Ecological understanding of host–pathogen dynamics is the basis for managing wildlife diseases. Since 2008, federal, state, and provincial agencies and tribal and private organizations have collaborated on bat and white‐nose syndrome (WNS) surveillance and monitoring, research, and management programs. Accordingly, scientists and managers have learned a lot about the hosts, pathogen, and dynamics of WNS. However, effective mitigation measures to combat WNS remain elusive. Host–pathogen systems are complex, and identifying ecological research priorities to improve management, choosing among various actions, and deciding when to implement those actions can be challenging. Through a cross‐disciplinary approach, a group of diverse subject matter experts created an influence diagram used to identify uncertainties and prioritize research needs for WNS management. Critical knowledge gaps were identified, particularly with respect to how WNS dynamics and impacts may differ among bat species. We highlight critical uncertainties and identify targets for WNS research. This tool can be used to maximize the likelihood of achieving bat conservation goals within the context and limitations of specific real‐world scenarios.
The El Tatio geothermal field in the Chilean Altiplano contains hydrothermal silica sinter deposits overlaying glacial and volcanic units, providing an opportunity to constrain the timing of deglaciation and volcanic activity in an area with sparse absolute chronologies. We obtained 51 new radiocarbon ages and δ13C values on the organic material trapped in these sinter deposits. Based on the δ13C values, we exclude 29 samples for possible contamination with bacterial mats that incorporate old carbon. We infer that hydrothermal activity initiated ~27 ka ago and has been nearly continuous ever since. The ages of the oldest sinter deposits coincide with ages of moraines that stabilized after the most recent deglaciation. Whereas late Pleistocene sinters are broadly distributed in the field, Holocene deposits are found around active hydrothermal features. Although recent volcanism is absent in the vicinity of El Tatio, persistent hydrothermal discharge implies a long‐lived magmatic heat source.
","language":"English","publisher":"America Geophysical Union","doi":"10.1029/2020GL087908","usgsCitation":"Munoz Saez, C., Manga, M., Hurwitz, S., Salgter, S., Churchill, D., Reich, M., Damby, D., and Morata, D., 2020, Radiocarbon dating of silica sinter and postglacial hydrothermal activity in the El Tatio geyser field: Geophysical Research Letters, v. 47, no. 11, e2020GL087908, 10 p., https://doi.org/10.1029/2020GL087908.","productDescription":"e2020GL087908, 10 p.","ipdsId":"IP-107089","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":456577,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020gl087908","text":"Publisher Index Page"},{"id":375776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile","otherGeospatial":"El Tatio Geothermal Field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.40087890624999,\n -22.938159639316396\n ],\n [\n -67.87353515625,\n -22.938159639316396\n ],\n [\n -67.87353515625,\n -22.271305748177625\n ],\n [\n -68.40087890624999,\n -22.271305748177625\n ],\n [\n -68.40087890624999,\n -22.938159639316396\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Munoz Saez, Carolina","contributorId":225418,"corporation":false,"usgs":false,"family":"Munoz Saez","given":"Carolina","email":"","affiliations":[{"id":37346,"text":"Universidad de Chile","active":true,"usgs":false}],"preferred":false,"id":791124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manga, Michael","contributorId":199572,"corporation":false,"usgs":false,"family":"Manga","given":"Michael","affiliations":[],"preferred":false,"id":791125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":791126,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salgter, Silvina","contributorId":225419,"corporation":false,"usgs":false,"family":"Salgter","given":"Silvina","email":"","affiliations":[{"id":37346,"text":"Universidad de Chile","active":true,"usgs":false}],"preferred":false,"id":791127,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Churchill, Dakota","contributorId":225420,"corporation":false,"usgs":false,"family":"Churchill","given":"Dakota","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":791128,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reich, Martin","contributorId":225421,"corporation":false,"usgs":false,"family":"Reich","given":"Martin","email":"","affiliations":[{"id":37346,"text":"Universidad de Chile","active":true,"usgs":false}],"preferred":false,"id":791129,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":791130,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morata, Diego","contributorId":225422,"corporation":false,"usgs":false,"family":"Morata","given":"Diego","email":"","affiliations":[{"id":37346,"text":"Universidad de Chile","active":true,"usgs":false}],"preferred":false,"id":791131,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210374,"text":"70210374 - 2020 - Erratum: Seismic survey design and effects on maternal polar bear dens","interactions":[],"lastModifiedDate":"2020-06-04T17:17:46.04055","indexId":"70210374","displayToPublicDate":"2020-05-30T08:59:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Erratum: Seismic survey design and effects on maternal polar bear dens","docAbstract":"Since the publication of this manuscript, readers have noted two errors in our analysis. The first is that we inadvertently stated that the forward looking infrared (FLIR) survey simulations only represented a single FLIR survey. In reality, the analysis assumed two independent FLIR surveys occurred prior to simulated seismic activity occurring. To evaluate the results for a single FLIR survey, readers can simply modify line 41 of the R code ‘jwmg21800-sup-0006-missed.dens.funcAnalysis.R’ to read ‘p2=0’ and re-run the analysis. The second error relates to our calculation of the expected number of dens in the 1002 Area.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21889","usgsCitation":"Wilson, R.H., and Durner, G.M., 2020, Erratum: Seismic survey design and effects on maternal polar bear dens: Journal of Wildlife Management, v. 84, no. 5, p. 1022-1024, https://doi.org/10.1002/jwmg.21889.","productDescription":"3 p.","startPage":"1022","endPage":"1024","ipdsId":"IP-118660","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":456580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21889","text":"Publisher Index Page"},{"id":375245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":790091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":790092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210388,"text":"70210388 - 2020 - Quantifying uncertainty for remote spectroscopy of surface composition","interactions":[],"lastModifiedDate":"2020-06-02T13:35:00.39489","indexId":"70210388","displayToPublicDate":"2020-05-30T08:15:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying uncertainty for remote spectroscopy of surface composition","docAbstract":"Remote surface measurements by imaging spectrometers play an important role in planetary and Earth science.\nTo make these measurements, investigators calibrate instrument data to absolute units, invert physical models to\nestimate atmospheric effects, and then determine surface properties from the spectral reflectance. This study\nquantifies the uncertainty in this process. Global missions demand predictive uncertainty models that can estimate\nfuture errors for varied environments and observing conditions. Here we validate uncertainty predictions\nwith remote surface composition retrievals and in situ measurements in a field analogue of Earth and planetary\nexploration. We consider rover transects at Cuprite, Nevada, and remote observations by NASA's Next-\nGeneration Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). We show that accounting for input\nuncertainties can benefit mineral detection methods such as constrained spectrum fitting. This suggests that\noperational uncertainty estimates could improve future NASA missions like the Earth Mineral dust source\nInvesTigation (EMIT) and the Lunar Trailblazer mission, as well as NASA's Decadal Surface Biology and Geology (SBG) Investigation.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.111898","usgsCitation":"Thompson, D.R., Braverman, A., Brodrick, P., Candela, A., Carmon, N., Clark, R., Connelly, D., Green, R., Kokaly, R.F., Li, L., Mahowald, N., Miller, R.L., Okin, G.S., Painter, T., Swayze, G.A., Turmon, M., Susilouto, J., and Wettergreen, D., 2020, Quantifying uncertainty for remote spectroscopy of surface composition: Remote Sensing of Environment, v. 247, 111898, 18 p., https://doi.org/10.1016/j.rse.2020.111898.","productDescription":"111898, 18 p.","ipdsId":"IP-115408","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":456584,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.111898","text":"Publisher Index Page"},{"id":375243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"247","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, David R. 0000-0003-0635-5876","orcid":"https://orcid.org/0000-0003-0635-5876","contributorId":225042,"corporation":false,"usgs":false,"family":"Thompson","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Braverman, Amy","contributorId":225043,"corporation":false,"usgs":false,"family":"Braverman","given":"Amy","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodrick, Philip","contributorId":225044,"corporation":false,"usgs":false,"family":"Brodrick","given":"Philip","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Candela, Alberto","contributorId":225045,"corporation":false,"usgs":false,"family":"Candela","given":"Alberto","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":790122,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carmon, Nimrod","contributorId":225046,"corporation":false,"usgs":false,"family":"Carmon","given":"Nimrod","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790123,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clark, Roger N.","contributorId":225047,"corporation":false,"usgs":false,"family":"Clark","given":"Roger N.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":790124,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Connelly, David","contributorId":225048,"corporation":false,"usgs":false,"family":"Connelly","given":"David","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":790125,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Green, Robert O.","contributorId":225049,"corporation":false,"usgs":false,"family":"Green","given":"Robert O.","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790126,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":790127,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Li, Longlei","contributorId":225050,"corporation":false,"usgs":false,"family":"Li","given":"Longlei","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":790128,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mahowald, Natalie","contributorId":225051,"corporation":false,"usgs":false,"family":"Mahowald","given":"Natalie","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":790129,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Ronald L.","contributorId":225052,"corporation":false,"usgs":false,"family":"Miller","given":"Ronald","email":"","middleInitial":"L.","affiliations":[{"id":41028,"text":"NASA GISS and Columbia University","active":true,"usgs":false}],"preferred":false,"id":790130,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Okin, Gregory S.","contributorId":225053,"corporation":false,"usgs":false,"family":"Okin","given":"Gregory","email":"","middleInitial":"S.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":790131,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Painter, Thomas H.","contributorId":225054,"corporation":false,"usgs":false,"family":"Painter","given":"Thomas H.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":790132,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":790133,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Turmon, Michael","contributorId":225055,"corporation":false,"usgs":false,"family":"Turmon","given":"Michael","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790134,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Susilouto, Jouni","contributorId":225056,"corporation":false,"usgs":false,"family":"Susilouto","given":"Jouni","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":790135,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wettergreen, David","contributorId":225057,"corporation":false,"usgs":false,"family":"Wettergreen","given":"David","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":790136,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70210695,"text":"70210695 - 2020 - Assessment of restorative maintenance practices on the infiltration capacity of permeable pavement","interactions":[],"lastModifiedDate":"2020-06-17T13:18:52.619516","indexId":"70210695","displayToPublicDate":"2020-05-30T08:12:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of restorative maintenance practices on the infiltration capacity of permeable pavement","docAbstract":"Permeable pavement has the potential to be an effective tool in managing stormwater runoff through retention of sediment and other contaminants associated with urban development. The infiltration capacity of permeable pavement declines as more sediment is captured, thereby reducing its ability to treat runoff. Regular restorative maintenance practices can alleviate this issue and prolong the useful life and benefits of the system. Maintenance practices used to restore the infiltration capacity of permeable pavement were evaluated on three surfaces: Permeable interlocking concrete pavers (PICP), pervious concrete (PC), and porous asphalt (PA). Each of the three test plots received a similar volume of runoff and sediment load from an adjacent, impervious asphalt parking lot. Six different maintenance practices were evaluated over a four-year period: Hand-held pressure washer and vacuum, leaf blower and push broom, vacuum-assisted street cleaner, manual disturbance of PICP aggregate, pressure washing and vacuuming, and compressed air and vacuuming. Of the six practices tested, five were completed on PICP, four on PC, and two on PA. Nearly all forms of maintenance resulted in increased average surface infiltration rates. Increases ranged from 94% to 1703% for PICP, 5% to 169% for PC, and 16% to 40% for PA. Disruption of the aggregate between the joints of PICP, whether by simple hand tools or sophisticated machinery, resulted in significant (p ≤ 0.05) gains in infiltration capacity. Sediment penetrated into the solid matrix of the PC and PA, making maintenance practices using a high-pressure wash followed by high-suction vacuum the most effective for these permeable pavement types. In all instances, when the same maintenance practice was done on multiple surfaces, PICP showed the greatest recovery in infiltration capacity.","language":"English","publisher":"MDPI","doi":"10.3390/w12061563","usgsCitation":"Danz, M., Selbig, W.R., and Buer, N., 2020, Assessment of restorative maintenance practices on the infiltration capacity of permeable pavement: Water, v. 12, no. 6, 1563, 17 p., https://doi.org/10.3390/w12061563.","productDescription":"1563, 17 p.","ipdsId":"IP-118229","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":456586,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12061563","text":"Publisher Index Page"},{"id":375660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane County","city":"Madison","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.51248168945312,\n 43.023725588820255\n ],\n [\n -89.30374145507812,\n 43.023725588820255\n ],\n [\n -89.30374145507812,\n 43.159112387154174\n ],\n [\n -89.51248168945312,\n 43.159112387154174\n ],\n [\n -89.51248168945312,\n 43.023725588820255\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Danz, Mari 0000-0002-4716-0170 medanz@usgs.gov","orcid":"https://orcid.org/0000-0002-4716-0170","contributorId":219227,"corporation":false,"usgs":true,"family":"Danz","given":"Mari","email":"medanz@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":790999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buer, Nicolas 0000-0002-4369-8715","orcid":"https://orcid.org/0000-0002-4369-8715","contributorId":204808,"corporation":false,"usgs":true,"family":"Buer","given":"Nicolas","email":"","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791001,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211588,"text":"70211588 - 2020 - Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space","interactions":[],"lastModifiedDate":"2023-08-31T17:33:18.95725","indexId":"70211588","displayToPublicDate":"2020-05-30T08:03:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space","docAbstract":"Within the Big Bend region of the northeastern Gulf of Mexico, one of the least developed coastlines in the continental USA, intertidal and subtidal populations of eastern oyster Crassostrea virginica (hereafter referred to as “oyster”) are a critical ecosystem and important economic constituent. We assessed trends in intertidal oyster populations, river discharge, and commercial fishing activity in the Suwannee River estuary within the Big Bend region using fisheries‐independent data from irregular monitoring efforts and publicly available environmental data. We used generalized linear models to evaluate counts of oysters from line‐transect surveys over time and space. We assessed model performance using simulation to understand potential bias and then evaluated whether these counts were related to freshwater inputs from the Suwannee River and commercial oyster fishing effort and landings at different time lags. We found that intertidal oyster counts have declined over time and that most of these declines are found in inshore intertidal oyster bars, which are becoming degraded. We also found a significant relationship between oyster counts and a 1‐year lag on mean daily Suwannee River discharge, but including commercial fishery trips or landings did not improve model fit. It is unclear whether declines in intertidal oyster bars are offset by formation of new oyster reefs elsewhere. These results quantify rapid declines in intertidal oyster reefs in a region of coastline with high conservation value that can be used to inform ongoing and proposed restoration projects in the region.","language":"English","publisher":"Wiley","doi":"10.1002/mcf2.10117","usgsCitation":"Moore, J.F., Pine, W.E., Frederick, P., Becker, S., Moreno, M., Dodrill, M., Boone, M., Sturmer, L., and Yurek, S., 2020, Trends in oyster populations in the northeastern Gulf of Mexico: An assessment of river discharge and fishing effects over time and space: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 12, no. 3, p. 191-204, https://doi.org/10.1002/mcf2.10117.","productDescription":"14 p.","startPage":"191","endPage":"204","ipdsId":"IP-114295","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456589,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10117","text":"Publisher Index Page"},{"id":377005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.51943969726561,\n 28.9913248161703\n ],\n [\n -82.67898559570311,\n 28.9913248161703\n ],\n [\n -82.67898559570311,\n 29.684473609006847\n ],\n [\n -83.51943969726561,\n 29.684473609006847\n ],\n [\n -83.51943969726561,\n 28.9913248161703\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-05-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, J. F","contributorId":236929,"corporation":false,"usgs":false,"family":"Moore","given":"J.","email":"","middleInitial":"F","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pine, W. E","contributorId":236930,"corporation":false,"usgs":false,"family":"Pine","given":"W.","email":"","middleInitial":"E","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frederick, P. C","contributorId":236931,"corporation":false,"usgs":false,"family":"Frederick","given":"P. C","affiliations":[{"id":47565,"text":"Department of Wildlife Ecology and Conservation, 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611","active":true,"usgs":false}],"preferred":false,"id":794729,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becker, Sarah","contributorId":210890,"corporation":false,"usgs":false,"family":"Becker","given":"Sarah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794730,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moreno, Marcos","contributorId":195527,"corporation":false,"usgs":false,"family":"Moreno","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":794731,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dodrill, Michael J. 0000-0002-7038-7170","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":206439,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794732,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boone, Matthew","contributorId":202724,"corporation":false,"usgs":false,"family":"Boone","given":"Matthew","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":794733,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sturmer, L","contributorId":236932,"corporation":false,"usgs":false,"family":"Sturmer","given":"L","email":"","affiliations":[{"id":47566,"text":"University of Florida Extension, Senatore George Kirkpatrick Marine Lab, 11350 SW 153rd Court, Cedar Key, FL 32625","active":true,"usgs":false}],"preferred":false,"id":794734,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216733,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":794735,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217880,"text":"70217880 - 2020 - Progress toward a preliminary karst depression density map for the conterminous United States","interactions":[],"lastModifiedDate":"2021-04-19T15:28:09.384114","indexId":"70217880","displayToPublicDate":"2020-05-30T07:44:24","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Progress toward a preliminary karst depression density map for the conterminous United States","docAbstract":"Most methods for the assessment of sinkhole hazard susceptibility are predicated upon knowledge of pre-existing closed depressions in karst areas. In the United States (U.S.), inventories of existing karst depressions are piecemeal, and are often obtained through inconsistent methodologies applied at the state or county level and at various scales. Here, we present a first attempt at defining a karst closed depression inventory across the conterminous U.S. using a common methodology. Automated algorithms for extraction of closed depressions from 1/3 arc-second (approximately 10 m resolution) National Elevation Dataset (NED) were run on the U.S. Geological Survey (USGS) “Yeti” high-performance computing cluster. The full NED was first conditioned to reduce the creation of artificial closed depressions by breaching digital dams at road and stream crossings, using the flowlines and transportation route vectors from the USGS National Map. The resulting depressions were selected according to location within geologic units having the potential for karst, and screened for occurrence in areas of developed land, open water and wetlands, and areas of glacial and alluvial sediment cover. The results were used as the input to create a nationwide depression density map. Our results were compared with karst depression density maps for diverse karst regions within states that have existing closed depression inventories. The individual state-scale maps compared favorably to the results obtained from the method applied universally across the nation and illustrated regional sinkhole hotspots in known areas of well-developed karst. Limitations of the automated method includes false positive depressions resulting from artifacts generated during the computer processing of the elevation models, and inclusion of depressions resulting from non-karst geomorphic processes. More thorough examination of the screening criteria for depressions is required.
Predicting the success of future investments in coastal and estuarine ecosystem restorations is limited by scarce data quantifying sediment budgets and transport processes of prior restorations. This study provides detailed analyses of the hydrodynamics and sediment fluxes of a recently restored U.S. Pacific Northwest estuary, a 61 ha former agricultural area near the mouth of the Stillaguamish River in Washington, USA. Water level, flow velocity, and suspended-sediment concentration (SSC) were measured between 21 March 2014 and 1 June 2015 at breaches excavated in the former flood-protection levee to determine transport patterns and the net sediment budget of the restoration area. SSC within the restoration area was primarily controlled by SSC variability of the nearby main stem Stillaguamish, but coastal processes also played a major role in sediment delivery. Fluvial sediment loading was dominated by runoff events associated with rainfall that lasted hours to a few days. Additionally, the 22 March 2014 SR 530 (Oso) landslide elevated sediment supply to the restoration area and coastal region for several weeks, indicating the importance of distal geomorphic events to coastal sediment budgets in small mountainous river systems. Sediment fluxes were controlled by river SSC and tidal dynamics, which set the quantity of water transported into the restoration area. Peak water discharge at the restoration area was about 12% of the river discharge, and peak sediment flux at the restoration area was about 5% of the river sediment discharge, although net sediment import was <1% of the total river load. Although sediment was imported to the restoration area, and inferred rates of accretion appear sufficient to keep pace with present rates of local sea-level rise, full recovery is challenged by significant lost grade from historical subsidence and will likely take decades to centuries. These results have implications for estuary restoration planning globally and indicate the importance of understanding coupled fluvial–coastal processes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2020.106869","usgsCitation":"Nowacki, D.J., and Grossman, E.E., 2020, Sediment transport in a restored, river-influenced Pacific Northwest estuary: Estuarine, Coastal and Shelf Science, v. 242, 106869, 10 p., https://doi.org/10.1016/j.ecss.2020.106869.","productDescription":"106869, 10 p.","ipdsId":"IP-117166","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":456594,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2020.106869","text":"Publisher Index Page"},{"id":436953,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RK8H7X","text":"USGS data release","linkHelpText":"Oceanographic measurements collected in the Stillaguamish River Delta, Port Susan, Washington, USA from March 2014 to July 2015"},{"id":375454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.86148071289061,\n 47.814076743593624\n ],\n [\n -122.16110229492186,\n 47.814076743593624\n ],\n [\n -122.16110229492186,\n 48.438312142641244\n ],\n [\n -122.86148071289061,\n 48.438312142641244\n ],\n [\n -122.86148071289061,\n 47.814076743593624\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"242","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nowacki, Daniel J. 0000-0002-7015-3710 dnowacki@usgs.gov","orcid":"https://orcid.org/0000-0002-7015-3710","contributorId":174586,"corporation":false,"usgs":true,"family":"Nowacki","given":"Daniel","email":"dnowacki@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":790572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":790573,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210393,"text":"70210393 - 2020 - Temporal and spatial variability of shallow soil moisture across four planar hillslopes on a tropical ocean island, San Cristóbal, Galápagos","interactions":[],"lastModifiedDate":"2020-06-02T12:30:23.389907","indexId":"70210393","displayToPublicDate":"2020-05-30T07:23:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Temporal and spatial variability of shallow soil moisture across four planar hillslopes on a tropical ocean island, San Cristóbal, Galápagos","docAbstract":"Study Region: This paper provides a summary of findings from temporal and spatial studies of soil water content on planar hillslopes across the equatorial island of San Cristóbal, Galápagos (Ecuador). \nStudy Focus: Soil water content (SWC) was measured to generate temporal and spatial records to determine seasonal variation and to investigate how the behavior of surface and near-surface root-zone soil water may support island-wide hydrogeology models. SWC probes were installed at four weather stations in a climosequence to generate a temporal record and spatial surveys of shallow SWC across the selected sites were completed during wet and dry seasons. Temporal differences in SWC were driven by seasonal variations in rainfall and evapotranspiration, while spatial variability remained high during both wet and dry seasons. Unsaturated hydraulic conductivity determined by mini-disk infiltrometers was highly variable across the slopes, as were other hydrologic variables. \nNew Hydrological Insights for the Region: The high heterogeneity of soil water and hydrologic characteristics provides a means to explain why little runoff is observed at the study sites: soils do not saturate uniformly across hillslopes, allowing for runoff generated in one part of the hillslope to be conducted into the soil in adjacent parts of the hillslope. The lack of connected surface runoff helps explain how water enters the groundwater system of the island.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2020.100692","usgsCitation":"Percy, M.S., Riveros-Iregui, D.A., Mirus, B.B., and Benninger, L.K., 2020, Temporal and spatial variability of shallow soil moisture across four planar hillslopes on a tropical ocean island, San Cristóbal, Galápagos: Journal of Hydrology: Regional Studies, v. 30, 100692, 20 p., https://doi.org/10.1016/j.ejrh.2020.100692.","productDescription":"100692, 20 p.","ipdsId":"IP-118110","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":456598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2020.100692","text":"Publisher Index Page"},{"id":375238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Galápagos","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.52685546875,\n -1.7026302136023004\n ],\n [\n -88.868408203125,\n -1.7026302136023004\n ],\n [\n -88.868408203125,\n 1.2852925793638545\n ],\n [\n -92.52685546875,\n 1.2852925793638545\n ],\n [\n -92.52685546875,\n -1.7026302136023004\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Percy, Madelyn S.","contributorId":225062,"corporation":false,"usgs":false,"family":"Percy","given":"Madelyn","email":"","middleInitial":"S.","affiliations":[{"id":41033,"text":"UNC Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":790152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riveros-Iregui, Diego A.","contributorId":225063,"corporation":false,"usgs":false,"family":"Riveros-Iregui","given":"Diego","email":"","middleInitial":"A.","affiliations":[{"id":41033,"text":"UNC Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":790153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":790154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benninger, Larry K.","contributorId":225064,"corporation":false,"usgs":false,"family":"Benninger","given":"Larry","email":"","middleInitial":"K.","affiliations":[{"id":41033,"text":"UNC Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":790155,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211837,"text":"70211837 - 2020 - A revised classification of the Xolmiini (Aves: Tyrannidae: Fluvicolinae), including a new genus for Muscisaxicola fluviatilis","interactions":[],"lastModifiedDate":"2020-08-07T20:47:00.093988","indexId":"70211837","displayToPublicDate":"2020-05-29T15:44:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3147,"text":"Proceedings of the Biological Society of Washington","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A revised classification of the Xolmiini (Aves: Tyrannidae: Fluvicolinae), including a new genus for Muscisaxicola fluviatilis","title":"A revised classification of the Xolmiini (Aves: Tyrannidae: Fluvicolinae), including a new genus for Muscisaxicola fluviatilis","docAbstract":"Recent studies using molecular phylogenetics have provided new insight into the composition of and relationships among species in the avian tribe Xolmiini. Key findings include the paraphyly of Xolmis, including the exclusion of X. dominicanus from the Xolmiini, and the apparent paraphyly of Muscisaxicola. We provide a revised classification of the Xolmiini, including a new genus for Muscisaxicola fluviatilis, based on the recent phylogenetic results.
","language":"English","publisher":"BioOne","doi":"10.2988/20-00002","usgsCitation":"Chesser, R., Harvey, M., Brumfield, R., and Derryberry, E.P., 2020, A revised classification of the Xolmiini (Aves: Tyrannidae: Fluvicolinae), including a new genus for Muscisaxicola fluviatilis: Proceedings of the Biological Society of Washington, v. 133, no. 1, p. 35-48, https://doi.org/10.2988/20-00002.","productDescription":"14 p.","startPage":"35","endPage":"48","ipdsId":"IP-116269","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":499868,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/biosci_pubs/3519","text":"External Repository"},{"id":377202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chesser, R. Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":894,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":795314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Michael G","contributorId":237791,"corporation":false,"usgs":false,"family":"Harvey","given":"Michael G","affiliations":[{"id":27996,"text":"Univ. of Tennessee","active":true,"usgs":false}],"preferred":false,"id":795315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumfield, Robb T","contributorId":215474,"corporation":false,"usgs":false,"family":"Brumfield","given":"Robb T","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":795316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derryberry, Elizabeth P","contributorId":237792,"corporation":false,"usgs":false,"family":"Derryberry","given":"Elizabeth","email":"","middleInitial":"P","affiliations":[{"id":27996,"text":"Univ. of Tennessee","active":true,"usgs":false}],"preferred":false,"id":795317,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211927,"text":"70211927 - 2020 - Recognition of typical antibiotic residues in environmental media related to groundwater in China (2009−2019)","interactions":[],"lastModifiedDate":"2020-08-11T19:37:23.234371","indexId":"70211927","displayToPublicDate":"2020-05-29T14:25:49","publicationYear":"2020","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":"Recognition of typical antibiotic residues in environmental media related to groundwater in China (2009−2019)","docAbstract":"The potential adverse environmental and health-related impacts of antibiotics are becoming more and more concerning. China is globally the largest antibiotic producer and consumer, possibly resulting in the ubiquity and high detection levels of antibiotics in environmental compartments. Clear status on the concentration levels and spatial distribution of antibiotic contamination in China's environment is necessary to gain insight into the establishment of legal and regulatory frameworks. This study collects information from over 170 papers reporting the occurrence and distribution of antibiotics in China's environment. A total of 110 antibiotics were detected, and 28 priority antibiotics were ubiquitous in China in almost all compartments of the environment, excluding the atmosphere. Seven dominant antibiotics in all environment compartments were identified by cluster analysis, including tetracycline, oxytetracycline, chlortetracycline, ofloxacin, enrofloxacin, norfloxacin, and ciprofloxacin. Meanwhile, sulfamethoxazole, sulfadiazine, and sulfamethazine were also frequently found in aqueous phases. Among the main basins where antibiotics were detected, the Haihe River Basin had higher median antibiotic concentrations in surface water compared to other basins, while the Huaihe River Basin had higher median concentrations in sediment. The median values of antibiotic concentrations in the sources were as follows: animal manure, 39 μg/kg (microgram per kilogram); WWTP (wastewater treatment plant) sludge, 39 μg/kg; animal wastewater, 156 ng/L (nanogram per liter); WWTP effluent: 15 ng/L. These concentrations are 1 − 2 orders of magnitude higher than that of the receptors (soil, 2.1 μg/kg; sediment, 4.7 μg/kg; surface water, 8.1 ng/L; groundwater, 2.9 ng/L), whether in solid or aqueous phases. Based on the number of detected antibiotics in various environmental compartments, animal farms and WWTPs are the main sources of antibiotics, and surface water and sediment are the main receptors of antibiotics. Hierarchical clustering identified the two main pathways of antibiotic transfer in various environmental compartments, which are from animal wastewater/WWTP effluent to surface water/sediment and from animal manure/WWTP sludge to soil/groundwater.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2020.122813","usgsCitation":"Huang, F., An, Z., Moran, M.J., and Liu, F., 2020, Recognition of typical antibiotic residues in environmental media related to groundwater in China (2009−2019): Journal of Hazardous Materials, v. 399, 122813, 13 p., https://doi.org/10.1016/j.jhazmat.2020.122813.","productDescription":"122813, 13 p.","ipdsId":"IP-109624","costCenters":[{"id":568,"text":"Southwest Biological Science 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continuously monitored since 1985 with currently 14 operational meteorological stations distributed throughout the valleys. Because climate is based on a 30‐year record of weather, this is the first study to truly define the contemporary climate of the McMurdo Dry Valleys. Mean air temperature and solar radiation based on all stations were −20°C and 102 W m−2, respectively. Depending on the site location, the mean annual air temperatures on the valleys floors ranged between −15°C and −30°C, and mean annual solar radiation varied between 72 and 122 W m−2. Surface air temperature decreased by 0.7°C per decade from 1986 to 2006 at Lake Hoare station (longest continuous record), after which the record is highly variable with no trend. All stations with sufficiently long records showed similar trend shifts in 2005 ±1 year. Summer is defined as November through February, using a physically based process: up‐valley warming from the coast associated with a change in atmospheric stability.
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Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.
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rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":789119,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lindsey, Kassandra O","contributorId":224689,"corporation":false,"usgs":false,"family":"Lindsey","given":"Kassandra","email":"","middleInitial":"O","affiliations":[{"id":12745,"text":"Colorado Geological Survey","active":true,"usgs":false}],"preferred":false,"id":789120,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McCoy, Kevin","contributorId":224690,"corporation":false,"usgs":false,"family":"McCoy","given":"Kevin","email":"","affiliations":[{"id":12745,"text":"Colorado Geological Survey","active":true,"usgs":false}],"preferred":false,"id":789121,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70210279,"text":"ofr20191134 - 2020 - Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","interactions":[],"lastModifiedDate":"2020-05-29T15:12:09.612507","indexId":"ofr20191134","displayToPublicDate":"2020-05-29T09:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1134","displayTitle":"Regional Hydrostratigraphic Framework of Joint Base McGuire-Dix-Lakehurst and Vicinity, New Jersey, in the Context of Perfluoroalkyl Substances Contamination of Groundwater and Surface Water","title":"Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water","docAbstract":"A study was conducted by the U.S. Geological Survey, in cooperation with the U.S. Air Force, to describe the regional hydrostratigraphy of shallow aquifers and confining units underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, in the context of contamination of groundwater and surface water by per- and polyfluoroalkyl substances (PFAS) potentially originating from JBMDL sources. The aquifers studied are two that crop out within JBMDL boundaries—the Kirkwood-Cohansey aquifer system and the Vincentown aquifer—and another aquifer near JBMDL that does not crop out at land surface—the Piney Point aquifer. The unconfined portion of the Vincentown aquifer and portions of the Kirkwood-Cohansey aquifer system that overlie the unconfined portion of the Vincentown aquifer are consolidated into, and described as, a single, separate unconfined aquifer system. Regionally extensive clay subunits that potentially create semiconfined hydrologic conditions within the mostly unconfined Kirkwood-Cohansey aquifer system also are identified. Two confining units were studied—the Manasquan-Shark River confining unit underlying the Kirkwood-Cohansey aquifer system, which includes the basal confining sediment in the Kirkwood Formation, and the Navesink-Hornerstown confining unit underlying the Vincentown aquifer. The hydrostratigraphic units are defined using available borehole geophysical logs, lithologic logs, and (or) drillers’ logs from 131 wells and are presented in a series of 8 aquifer structure maps and 12 cross sections. The framework positions JBMDL into a regional hydrostratigraphic structure for which higher-resolution delineation of the shallow aquifers can be constructed to determine potential pathways of PFAS contamination in groundwater to off-site drinking water wells in areas adjacent to JBMDL.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191134","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., 2020, Regional hydrostratigraphic framework of Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, in the context of perfluoroalkyl substances contamination of groundwater and surface water: U.S. Geological Survey Open-File Report 2019–1134, 42 p., https://doi.org/10.3133/ofr20191134.","productDescription":"Report: viii, 42 p.; 12 Plates: 30 x 24 inches; 2 Tables","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107327","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375120,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate06.pdf","text":"Plate 6","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375125,"rank":13,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate11.pdf","text":"Plate 11","size":"533 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections F-F’ through I-I’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1134/coverthb.jpg"},{"id":375114,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134.pdf","text":"Report","size":"9.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1134"},{"id":375115,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate01.pdf","text":"Plate 1","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of well locations and outcrop areas of hydrostratigraphic units, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375116,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate02.pdf","text":"Plate 2","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375117,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate03.pdf","text":"Plate 3","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375122,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate08.pdf","text":"Plate 8","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the unconfined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375123,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate09.pdf","text":"Plate 9","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the bottom of the Navesink-Hornerstown confining unit, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375124,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate10.pdf","text":"Plate 10","size":"588 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections A-A’ through E-E’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375127,"rank":15,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.xlsx","text":"Table 3","size":"23.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey (Preferred method to view file)"},{"id":375128,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_table03.csv","text":"Table 3","size":"10.2 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Wells used to develop a hydrostratigraphic framework, and interpreted aquifer structure points, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375118,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate04.pdf","text":"Plate 4","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of semiconfining subunits within the Kirkwood-Cohansey aquifer system, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375119,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate05.pdf","text":"Plate 5","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the top of the Piney Point aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375121,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate07.pdf","text":"Plate 7","size":"755 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Map of the thickness of the confined portion of the Vincentown aquifer, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"},{"id":375126,"rank":14,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1134/ofr20191134_plate12.pdf","text":"Plate 12","size":"409 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Sections J-J’ through L-L’, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey"}],"country":"United States","state":"New Jersey","otherGeospatial":"Joint Base McGuire-Dix-Lakehurst","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.74822998046875,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 39.886557705928475\n ],\n [\n -74.25796508789062,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 40.11799004890473\n ],\n [\n -74.74822998046875,\n 39.886557705928475\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
West Africa represents a wide gradient of climates, extending from tropical conditions along the Guinea Coast to the dry deserts of the south Sahara, and it has some of the lowest income, most vulnerable populations on the planet, which increases catastrophic impacts of low and high frequency climate variability. This paper investigates low and high frequency climate variability in West African monthly and seasonal precipitation and reference evapotranspiration from the early 1980s to 2016. We examine the impact of those trends and how they interact with payouts from index insurance products. Understanding low and high frequency variability in precipitation and reference evapotranspiration at these scales can provide insight into trends during periods critical to agricultural performance across the region. For index insurance, it is important to identify low-frequency variability, which can result in radical departures between designed/planned and actual insurance payouts, especially in the later part of a 30-year period, a common climate analysis period. We find that evaporative demand and precipitation are not perfect substitutes for monitoring crop deficits and that there may be space to use both for index insurance design. We also show that low yields—aligned with the need for insurance payouts—can be predicted using classification trees that include both precipitation and reference evapotranspiration.
","language":"English","publisher":"MDPI","doi":"10.3390/RS12152432","usgsCitation":"Blakeley, S., Sweeney, S., Husak, G., Harrison, L., Funk, C., Peterson, P., and Osgood, D.E., 2020, Identifying Precipitation and Reference Evapotranspiration Trends in West Africa to Support Drought Insurance: Remote Sensing, v. 12, no. 15, 2432, 29 p., https://doi.org/10.3390/RS12152432.","productDescription":"2432, 29 p.","ipdsId":"IP-120726","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":456609,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12152432","text":"Publisher Index Page"},{"id":429401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"West Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 20,\n 20\n ],\n [\n -18,\n 20\n ],\n [\n -18,\n 0\n ],\n [\n 20,\n 0\n ],\n [\n 20,\n 20\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"15","noUsgsAuthors":false,"publicationDate":"2020-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Blakeley, Sari","contributorId":337011,"corporation":false,"usgs":false,"family":"Blakeley","given":"Sari","email":"","affiliations":[{"id":80950,"text":"UCSB Climate Hazards Center","active":true,"usgs":false}],"preferred":false,"id":901759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweeney, Stuart","contributorId":337012,"corporation":false,"usgs":false,"family":"Sweeney","given":"Stuart","email":"","affiliations":[{"id":35298,"text":"UCSB Geography Department","active":true,"usgs":false}],"preferred":false,"id":901760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":901761,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":901762,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":901763,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Pete","contributorId":337013,"corporation":false,"usgs":false,"family":"Peterson","given":"Pete","affiliations":[{"id":80950,"text":"UCSB Climate Hazards Center","active":true,"usgs":false}],"preferred":false,"id":901764,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osgood, Daniel E","contributorId":337014,"corporation":false,"usgs":false,"family":"Osgood","given":"Daniel","email":"","middleInitial":"E","affiliations":[{"id":80951,"text":"International Research Institute","active":true,"usgs":false}],"preferred":false,"id":901765,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211652,"text":"70211652 - 2020 - Capture of environmental DNA (eDNA) from water samples by flocculation","interactions":[],"lastModifiedDate":"2020-08-06T18:55:23.121348","indexId":"70211652","displayToPublicDate":"2020-05-29T08:38:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5994,"text":"JOVE Journal Of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"Capture of environmental DNA (eDNA) from water samples by flocculation","docAbstract":"The analysis of environmental DNA (eDNA) has become a widely used approach to problem solving in species management. The detection of cryptic species including invasive and (or) species at risk is the goal, typically accomplished by testing water and sediment for the presence of characteristic DNA signatures. Reliable and efficient procedures for the capture of eDNA are required, especially those that can be performed easily in the field by personnel with limited training and citizen scientists. The capture of eDNA using membrane filtration is widely used currently. This approach has inherent issues that include the choice of filter material and porosity, filter fouling, and time required on site for the process to be performed. Flocculation offers an alternative that can be easily implemented and applied to sampling regimes that strive to cover broad territories in limited time.
","language":"English","publisher":"JOVE","doi":"10.3791/60967","usgsCitation":"Schill, W., 2020, Capture of environmental DNA (eDNA) from water samples by flocculation: JOVE Journal Of Visualized Experiments, v. 159, e60967, https://doi.org/10.3791/60967.","productDescription":"e60967","onlineOnly":"Y","ipdsId":"IP-117636","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"159","noUsgsAuthors":false,"publicationDate":"2020-05-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Schill, W. Bane 0000-0002-9217-984X","orcid":"https://orcid.org/0000-0002-9217-984X","contributorId":213903,"corporation":false,"usgs":true,"family":"Schill","given":"W. Bane","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794938,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70217614,"text":"70217614 - 2020 - Pervasive shifts in forest dynamics in a changing world","interactions":[],"lastModifiedDate":"2021-01-25T14:56:41.188464","indexId":"70217614","displayToPublicDate":"2020-05-29T08:26:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Pervasive shifts in forest dynamics in a changing world","docAbstract":"Forest dynamics arise from the interplay of environmental drivers and disturbances with the demographic processes of recruitment, growth, and mortality, subsequently driving biomass and species composition. However, forest disturbances and subsequent recovery are shifting with global changes in climate and land use, altering these dynamics. Changes in environmental drivers, land use, and disturbance regimes are forcing forests toward younger, shorter stands. Rising carbon dioxide, acclimation, adaptation, and migration can influence these impacts. Recent developments in Earth system models support increasingly realistic simulations of vegetation dynamics. In parallel, emerging remote sensing datasets promise qualitatively new and more abundant data on the underlying processes and consequences for vegetation structure. When combined, these advances hold promise for improving the scientific understanding of changes in vegetation demographics and disturbances.
The effects of extreme concentrations of toxic metalloids, such as arsenic (As) and antimony (Sb), on larval amphibians are not well-understood. We sampled Western Toad tadpoles (Anaxyrus boreas) living in As- and Sb-contaminated wetlands throughout their development. Although the tadpoles completed metamorphosis, they accumulated among the highest concentrations of As and Sb ever reported for a living vertebrate (3866.9 mg/kg; 315.0 mg/kg (dry weight), respectively). Ingestion of contaminated sediment had a more important role in metalloid accumulation than aqueous exposure alone. Metalloids were initially concentrated in the gut; however, by metamorphosis, the majority were found in other tissues. These concentrations subsequently decreased with the onset of metamorphosis, yet remained quite elevated. Sublethal effects, including delayed development and reduced size at metamorphosis, were associated with elevated metalloid exposure. The presence of organic arsenicals in tadpole tissues suggests they have the ability to biomethylate inorganic As compounds. The arsenical trimethyl arsine oxide accounted for the majority of extractable organic As, with lesser amounts of monomethylarsonic acid and dimethylarsinic acid. Our findings demonstrate remarkable tolerance of toad tadpoles to extreme metalloid exposure and implicate physiological processes mediating that tolerance.
Bathymetric and topographic surveys performed annually along the coastlines of northern Oregon and southwestern Washington documented changes in beach and nearshore morphology between 2014 and 2019. Volume change analysis revealed measurable localized erosion and deposition throughout the study area, but significant net erosion at the regional scale (several kilometers [km]) was limited to Benson Beach, Wash., a 3-km-long stretch of coastline immediately north of the Columbia River inlet. Despite the placement of approximately 6.3 million cubic meters (Mm3) of sand dredged from the Columbia River navigational channel at nearshore placement sites located nearby, Benson Beach eroded 2.1±0.8 Mm3 over the 5-year (yr) monitoring time period (420,000 cubic meters/year [m3/yr]). A hydrodynamic and sediment transport model was applied to simulate sediment transport fluxes, and a new visualization technique was developed to evaluate the linkages between nearshore dredge placement sites and adjacent coastlines near the mouth of the Columbia River. The model results indicate the dominance of wave processes on sediment-transport patterns outside of the inlet and suggest that the current configuration of the nearshore dredge placement sites can be improved to more efficiently enhance the sediment budget of Benson Beach to reduce erosion and mitigate associated coastal change hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201045","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers Portland District and Northwest Association of Networked Ocean Observing Systems","usgsCitation":"Stevens, A.W., Elias, E., Pearson, S., Kaminsky, G.M., Ruggiero, P.R., Weiner, H.M., and Gelfenbaum, G.R., 2020, Observations of coastal change and numerical modeling of sediment-transport pathways at the mouth of the Columbia River and its adjacent littoral cell: U.S. Geological Survey Open-File Report 2020–1045, 82 p., https://doi.org//10.3133/ofr20201045.","productDescription":"Report: xii, 82 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-114630","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":375095,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1045/coverthb.jpg"},{"id":375096,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1045/ofr20201045.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":375097,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org//10.5066/P9W15JX8","linkHelpText":"Beach topography and nearshore bathymetry of the Columbia River littoral cell, Washington and Oregon"}],"country":"United States","state":"Oregon, Washinton","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.07135009765625,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.10180436619509\n ],\n [\n -123.57147216796875,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.35261512930026\n ],\n [\n -124.07135009765625,\n 46.10180436619509\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
The U.S. Geological Survey, in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention, assessed the chemical characteristics and the occurrence, distribution, and oxidation state of inorganic arsenic in drinking water from selected domestic well-water supplies in Maine in 2001–2 and 2006–7.
The data collected provide support for evaluating arsenic-removal efficiencies of household water-purification systems and provide information to State and local officials that can be used in determining a water-treatment approach for the removal of arsenic from drinking water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1125","collaboration":"Prepared in cooperation with the U.S. Centers for Disease Control and Prevention and the Maine Center for Disease Control and Prevention","usgsCitation":"Culbertson, C.W., Caldwell, J.M., Schalk, L.F., Manassaram, D., Backer, L.C., and Smith, A.E., 2020, Methods of collection and quality assessment of arsenic data in well-water supplies in Maine, 2001–2 and 2006–7: U.S. Geological Survey Data Series 1125, 11 p., https://doi.org/10.3133/ds1125.","productDescription":"Report: v, 11 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-025715","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":375105,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1125/ds1125.pdf","text":"Report","size":"1.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1125"},{"id":375104,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X5HVDF","text":"USGS data release","linkHelpText":"Arsenic datasets and other physical and chemical measurements for selected domestic well-water supplies in Maine—2001–2 and 2006–7"},{"id":375103,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1125/coverthb.jpg"}],"country":"United States","state":"Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.16943359374999,\n 43.02071359427862\n ],\n [\n -66.15966796874999,\n 43.02071359427862\n ],\n [\n -66.15966796874999,\n 44.87144275016589\n ],\n [\n -71.16943359374999,\n 44.87144275016589\n ],\n [\n -71.16943359374999,\n 43.02071359427862\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The Amphibian Research and Monitoring Initiative (ARMI) was established within the U.S. Geological Survey in 2000 as a result of Congressional funding for Department of the Interior agencies to study amphibians and provide information to help manage amphibians and address threats. As the research arm of the Department of the Interior, the U.S. Geological Survey is providing scientific leadership for this effort with a team of research scientists who are global leaders in amphibian conservation science. This postcard has been developed to commemorate the 20th anniversary of ARMI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip198","usgsCitation":"Ball, L.C., 2020, Amphibian Research and Monitoring Initiative (ARMI) 20th anniversary postcard: U.S. Geological Survey General Information Product 198, 2 p., https://doi.org/10.3133/gip198.","productDescription":"Postcard; 2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118795","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":375099,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/198/gip198.pdf","text":"Report","size":"922 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 198"},{"id":375098,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/198/coverthb2.jpg"}],"contact":"Environments Program
Office of the Associate Director for Ecosystems
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Amphibian Research and Monitoring Initiative (ARMI)
Most wetlands have been subject to changes in flooding regimes by climate change and human activities, resulting in widespread alteration of wetland plants at different organizational levels. However, scaling the responses of wetland plants to changes in flooding regimes is still challenging, because flooding could indirectly affect wetland plants through affecting environment factors (e.g. soil properties). During the non-flooding period, we investigated leaf N and P stoichiometry at three organizational levels (intra-species, inter-species, inter-community) along a flooding duration gradient in a lakeshore meadow of Poyang Lake floodplain, China. At the intra-species level, leaf N and P stoichiometry showed species-specific responses to flooding duration. At the inter-species level, leaf N or P contents or N:P ratio showed no significant response to flooding duration. At the inter-community level, leaf N and P contents significantly increased with flooding duration, while leaf N:P ratio decreased. At each organizational level, leaf N and P stoichiometry showed poor correlation with soil N and P stoichiometry. Moreover, intra-specific responses of leaf N and P contents to flooding duration and soil nutrient content increased with mean flooding duration of species distribution, which was the index of species hydrological niche. Intraspecific variation had lower contribution than species turnover to variations in community leaf nutrient stoichiometry. In all, flooding duration affected leaf N and P stoichiometry mainly through direct pathway at the intra-species and inter-community level, rather than the indirect pathway via soil nutrient stoichiometry. Therefore, our results have implications for scaling up from environmental conditions to ecosystem processes via wetland plant communities.
The effects of harvest on cooperatively breeding species are often more complex than simply subtracting the number of animals that died from the group count. Changes in demographic rates, particularly dispersal, could offset some effects of harvest mortality in groups but this is rarely explored with cooperative breeders. We asked whether a cooperatively breeding species known for long-distance dispersal could compensate for the effect of harvest mortality on density by adopting immigrants into the group. We used genetic samples to estimate the minimum density of gray wolves (Canis lupus) and proportion of immigrants in groups in the northern US Rocky Mountains after an annual harvest regime was initiated and in the Canadian Rocky Mountains where wolves were managed consistently under an annual harvest regime. We tested whether immigration (1) compensated, (2) partially compensated or (3) did not compensate numerically for harvest mortality in groups and hypothesized immigration would increase with increasing harvest intensity. Density of wolves in groups declined after harvest was initiated whereas immigration into groups was consistently low and did not change with harvest in the US study area. Immigration into groups was similarly low and density even lower in the Canadian study area compared to the US study area. Our results indicate immigration did not compensate for harvest mortality in groups in two separate populations of a cooperatively breeding carnivore. We hypothesize the social structure of wolf groups may limit the potentially compensatory response of immigration in some populations.