Re-examination of previously published dissolved iron time-series data from Ocean Station Papa in the central Gulf of Alaska (GoA) reveals 33-70% increases in the dissolved iron inventories occurring between September and February of successive years, implying a source of Fe to this region during autumn or early winter. Because I can virtually rule out many possible iron sources at this time of year, I suggest Alaskan glacial dust is the likely iron source. Large plumes of such dust are known to be generated regularly in the autumn by anomalous offshore winds and channelled through mountain gaps, simultaneously from several locations spanning ∼1000 km of the northern Gulf of Alaska coastline. Large dust flux events occur when below-freezing, low-humidity air temperatures persist for many days during the autumn. I suggest that existing state-of-the-art global dust models fail to reproduce this Alaskan dust flux because the model spatial resolution is too coarse to resolve the high winds through the narrow mountain gaps that generate the dust. Future work that could help to confirm this Fe source to the central GoA includes time-series profiles of iron concentrations, and ancillary information from sensor-equipped profiling floats. If this mechanism of Fe supply to the central GoA were confirmed, it would imply this Alaskan dust is transported ≥ 1100 km from the coast, more than twice as far as has been visually documented from satellite observations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006323","usgsCitation":"Crusius, J., 2021, Dissolved Fe supply to the central Gulf of Alaska is inferred to be derived from Alaskan glacial dust that is not resolved by dust transport models: JGR-Biogeosciences, v. 126, e2021JG006323, 13 p., https://doi.org/10.1029/2021JG006323.","productDescription":"e2021JG006323, 13 p.","ipdsId":"IP-102176","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":385832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.28125,\n 51.39920565355378\n ],\n [\n -131.1328125,\n 51.39920565355378\n ],\n [\n -131.1328125,\n 59.5343180010956\n ],\n [\n -153.28125,\n 59.5343180010956\n ],\n [\n -153.28125,\n 51.39920565355378\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":816240,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220525,"text":"ofr20211043 - 2021 - Dynamics of endangered sucker populations in Clear Lake Reservoir, California","interactions":[],"lastModifiedDate":"2021-05-19T12:01:59.893466","indexId":"ofr20211043","displayToPublicDate":"2021-05-18T16:18:22","publicationYear":"2021","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":"2021-1043","displayTitle":"Dynamics of Endangered Sucker Populations in Clear Lake Reservoir, California","title":"Dynamics of endangered sucker populations in Clear Lake Reservoir, California","docAbstract":"In collaboration with the Bureau of Reclamation, the U.S. Geological Survey began a consistent monitoring program for endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Clear Lake Reservoir, California, in fall 2004. The program was intended to improve understanding of the Clear Lake Reservoir populations because they are important to recovery efforts for these species. We report results from the ongoing program and include sampling efforts through fall 2019. We summarize catches and passive integrated transponder (PIT) tagging efforts from trammel net sampling in the fall seasons (September–October each year) and detections of PIT-tagged suckers on remote antennas in the spring in each year from 2006 to 2019. We also combine the data from physical captures and remote detections in capture-recapture models to provide estimates of annual survival for suckers in the reservoir.
A lack of genetic distinctiveness between shortnose suckers and Klamath largescale suckers (Catostomus snyderi) in the Lost River subbasin, including Clear Lake Reservoir, is a likely cause of past difficulty in identification of these species. Field identification can be subjective for many captured individuals, and very few individuals were identified as Klamath largescale suckers in the most recent years of our monitoring program. For this report, we combine individuals that were identified as either shortnose sucker (SNS) or Klamath largescale sucker (KLS) into a single “SNS-KLS” group for most analyses. Identification of Lost River suckers (LRS) is based on external morphological characteristics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211043","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Hayes, B.S., Harris, A.C., Janney, E.C., Kelsey, C.M., Perry, R.W., and Burdick, S.M., 2021, Dynamics of endangered sucker populations in Clear Lake Reservoir, California: U.S. Geological Survey Open-File Report 2021–1043, 59 p., https://doi.org/10.3133/ofr20211043.","productDescription":"v, 59 p.","onlineOnly":"Y","ipdsId":"IP-108970","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":385709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1043/coverthb.jpg"},{"id":385710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1043/ofr20211043.pdf","text":"Report","size":"12.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1043"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25747680664064,\n 41.78360106648078\n ],\n [\n -121.01852416992186,\n 41.78360106648078\n ],\n [\n -121.01852416992186,\n 41.96663812286332\n ],\n [\n -121.25747680664064,\n 41.96663812286332\n ],\n [\n -121.25747680664064,\n 41.78360106648078\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
In 2015–16, a comparison study of stream sediment collection techniques was done for a U.S. Geological Survey streamgage on the Nemadji River near South Superior, Wisconsin (U.S. Geological Survey station number 04024430) to provide an adjustment factor for comparing suspended-sediment rating curves for two historical periods 1973–86 and 2006–16. During 1973–1986, the U.S. Geological Survey used the equal-width-increment technique to collect suspended-sediment concentration data (EWI SSC). The Wisconsin Department of Natural Resources and Minnesota Pollution Control Agency collected grab samples for total suspended solids (grab TSS) concentration starting in 2006 and continuing beyond 2016. In addition to the comparison study of suspended-sediment concentrations, bedload and bed material samples were collected in 2015–16, and the modified Einstein procedure was run to further characterize total sediment loads. The 2015–16 study indicated that the EWI SSC and grab TSS concentrations were different, but not as much as expected, especially on the high end where grab TSS concentrations were sometimes higher than EWI SSC concentrations, possibly due to a combination of a high percentage of fines in suspension and higher concentrations in the center of the channel than the margins. The 2015–16 measured bedload made up a small percentage of total sediment load, and bedload and streambed particle sizes are 90 to 100 percent sand sized or smaller. The relative proportion of measured bedload to total load decreased with increased streamflow, and for streamflows greater than 1,800 cubic feet per second, the suspended load made up 98 percent of the total load. Calculated 2015–16 instantaneous total sediment loads from the modified Einstein procedure were up to 70 percent of the measured loads for flows less than 1,000 cubic feet per second and near or more than 100 percent for flows greater than 1,000 cubic feet per second. The sediment rating curve developed for the 2006–16 adjusted grab TSS data had a similar slope but a lower intercept than its 1973–86 EWI SSC counterpart, indicating that for a given streamflow, suspended-sediment concentrations were lower for 2006–16 compared to 1973–86. The negative offset equates to estimates of annual suspended-sediment loads in 2006–16 being on average 87 percent of the 1973–86 loads. Over the period 2009–16, annual suspended-sediment loads ranged from a low of about 21,000 tons per year in 2015 to a high of 167,000 tons per year in 2012 with a mean of 85,000 tons per year. However, reductions in suspended-sediment concentrations are likely obscured by large loads during years with flooding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211003","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., 2021, Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016: U.S. Geological Survey Open-File Report 2021–1003, 27 p., https://doi.org/10.3133/ofr20211003.","productDescription":"Report: viii, 27 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-085024","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FX0X6Y","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Selected sediment data and results from regression models, modified Einstein Procedure, and loads estimation for the Nemadji River, 1973–2016"},{"id":385360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1003/ofr20211003.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1003"},{"id":385359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1003/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Nemadji River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.55157470703125,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.38672781370433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Earthquake early warning (EEW) systems can quickly identify the beginning of a significant earthquake rupture, but the first seconds of seismic data have not been found to predict the final rupture length. We present two approaches for estimating probabilities of rupture length given the rupture initiation from an EEW system. In the first approach, bends and steps on the fault are interpreted as physical mechanisms for rupture arrest. Arrest probability relations are developed from empirical observations and depend on bend angle and step size. Probability of arrest compounds serially with increasing rupture length as bends or steps are encountered. In the second approach, time‐independent rates among ruptures from the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), are interpreted to apply to the time‐dependent condition in which rupture grows from a known starting point. Length probabilities from a Gutenberg–Richter magnitude–frequency relation provide a reference of comparison. We illustrate the new approach using the discretized fault model for California developed for UCERF3. For the case of rupture initiating on the southeast end of the San Andreas fault we find the geometric complexity of the Mill Creek section impedes most ruptures, and only ∼5% are predicted to reach to San Bernardino on the eastern edge of the greater Los Angeles region. Conditional probabilities of length can be precompiled in this manner for any initiation point on the fault system and thus are of potential value in seismic hazard and EEW applications.
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\"}}]}","volume":"111","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Biasi, Glenn 0000-0003-0940-5488 gbiasi@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-5488","contributorId":195946,"corporation":false,"usgs":true,"family":"Biasi","given":"Glenn","email":"gbiasi@usgs.gov","affiliations":[],"preferred":true,"id":929127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wesnousky, Steven G.","contributorId":193416,"corporation":false,"usgs":false,"family":"Wesnousky","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":33746,"text":"Center for Neotectonic Studies, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":929128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221794,"text":"70221794 - 2021 - Wave-driven flood-forecasting on reef-lined coasts early warning system (WaveFoRCE)","interactions":[],"lastModifiedDate":"2021-07-07T12:06:55.985933","indexId":"70221794","displayToPublicDate":"2021-05-18T07:06:35","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"title":"Wave-driven flood-forecasting on reef-lined coasts early warning system (WaveFoRCE)","docAbstract":"Increasing the resilience of coastal communities while decreasing the risk to them are key to the continued inhabitance and sustainability of these areas. Low-lying coral reef-lined islands are experiencing storm wave-driven flood events that currently strike with little to no warning. These events are occurring more frequently and with increasing severity. There is a need along the world’s coral reef-lined coasts for a tool that can forecast the timing and severity of wave-driven flooding events. Without this tool, coastal communities are vulnerable to:
loss of life from drowning • loss of, and damage to, property and infrastructure • decreasing viability of communities via loss of, and damage to crops, fishing (via decreased water quality and wave-damaged reefs), and freshwater resources • reduction of livable land due to increased erosion and salt intrusion. The currently available tools were developed for sandy shorelines and do not accurately predict wave-driven flooding on reef-lined coasts, leaving inhabitants without accurate and timely warnings. In addition, the flood models that do exist for reef-lined coasts have only been implemented on a small number of areas throughout the world because running these models is costly and requires a high level of computing power. Using these existing models and techniques to generate high-resolution forecasts for wave-driven flooding for all reef-lined coasts would cost approximately US$1 billion. To remedy this issue, an international team associated with the GEO Blue Planet initiative is working to develop a wave-driven flood-forecasting early-warning system (EWS) for coral reef-lined coasts known as WaveFoRCE. The system aims to provide all nations and people living on a coral reef-lined coast anywhere in the world with an up to 7.5-day forecast of storm wave-driven flood events.
","largerWorkType":{"id":25,"text":"Newsletter"},"largerWorkTitle":"Environment Coastal & Offshore (ECO)","language":"English","publisher":"United Nations","usgsCitation":"Skirving, W., Storlazzi, C.D., and Smail, E.A., 2021, Wave-driven flood-forecasting on reef-lined coasts early warning system (WaveFoRCE), p. 144-147.","productDescription":"4 p.","startPage":"144","endPage":"147","ipdsId":"IP-127710","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386977,"type":{"id":15,"text":"Index Page"},"url":"https://www.oceandecade.org/news/128/ECO-Magazine--special-digital-issue-on-the-Ocean-Decade-May-2021"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skirving, William","contributorId":224303,"corporation":false,"usgs":false,"family":"Skirving","given":"William","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smail, Emily A","contributorId":217219,"corporation":false,"usgs":false,"family":"Smail","given":"Emily","email":"","middleInitial":"A","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818747,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221150,"text":"70221150 - 2021 - Aeolian sediments in paleowetland deposits of the Las Vegas Formation","interactions":[],"lastModifiedDate":"2022-01-06T17:13:04.657899","indexId":"70221150","displayToPublicDate":"2021-05-17T08:21:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Aeolian sediments in paleowetland deposits of the Las Vegas Formation","docAbstract":"The Las Vegas Formation (LVF) is a well-characterized sequence of groundwater discharge (GWD) deposits exposed in and around the Las Vegas Valley in southern Nevada. Nearly monolithologic bedrock surrounds the valley, which provides an excellent opportunity to test the hypothesis that GWD deposits include an aeolian component. Mineralogical data indicate that the LVF sediments are dominated by carbonate minerals, similar to the local bedrock, but silicate minerals are also present. The median particle size is ~35 μm, consistent with modern dust in the region, and magnetic properties contrast strongly with local bedrock, implying an extralocal origin. By combining geochemical data from the LVF sediments and modern dust, we found that an average of ~25% of the LVF deposits were introduced by aeolian processes. The remainder consists primarily of authigenic groundwater carbonate as well as minor amounts of alluvial material and soil carbonate. Our data also show that the aeolian sediments accumulated in spring ecosystems in the Las Vegas Valley in a manner that was independent of both time and the specific hydrologic environment. These results have broad implications for investigations of GWD deposits located elsewhere in the southwestern U.S. and worldwide.
Coastal salt marshes, which provide valuable ecosystem services such as flood mitigation and carbon sequestration, are threatened by rising sea level. In response, these ecosystems migrate landward, converting available upland into salt marsh. In the coastal-plain surrounding Chesapeake Bay, United States, conversion of coastal forest to salt marsh is well-documented and may offset salt marsh loss due to sea level rise, sediment deficits, and wave erosion. Land slope at the marsh-forest boundary is an important factor determining migration likelihood, however, the standard method of using field measurements to assess slope across the marsh-forest boundary is impractical on the scale of an estuary. Therefore, we developed a general slope quantification method that uses high resolution elevation data and a repurposed shoreline analysis tool to determine slope along the marsh-forest boundary for the entire Chesapeake Bay coastal-plain and find that less than 3% of transects have a slope value less than 1%; these low slope environments offer more favorable conditions for forest to marsh conversion. Then, we combine the bay-wide slope and elevation data with inundation modeling from Hurricane Isabel to determine likelihood of coastal forest conversion to salt marsh. This method can be applied to local and estuary-scale research to support management decisions regarding which upland forested areas are more critical to preserve as available space for marsh migration.
Riparian ecosystems provide critical habitat for many species, yet assessment of vegetation condition at local scales is difficult to measure when considering large areas over long time periods. We present a framework to map and monitor two deciduous cover types, upland and riparian, occupying a small fraction of an expansive, mountainous landscape in north-central Wyoming. Initially, we developed broad-scale predictions of predominant woody vegetation types by integrating Landsat data into species distribution models and combining subsequent outputs into a synthesis map. Then, we evaluated a 35-year Landsat time series (1985–2019) using the Mann-Kendall test to identify significant trends in the condition of upland and riparian deciduous vegetation and assessed the rate and direction of change using the Theil-Sen estimator. Finally, we used plot level data to assess the utility of the framework to detect bottom-up controls (ungulate browse pressure and management actions) on vegetation condition. The synthesis map had an overall correct classification rate of 87% and field data indicated deciduous vegetation within 45 m of coniferous forest faces increased pressure of conifer expansion. The trend assessment identified consistent patterns operating at the landscape scale across both upland and riparian deciduous vegetation; a predominant greening trend was observed for 12 years followed by a 9-year browning trend, before switching back to a greening trend for the last 13 years of the study. Our results indicate trends are driven by the climate of the measurement period at the landscape scale. Although we did not find conclusive evidence to establish a strong link between browse pressure and satellite data, we highlight examples where prevailing trends can be overridden by local disturbance or management intervention. This framework is transferable to other understudied riparian environments throughout western North America to provide insight on ecohydrological processes and assess global and local stressors across broad spatiotemporal scales.
Binary regression models are commonly used in disciplines such as epidemiology and ecology to determine how spatial covariates influence individuals. In many studies, binary data are shared in a spatially aggregated form to protect privacy. For example, rather than reporting the location and result for each individual that was tested for a disease, researchers may report that a disease was detected or not detected within geopolitical units. Often, the spatial aggregation process obscures the values of response variables, spatial covariates, and locations of each individual, which makes recovering individual-level inference difficult. We show that applying a series of transformations, including a change of support, to a bivariate point process model allows researchers to recover individual-level inference for spatial covariates from spatially aggregated binary data. The series of transformations preserves the convenient interpretation of desirable binary regression models that are commonly applied to individual-level data. Using a simulation experiment, we compare the performance of our proposed method under varying types of spatial aggregation against the performance of standard approaches using the original individual-level data. We illustrate our method by modeling individual-level probability of infection using a data set that has been aggregated to protect an at-risk and endangered species of bats. Our simulation experiment and data illustration demonstrate the utility of the proposed method when access to original non-aggregated data is impractical or prohibited.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.spasta.2021.100514","usgsCitation":"Walker, N., Hefley, T.J., Ballmann, A., Russell, R., and Walsh, D.P., 2021, Recovering individual-level spatial inference from aggregated binary data: Spatial Statistics, v. 44, 100514, 14 p.; Data release, https://doi.org/10.1016/j.spasta.2021.100514.","productDescription":"100514, 14 p.; Data release","ipdsId":"IP-118748","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":452237,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://arxiv.org/abs/2004.12013","text":"Publisher Index Page"},{"id":386279,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418318,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XUPDIB","text":"USGS data release","description":"USGS data release","linkHelpText":"Pseudogymnoascus destructans detections by US county (2008-2012)"}],"country":"United States","otherGeospatial":"Northeast and Midwest United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.20703125,\n 36.87962060502676\n ],\n [\n -66.26953125,\n 36.87962060502676\n ],\n [\n -66.26953125,\n 49.15296965617042\n ],\n [\n -97.20703125,\n 49.15296965617042\n ],\n [\n -97.20703125,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Nelson","contributorId":259320,"corporation":false,"usgs":false,"family":"Walker","given":"Nelson","email":"","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":817117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":817118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":817119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":817120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":817121,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220612,"text":"70220612 - 2021 - Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest","interactions":[],"lastModifiedDate":"2021-12-10T16:26:48.54244","indexId":"70220612","displayToPublicDate":"2021-05-17T06:49:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest","docAbstract":"Recent studies have shown the oxygen isotopic composition (δ18O) of modern terrestrial gastropod shells is determined largely by the δ18O of precipitation. This implies that fossil shells could be used to reconstruct the δ18O of paleo-precipitation as long as the isotopic system, including the hydrologic pathways of the local watershed and the gastropod systematics, is well understood. In this study, we measured the δ18O values of 456 individual gastropod shells collected from paleowetland deposits in the San Pedro Valley, Arizona that range in age from ca. 29.1 to 9.8 ka. Isotopic differences of up to 2‰ were identified among the four taxa analyzed (Succineidae, Pupilla hebes, Gastrocopta tappaniana, and Vallonia gracilicosta), with Succineidae shells yielding the highest values and V. gracilicosta shells exhibiting the lowest values. We used these data to construct a composite isotopic record that incorporates these taxonomic offsets, and found shell δ18O values increased by ~4‰ between the last glacial maximum and early Holocene, which is similar to the magnitude, direction, and rate of isotopic change recorded by speleothems in the region. These results suggest the terrestrial gastropods analyzed here may be used as a proxy for past climate in a manner that is complementary to speleothems, but potentially with much greater spatial coverage.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2021.18","usgsCitation":"Rech, J.A., Pigati, J.S., Springer, K.B., Bosch, S., Nekola, J.C., and Yanes, Y., 2021, Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest: Quaternary Research, v. 104, p. 43-53, https://doi.org/10.1017/qua.2021.18.","productDescription":"11 p.","startPage":"43","endPage":"53","onlineOnly":"N","ipdsId":"IP-122769","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436362,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EISWFZ","text":"USGS data release","linkHelpText":"Data release for Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest"},{"id":385834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Nevada, New Mexico, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.1904296875,\n 42.032974332441405\n ],\n [\n -119.92675781249999,\n 39.16414104768742\n ],\n [\n -114.9169921875,\n 35.35321610123823\n ],\n [\n -114.9609375,\n 32.731840896865684\n ],\n [\n -111.005859375,\n 31.240985378021307\n ],\n [\n -108.19335937499999,\n 31.466153715024294\n ],\n [\n -108.1494140625,\n 31.80289258670676\n ],\n [\n -106.34765625,\n 31.728167146023935\n ],\n [\n -103.1396484375,\n 31.952162238024975\n ],\n [\n -103.095703125,\n 36.94989178681327\n ],\n [\n -102.041015625,\n 36.98500309285596\n ],\n [\n -102.0849609375,\n 41.0130657870063\n ],\n [\n -110.9619140625,\n 40.91351257612758\n ],\n [\n -110.9619140625,\n 42.00032514831621\n ],\n [\n -120.1904296875,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","noUsgsAuthors":false,"publicationDate":"2021-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rech, Jason A.","contributorId":117323,"corporation":false,"usgs":false,"family":"Rech","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":816199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":816200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":816201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bosch, Stephanie","contributorId":258260,"corporation":false,"usgs":false,"family":"Bosch","given":"Stephanie","email":"","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":816202,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":816203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yanes, Yurena","contributorId":197219,"corporation":false,"usgs":false,"family":"Yanes","given":"Yurena","email":"","affiliations":[],"preferred":false,"id":816204,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229404,"text":"70229404 - 2021 - Moose habitat selection and fitness consequences during two critical winter tick life stages in Vermont, United States","interactions":[],"lastModifiedDate":"2022-03-07T12:54:30.254398","indexId":"70229404","displayToPublicDate":"2021-05-17T06:41:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Moose habitat selection and fitness consequences during two critical winter tick life stages in Vermont, United States","docAbstract":"The moose (Alces alces) is a charismatic species in decline across much of their southern distribution in North America. In the northeastern United States, much of the reduction has been attributed to winter tick (Dermacentor albipictus) infestations. Winter ticks are fairly immobile throughout all life stages, and therefore their distribution patterns at any given time are shaped largely by the occurrence of moose across the landscape during the peak of two critical time periods: fall questing (when ticks latch onto moose) and spring drop-off (when engorged female ticks detach from moose). We used recent land cover and lidar data within a dynamic occupancy modeling framework to estimate first-order habitat selection (use vs. non-use) of female moose (n = 74) during the tick questing and drop-off periods. Patch extinction and colonization rates between the fall questing and spring drop-off periods were strongly influenced by habitat and elevation, but these effects were diminished during the fall questing period when moose were more active across the landscape. From the fall questing period to the spring drop-off period, patches where colonization was high and extinction was low had higher proportions of young (shrub/forage) mixed forest at higher elevations. Further, we evaluated the fitness consequences of habitat selection by adult females during the fall questing period, when females and their calves acquire ticks. We compared Resource Selection Functions (RSF) for five females that successfully reared a calf to age 1 with five females whose calves perished due to ticks. Adult female moose whose offspring perished selected habitats in the fall that spatially coincided with areas of high occupancy probability during the spring tick drop-off period. In contrast, adult female moose whose offspring survived selected areas where the probability of occupancy during the spring drop-off was low; at present, natural selection may favor female adults who do not select the same habitats in fall as in spring. Our model coefficients and mapped results define “hotspots” that are likely encouraging the deleterious effects of the tick-moose cycle. These findings fill knowledge gaps about moose habitat selection that may improve the effectiveness of management aimed at reversing declining population trends.
Annual variation in phenology can have profound effects on the behavior of animals. As climate change advances spring phenology in ecosystems around the globe, it is becoming increasingly important to understand how animals respond to variation in the timing of seasonal events and how their responses may shift in the future. We investigated the influence of spring phenology on the behavior of migratory, barren-ground caribou (Rangifer tarandus), a species that has evolved to cope with short Arctic summers. Specifically, we examined the effect of spring snow melt and vegetation growth on the current and potential future space-use patterns of the Porcupine Caribou Herd (PCH), which exhibits large, inter-annual shifts in their calving and post-calving distributions across the U.S.–Canadian border. We quantified PCH selection for snow melt and vegetation phenology using machine learning models, determined how selection resulted in annual shifts in space-use, and then projected future distributions based on climate-driven phenology models. Caribou exhibited strong, scale-dependent selection for both snow melt and vegetation growth. During the calving season, caribou selected areas at finer scales where the snow had melted and vegetation was greening, but within broader landscapes that were still brown or snow covered. During the post-calving season, they selected vegetation with intermediate biomass expected to have high forage quality. Annual variation in spring phenology predicted major shifts in PCH space-use. In years with early spring phenology, PCH predominately used habitat in Alaska, while in years with late phenology, they spent more time in Yukon. Future climate conditions were projected to advance spring phenology, shifting PCH calving and post-calving distributions further west into Alaska. Our results demonstrate that caribou selection for habitat in specific phenological stages drive dramatic shifts in annual space-use patterns, and will likely affect future distributions, underscoring the importance of maintaining sufficient suitable habitat to allow for behavioral plasticity.
In 2017, Mount Agung produced a small (VEI 2) eruption that was preceded by an energetic volcano-tectonic (VT) swarm (>800 earthquakes per day up to M4.9) and two months of declining activity. The period of decreased seismic activity complicated forecasting efforts for scientists monitoring the volcano. We examine the time history of earthquake families at Mount Agung in search of additional insight into the temporal changes in the shallow crust prior to eruption. Specifically, we analyze the period of declining seismic activity about five weeks prior to the eruption when forecasting uncertainty was greatest. We use REDPy (Hotovec-Ellis and Jeffries, 2016) to build a catalog of 6,508 earthquakes from 18 October 2017–15 February 2018 and group them into families of repeating earthquakes based on waveform similarity using a cross-correlation coefficient threshold of 0.8. We show that the evolution of earthquake families provides evidence that Mount Agung was progressing toward eruption even though overall earthquake rates and seismic-energy-release declined. We find that earthquake families that dominated seismicity during the beginning of the crisis ceased near the onset of tremor on 12 November 2017. Then, earthquake families took on characteristics commonly observed during effusive phases of eruptions on 15 November—a full six days before the first phreatomagmatic eruption on 21 November 2017 and a full ten days before the actual onset of lava effusion on 25 November 2017. We interpret the transitions in seismicity as the manifestation of a three-phase physical model including an Intrusion Phase, a Transition Phase, and a Eruptive Phase. During the Intrusion Phase, seismicity was dominated by VT earthquakes with a relatively high percentage of repeaters (59%) grouped into numerous (65) simultaneous families. During the Eruptive Phase, seismicity included both VT and low frequency earthquakes that grouped into relatively long-lived families despite a low overall percentage of repeaters (14%). The Transition Phase exhibited characteristics of earthquake families between the Intrusion Phase and Eruptive Phase. We conclude that the time history of earthquake families provides insight into the evolution of the stress distribution in the volcanic edifice, the development of the volcanic conduit, and seismogenesis of magma effusion. Finally, we discuss the role that repeating earthquakes could play in real-time monitoring at restless volcanoes. Our work suggests eruption forecasts can be improved by incorporating automatic processing codes to assist seismologists during sustained periods of high earthquake rates, even at sparsely monitored volcanoes.
What is already known about this topic?
Increases in COVID-19 cases in March and early April occurred despite a large-scale vaccination program. Increases coincided with the spread of SARS-CoV-2 variants and relaxation of nonpharmaceutical interventions (NPIs).
What is added by this report?
Data from six models indicate that with high vaccination coverage and moderate NPI adherence, hospitalizations and deaths will likely remain low nationally, with a sharp decline in cases projected by July 2021. Lower NPI adherence could lead to substantial increases in severe COVID-19 outcomes, even with improved vaccination coverage.
What are the implications for public health practice?
High vaccination coverage and compliance with NPIs are essential to control COVID-19 and prevent surges in hospitalizations and deaths in the coming months.
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We evaluated effects of elk and bison herbivory on narrowleaf cottonwood (Populus angustifolia) communities in a semiarid ecosystem in southern Colorado. Cottonwoods in this ecosystem have been aged at ≥300 years old and are among the oldest cottonwood trees in North America. We compared browsing intensity and structural and productivity responses of cottonwood to ungulate herbivory. We compared responses in sites with elk and bison, sites with elk but no bison, and sites where both ungulates were excluded. We found that the majority of browsing on cottonwood occurred during summer in this high desert ecosystem. Areas with both elk and bison had higher browse utilization than areas with only elk, but diet data indicated that elk consumed a much greater proportion of cottonwood than bison. Overall, browse utilization observed in this study was low to moderate compared to other studies, and our results may not be representative of sites experiencing intense year-round herbivory. Removal of all ungulate herbivory led to taller and denser cottonwood suckers; however, other environmental factors, in addition to herbivory, still strongly limit cottonwood growth and recruitment in this ecosystem.
","language":"English","publisher":"Brigham Young University","doi":"10.3398/064.081.0109","usgsCitation":"Zeigenfuss, L.C., and Schoenecker, K., 2021, Effects of elk and bison herbivory on narrowleaf cottonwood: Western North American Naturalist, v. 81, no. 1, p. 97-112, https://doi.org/10.3398/064.081.0109.","productDescription":"16 p.","startPage":"97","endPage":"112","ipdsId":"IP-080677","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Great Sand Dunes ecosystem of the San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.80795288085936,\n 37.615319243559085\n ],\n [\n -105.40557861328125,\n 37.615319243559085\n ],\n [\n -105.40557861328125,\n 37.996162679728116\n ],\n [\n -105.80795288085936,\n 37.996162679728116\n ],\n [\n -105.80795288085936,\n 37.615319243559085\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zeigenfuss, Linda C.","contributorId":280062,"corporation":false,"usgs":false,"family":"Zeigenfuss","given":"Linda","email":"","middleInitial":"C.","affiliations":[{"id":57415,"text":"LZ Ecology","active":true,"usgs":false}],"preferred":false,"id":835965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220504,"text":"70220504 - 2021 - Emerging dominance of Paratrochammina simplissima (Cushman and McCulloch) in the northern Gulf of Mexico following hydrologic and geomorphic changes","interactions":[],"lastModifiedDate":"2025-05-13T16:07:15.741437","indexId":"70220504","displayToPublicDate":"2021-05-14T07:25:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8601,"text":"Estuarine, Coastal, and Shelf Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Emerging dominance of Paratrochammina simplissima (Cushman and McCulloch) in the northern Gulf of Mexico following hydrologic and geomorphic changes","title":"Emerging dominance of Paratrochammina simplissima (Cushman and McCulloch) in the northern Gulf of Mexico following hydrologic and geomorphic changes","docAbstract":"Grand Bay estuary in coastal Mississippi and Alabama (USA) has undergone significant geomorphic changes over the last few centuries as a result of anthropogenic (bridge, road, and hardened shoreline construction) and climatic (extreme storm events) processes, which reduce freshwater input, sediment supply, and degrade barrier islands. To investigate how geomorphic changes may have altered the Grand Bay estuary, sediment push cores were collected for foraminiferal, sedimentological (organic matter content, grain-size distribution), and radiochemical (210Pb,137Cs, and 7Be) analyses. Clay normalized geochronologies were determined with a constant rate of supply model. Based on downcore age-depth relationships, select intervals were analyzed for foraminifera in order to assess alterations in the microfossil assemblage in Grand Bay estuary over the 20th Century. All estuarine samples were low diversity (species richness: 1–10; Fisher's alpha diversity: 0.14–1.75); two species, Ammotium salsum and Paratrochammina simplissima, dominated all downcore assemblages. Paratrochammina simplissima increased in abundance up-core from a minor subsidiary species (median = 4.7% at 19–20 cm) to dominant or co-dominant with A. salsum over the 20th and early 21st Centuries in six cores, comprising up to 60.7% of a single sample. The emerging dominance of P. simplissima since ~1950 along with the reduction of brackish-estuarine taxa and introduction of calcareous species signifies increased salinity and less marsh organic matter preserved in the sediments. While seasonal dissolution limits our ability to chronologically constrain the introduction of calcareous species, P. simplissima, a species not referenced in taxonomic data from the northern Gulf of Mexico until 2012, is well constrained, following its first occurrence in the 1930s.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2021.107312","usgsCitation":"Ellis, A.M., and Smith, C., 2021, Emerging dominance of Paratrochammina simplissima (Cushman and McCulloch) in the northern Gulf of Mexico following hydrologic and geomorphic changes: Estuarine, Coastal, and Shelf Science, v. 255, 107312, 15 p., https://doi.org/10.1016/j.ecss.2021.107312.","productDescription":"107312, 15 p.","ipdsId":"IP-123715","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":385701,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.52484130859375,\n 29.99062347853047\n ],\n [\n -88.363037109375,\n 29.99062347853047\n ],\n [\n -88.363037109375,\n 30.38709188778112\n ],\n [\n -89.52484130859375,\n 30.38709188778112\n ],\n [\n -89.52484130859375,\n 29.99062347853047\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"255","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ellis, Alisha M. 0000-0002-1785-020X aellis@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-020X","contributorId":192957,"corporation":false,"usgs":true,"family":"Ellis","given":"Alisha","email":"aellis@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":815845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":815846,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70231206,"text":"70231206 - 2021 - The 2018 update of the US National Seismic Hazard Model: Ground motion models in the western US","interactions":[],"lastModifiedDate":"2022-05-03T11:58:19.866725","indexId":"70231206","displayToPublicDate":"2021-05-14T06:51:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Ground motion models in the western US","docAbstract":"The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous U.S. NSHM includes significant changes to the underlying ground motion models (GMMs), most of which are necessary to enable the new multi-period response spectra (MPRS) requirements of seismic design regulations that use hazard results for 22 spectral periods and eight site classes. This article focuses on the GMMs used in the western United States (WUS) and is a companion to a recent article on the GMMs used in the central and eastern United States (CEUS). In the WUS, for crustal and subduction earthquakes, two models used in previous versions of the NSHM are excluded to provide consistency over all considered periods and site classes. To more accurately estimate ground motions at long periods in the vicinity of Los Angeles, San Francisco, Salt Lake City, and Seattle, the 2018 NSHM incorporates deep sedimentary basin depth from local seismic velocity models. The subduction GMMs considered lack basin depth terms and are modified to include an additional scale factor to account for this. This article documents the WUS GMMs used in the 2018 NSHM update and provides detail on the changes to GMM medians, aleatory variability, epistemic uncertainty, and site-effect models. It compares each of these components with those considered in prior NSHMs and discusses their total effect on hazard.
In environmental participatory modeling (PM), both computer and non-computer-based modeling techniques are used to aid participatory problem description, solution, and decision-making actions in environmental contexts. Although many PM case studies have been published, few efforts have sought to systematically describe and understand dominant PM processes or establish best practices for PM. As a first step, we have reviewed a random sample of environmental PM case study articles (n = 60) using a novel PM process evaluation instrument. We found that significant work likely remains for PM to fully support participatory and integrated planning processes. While PM reports systematically address knowledge integration and learning, they often neglect the facilitation of a multi-value perspective within a democratic process, and the integration across organizations within a governance system. If not reported, we suspect these aspects are also neglected in practice. We conclude with key research and practice issues for improving PM as an approach for real-world participatory planning and governance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105073","usgsCitation":"Hedelin, B., Gray, S., Woehlke, S., BenDor, T., Singer, A., Jordan, R., Zellner, M., Giabbanelli, P., Glynn, P., Jenni, K., Jetter, A., Kolgani, N., Laursen, B., Leong, K.M., Schmitt Olabisi, L., and Sterling, E., 2021, What's left before participatory modeling can fully support real-world environmental planning processes: A case study review: Environmental Modelling & Software, v. 143, 105073, 15 p., https://doi.org/10.1016/j.envsoft.2021.105073.","productDescription":"105073, 15 p.","ipdsId":"IP-129309","costCenters":[],"links":[{"id":452273,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105073","text":"Publisher Index Page"},{"id":389153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"143","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hedelin, B.","contributorId":265685,"corporation":false,"usgs":false,"family":"Hedelin","given":"B.","affiliations":[],"preferred":false,"id":823192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, S.","contributorId":265686,"corporation":false,"usgs":false,"family":"Gray","given":"S.","email":"","affiliations":[],"preferred":false,"id":823193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woehlke, S.","contributorId":265687,"corporation":false,"usgs":false,"family":"Woehlke","given":"S.","email":"","affiliations":[],"preferred":false,"id":823194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"BenDor, T. K.","contributorId":19011,"corporation":false,"usgs":true,"family":"BenDor","given":"T. K.","affiliations":[],"preferred":false,"id":823195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singer, A.","contributorId":265688,"corporation":false,"usgs":false,"family":"Singer","given":"A.","affiliations":[],"preferred":false,"id":823196,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordan, R.","contributorId":62742,"corporation":false,"usgs":true,"family":"Jordan","given":"R.","email":"","affiliations":[],"preferred":false,"id":823197,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zellner, M.","contributorId":265689,"corporation":false,"usgs":false,"family":"Zellner","given":"M.","email":"","affiliations":[],"preferred":false,"id":823198,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Giabbanelli, P.","contributorId":265690,"corporation":false,"usgs":false,"family":"Giabbanelli","given":"P.","affiliations":[],"preferred":false,"id":823199,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glynn, P.","contributorId":56394,"corporation":false,"usgs":true,"family":"Glynn","given":"P.","affiliations":[],"preferred":false,"id":823200,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jenni, K.","contributorId":131113,"corporation":false,"usgs":false,"family":"Jenni","given":"K.","email":"","affiliations":[{"id":7250,"text":"Insight Decisions LCC, 2200 Quitman Street, Denver, CO 80212","active":true,"usgs":false}],"preferred":false,"id":823201,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jetter, A","contributorId":265691,"corporation":false,"usgs":false,"family":"Jetter","given":"A","email":"","affiliations":[],"preferred":false,"id":823202,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kolgani, N.","contributorId":265692,"corporation":false,"usgs":false,"family":"Kolgani","given":"N.","email":"","affiliations":[],"preferred":false,"id":823203,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Laursen, B.","contributorId":265693,"corporation":false,"usgs":false,"family":"Laursen","given":"B.","email":"","affiliations":[],"preferred":false,"id":823204,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Leong, K. M.","contributorId":265694,"corporation":false,"usgs":false,"family":"Leong","given":"K.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":823205,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schmitt Olabisi, L.","contributorId":265695,"corporation":false,"usgs":false,"family":"Schmitt Olabisi","given":"L.","email":"","affiliations":[],"preferred":false,"id":823206,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sterling, E.","contributorId":265696,"corporation":false,"usgs":false,"family":"Sterling","given":"E.","email":"","affiliations":[],"preferred":false,"id":823207,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70220443,"text":"70220443 - 2021 - Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species","interactions":[],"lastModifiedDate":"2021-08-03T16:11:08.337078","indexId":"70220443","displayToPublicDate":"2021-05-13T08:05:48","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species","docAbstract":"Ecosystem-based management relies on understanding how perturbations influence ecosystem structure and function (e.g., invasive species, exploitation, abiotic changes). However, data on unimpacted systems are scarce; therefore, we often rely on impacted systems to make inferences about ‘natural states.’ Among the Laurentian Great Lakes, Lake Superior provides a unique case study to address non-native species impacts because the food web is dominated by native species. Additionally, Lake Superior is both vertically (benthic versus pelagic) and horizontally (nearshore versus offshore) structured by depth, providing an opportunity to compare the function of these sub-food webs. We developed an updated Lake Superior EcoPath model using data from the 2005/2006 lake-wide multi-agency surveys covering multiple trophic levels. We then compared trophic transfer efficiency (TTE) to previously published EcoPath models. Finally, we compared ecosystem function of the 2005/2006 ecosystem to that with non-native linkages removed and compared native versus non-native species-specific approximations of TTE and trophic flow. Lake Superior was relatively efficient (TTE = 0.14) compared to systems reported in a global review (average TTE = 0.09), and the microbial loop was highly efficient (TTE > 0.20). Non-native species represented a very small proportion (<0.01%) of total biomass and were generally more efficient and had higher trophic flow compared to native species. Our results provide valuable insight into the importance of the microbial loop and represent a baseline estimate of non-native species impacts on Lake Superior. Finally, this work is a starting point for further model development to predict future changes in the Lake Superior ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.04.010","usgsCitation":"Mathias, B.G., Hrabik, T.R., Hoffman, J.C., Gorman, O., Seider, M., Sierszen, M.E., Vinson, M., Yule, D.L., and Yurista, P.M., 2021, Trophic transfer efficiency in the Lake Superior food web: Assessing the impacts of non-native species: Journal of Great Lakes Research, v. 47, no. 4, p. 1146-1158, https://doi.org/10.1016/j.jglr.2021.04.010.","productDescription":"13 p.","startPage":"1146","endPage":"1158","ipdsId":"IP-115192","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452278,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9067395","text":"External Repository"},{"id":436366,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W93YXH","text":"USGS data release","linkHelpText":"Compilation of Data for Parameterization of an Ecopath Model of Lake Superior at the Beginning of the 21st Century (2001-2016)"},{"id":385642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.63671874999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 46.195042108660154\n ],\n [\n -83.84765624999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 49.83798245308484\n ],\n [\n -92.63671874999997,\n 46.195042108660154\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathias, Bryan G.","contributorId":240743,"corporation":false,"usgs":false,"family":"Mathias","given":"Bryan","email":"","middleInitial":"G.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":815547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":815548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoffman, Joel C.","contributorId":84244,"corporation":false,"usgs":false,"family":"Hoffman","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815549,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman, Owen 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":216889,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seider, Michael J.","contributorId":258016,"corporation":false,"usgs":false,"family":"Seider","given":"Michael J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sierszen, Michael E.","contributorId":63320,"corporation":false,"usgs":false,"family":"Sierszen","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815552,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815553,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815554,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yurista, Peder M.","contributorId":127358,"corporation":false,"usgs":false,"family":"Yurista","given":"Peder","email":"","middleInitial":"M.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":815555,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221058,"text":"70221058 - 2021 - Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range","interactions":[],"lastModifiedDate":"2021-08-03T16:15:41.13252","indexId":"70221058","displayToPublicDate":"2021-05-12T10:44:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range","docAbstract":"Invasive species are a global threat to ecosystem biodiversity and function; non-native grass invasion has been particularly problematic in sparsely vegetated ecosystems such as open dunes. Native plant population responses to invasion, however, are infrequently translated to landscape scales, limiting the effectiveness of these data for addressing conservation issues. We quantified population density, total population size, and age class distribution of the federally-endangered plant species Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii), at sites along a non-native grass invasion gradient in California, USA. We then scaled relationships between invasion and plant density across the species’ range using spatial models and remote sensing data. Adult and juvenile O. deltoides subsp. howellii densities were more than 10 times higher in non-invaded areas (grids with 10% total plant cover) when compared to highly-invaded areas (grids with 80% total plant cover). The ratio of O. deltoides subsp. howellii juveniles to adults decreased to less than 1 at 54% total cover, highlighting sensitivity of the regeneration niche to invasion. Spatial models mapped hotspots of O. deltoides subsp. howellii abundance and population structure across the landscape at sub-meter scales. Scaling the impacts of increasing invasion on plant species of conservation concern holds promise when coupled with remote sensing approaches, especially in naturally low-cover ecosystems where readily available metrics (e.g., Normalized Difference Vegetation Index) can be used to quantify invasion. These spatial models inform how future invasive species management may influence population size and spatial distribution of species of conservation concern.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-021-02516-5","usgsCitation":"Jones, S., Kennedy, A., Freeman, C.M., and Thorne, K., 2021, Intensity of grass invasion negatively correlated with population density and age structure of an endangered dune plant across its range: Biological Invasions, v. 23, p. 2451-2471, https://doi.org/10.1007/s10530-021-02516-5.","productDescription":"21 p.","startPage":"2451","endPage":"2471","ipdsId":"IP-126563","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":436368,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PRVA0M","text":"USGS data release","linkHelpText":"Antioch Dunes evening primrose (Oenothera deltoides subsp. howellii) juvenile and adult abundance across the known range, California, USA (2019)"},{"id":386030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Antioch","otherGeospatial":"San Francisco Bay-Delta region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.92729949951172,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 37.998597644907385\n ],\n [\n -121.6691207885742,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 38.089174937729794\n ],\n [\n -121.92729949951172,\n 37.998597644907385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2021-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Anna 0000-0002-6530-7498","orcid":"https://orcid.org/0000-0002-6530-7498","contributorId":259164,"corporation":false,"usgs":true,"family":"Kennedy","given":"Anna","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Chase M. 0000-0003-4211-6709 cfreeman@usgs.gov","orcid":"https://orcid.org/0000-0003-4211-6709","contributorId":150052,"corporation":false,"usgs":true,"family":"Freeman","given":"Chase","email":"cfreeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":816669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222453,"text":"70222453 - 2021 - Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","interactions":[],"lastModifiedDate":"2021-11-01T15:38:15.192062","indexId":"70222453","displayToPublicDate":"2021-05-12T08:43:23","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":"Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars","docAbstract":"Structure‐from‐motion (SfM) modeling has dramatically increased the speed of generating geometrically accurate orthophoto mosaics of paleoseismic trenches, but some aspects of this technique remain time and labor intensive. Model accuracy relies on control points to establish scale, reduce distortion, and orient 3D models. Traditional SfM methods use total station or Global Navigation Satellite System (GNSS) surveys to constrain models, but collecting control points along a vertical trench wall is often inhibited by poor line of sight to the survey sensor or limited sky view and requires many hours in the field and office. We used physical scale bars printed with coded targets to constrain SfM models of a dusty, 46‐m‐long trench excavation across the Teton fault (Wyoming, U.S.A.). We present a workflow for generating quick and accurate 3D SfM models and orthophoto mosaics and compare the effectiveness of using scale bar, GNSS, and total‐station control in the models. Our results show that the scale bar model deviates from total station survey points by an average of 3.1 cm (maximum of 5.3 cm). In addition, the scale‐bar model only deviates an average of 1.7 cm (maximum 3.5 cm) when compared to the best model alternative, the SfM model controlled by the total station survey. Scale bars eliminate several hours needed to collect and incorporate control points from total station or GNSS surveys and significantly simplify the workflow, at the cost of slightly increased 3D model and orthophoto mosaic error. Our results further suggest that trench models can be constrained with at least four physical scale bars, but using five to six physical scale bars provides redundant control for field deployment and model optimization. The scale bar method for paleoseismic trenches proves to be portable and fast, minimizes the need for specialized survey equipment, and maintains model accuracy needed for mapping trench walls.
Algal and cyanobacterial blooms can foul water systems, inhibit recreation, and produce cyanotoxins, which can be toxic to humans, domestic animals, and wildlife. Blooms that recur yearly present a special challenge, in that chronic effects of most cyanotoxins are unknown. To better understand cyanotoxin timing, possible environmental triggers, and inter-relations among taxa and toxins in bloom communities, recurring cyanobacterial blooms were investigated at three recreational sites in Kabetogama Lake in Voyageurs National Park from 2016-2019. Results indicated that peak neurotoxin concentrations occurred before peak microcystin concentrations and that toxin-forming cyanobacteria were present before visible blooms, which is a serious human health concern. Two cyanotoxin mixture models (MIX) and two microcystin (MC) models were developed using near-real-time environmental variables and additional comprehensive variables based on laboratory analyses. Comprehensive models explained more variability than the environmental models and neither MIX model was a better fit than the MC models. However, the MIX models produced no false negatives, indicating that all observations above human-health regulatory guidelines were simulated by the MIX models. The results show that a model based on a cyanotoxin mixture is more protective of human health than a model based on microcystin alone. In 2019, 7 of 19 toxins were detected in various mixtures. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated with microcystin-YR, while Pseudanabaena sp. and Synechococcus sp. were negatively correlated to several toxins. Jaccard and Sorenson indices indicated strong same-day similarities among the three bloom communities. Nitrogen-fixing cyanobacteria were present at every site, and when combined with internal loading of phosphorus, might explain similarities among sites, and why seasonal differences, even in samples from the same site, were stronger. Information from this dissertation adds to the body of work on recurring blooms and under-studied toxins and toxin mixtures, providing a better understanding of future research options for freshwater cyanotoxins in and outside of Voyageurs National Park.
","language":"English","publisher":"North Dakota State University","usgsCitation":"Christensen, V., 2021, Freshwater cyanotoxin mixtures in recurring cyanobacterial blooms in Voyageurs National Park, 221 p.","productDescription":"221 p.","ipdsId":"IP-128041","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409284,"type":{"id":15,"text":"Index Page"},"url":"https://www.proquest.com/docview/2547519599","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake, Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.7287375311439,\n 48.44384887858732\n ],\n [\n -92.74528481592849,\n 48.46823569471036\n ],\n [\n -92.85651934142741,\n 48.45238559671293\n ],\n [\n -92.80320031267578,\n 48.47311165228035\n ],\n [\n -92.9355785909554,\n 48.46823569471036\n ],\n [\n -93.01371854688433,\n 48.52184546050012\n ],\n [\n -93.05508675884663,\n 48.53280411143439\n ],\n [\n -93.11300225559437,\n 48.51271143988237\n ],\n [\n -93.11759872359,\n 48.48469017375146\n ],\n [\n -93.06703757563596,\n 48.47494001557638\n ],\n [\n -93.06060252044176,\n 48.44628808733975\n ],\n [\n -93.02199218927704,\n 48.431041110668644\n ],\n [\n -92.98062397731476,\n 48.41151830276564\n ],\n [\n -92.95120658214137,\n 48.426161111635196\n ],\n [\n -92.92822424216214,\n 48.42189072806485\n ],\n [\n -92.9034033149849,\n 48.43226103720582\n ],\n [\n -92.86755086461727,\n 48.42189072806485\n ],\n [\n -92.80871607427095,\n 48.410908094197964\n ],\n [\n -92.78113726629607,\n 48.40480560576938\n ],\n [\n -92.7287375311439,\n 48.44384887858732\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856888,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220886,"text":"70220886 - 2021 - Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","interactions":[],"lastModifiedDate":"2021-06-30T19:00:04.291567","indexId":"70220886","displayToPublicDate":"2021-05-12T07:16:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","docAbstract":"The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.
Maintaining functional connectivity is critical for the long-term conservation of wildlife populations. Landscape genomics provides an opportunity to assess long-term functional connectivity by relating environmental variables to spatial patterns of genomic variation resulting from generations of movement, dispersal and mating behaviors. Identifying landscape features associated with gene flow at large geographic scales for highly mobile species is becoming increasingly possible due to more accessible genomic approaches, improved analytical methods and enhanced computational power. We characterized the genetic structure and diversity of migratory mule deer Odocoileus hemionus using 4051 single nucleotide polymorphisms in 406 individuals sampled across multiple habitats throughout Wyoming, USA. We then identified environmental variables associated with genomic variation within genetic groups and statewide using a stepwise approach to first evaluate nonlinear relationships of landscape resistance with genetic distances and then use mixed-effects modeling to choose top landscape genomic models. We identified three admixed genetic groups of mule deer and found that environmental variables associated with gene flow varied among genetic groups, revealing scale-dependent and regional variation in functional connectivity. At the statewide scale, more gene flow occurred in areas with low elevation and mixed habitat. In the southern genetic group, more gene flow occurred in areas with low elevation. In the northern genetic group, more gene flow occurred in grassland and forest habitats, while highways and energy infrastructure reduced gene flow. In the western genetic group, the null model of isolation by distance best represented genetic patterns. Overall, our findings highlight the role of different seasonal ranges on mule deer genetic connectivity, and show that anthropogenic features hinder connectivity. This study demonstrates the value of combining a large, genome-wide marker set with recent advances in landscape genomics to evaluate functional connectivity in a wide-ranging migratory species.