Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992–2002) and data from long-term, fixed-site water-quality monitoring program (1990–2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992–2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007–2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.
Groundwater discharge zones in streams are important habitats for aquatic organisms. The use of discharge zones for thermal refuge and spawning by fish and other biota renders them susceptible to potential focused discharge of groundwater contamination. Currently, there is a paucity of information about discharge zones as a potential exposure pathway of chemicals to stream ecosystems. Using thermal mapping technologies to locate groundwater discharges, shallow groundwater and surface water from three rivers in the Chesapeake Bay Watershed, USA were analyzed for phytoestrogens, pesticides and their degradates, steroid hormones, sterols and bisphenol A. A Bayesian censored regression model was used to compare groundwater and surface water chemical concentrations. The most frequently detected chemicals in both ground and surface water were the phytoestrogens genistein (79%) and formononetin (55%), the herbicides metolachlor (50%) and atrazine (74%), and the sterol cholesterol (88%). There was evidence suggesting groundwater discharge zones could be a unique exposure pathway of chemicals to surface water systems, in our case, metolachlor sulfonic acid (posterior mean concentration = 150 ng/L in groundwater and 4.6 ng/L in surface water). Our study also demonstrated heterogeneity of chemical concentration in groundwater discharge zones within a stream for the phytoestrogen formononetin, the herbicides metolachlor and atrazine, and cholesterol. Results support the hypothesis that discharge zones are an important source of exposure of phytoestrogens and herbicides to aquatic organisms. To manage critical resources within the Chesapeake Bay Watershed, more work is needed to characterize exposure in discharge zones more broadly across time and space.
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J.","contributorId":261148,"corporation":false,"usgs":false,"family":"Thompson","given":"Tyler","email":"","middleInitial":"J.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":819369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":819370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":819372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":819374,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":819368,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223706,"text":"70223706 - 2021 - More than one way to kill a spruce forest: The role of fire and climate in the late-glacial termination of spruce woodlands across the southern Great Lakes","interactions":[],"lastModifiedDate":"2021-09-02T12:53:25.277365","indexId":"70223706","displayToPublicDate":"2020-10-08T07:44:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"More than one way to kill a spruce forest: The role of fire and climate in the late-glacial termination of spruce woodlands across the southern Great Lakes","docAbstract":"The landslide complex at Gold Basin, Washington, has been drawing considerable attention after a catastrophic runout of the nearby landslide at Oso, Washington, in 2014. To evaluate potential threats of the Gold Basin landslide to the campground down the slope, remote sensing and numerical modeling were integrated to monitor recent landslide activity and simulate hypothetical runout scenarios. Bare-earth LiDAR DEM (digital elevation model) differencing, InSAR (Interferometric Synthetic Aperture Radar), and offset tracking of SAR images reveal that localized collapses at the headscarps have been the primary type of landslide activity at Gold Basin from 2005 to 2019, and currently no signs indicative of movement of a large centralized block or a deep-seated main body were detected. The maximum horizontal deformation rate is 5 m/year occurring primarily from headscarp recession of the middle lobe, and the annual landsliding volume of the whole landslide complex averages 1.03 × 105 m3. From three-dimensional limit equilibrium analysis of generalized terrace structures, the maximum landslide volume is estimated as 2.0 × 106 m3. Simulations of hypothetical runout scenarios were carried out using the depth-averaged two-phase model D-claw with above-obtained landslide geometry constraints. The simulation results demonstrate that debris flows with volume less than 105 m3 only pose limited threats to the campground, while volumes over 106 m3 could cause severe damages. Consequently, the estimated maximum landslide volume of 2.0 × 106 m3 suggests a potential risk to the campground nearby. Adaption of our methodology could prove useful for evaluating other similar landslides globally for hazards prevention and mitigation.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-020-01533-0","usgsCitation":"Xu, Y., George, D.L., Kim, J., Lu, Z., Riley, M., Griffin, T., and de la Fuente, J., 2021, Landslide monitoring and runout hazard assessment by integrating multi-source remote sensing and numerical models: An application to the Gold Basin landslide complex, northern Washington: Landslides, v. 18, p. 1131-1141, https://doi.org/10.1007/s10346-020-01533-0.","productDescription":"11 p.","startPage":"1131","endPage":"1141","ipdsId":"IP-118305","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":464027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Gold Basin landslide complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.70,\n 48.2855\n ],\n [\n -121.70,\n 48.0755\n ],\n [\n -121.855,\n 48.0755\n ],\n [\n -121.855,\n 48.2855\n ],\n [\n -121.70,\n 48.2855\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Xu, Yuankun","contributorId":261747,"corporation":false,"usgs":false,"family":"Xu","given":"Yuankun","email":"","affiliations":[{"id":52987,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75205, USA","active":true,"usgs":false}],"preferred":false,"id":918501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Jin-Woo","contributorId":69486,"corporation":false,"usgs":true,"family":"Kim","given":"Jin-Woo","affiliations":[],"preferred":false,"id":918503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lu, Zhong","contributorId":344911,"corporation":false,"usgs":false,"family":"Lu","given":"Zhong","affiliations":[],"preferred":false,"id":918504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Mark","contributorId":346244,"corporation":false,"usgs":false,"family":"Riley","given":"Mark","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":918505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Griffin, Todd","contributorId":346245,"corporation":false,"usgs":false,"family":"Griffin","given":"Todd","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":918506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"de la Fuente, Juan","contributorId":346246,"corporation":false,"usgs":false,"family":"de la Fuente","given":"Juan","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":918507,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217785,"text":"70217785 - 2021 - Dendritic reidite from the Chesapeake Bay impact horizon, Ocean Drilling Program Site 1073 (offshore northeastern USA): A fingerprint of distal ejecta?","interactions":[],"lastModifiedDate":"2021-02-02T12:38:43.102242","indexId":"70217785","displayToPublicDate":"2020-10-07T06:33:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Dendritic reidite from the Chesapeake Bay impact horizon, Ocean Drilling Program Site 1073 (offshore northeastern USA): A fingerprint of distal ejecta?","docAbstract":"High-pressure minerals provide records of processes not normally preserved in Earth’s crust. Reidite, a quenchable polymorph of zircon, forms at pressures >20 GPa during shock compression. However, there is no broad consensus among empirical, experimental, and theoretical studies on the nature of the polymorphic transformation. Here we decipher a multistage history of reidite growth recorded in a zircon grain in distal impact ejecta (offshore northeastern United States) from the ca. 35 Ma Chesapeake Bay impact event which, remarkably, experienced near-complete conversion (89%) to reidite. The grain displays two distinctive reidite habits: (1) intersecting sets of planar lamellae that are dark in cathodoluminescence (CL); and (2) dendritic epitaxial overgrowths on the lamellae that are luminescent in CL. While the former is similar to that described in literature, the latter has not been previously reported. A two-stage growth model is proposed for reidite formation at >40 GPa in Chesapeake Bay impact ejecta: formation of lamellar reidite by shearing during shock compression, followed by dendrite growth, also at high pressure, via recrystallization. The dendritic reidite is interpreted to nucleate on lamellae and replace damaged zircon adjacent to lamellae, which may be amorphous ZrSiO4 or possibly an intermediate phase, all before quenching. These results provide new insights on the microstructural evolution of the high-pressure polymorphic transformation over the microseconds-long interval of reidite stability during meteorite impact. Given the formation conditions, dendritic reidite may be a unique indicator of distal ejecta.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G47860.1","usgsCitation":"Cavosie, A.J., Biren, M.C., Hodges, K.V., Wartho, J., Horton,, J., and Koeberl, C., 2021, Dendritic reidite from the Chesapeake Bay impact horizon, Ocean Drilling Program Site 1073 (offshore northeastern USA): A fingerprint of distal ejecta?: Geology, v. 49, no. 2, p. 201-205, https://doi.org/10.1130/G47860.1.","productDescription":"5 p.","startPage":"201","endPage":"205","ipdsId":"IP-118547","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":486996,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":382866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay impact","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.2890625,\n 37.055177106660814\n ],\n [\n -75.1025390625,\n 37.055177106660814\n ],\n [\n -75.1025390625,\n 38.591113776147445\n ],\n [\n -76.2890625,\n 38.591113776147445\n ],\n [\n -76.2890625,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-10-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavosie, Aaron J.","contributorId":248705,"corporation":false,"usgs":false,"family":"Cavosie","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":49985,"text":"Curtin University, Perth, WA, 6102, Australia","active":true,"usgs":false}],"preferred":false,"id":809646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biren, Marc C","contributorId":248706,"corporation":false,"usgs":false,"family":"Biren","given":"Marc","email":"","middleInitial":"C","affiliations":[{"id":36436,"text":"Arizona State University, Tempe, AZ","active":true,"usgs":false}],"preferred":false,"id":809647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, Kip V. 0000-0003-2805-8899","orcid":"https://orcid.org/0000-0003-2805-8899","contributorId":229558,"corporation":false,"usgs":false,"family":"Hodges","given":"Kip","email":"","middleInitial":"V.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":809648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wartho, Jo-Anne","contributorId":248707,"corporation":false,"usgs":false,"family":"Wartho","given":"Jo-Anne","email":"","affiliations":[{"id":49986,"text":"GEOMAR Helmholltz Centre for Ocean Research, Kiel, Germany","active":true,"usgs":false}],"preferred":false,"id":809649,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Horton,, J. Wright Jr. 0000-0001-6756-6365","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":219824,"corporation":false,"usgs":true,"family":"Horton,","given":"J. Wright","suffix":"Jr.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":809650,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koeberl, Christian","contributorId":219447,"corporation":false,"usgs":false,"family":"Koeberl","given":"Christian","email":"","affiliations":[],"preferred":false,"id":809651,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217997,"text":"70217997 - 2021 - Evaluating the dynamics of groundwater, lakebed transport, nutrient inflow and algal blooms in Upper Klamath Lake, Oregon, USA","interactions":[],"lastModifiedDate":"2021-02-11T19:59:24.92397","indexId":"70217997","displayToPublicDate":"2020-10-06T13:54:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the dynamics of groundwater, lakebed transport, nutrient inflow and algal blooms in Upper Klamath Lake, Oregon, USA","docAbstract":"Transport of nutrients to lakes can occur via surface-water inflow, atmospheric deposition, groundwater (GW) inflow and benthic processes. Identifying and quantifying within-lake nutrient sources and recycling processes is challenging. Prior studies in hypereutrophic Upper Klamath Lake, Oregon, USA, indicated that ~60% of the early summer phosphorus (P) load to the lake was internal and hypothesized to be lakebed sediment release. Dynamic nutrient transport processes were examined to better characterize the nutrient sources. One-dimensional heat transport models calibrated to observed lakebed temperatures and a cross-sectional GW flow model provided estimates of GW-inflow rates that were greatest in spring and decreased through summer. One-dimensional solute transport models calibrated to observed lakebed pore-water dissolved silica (Si) and dissolved phosphate-phosphorus (DP) concentrations indicated that nutrients were transported from the lakebed by advection, diffusion, and enhanced mixing by benthic organisms and waves, and that DP removal occurred near the lakebed interface. Estimated water, Si, DP and total-phosphorus (TP) budgets indicated that GW contributed 21% of lake water inflow and at least 26, 20 and 16% of total Si, DP and TP inflow, respectively, when conservatively assuming background GW nutrient concentrations. However, lakebed GW (LGW) is enriched in nutrients during flow through lakebed sediment and the estimated GW contribution increased to 29 (33), 49 (67) and 43% (61%) of total Si, DP and TP inflow, respectively, if 20% (50%) of GW inflow to the lake was assumed to have LGW concentrations. Net nutrient inflow to the lake was greatest in spring and coincident with the annual diatom bloom. Inflowing dissolved nutrients appear to be assimilated by diatoms during the spring and become available for the summer Aphanizomenon flos-aquae bloom when the diatoms senesce. Thus, nutrient-enriched GW inflow and nutrient recycling by successive algal blooms must be considered when evaluating internal nutrient loading to lakes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.142768","usgsCitation":"Essaid, H.I., Kuwabara, J.S., Corson-Dosch, N., Carter, J.L., and Topping, B.R., 2021, Evaluating the dynamics of groundwater, lakebed transport, nutrient inflow and algal blooms in Upper Klamath Lake, Oregon, USA: Science of the Total Environment, v. 765, 142768, 16 p., https://doi.org/10.1016/j.scitotenv.2020.142768.","productDescription":"142768, 16 p.","ipdsId":"IP-115458","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436656,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98C5H5N","text":"USGS data release","linkHelpText":"MODFLOW, MT3D-USGS and VS2DH simulations used to estimate groundwater and nutrient inflow to Upper Klamath Lake, Oregon"},{"id":383225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10273742675781,\n 42.21987327563142\n ],\n [\n -121.79374694824219,\n 42.21987327563142\n ],\n [\n -121.79374694824219,\n 42.6026307853624\n ],\n [\n -122.10273742675781,\n 42.6026307853624\n ],\n [\n -122.10273742675781,\n 42.21987327563142\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"765","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":810173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corson-Dosch, Nicholas 0000-0002-6776-6241","orcid":"https://orcid.org/0000-0002-6776-6241","contributorId":202630,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Nicholas","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, James L. 0000-0002-0104-9776","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":215951,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":810176,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216475,"text":"70216475 - 2021 - Free-roaming horses disrupt greater sage-grouse lekking activity in the Great Basin","interactions":[],"lastModifiedDate":"2020-11-20T13:32:59.355157","indexId":"70216475","displayToPublicDate":"2020-10-05T07:27:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Free-roaming horses disrupt greater sage-grouse lekking activity in the Great Basin","docAbstract":"Greater Sage-Grouse (Centrocercus urophasianus; hereafter, sage-grouse) and free-roaming horses (Equus caballus) co-occur within large portions of sagebrush ecosystems within the Great Basin of western North America. In recent decades, sage-grouse populations have declined substantially while concomitant free-roaming horse populations have increased drastically. Although multiple studies have reported free-roaming horses adversely impacting native ungulate species, direct interactions between free-roaming horses and sage-grouse have not been documented previously. We compiled sage-grouse lek count data and associated ungulate observations during spring of 2010 and 2013–2018. We used Bayesian multinomial logistic models to examine the response of breeding male sage-grouse to the presence of native (i.e. mule deer, pronghorn) and non-native (i.e. cattle, free-roaming horses) ungulates on active sage-grouse leks (traditional breeding grounds). We found sage-grouse were approximately five times more likely to be present on active leks concurrent with native ungulates compared to non-native ungulates. Of the four different ungulate species, sage-grouse were least likely to be at active leks when free-roaming horses were present. Our results indicate that free-roaming horse presence at lek sites negatively influences sage-grouse lekking activity. Because sage-grouse population growth is sensitive to breeding success, disruption of leks by free-roaming horses could reduce breeding opportunities and limit breeding areas within sage-grouse habitat.
The Conservation Reserve Program (CRP) has the potential to influence the distribution and abundance of grasslands in many agricultural landscapes, and thereby provide habitat for grassland-dependent wildlife. Greater prairie-chickens (Tympanuchus cupido pinnatus) are a grassland-dependent species with large area requirements and have been used as an indicator of grassland ecosystem function; they are also a species of conservation concern across much of their range. Greater prairie-chicken populations respond to the amount and configuration of grasslands and wetlands in agriculturally dominated landscapes, which in turn can be influenced by the CRP; however, CRP enrollments and enrollment caps have declined from previous highs. Therefore, prioritizing CRP reenrollments and new enrollments to achieve the greatest benefit for grassland-dependent wildlife seems prudent. We used models relating either lek density or the number of males at leks to CRP enrollments and the resulting landscape structure to predict changes in greater prairie-chicken abundance related to changes in CRP enrollments. We simulated 3 land-cover scenarios: expiration of existing CRP enrollments, random, small-parcel (4,040 m2) addition of CRP grasslands, and strategic, large-parcel (80,000 m2) addition of CRP grasslands. Large-parcel additions were the average enrollment size in northwestern Minnesota, USA, within the context of a regional prairie restoration plan. In our simulations of CRP enrollment expirations, the abundance of greater prairie-chickens declined when grassland landscape contiguity declined with loss of CRP enrollments. Simulations of strategic CRP enrollment with large parcels to increase grassland contiguity more often increased greater prairie-chicken abundance than random additions of the same area in small parcels that did not increase grassland contiguity. In some cases, CRP enrollments had no or a negative predicted change in greater prairie-chicken abundance because they provided insufficient grassland contiguity on the landscape, or increased cover-type fragmentation. Predicted greater prairie-chicken abundance increased under large-parcel and small-parcel scenarios of addition of CRP grassland; the greatest increases were associated with large-parcel additions. We suggest that strategic application of the CRP to improve grassland contiguity can benefit greater prairie-chicken populations more than an opportunistic approach lacking consideration of the larger landscape context. Strategic implementation of the CRP can benefit greater prairie-chicken populations in northwestern Minnesota, and likely elsewhere in landscapes where grassland continuity may be a limiting factor.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21960","usgsCitation":"Adkins, K., Roy, C.L., Wright, R.G., and Andersen, D.E., 2021, Simulating strategic implementation of the CRP to increase Greater prairie-chicken abundance: Journal of Wildlife Management, v. 85, no. 1, p. 27-40, https://doi.org/10.1002/jwmg.21960.","productDescription":"14 p.","startPage":"27","endPage":"40","ipdsId":"IP-114569","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.05322265625,\n 45.98169518512228\n ],\n [\n -94.81201171875,\n 45.98169518512228\n ],\n [\n -94.81201171875,\n 48.472921272487824\n ],\n [\n -97.05322265625,\n 48.472921272487824\n ],\n [\n -97.05322265625,\n 45.98169518512228\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Adkins, Kalysta","contributorId":274612,"corporation":false,"usgs":false,"family":"Adkins","given":"Kalysta","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":833978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Charlotte L.","contributorId":274613,"corporation":false,"usgs":false,"family":"Roy","given":"Charlotte","email":"","middleInitial":"L.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Robert G.","contributorId":274614,"corporation":false,"usgs":false,"family":"Wright","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833977,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230082,"text":"70230082 - 2021 - Volcano geodesy: A critical tool for assessing the state of volcanoes and their potential for hazardous eruptive activity","interactions":[],"lastModifiedDate":"2022-03-28T14:33:49.793563","indexId":"70230082","displayToPublicDate":"2020-10-02T09:27:40","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Volcano geodesy: A critical tool for assessing the state of volcanoes and their potential for hazardous eruptive activity","docAbstract":"Since the beginning of the 20th century, volcano geodesy has evolved from time- and personnel-intensive methods for collecting discrete measurements to automated and/or remote tools that provide data with exceptional spatiotemporal resolution. By acknowledging and overcoming limitations related to data collection and interpretation, geodesy becomes a powerful tool for forecasting the onset and tracking the evolution of volcanic eruptions. In addition, geodetic data can be used for novel applications, such as mapping surface and topographic change due to the emplacement of volcanic deposits, detecting volcanic plumes, and constraining the properties of magmatic systems. These collective capabilities provide critical support for understanding magmatic processes at erupting volcanoes, while also offering important baseline data in advance of potential volcanic unrest. Future developments in volcano geodesy will involve not just new technology, but also advanced modeling and automated analysis methods that will provide a new understanding of the volcanic activity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Forecasting and planning for volcanic hazards, risks, and disasters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-818082-2.00003-2","usgsCitation":"Poland, M., and de Zeeuw-van Dalfsen, E., 2021, Volcano geodesy: A critical tool for assessing the state of volcanoes and their potential for hazardous eruptive activity, chap. 3 of Forecasting and planning for volcanic hazards, risks, and disasters, p. 75-115, https://doi.org/10.1016/B978-0-12-818082-2.00003-2.","productDescription":"41 p.","startPage":"75","endPage":"115","ipdsId":"IP-108637","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":397705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":838969,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219446,"text":"70219446 - 2021 - Harnessing landscape genomics to identify future climate resilient genotypes in a desert annual","interactions":[],"lastModifiedDate":"2021-04-07T11:43:48.856539","indexId":"70219446","displayToPublicDate":"2020-10-02T06:38:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2774,"text":"Molecular Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Harnessing landscape genomics to identify future climate resilient genotypes in a desert annual","docAbstract":"Local adaptation features critically in shaping species responses to changing environments, complicating efforts to revegetate degraded areas. Rapid climate change poses an additional challenge that could reduce fitness of even locally sourced seeds in restoration. Predictive restoration strategies that apply seeds with favourable adaptations to future climate may promote long‐term resilience. Landscape genomics is increasingly used to assess spatial patterns in local adaption and may represent a cost‐efficient approach for identifying future‐adapted genotypes. To demonstrate such an approach, we genotyped 760 plants from 64 Mojave Desert populations of the desert annual Plantago ovata. Genome scans on 5,960 SNPs identified 184 potentially adaptive loci related to climate and satellite vegetation metrics. Causal modelling indicated that variation in potentially adaptive loci was not confounded by isolation by distance or isolation by habitat resistance. A generalized dissimilarity model (GDM) attributed spatial turnover in potentially adaptive loci to temperature, precipitation and NDVI amplitude, a measure of vegetation green‐up potential. By integrating a species distribution model (SDM), we find evidence that summer maximum temperature may both constrain the range of P. ovata and drive adaptive divergence in populations exposed to higher temperatures. Within the species’ current range, warm‐adapted genotypes are predicted to experience a fivefold expansion in climate niche by midcentury and could harbour key adaptations to cope with future climate. We recommend eight seed transfer zones and project each zone into its relative position in future climate. Prioritizing seed collection efforts on genotypes with expanding future habitat represents a promising strategy for restoration practitioners to address rapidly changing climates.
","language":"English","publisher":"Wiley","doi":"10.1111/mec.15672","usgsCitation":"Shryock, D., Washburn, L.K., DeFalco, L., and Esque, T., 2021, Harnessing landscape genomics to identify future climate resilient genotypes in a desert annual: Molecular Ecology, v. 30, no. 3, p. 698-717, https://doi.org/10.1111/mec.15672.","productDescription":"20 p.","startPage":"698","endPage":"717","ipdsId":"IP-112517","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436657,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92XN5OW","text":"USGS data release","linkHelpText":"Genetic and Habitat Data for Plantago ovata in the Mojave Desert"},{"id":384894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.30126953125,\n 36.27970720524017\n ],\n [\n -116.90551757812499,\n 35.191766965947394\n ],\n [\n -116.46606445312499,\n 34.352506668675936\n ],\n [\n -114.9609375,\n 34.05265942137599\n ],\n [\n -114.345703125,\n 34.379712580462204\n ],\n [\n -113.543701171875,\n 35.505400093441324\n ],\n [\n -116.30126953125,\n 36.27970720524017\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Shryock, Daniel F. 0000-0003-0330-9815 dshryock@usgs.gov","orcid":"https://orcid.org/0000-0003-0330-9815","contributorId":208659,"corporation":false,"usgs":true,"family":"Shryock","given":"Daniel F.","email":"dshryock@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Washburn, Loraine K","contributorId":256960,"corporation":false,"usgs":false,"family":"Washburn","given":"Loraine","email":"","middleInitial":"K","affiliations":[{"id":51917,"text":"Rancho Santa Ana Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":813586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeFalco, Lesley A. 0000-0002-7542-9261","orcid":"https://orcid.org/0000-0002-7542-9261","contributorId":208658,"corporation":false,"usgs":true,"family":"DeFalco","given":"Lesley A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":813589,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220860,"text":"70220860 - 2021 - Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA)","interactions":[],"lastModifiedDate":"2021-05-27T11:59:40.427832","indexId":"70220860","displayToPublicDate":"2020-10-01T07:25:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA)","docAbstract":"Potential effects of projected climate variability on base flow and groundwater storage in the North Fork Red River aquifer, Oklahoma (USA), were estimated using downscaled climate model data coupled with a numerical groundwater-flow model. The North Fork Red River aquifer discharges groundwater to the North Fork Red River, which provides inflow to Lake Altus. To approximate future conditions, Coupled Model Intercomparison Project Phase 5 climate data were downscaled to the watershed and a time-series of scaling factors were developed and interpolated for three climate scenarios (central tendency, warmer and drier, and less warm and wetter) representing future climate conditions for the period 2045–2074. These scaling factors were then applied to a soil-water-balance model to produce groundwater recharge and evapotranspiration estimates. A MODFLOW groundwater-flow model of the North Fork Red River aquifer used the scaled recharge and evapotranspiration data to estimate changes in base flow and water-surface elevation of Lake Altus. Compared to a baseline scenario, the mean percent change in annual base flow during 2045–2074 was −10.8 and −15.9% for the central tendency and warmer/drier scenarios, respectively; the mean percent change in annual base flow for the less-warm/wetter scenario was +15.7%. The mean annual percent change in groundwater storage for the central tendency, warmer/drier, and less-warm/wetter climate scenarios and the baseline are −2.7, −3.2, and +3.0%, respectively. The range of outcomes from the climate scenarios may be influenced by variability in the downscaled climate data for precipitation more than for temperature.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-020-02230-x","usgsCitation":"Labriola, L., Ellis, J., Gangopadhyay, S., Pruitt, T., Kirstetter, P., and Hong, Y., 2021, Evaluating the effects of downscaled climate projections on groundwater storage and simulated base-flow contribution to the North Fork Red River and Lake Altus, southwest Oklahoma (USA): Hydrogeology Journal, v. 28, no. 8, p. 2903-2916, https://doi.org/10.1007/s10040-020-02230-x.","productDescription":"14 p.","startPage":"2903","endPage":"2916","ipdsId":"IP-111529","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":436658,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91DWW91","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used in simulations of selected climate scenarios of groundwater availability in the North Fork Red River aquifer, southwestern Oklahoma"},{"id":385978,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.00927734375,\n 33.706062655101206\n ],\n [\n -94.37255859375,\n 33.706062655101206\n ],\n [\n -94.37255859375,\n 35.47856499535729\n ],\n [\n -97.00927734375,\n 35.47856499535729\n ],\n [\n -97.00927734375,\n 33.706062655101206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-10-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Labriola, L.G. 0000-0002-5096-2940","orcid":"https://orcid.org/0000-0002-5096-2940","contributorId":216625,"corporation":false,"usgs":true,"family":"Labriola","given":"L.G.","email":"","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellis, J.H. 0000-0001-7161-3136 jellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7161-3136","contributorId":196287,"corporation":false,"usgs":true,"family":"Ellis","given":"J.H.","email":"jellis@usgs.gov","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":816475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pruitt, Tom","contributorId":257612,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":816476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirstetter, Pierre","contributorId":258774,"corporation":false,"usgs":false,"family":"Kirstetter","given":"Pierre","affiliations":[{"id":52282,"text":"School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, USA","active":true,"usgs":false}],"preferred":false,"id":816477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hong, Yang","contributorId":258775,"corporation":false,"usgs":false,"family":"Hong","given":"Yang","affiliations":[{"id":52282,"text":"School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73072, USA","active":true,"usgs":false}],"preferred":false,"id":816478,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217576,"text":"70217576 - 2021 - Direct and indirect effects of a keystone engineer on a shrubland-prairie food web","interactions":[],"lastModifiedDate":"2021-01-25T12:42:33.008","indexId":"70217576","displayToPublicDate":"2020-10-01T07:11:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Direct and indirect effects of a keystone engineer on a shrubland-prairie food web","docAbstract":"Keystone engineers are critical drivers of biodiversity throughout ecosystems worldwide. Within the North American Great Plains, the black‐tailed prairie dog is an imperiled ecosystem engineer and keystone species with well‐documented impacts on the flora and fauna of rangeland systems. However, because this species affects ecosystem structure and function in myriad ways (i.e., as a consumer, a prey resource, and a disturbance vector), it is unclear which effects are most impactful for any given prairie dog associate. We applied structural equation models (SEM) to disentangle direct and indirect effects of prairie dogs on multiple trophic levels (vegetation, arthropods, and birds) in the Thunder Basin National Grassland. Arthropods did not show any direct response to prairie dog occupation, but multiple bird species and vegetation parameters were directly affected. Surprisingly, the direct impact of prairie dogs on colony‐associated avifauna (Horned Lark [Eremophila alpestris] and Mountain Plover [Charadrius montanus]) had greater support than a mediated effect via vegetation structure, indicating that prairie dog disturbance may be greater than the sum of its parts in terms of impacts on localized vegetation structure. Overall, our models point to a combination of direct and indirect impacts of prairie dogs on associated vegetation, arthropods, and avifauna. The variation in these impacts highlights the importance of examining the various impacts of keystone engineers, as well as highlighting the diverse ways that black‐tailed prairie dogs are critical for the conservation of associated species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3195","usgsCitation":"Duchardt, C.J., Porensky, L.M., and Pearse, I.S., 2021, Direct and indirect effects of a keystone engineer on a shrubland-prairie food web: Ecology, v. 102, no. 1, e03195, 13 p., https://doi.org/10.1002/ecy.3195.","productDescription":"e03195, 13 p.","ipdsId":"IP-118463","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":436659,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GI27PX","text":"USGS data release","linkHelpText":"Data on prairie dogs, plants, arthropod biomass, and birds for Thunder Basin, Wyoming in 2017"},{"id":382485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Thunder Basin National Grassland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.787353515625,\n 43.07691312608711\n ],\n [\n -104.183349609375,\n 43.07691312608711\n ],\n [\n -104.183349609375,\n 44.166444664458595\n ],\n [\n -105.787353515625,\n 44.166444664458595\n ],\n [\n -105.787353515625,\n 43.07691312608711\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Duchardt, Courtney J. 0000-0003-4563-0199","orcid":"https://orcid.org/0000-0003-4563-0199","contributorId":239754,"corporation":false,"usgs":false,"family":"Duchardt","given":"Courtney","middleInitial":"J.","affiliations":[{"id":48000,"text":"U Wyoming","active":true,"usgs":false}],"preferred":false,"id":808721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Porensky, Lauren M. 0000-0001-6883-2442","orcid":"https://orcid.org/0000-0001-6883-2442","contributorId":239755,"corporation":false,"usgs":false,"family":"Porensky","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":808722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808723,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222937,"text":"70222937 - 2021 - Select techniques for detecting and quantifying seepage from unlined canals","interactions":[],"lastModifiedDate":"2021-08-10T15:51:00.827832","indexId":"70222937","displayToPublicDate":"2020-09-30T10:39:31","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"ST-2020-19144-01","title":"Select techniques for detecting and quantifying seepage from unlined canals","docAbstract":"Canal seepage losses affect the ability of water conveyance structures to maximize efficiency and can be a precursor to canal failure. Identification and quantification of canal seepage out of unlined canals is a complex interaction affected by geology, canal stage, operations, embankment geometry, siltation, animal burrows, structures, and other physical characteristics. Seepage out of unlined canals can be coarsely estimated using a mass balance-type approach (water in minus water out with the difference assumed to be a combination of seepage and evapotranspiration). More sophisticated methods are used in some instances but are typically limited efforts aimed at quantifying seepage in a specific location.
Seepage is generally broken out into two categories: diffuse and concentrated (or focused) seepage. Diffuse seepage is where the seepage discharges relatively constant over a given area, whereas concentrated (point discharge source) seepage discharges along preferentially focused areas. Diffuse seepage typically occurs in homogeneous conditions where the amount of water flowing into the subsurface is controlled by soil permeability and canal stage. Conversely, concentrated seepage occurs in areas of heterogeneous conditions where water flows into bedrock fractures, rodent burrows or other pre-existing discrete flow-paths. Concentrated seepage can also develop in the advent of sudden or excessive increases in hydraulic gradient which can lead to heaving, cracking, and development of backward erosion piping flow-paths. Concentrated and diffuse seepage can lead to seeps, in this case, a surface expression of water fed by irrigation water on canal embankment or at distal regions away from the canal.
This report focuses on work funded by the Research and Development Office from Fiscal Year 2016 through 2021 and the references provided pertain primarily to those efforts. This report also provides a generalized framework for how and when to investigate seepage out of an unlined canal based on the type of seepage, level of understanding about the seepage locations, geology, and knowledge of the subsurface conditions. The various methods used to locate seeps and quantify canal seepage are discussed in further detail, with references provided for the reader.
The following seepage investigation scenarios are discussed within the report:
1. Idealized workflow insensitive to time with highest quality data required
2. General workflow sensitive to time with highest quality data required
3. General workflow insensitive to time with lowest cost items preceding more costly techniques
4. Newly developed concentrated seep(s), concern about consequences (time sensitive)
5. Newly developed or rapidly increasing diffuse seepage, concern about consequences (time sensitive)
6. Existing concentrated seep(s), limited concern about consequences, poor geologic understanding
7. Existing concentrated seep(s), limited concern about consequences, good geologic understanding
8. Existing diffuse seepage, limited concern about consequences, poor geologic understanding
9. Existing diffuse seepage, limited concern about consequences, good geologic understanding
A workflow is given for each scenario which details recommended steps and the order in which those steps should be taken to maximize efficiency and data quality. The various seepage investigation techniques and estimated costs are discussed in more detail later in this report.
The next step is to take the data collected from the various methods and incorporate them into canal operations models to optimize deliveries. This step could also include the development of 3D seepage models to better understand the larger-scale groundwater-surface water interactions and how they are affected by the water delivery system.
","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Lindenbach, E.J., Kang, J.B., Rittgers, J.B., and Naranjo, R.C., 2021, Select techniques for detecting and quantifying seepage from unlined canals: Final Report ST-2020-19144-01, viii, 75 p.","productDescription":"viii, 75 p.","ipdsId":"IP-122681","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":387819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387793,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/research/projects/download_product.cfm?id=2955"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lindenbach, Evan J.","contributorId":263642,"corporation":false,"usgs":false,"family":"Lindenbach","given":"Evan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":820920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kang, Jong Beom","contributorId":263643,"corporation":false,"usgs":false,"family":"Kang","given":"Jong","email":"","middleInitial":"Beom","affiliations":[],"preferred":false,"id":820921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rittgers, Justin B.","contributorId":263644,"corporation":false,"usgs":false,"family":"Rittgers","given":"Justin","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":820922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220134,"text":"70220134 - 2021 - Moderate susceptibility to subcutaneous plague (Yersinia pestis) challenge in vaccine-treated and untreated Sonoran deer mice (Peromyscus maniculatus sonoriensis) and northern grasshopper mice (Onychomys leucogaster)","interactions":[],"lastModifiedDate":"2022-01-24T16:03:19.959223","indexId":"70220134","displayToPublicDate":"2020-09-29T06:54:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Moderate susceptibility to subcutaneous plague (Yersinia pestis) challenge in vaccine-treated and untreated Sonoran Deer Mice (Peromyscus maniculatus sonoriensis) and Northern Grasshopper Mice (Onychomys leucogaster)","title":"Moderate susceptibility to subcutaneous plague (Yersinia pestis) challenge in vaccine-treated and untreated Sonoran deer mice (Peromyscus maniculatus sonoriensis) and northern grasshopper mice (Onychomys leucogaster)","docAbstract":"The variable response of wild mice to Yersinia pestis infection, the causative agent of plague, has generated much speculation concerning their role in the ecology of this potentially lethal disease. Researchers have questioned the means by which Y. pestis is maintained in nature and also sought methods for managing the disease. Here we assessed the efficacy of a new tool, the sylvatic plague vaccine (SPV), in wild-caught northern grasshopper mice (Onychomys leucogaster) and commercially acquired Sonoran deer mice (Peromyscus maniculatus sonoriensis). More than 40% of the animals survived a subcutaneous Y. pestis challenge of 175,000 colony forming units (over 30,000 times the white mouse 50% lethal dose) in both vaccine-treated and control groups. Our results indicate that SPV distribution is unlikely to protect adult mice from plague infection in field settings and corroborate the heterogeneous response to Y. pestis infection in mice reported by others.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-20-00122","usgsCitation":"Bron, G., Smith, S., Williamson, J.L., Tripp, D.W., and Rocke, T.E., 2021, Moderate susceptibility to subcutaneous plague (Yersinia pestis) challenge in vaccine-treated and untreated Sonoran deer mice (Peromyscus maniculatus sonoriensis) and northern grasshopper mice (Onychomys leucogaster): Journal of Wildlife Diseases, v. 57, no. 3, p. 632-636, https://doi.org/10.7589/JWD-D-20-00122.","productDescription":"5 p.","startPage":"632","endPage":"636","ipdsId":"IP-122718","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":385242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bron, Gebbiena","contributorId":170006,"corporation":false,"usgs":false,"family":"Bron","given":"Gebbiena","affiliations":[{"id":25647,"text":"University of Wisconsin - Madison, School of Veterinary Medicine, Department of 4 Pathobiological Sciences","active":true,"usgs":false}],"preferred":false,"id":814557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Susan 0000-0001-6478-5028 susansmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6478-5028","contributorId":139497,"corporation":false,"usgs":true,"family":"Smith","given":"Susan","email":"susansmith@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":814558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Judy L. 0000-0001-7110-1632 jwilliamson@usgs.gov","orcid":"https://orcid.org/0000-0001-7110-1632","contributorId":3647,"corporation":false,"usgs":true,"family":"Williamson","given":"Judy","email":"jwilliamson@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tripp, Daniel W.","contributorId":17910,"corporation":false,"usgs":false,"family":"Tripp","given":"Daniel","email":"","middleInitial":"W.","affiliations":[{"id":13449,"text":"Colorado Division of Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":814559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":814560,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216786,"text":"70216786 - 2021 - Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling","interactions":[],"lastModifiedDate":"2020-12-07T15:10:38.473531","indexId":"70216786","displayToPublicDate":"2020-09-24T09:08:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling","docAbstract":"The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June–October dynamics of chlorophyll a, nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008–2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.
The mechanisms causing invasive species impact are rarely empirically tested, limiting our ability to understand and predict subsequent changes in invaded plant communities. Invader disruption of native mutualistic interactions is a mechanism expected to have negative effects on native plant species. Specifically, disruption of native plant‐fungal mutualisms may provide non‐mycorrhizal plant invaders an advantage over mycorrhizal native plants. Invasive Alliaria petiolata (garlic mustard) produces secondary chemicals toxic to soil microorganisms including mycorrhizal fungi, and is known to induce physiological stress and reduce population growth rates of native forest understory plant species. Here, we report on a 11‐yr manipulative field experiment in replicated forest plots testing if the effects of removal of garlic mustard on the plant community support the mutualism disruption hypothesis within the entire understory herbaceous community. We compare community responses for two functional groups: the mycorrhizal vs. the non‐mycorrhizal plant communities. Our results show that garlic mustard weeding alters the community composition, decreases community evenness, and increases the abundance of understory herbs that associate with mycorrhizal fungi. Conversely, garlic mustard has no significant effects on the non‐mycorrhizal plant community. Consistent with the mutualism disruption hypothesis, our results demonstrate that allelochemical producing invaders modify the plant community by disproportionately impacting mycorrhizal plant species. We also demonstrate the importance of incorporating causal mechanisms of biological invasion to elucidate patterns and predict community‐level responses.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3201","usgsCitation":"Roche, M., Pearse, I., Bialic-Murphy, L., Kivlin, S.N., Sofaer, H., and Kalisz, S., 2021, Negative effects of an allelopathic invader on AM fungal plant species drive community‐level responses: Ecology, v. 102, no. 1, e03201, 12 p., https://doi.org/10.1002/ecy.3201.","productDescription":"e03201, 12 p.","ipdsId":"IP-118543","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454423,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3201","text":"Publisher Index Page"},{"id":436663,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VP7BFU","text":"USGS data release","linkHelpText":"Data on the impacts of garlic mustard from a weeding experiment in Pennsylvania 2006-2016"},{"id":436662,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VP7BFU","text":"USGS data release","linkHelpText":"Data on the impacts of garlic mustard from a weeding experiment in Pennsylvania 2006-2016"},{"id":382484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Roche, Morgan 0000-0002-2276-3944","orcid":"https://orcid.org/0000-0002-2276-3944","contributorId":248273,"corporation":false,"usgs":false,"family":"Roche","given":"Morgan","affiliations":[{"id":49844,"text":"U Tennessee","active":true,"usgs":false}],"preferred":false,"id":808724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bialic-Murphy, Lalasia 0000-0001-6046-8316","orcid":"https://orcid.org/0000-0001-6046-8316","contributorId":248274,"corporation":false,"usgs":false,"family":"Bialic-Murphy","given":"Lalasia","email":"","affiliations":[{"id":49844,"text":"U Tennessee","active":true,"usgs":false}],"preferred":false,"id":808726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kivlin, Stephanie N 0000-0003-2442-7773","orcid":"https://orcid.org/0000-0003-2442-7773","contributorId":248275,"corporation":false,"usgs":false,"family":"Kivlin","given":"Stephanie","email":"","middleInitial":"N","affiliations":[{"id":49844,"text":"U Tennessee","active":true,"usgs":false}],"preferred":false,"id":808727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808728,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalisz, Susan 0000-0002-1761-5752","orcid":"https://orcid.org/0000-0002-1761-5752","contributorId":248276,"corporation":false,"usgs":false,"family":"Kalisz","given":"Susan","email":"","affiliations":[{"id":49844,"text":"U Tennessee","active":true,"usgs":false}],"preferred":false,"id":808729,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70223267,"text":"70223267 - 2021 - Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center","interactions":[],"lastModifiedDate":"2021-08-19T16:05:23.41401","indexId":"70223267","displayToPublicDate":"2020-09-23T11:01:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center","docAbstract":"Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations. Automatic seismic arrival detections made from standard picking methods (e.g., short‐term average/long‐term average [STA/LTA]) are fed to trained neural network models to improve automatic seismic‐arrival (pick) timing and estimate seismic‐arrival phase type and source‐station distances. These additional data are used to improve the capabilities of the NEIC associator. We compile a dataset of 1.3 million seismic‐phase arrivals that represent a globally distributed set of source‐station paths covering a range of phase types, magnitudes, and source distances. We train three separate convolutional neural network models to predict arrival time onset, phase type, and distance. We validate the performance of the trained networks on a subset of our existing dataset and further extend validation by exploring the model performance when applied to NEIC automatic pick data feeds. We show that the information provided by these models can be useful in downstream event processing, specifically in seismic‐phase association, resulting in reduced false associations and improved location estimates.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200178","usgsCitation":"Yeck, W.L., Patton, J., Ross, Z.E., Hayes, G., Guy, M.M., Ambruz, N., Shelly, D.R., Benz, H.M., and Earle, P.S., 2021, Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center: Seismological Research Letters, v. 92, no. 1, p. 4469-480, https://doi.org/10.1785/0220200178.","productDescription":"12 p.","startPage":"4469","endPage":"480","ipdsId":"IP-120508","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436665,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OHF4WL","text":"USGS data release","linkHelpText":"Waveform Data and Metadata used to National Earthquake Information Center Deep-Learning Models"},{"id":436664,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ICQPUR","text":"USGS data release","linkHelpText":"neic-machine-learning"},{"id":388157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":821548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patton, John 0000-0003-0142-5118","orcid":"https://orcid.org/0000-0003-0142-5118","contributorId":218681,"corporation":false,"usgs":true,"family":"Patton","given":"John","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821549,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Zachary E.","contributorId":196001,"corporation":false,"usgs":false,"family":"Ross","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":821550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821551,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guy, Michelle M. 0000-0003-3450-4656 mguy@usgs.gov","orcid":"https://orcid.org/0000-0003-3450-4656","contributorId":173432,"corporation":false,"usgs":true,"family":"Guy","given":"Michelle","email":"mguy@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821552,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ambruz, Nicholas 0000-0002-3660-3546","orcid":"https://orcid.org/0000-0002-3660-3546","contributorId":218684,"corporation":false,"usgs":true,"family":"Ambruz","given":"Nicholas","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821553,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":821554,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821555,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":821556,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70214567,"text":"70214567 - 2021 - Net-spinning caddisfly distribution in large regulated rivers","interactions":[],"lastModifiedDate":"2020-12-29T21:34:43.821143","indexId":"70214567","displayToPublicDate":"2020-09-20T09:11:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Net-spinning caddisfly distribution in large regulated rivers","docAbstract":"Lake Tahoe, a large freshwater lake of the eastern Sierra Nevada in California and Nevada, has 63 tributaries that are sources of nutrients and sediment to the lake. The Tahoe watershed is relatively small, and the surface area of the lake occupies about 38% of the watershed area (1313 km2). Only about 6% of the watershed is urbanized or residential land, and as part of a plan to maintain water clarity, wastewater is exported out of the basin. The lake's clarity has been diminishing due to algae and fine sediment, prompting development of management plans. Much of the annual discharge and nutrient load to the lake results from snowmelt in the spring and summer months. To understand the relative importance of land use, climate, forest management, and other factors affecting trends in nutrient stream concentrations and loads, a Weighted Regression on Time Discharge and Season (WRTDS) model simulated these trends over a time frame of >25 years (mid-1970s to 2017). All studied locations generally show nitrate concentration and load trending down. Ammonium concentration and load initially trended down then increased continuously after 2005. Some locations show initially decreasing orthophosphate trends, followed by small significant increases in concentration and loads starting around 2000 to 2005. Total Kjeldahl nitrogen, total phosphorus and suspended sediment mostly trended downward. Overall, the trends in various forms of nitrogen were observed at most sites irrespective of the degree of development and indicate a change in ecological conditions is affecting the nitrogen cycle throughout the watershed, most likely attributable to forest aggradation and fire suppression. Ratios of bioavailable nitrogen in the form of nitrate and ammonium to orthophosphate have also trended downward during the period of record suggesting a shift of these streams from phosphorus limited to nitrogen limited.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.141815","usgsCitation":"Domagalski, J.L., Morway, E.D., Alvarez, N.L., Hutchins, J., Rosen, M.R., and Coats, R., 2021, Trends in nitrogen, phosphorus, and sediment concentrations and loads in streams draining to Lake Tahoe, California, Nevada, USA: Science of the Total Environment (STOTEN), v. 752, 141815, 17 p., https://doi.org/10.1016/j.scitotenv.2020.141815.","productDescription":"141815, 17 p.","ipdsId":"IP-116547","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":436671,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98T2HNM","text":"USGS data release","linkHelpText":"Discharge, nutrient, and suspended sediment data for selected streams in the Lake Tahoe watershed"},{"id":436670,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98T2HNM","text":"USGS data release","linkHelpText":"Discharge, nutrient, and suspended sediment data for selected streams in the Lake Tahoe watershed"},{"id":378607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70214032/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.27282714843749,\n 38.807610542357594\n ],\n [\n -119.80865478515625,\n 38.807610542357594\n ],\n [\n -119.80865478515625,\n 39.31942523123949\n ],\n [\n -120.27282714843749,\n 39.31942523123949\n ],\n [\n -120.27282714843749,\n 38.807610542357594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"752","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, Nancy L. 0000-0001-8037-1001 nalvarez@usgs.gov","orcid":"https://orcid.org/0000-0001-8037-1001","contributorId":206530,"corporation":false,"usgs":true,"family":"Alvarez","given":"Nancy","email":"nalvarez@usgs.gov","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hutchins, Juliet 0000-0001-7385-4160","orcid":"https://orcid.org/0000-0001-7385-4160","contributorId":240999,"corporation":false,"usgs":false,"family":"Hutchins","given":"Juliet","email":"","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":799285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":799286,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coats, Robert 0000-0002-0402-032X","orcid":"https://orcid.org/0000-0002-0402-032X","contributorId":241000,"corporation":false,"usgs":false,"family":"Coats","given":"Robert","email":"","affiliations":[{"id":48187,"text":"Hydroikos Ltd","active":true,"usgs":false}],"preferred":false,"id":799287,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214978,"text":"70214978 - 2021 - Hydrocarbons to carboxyl-rich alicyclic molecules: A continuum model to describe biodegradation of petroleum-derived dissolved organic matter in contaminated groundwater plumes","interactions":[],"lastModifiedDate":"2020-10-05T12:45:51.418963","indexId":"70214978","displayToPublicDate":"2020-09-19T07:35:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2331,"text":"Journal of Hazardous Materials","active":true,"publicationSubtype":{"id":10}},"title":"Hydrocarbons to carboxyl-rich alicyclic molecules: A continuum model to describe biodegradation of petroleum-derived dissolved organic matter in contaminated groundwater plumes","docAbstract":"Relationships between dissolved organic matter (DOM) reactivity and chemical composition in a groundwater plume containing petroleum-derived DOM (DOMHC) were examined by quantitative and qualitative measurements to determine the source and chemical composition of the compounds that persist downgradient. Samples were collected from a transect down the core of the plume in the direction of groundwater flow. An exponential decrease in dissolved organic carbon concentration resulting from biodegradation along the transect correlated with a continuous shift in fluorescent DOMHC from shorter to longer wavelengths. Moreover, ultrahigh resolution mass spectrometry showed a shift from low molecular weight (MW) aliphatic, reduced compounds to high MW, unsaturated (alicyclic/aromatic), high oxygen compounds that are consistent with carboxyl-rich alicyclic molecules. The degree of condensed aromaticity increased downgradient, indicating that compounds with larger, conjugated aromatic core structures were less susceptible to biodegradation. Nuclear magnetic resonance spectroscopy showed a decrease in alkyl (particularly methyl) and an increase in aromatic/olefinic structural motifs. Collectively, data obtained from the combination of these complementary analytical techniques indicated that changes in the DOMHC composition of a groundwater plume are gradual, as relatively low molecular weight (MW), reduced, aliphatic compounds from the oil source were selectively degraded and high MW, alicyclic/aromatic, oxidized compounds persisted.
Environmental DNA (eDNA) has emerged as a potentially powerful tool for use in conservation and resource management, including for tracking the recolonization dynamics of fish populations. We used eDNA to assess the effectiveness of dam removal to restore fish passage on the Elwha River in Washington State (USA). Using a suite of 11 species‐specific eDNA polymerase chain reaction (PCR) assays, we showed that most targeted anadromous species (five Pacific Salmon species and Pacific Lamprey) were able to pass upstream of both former dam sites. Multiscale occupancy modeling showed that the timing and spatial extent of recolonization differed among species during the four years of post‐dam removal monitoring. More abundant species like Chinook Salmon and Coho Salmon migrated farther into the upper portions of the watershed than less abundant species like Pink Salmon and Chum Salmon. Sampling also allowed assessment of potamodromous fish species. Bull Trout and Rainbow Trout, ubiquitous species in the watershed, were detected at all sampling locations. Environmental DNA from Brook Trout, a non‐native species isolated between the dams prior to dam removal, was detected downstream of Elwha dam but rarely upstream of the Glines Canyon Dam suggested that the species has not expanded its range appreciably in the watershed following dam removal. We found that eDNA was an effective tool to assess the response of fish populations to large‐scale dam removal on the Elwha River.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.134","usgsCitation":"Duda, J.J., Hoy, M.S., Chase, D.M., Pess, G.R., Brenkman, S.J., McHenry, M.M., and Ostberg, C.O., 2021, Environmental DNA is an effective tool to track recolonizing migratory fish following large‐scale dam removal: Environmental DNA, v. 3, no. 1, p. 121-141, https://doi.org/10.1002/edn3.134.","productDescription":"21 p.","startPage":"121","endPage":"141","ipdsId":"IP-117988","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":454438,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.134","text":"Publisher Index Page"},{"id":436672,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96R5Q0M","text":"USGS data release","linkHelpText":"Environmental DNA (eDNA) is an Effective Tool to Track Recolonizing Migratory Fish Following Large-Scale Dam Removal, field data"},{"id":382487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":808709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoy, Marshal S. 0000-0003-2828-9697","orcid":"https://orcid.org/0000-0003-2828-9697","contributorId":220730,"corporation":false,"usgs":true,"family":"Hoy","given":"Marshal","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":808710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chase, Dorothy M. 0000-0002-7759-2687","orcid":"https://orcid.org/0000-0002-7759-2687","contributorId":203926,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy","email":"","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":808711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":808712,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brenkman, Samuel J.","contributorId":138941,"corporation":false,"usgs":false,"family":"Brenkman","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":12587,"text":"Olympic National Park, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":808713,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McHenry, Michael M","contributorId":239726,"corporation":false,"usgs":false,"family":"McHenry","given":"Michael","email":"","middleInitial":"M","affiliations":[{"id":16823,"text":"Lower Elwha Klallam Tribe, Port Angeles, Washington","active":true,"usgs":false}],"preferred":false,"id":808714,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ostberg, Carl O. 0000-0003-1479-8458","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":220731,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":808715,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70215617,"text":"70215617 - 2021 - Genetic diversity, population structure, and historical demography of a highly vagile and human‐impacted seabird in the Pacific Ocean: The red‐tailed tropicbird, Phaethon rubricauda","interactions":[],"lastModifiedDate":"2021-03-05T21:04:27.61783","indexId":"70215617","displayToPublicDate":"2020-09-16T09:04:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Genetic diversity, population structure, and historical demography of a highly vagile and human‐impacted seabird in the Pacific Ocean: The red‐tailed tropicbird, Phaethon rubricauda","title":"Genetic diversity, population structure, and historical demography of a highly vagile and human‐impacted seabird in the Pacific Ocean: The red‐tailed tropicbird, Phaethon rubricauda","docAbstract":"This review evaluates the importance of plants and associated biological processes in determining the vulnerability of coastal wetlands to sea-level rise. Coastal wetlands occur across a broad sedimentary continuum from minerogenic to biogenic, providing an opportunity to examine the relative importance of biological processes in wetland resilience to sea-level rise. We explore how plants influence sediment accretion, elevation capital (vertical position in the tidal frame), and compaction or erosion of deposited material. We focus on salt marsh and mangrove wetlands, which occupy a similar physiographic niche and display similar physical and biological controls on resilience to sea-level rise. In both habitats, plants stabilize emergent mudflats and help sustain the wetland position in the tidal frame relative to ocean height through both surface and subsurface process controls on soil elevation. Plants influence soil elevations by modifying (1) mineral sediment deposition and retention, (2) organic matter contributions to soil volume, and (3) resistance to compaction and erosion. Recognition of the importance of plants in coastal wetland resilience to sea-level rise is key to accurate predictions about the future fate of salt marshes and mangrove forests and for development of effective management and restoration plans.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-020-00834-w","usgsCitation":"Cahoon, D.R., McKee, K.L., and James Morris, 2021, How plants influence resilience of salt marsh and mangrove wetlands to sea-level rise: Estuaries and Coasts, v. 44, p. 883-898, https://doi.org/10.1007/s12237-020-00834-w.","productDescription":"16 p.","startPage":"883","endPage":"898","ipdsId":"IP-118213","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":378521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","noUsgsAuthors":false,"publicationDate":"2020-09-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":798960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKee, Karen L. 0000-0001-7042-670X mckeek@usgs.gov","orcid":"https://orcid.org/0000-0001-7042-670X","contributorId":704,"corporation":false,"usgs":true,"family":"McKee","given":"Karen","email":"mckeek@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":798961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James Morris","contributorId":240798,"corporation":false,"usgs":false,"family":"James Morris","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":798962,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218228,"text":"70218228 - 2021 - Latitudinal patterns of alien plant invasions","interactions":[],"lastModifiedDate":"2021-02-19T18:17:36.387653","indexId":"70218228","displayToPublicDate":"2020-09-10T12:16:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Latitudinal patterns of alien plant invasions","docAbstract":"Latitudinal patterns of biodiversity have long been a central topic in ecology and evolutionary biology. However, while most previous studies have focused on native species, little effort has been devoted to latitudinal patterns of plant invasions (with a few exceptions based on data from sparse locations). Using the most up‐to‐date worldwide native and alien plant distribution data from 801 regions (including islands), we compared invasion levels (i.e. alien richness/total richness) in the Northern and Southern Hemispheres and across continental regions and islands around the globe. Results from quantile regressions using B‐splines to model nonlinearity showed (1) declining richness with increasing latitude, although the highest alien richness occurs at around 40 degrees in both hemispheres, (2) decreasing invasion levels towards higher latitudes on islands but a unimodal pattern in invasion level in continental regions in each hemisphere, (3) significantly higher invasion levels on islands than in continental regions and (4) a greater variability in invasion levels on islands at low latitudes than on high‐latitude islands. In continental regions, only the mid‐latitudes had high variability with both low and high invasion levels. Our findings identified latitudes with invasion hotspots where management is urgently needed, and latitudes with many areas of low invasions but high conservation potential where prevention of future invasions should be the priority.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.13943","usgsCitation":"Guo, Q., Cade, B.S., Dawson, W., Essl, F., Kreft, H., Pergl, J., van Kleunen, M., Weigelt, P., Winter, M., and Pyšek, P., 2021, Latitudinal patterns of alien plant invasions: Journal of Biogeography, v. 48, no. 2, p. 253-262, https://doi.org/10.1111/jbi.13943.","productDescription":"10 p.","startPage":"253","endPage":"262","ipdsId":"IP-119112","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":454448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.13943","text":"Publisher Index Page"},{"id":383380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Guo, Qinfeng","contributorId":214263,"corporation":false,"usgs":false,"family":"Guo","given":"Qinfeng","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":810509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":810510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dawson, Wayne","contributorId":193105,"corporation":false,"usgs":false,"family":"Dawson","given":"Wayne","email":"","affiliations":[],"preferred":false,"id":810511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Essl, Franz","contributorId":167872,"corporation":false,"usgs":false,"family":"Essl","given":"Franz","email":"","affiliations":[{"id":24846,"text":"Division of Conservation Biology, Vegetation and Landscape Ecology, University of Vienna","active":true,"usgs":false}],"preferred":false,"id":810512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kreft, Holger","contributorId":193108,"corporation":false,"usgs":false,"family":"Kreft","given":"Holger","email":"","affiliations":[],"preferred":false,"id":810513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pergl, Jan","contributorId":193109,"corporation":false,"usgs":false,"family":"Pergl","given":"Jan","email":"","affiliations":[],"preferred":false,"id":810514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van Kleunen, Mark","contributorId":193107,"corporation":false,"usgs":false,"family":"van Kleunen","given":"Mark","email":"","affiliations":[],"preferred":false,"id":810515,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weigelt, Patrick","contributorId":193111,"corporation":false,"usgs":false,"family":"Weigelt","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":810516,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Winter, Marten","contributorId":178720,"corporation":false,"usgs":false,"family":"Winter","given":"Marten","email":"","affiliations":[],"preferred":false,"id":810517,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pyšek, Petr","contributorId":251754,"corporation":false,"usgs":false,"family":"Pyšek","given":"Petr","affiliations":[{"id":17790,"text":"Czech Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":810518,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70219208,"text":"70219208 - 2021 - Assessing the ecological risks of per‐ and polyfluoroalkyl substances: Current state‐of‐the science and a proposed path forward","interactions":[],"lastModifiedDate":"2021-04-01T11:26:50.678979","indexId":"70219208","displayToPublicDate":"2020-09-08T06:56:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the ecological risks of per‐ and polyfluoroalkyl substances: Current state‐of‐the science and a proposed path forward","docAbstract":"Per‐ and poly‐fluoroalkyl substances (PFAS) encompass a large, heterogenous group of chemicals of potential concern to human health and the environment. Based on information for a few relatively well‐understood PFAS such as perfluorooctane sulfonate and perfluorooctanoate, there is ample basis to suspect that at least a subset can be considered persistent, bioaccumulative, and/or toxic. However, data suitable for determining risks in either prospective or retrospective assessments are lacking for the majority of PFAS. In August 2019, the Society of Environmental Toxicology and Chemistry sponsored a workshop that focused on the state‐of‐the‐science supporting risk assessment of PFAS. The present review summarizes discussions concerning the ecotoxicology and ecological risks of PFAS. First, we summarize currently available information relevant to problem formulation/prioritization, exposure, and hazard/effects of PFAS in the context of regulatory and ecological risk assessment activities from around the world. We then describe critical gaps and uncertainties relative to ecological risk assessments for PFAS and propose approaches to address these needs. Recommendations include the development of more comprehensive monitoring programs to support exposure assessment, an emphasis on research to support the formulation of predictive models for bioaccumulation, and the development of in silico, in vitro, and in vivo methods to efficiently assess biological effects for potentially sensitive species/endpoints. Addressing needs associated with assessing the ecological risk of PFAS will require cross‐disciplinary approaches that employ both conventional and new methods in an integrated, resource‐effective manner.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4869","usgsCitation":"Ankley, G., Cureton, P., Hoke, R.A., Houde, M., Kumar, A., Kurias, J., Lanno, R.P., McCarthy, C., Newsted, J.L., Salice, C.J., Sample, B.E., Sepúlveda, M., Steevens, J.A., and Valsecchi, S., 2021, Assessing the ecological risks of per‐ and polyfluoroalkyl substances: Current state‐of‐the science and a proposed path forward: Environmental Toxicology and Chemistry, v. 40, no. 3, p. 564-605, https://doi.org/10.1002/etc.4869.","productDescription":"42 p.","startPage":"564","endPage":"605","ipdsId":"IP-119653","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":454450,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.4869","text":"Publisher Index 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