis of biological samples collected with ROV Odysseus maintain long-term data flows and fill critical data gaps on the biology and ecology at impacted and reference sites, assess potential ongoing impacts from threats, refine predictive habitat models, help target locations for direct restoration and protection, and determine a baseline for health and condition. Multibeam echosounder data can help document the broadscale abundance and distribution of MDBC, characterize benthic habitats, and provide information that can help guide future ROV surveys.
","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/nwxc-ab95","usgsCitation":"Clark, R., and Demopoulos, A., 2023, Cruise Report for NOAA Ship Nancy Foster Cruise NF-22-06: DWH MDBC Cruise Report CR-23-03, 33 p., https://doi.org/10.25923/nwxc-ab95.","productDescription":"33 p.","ipdsId":"IP-153687","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":422038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.5,\n 30\n ],\n [\n -91.5,\n 30\n ],\n [\n -91.5,\n 27\n ],\n [\n -87.5,\n 27\n ],\n [\n -87.5,\n 30\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":886574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222183,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":886575,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260095,"text":"70260095 - 2023 - Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","interactions":[],"lastModifiedDate":"2024-10-28T12:02:39.587199","indexId":"70260095","displayToPublicDate":"2023-09-30T07:00:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","docAbstract":"Cretaceous through Eocene plutonic rocks in northeastern Washington, USA, document a 60 m.y. history of crustal thickening and subsequent collapse and extension in response to two terrane-accretion events. Rocks emplaced 113–53 Ma have increasing La/Yb ratios reflecting orogenic plateau development after arrival of the Insular terrane by 100 Ma. Plutons emplaced 52–45 Ma (the Challis episode) document collapse of this plateau and define a SW-younging age progression attributed to breakoff and rollback of the Farallon slab following accretion of the Siletzia terrane at ca. 50 Ma. All of the rocks have chemical traits of arc magmas, likely inherited from their lower-crustal sources, but low B/Be ratios and the lack of evidence for amphibole fractionation indicate the Eocene magmas formed under drier conditions than are typical of active subduction settings. These magmas also originated at greater depth (eclogitic vs. gabbroic source) and were emplaced more shallowly than the earlier ones. All rocks have overlapping Sr-Nd and O isotopic data, indicating significant contributions from older continental crust, and depleted mantle Nd model ages become older toward the east, defining three regions that correspond with previously inferred lower-crustal domains. Farallon slab rollback also drove extension (core complex formation, dike swarms) and crustal uplift, which, along with voluminous magmatism, define the Challis episode. This tectonic model is further supported by seismic tomography, which has identified remnants of a detached slab in the upper mantle beneath the region.