Demographic models enhance understanding of drivers of population growth and inform conservation efforts to prevent population declines and extinction. For species with complex life histories, however, parameterizing demographic models is challenging because some life stages can be difficult to study directly. Integrated population models (IPMs) empower researchers to estimate vital rates for organisms that have cryptic or widely dispersing early life stages by integrating multiple demographic data sources. For a stream‐inhabiting frog (Rana boylii) that is declining through much of its range in Oregon and California, USA, we collected egg‐mass counts and capture–mark–recapture data on adults from two populations in California to fit IPMs that estimate adult abundance and the survival rate of both marked and unobserved life stages. Estimates of adult abundance based on long‐term monitoring of egg‐mass counts showed that study populations fluctuated greatly inter‐annually but were stable at longer timescales (i.e., decades). Adult female survival during 5–6 yr of capture–mark–recapture study periods was nearly equal in each population. Survival rate of R. boylii eggs to the subadult stage is low on average (0.002) but highly variable among years depending on post‐oviposition stream flow. Population viability analysis showed that survival of adult and subadult life stages has the greatest proportional effect on population growth; the survival of egg and tadpole life stages, however, is more malleable by management interventions. For example, simulations showed head‐starting of tadpoles, salvaging stranded egg masses, and limiting aseasonal pulsed flows could dramatically reduce the threat of extirpation. This study demonstrates the value of integrating multiple demographic data sources to construct models of population dynamics in species with complex life histories.
Plague is a non-native disease in North America that reduces survival of many mammals. Previous studies have focused on epizootic plague which causes acute mortality events and dramatic declines in local abundance. We know much less about enzootic plague which causes less punctuated reductions in survival and abundance of infected populations. As a result, enzootic plague is much more difficult to detect because changes in population attributes are more subtle and Yersinia pestis prevalence is likely lower relative to epizootic plague outbreaks. The northern Idaho ground squirrel (Urocitellus brunneus) is a threatened species which coexists with Columbian ground squirrels (Urocitellus columbianus) and yellow-pine chipmunks (Neotamias amoenus) throughout their restricted distribution in central Idaho. Columbian ground squirrels and yellow-pine chipmunks are more abundant and widespread than northern Idaho ground squirrels and both are known hosts for plague. Hence, enzootic plague may be one cause of rarity for northern Idaho ground squirrels but its effect on this threatened species has not been evaluated. We conducted three controlled and randomized field experiments to examine the effects of plague in northern Idaho ground squirrels and the two coexisting species: 1) a plague vaccine experiment, 2) a paired flea-reduction experiment, and 3) a non-paired flea-reduction experiment. For Experiment 1, we hypothesized that if enzootic plague is present, vaccinated animals would have higher survival. Furthermore, Experiments 2 and 3 tested the prediction that untreated, control animals should have lower survival than those in areas where fleas are experimentally removed or reduced because fleas are the main vector for plague. In the plague vaccine experiment, vaccinated chipmunks had 4.65% higher apparent survival compared to chipmunks that received a placebo for intervals when the vaccine is believed to be effective. Apparent annual survival increased for all three species on experimental flea-reduction plots compared to non-treated plots for the paired experiment but results were mixed for the non-paired experiment. Taken together, our results suggest that enzootic plague is present and negatively impacting survival of northern Idaho ground squirrels and two coexisting species.
Climate change and non-native species are considered two of the biggest threats to native salmonids in North America. We evaluated how non-native salmonids and stream temperature and discharge were associated with Yellowstone cutthroat trout (Oncorhynchus clarkii bouvieri) distribution, abundance, and body size to gain a more complete understanding of the existing threats to native populations. Allopatric Yellowstone cutthroat trout were distributed across a wide range of average August temperatures (3.2 to 17.7 °C), but occurrence significantly declined at colder temperatures (<10 °C) with increasing numbers of non-natives. At warmer temperatures, occurrence remained high, despite sympatry with non-natives. Yellowstone cutthroat trout relative abundance was significantly reduced with increasing abundance of non-natives, with the greatest impacts at colder temperatures. Body sizes of large Yellowstone cutthroat trout (90th percentile) significantly increased with warming temperatures and larger stream size, highlighting the importance of access to these more productive stream segments. Considering multiple population-level attributes demonstrates the complexities of how native salmonids (such as Yellowstone cutthroat trout) are likely to be affected by shifting climates.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0408","usgsCitation":"Al-Chokhachy, R., Lien, M., Shepard, B.B., and High, B., 2021, The interactive effects of stream temperature, stream size, and non-native species on Yellowstone cutthroat trout: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 8, p. 1073-1083, https://doi.org/10.1139/cjfas-2020-0408.","productDescription":"11 p.","startPage":"1073","endPage":"1083","ipdsId":"IP-108988","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":501010,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/106639","text":"External Repository"},{"id":396605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Wyoming","otherGeospatial":"Teton River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.74493408203125,\n 43.38508989465156\n ],\n [\n -110.7861328125,\n 43.47883342917123\n ],\n [\n -110.70098876953125,\n 43.66588482492509\n ],\n [\n -110.52520751953125,\n 43.82858280301419\n ],\n [\n -110.53619384765625,\n 43.92559366355069\n ],\n [\n -110.70098876953125,\n 44.05995928349327\n ],\n [\n -110.58837890625,\n 44.32384807250689\n ],\n [\n -110.85479736328125,\n 44.4377021634654\n ],\n [\n -111.26129150390625,\n 44.4808302785626\n ],\n [\n -111.37664794921875,\n 44.50238238974582\n ],\n [\n -111.61285400390625,\n 44.374913492661456\n ],\n [\n -112.2802734375,\n 44.321883129398586\n ],\n [\n -112.52471923828125,\n 44.29436701558004\n ],\n [\n -112.69500732421875,\n 44.16447445668456\n ],\n [\n -112.66204833984375,\n 44.04219306625442\n ],\n [\n -112.2637939453125,\n 43.739352079154706\n ],\n [\n -111.92596435546875,\n 43.69965122967144\n ],\n [\n -111.67877197265624,\n 43.59232754538541\n ],\n [\n -111.4178466796875,\n 43.574421623084234\n ],\n [\n -111.21185302734375,\n 43.401056495052906\n ],\n [\n -111.06353759765625,\n 43.229195113965005\n ],\n [\n -110.74493408203125,\n 43.38508989465156\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K.","contributorId":287433,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":836755,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lien, Michael","contributorId":287434,"corporation":false,"usgs":false,"family":"Lien","given":"Michael","email":"","affiliations":[{"id":61583,"text":"Friends of the Teton River","active":true,"usgs":false}],"preferred":false,"id":836756,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":836757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"High, Brett","contributorId":274499,"corporation":false,"usgs":false,"family":"High","given":"Brett","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":836758,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217009,"text":"70217009 - 2021 - Letter to the editor: Using classification systems to integrate ecosystem services with decision making tools","interactions":[],"lastModifiedDate":"2021-04-14T14:12:31.138583","indexId":"70217009","displayToPublicDate":"2021-02-14T09:05:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Letter to the editor: Using classification systems to integrate ecosystem services with decision making tools","docAbstract":"No abstract available.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2021.101257","usgsCitation":"Finisdore, J., Lamothe, K.A., Rhodes, C., Obst, C., Booth, P., Haines-Young, R., Russell, M., Houdet, J.R., Maynard, S., Wielgus, J., and Rowcroft, P., 2021, Letter to the editor: Using classification systems to integrate ecosystem services with decision making tools: Ecosystem Services, v. 48, 101257, 2 p., https://doi.org/10.1016/j.ecoser.2021.101257.","productDescription":"101257, 2 p.","ipdsId":"IP-123739","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":453448,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8048124","text":"Publisher Index Page"},{"id":385091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Finisdore, John","contributorId":245879,"corporation":false,"usgs":false,"family":"Finisdore","given":"John","email":"","affiliations":[{"id":49358,"text":"IDEEA, in Melbourne AUSL","active":true,"usgs":false}],"preferred":false,"id":807253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamothe, Karl A.","contributorId":245880,"corporation":false,"usgs":false,"family":"Lamothe","given":"Karl","email":"","middleInitial":"A.","affiliations":[{"id":49360,"text":"graduate student in Canada","active":true,"usgs":false}],"preferred":false,"id":807254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rhodes, Charles 0000-0002-9040-3684","orcid":"https://orcid.org/0000-0002-9040-3684","contributorId":245881,"corporation":false,"usgs":true,"family":"Rhodes","given":"Charles","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":807255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Obst, Carl","contributorId":176851,"corporation":false,"usgs":false,"family":"Obst","given":"Carl","email":"","affiliations":[],"preferred":false,"id":814240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Booth, Pieter","contributorId":257431,"corporation":false,"usgs":false,"family":"Booth","given":"Pieter","email":"","affiliations":[],"preferred":false,"id":814241,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haines-Young, Roy","contributorId":257432,"corporation":false,"usgs":false,"family":"Haines-Young","given":"Roy","email":"","affiliations":[],"preferred":false,"id":814242,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Russell, Marc","contributorId":257433,"corporation":false,"usgs":false,"family":"Russell","given":"Marc","affiliations":[],"preferred":false,"id":814243,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Houdet, Joel Robert","contributorId":257434,"corporation":false,"usgs":false,"family":"Houdet","given":"Joel","email":"","middleInitial":"Robert","affiliations":[],"preferred":false,"id":814244,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Maynard, Simone","contributorId":191652,"corporation":false,"usgs":false,"family":"Maynard","given":"Simone","email":"","affiliations":[],"preferred":false,"id":814245,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wielgus, Jeffrey","contributorId":257435,"corporation":false,"usgs":false,"family":"Wielgus","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":814246,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rowcroft, Petrina","contributorId":257436,"corporation":false,"usgs":false,"family":"Rowcroft","given":"Petrina","email":"","affiliations":[],"preferred":false,"id":814247,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70237906,"text":"70237906 - 2021 - Evidence of preferential flow activation in the vadose zone via geophysical monitoring","interactions":[],"lastModifiedDate":"2022-10-31T11:57:50.049069","indexId":"70237906","displayToPublicDate":"2021-02-14T06:52:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of preferential flow activation in the vadose zone via geophysical monitoring","docAbstract":"Coral reefs generate substantial volumes of carbonate sediment, which is redistributed throughout the reef‐lagoon system. However, there is little understanding of the specific processes that transport this sediment produced on the outer portions of coral reefs throughout a reef‐lagoon system. Furthermore, the separate contributions of currents, sea‐swell waves, and infragravity waves to transport, which are all strongly influenced by the presence of a reef, is not fully understood. Here, we show that in reef‐lagoon systems most suspended sediment is transported close to the seabed and can, at times, be suspended higher in the water column during oscillatory flow transitions (i.e., near slack flow) at sea‐swell wave frequencies, and during the peak onshore oscillatory velocity phase at infragravity wave frequencies. While these wave frequencies contribute to the transport of suspended sediment offshore and onshore, respectively, the net flux is small. Mean currents are the primary transport mechanism and responsible for almost 2 orders of magnitude more suspended‐sediment flux than sea‐swell and infragravity waves. Whilst waves may not be the primary mechanism for the transport of sediment, our results suggest they are an important driver of sediment suspension from the seabed, as well as contributing to the partitioning of sediment grain sizes from the reef to the shoreline. As the ocean wave climate changes, sea level rises, and the composition of reef benthic communities change, the relative importance of mean currents, sea‐swell waves, and infragravity waves is likely to change, and this will affect how sediment is redistributed throughout reef‐lagoon systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC017010","usgsCitation":"Pomeroy, A., Storlazzi, C.D., Rosenberger, K.J., Lowe, R., Hansen, J., and Buckley, M.L., 2021, The contribution of currents, sea-swell waves, and infragravity waves to suspended-sediment transport across a coral reef-lagoon system.: JGR Oceans, v. 126, no. 3, e2020JC017010, 26 p., https://doi.org/10.1029/2020JC017010.","productDescription":"e2020JC017010, 26 p.","ipdsId":"IP-124202","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jc017010","text":"Publisher Index Page"},{"id":385282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Ningaloo Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 113.6370849609375,\n -22.550610920226646\n ],\n [\n 113.69888305664062,\n -22.532853707527117\n ],\n [\n 113.76068115234374,\n -22.38690459799015\n ],\n [\n 113.8623046875,\n -22.146707780012616\n ],\n [\n 113.98452758789062,\n -21.86532228248991\n ],\n [\n 113.27041625976562,\n -21.90737455082829\n ],\n [\n 113.13858032226562,\n -22.673580199535557\n ],\n [\n 113.27316284179688,\n -22.823023136184315\n ],\n [\n 113.66729736328125,\n -22.72172372713301\n ],\n [\n 113.6810302734375,\n -22.658373466642733\n ],\n [\n 113.653564453125,\n -22.58104653946133\n ],\n [\n 113.6370849609375,\n -22.550610920226646\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Pomeroy, Andrew","contributorId":182033,"corporation":false,"usgs":false,"family":"Pomeroy","given":"Andrew","affiliations":[],"preferred":false,"id":814613,"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":814614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","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":814615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowe, Ryan","contributorId":177845,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[],"preferred":false,"id":814616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff","contributorId":149139,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[],"preferred":false,"id":814617,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":814618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227143,"text":"70227143 - 2021 - Historical data provide important context for understanding declines in Cutthroat Trout","interactions":[],"lastModifiedDate":"2022-01-03T15:37:47.456251","indexId":"70227143","displayToPublicDate":"2021-02-13T08:38:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Historical data provide important context for understanding declines in Cutthroat Trout","docAbstract":"We used historical stocking and population survey records of Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri and other salmonids in the North Fork Shoshone River drainage, Wyoming to summarize fish stocking history and population trends. Based on 98 years of historical records, we found that despite extensive stocking of Yellowstone Cutthroat Trout and minimal stocking of nonnative salmonids after about 1950, populations of wild Yellowstone Cutthroat Trout declined relative to those of nonnative salmonid species. The timing of increases in nonnative salmonids (1970s) did not coincide with their period of most intensive stocking (1935–1950). It is plausible that Yellowstone Cutthroat Trout populations persisted because of high levels of supplemental stocking from 1935 to 1965 and declined with reduced stocking efforts in the 1970s, thereby allowing the increase of introduced nonnative salmonids. The establishment of nonnative salmonids likely further reduced stocking success of Yellowstone Cutthroat Trout due to competition and hybridization. This study demonstrates that an understanding of long-term stocking records and population survey data can be useful for developing and implementing successful management frameworks for the conservation of imperiled fish populations across the United States.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10593","usgsCitation":"Nordberg, B.J., Mandeville, E., Walters, A.W., Burckhardt, J.C., and Wagner, C.E., 2021, Historical data provide important context for understanding declines in Cutthroat Trout: North American Journal of Fisheries Management, v. 41, no. 3, p. 809-819, https://doi.org/10.1002/nafm.10593.","productDescription":"11 p.","startPage":"809","endPage":"819","ipdsId":"IP-107228","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":393734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"North Fork Shoshone River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 44.40\n ],\n [\n -109,\n 44.40\n ],\n [\n -109,\n 44.55\n ],\n [\n -110,\n 44.55\n ],\n [\n -110,\n 44.40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nordberg, Brittany J.","contributorId":270690,"corporation":false,"usgs":false,"family":"Nordberg","given":"Brittany","email":"","middleInitial":"J.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":829772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mandeville, Elizabeth G.","contributorId":270691,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth G.","affiliations":[{"id":56198,"text":"uwyo","active":true,"usgs":false}],"preferred":false,"id":829773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":829771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burckhardt, Jason C.","contributorId":270692,"corporation":false,"usgs":false,"family":"Burckhardt","given":"Jason","email":"","middleInitial":"C.","affiliations":[{"id":56161,"text":"wygf","active":true,"usgs":false}],"preferred":false,"id":829774,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, Catherine E.","contributorId":270693,"corporation":false,"usgs":false,"family":"Wagner","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":56198,"text":"uwyo","active":true,"usgs":false}],"preferred":false,"id":829775,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219530,"text":"70219530 - 2021 - Would you like to know more? The effect of personalized wildfire risk information and social comparisons on information-seeking behavior in the wildland–urban interface","interactions":[],"lastModifiedDate":"2021-04-13T13:24:44.123688","indexId":"70219530","displayToPublicDate":"2021-02-13T08:23:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Would you like to know more? The effect of personalized wildfire risk information and social comparisons on information-seeking behavior in the wildland–urban interface","docAbstract":"Private landowners are important actors in landscape-level wildfire risk management. Accordingly, wildfire programs and policy encourage wildland–urban interface homeowners to engage with local organizations to properly mitigate wildfire risk on their parcels. We investigate whether parcel-level wildfire risk assessment data, commonly used to inform community-level planning and resource allocation, can be used to “nudge” homeowners to engage further with a regional wildfire organization. We sent 4564 households in western Colorado a letter that included varying combinations of risk information about their community, their parcels, and their neighbors’ parcels, and we measured follow-up visits to a personalized “Web site”. We find that the effect of providing parcel-specific information depends on baseline conditions: Informing homeowners about their property’s wildfire risk increases information-seeking among homeowners of the highest-risk parcels by about 5 percentage points and reduces information-seeking among homeowners of lower-risk parcels by about 6 percentage points. Parcel-specific information also increases the overall response in the lowest risk communities by more than 10 percentage points. Further, we find evidence of a 6-percentage point increase in response rate associated with receiving a social comparison treatment that signals neighboring properties as being either low or moderate risk on average. These results, especially considered against the 13 percent overall average response rate, offer causal evidence that providing parcel-specific wildfire risk information can influence behavior. As such, we demonstrate the effectiveness of simple outreach in engaging wildland–urban interface homeowners with wildfire risk professionals in ways that leverage existing data.
Drainage (or stormwater) systems are a potential source of marine debris. Approximately 67 km (33%) of the land along the Mediterranean coast of Israel is considered urban, covered by concrete and asphalt. The purpose of the present pilot study was to determine the composition of the solid waste in a drainage system and evaluate to what extent municipal sources contribute to marine debris. We sampled the waste in Netanya, a medium-size city (245,000 residents) on the central Mediterranean coast of Israel. Samples were taken from seven street stormwater receptacles prior to the first significant rain and then on the beach near a drainage outlet, a few hours after this substantial rain. In terms of composition of the debris, paper, cigarette butts, and sanitary items made up a higher proportion of the drainage system debris than those items did on the beach. In contrast, single-use items, polystyrene pieces, bottle caps, and plastic drinking bottles composed more of the debris on the beaches compared to the debris in the drainage system. Overall, we found that municipal stormwater systems contribute significant amounts of solid waste to marine debris on Israeli beaches. Preventing the waste from reaching the streets might help reduce marine debris on the beaches, especially at the beginning of the rainy season. There are multiple solutions, but all will require creativity and resources and constant maintenance. Educating the public to prevent disposal of solid waste items in the street is also important as a way to reduce terrestrial as well as marine debris.
Exposure to high concentration geogenic arsenic via groundwater is a worldwide health concern. Well installation introduces oxic drilling fluids and hypochlorite (a strong oxidant) for disinfection, thus inducing geochemical disequilibrium. Well installation causes changes in geochemistry lasting 12 + months, as illustrated in a recent study of 250 new domestic wells in Minnesota, north-central United States. One study well had extremely high initial arsenic (1550 µg/L) that substantially decreased after 15 months (5.2 µg/L). The drilling and development of the study well were typical and ordinary; nothing observable indicated the very high initial arsenic concentration. We hypothesized that oxidation of arsenic-containing sulfides (which lowers pH) combined with low pH dissolution of arsenic-bearing Fe (oxyhydr)oxides caused the very high arsenic concentration. Geochemical equilibrium considerations and modeling supported our hypothesis. Groundwater equilibrium redox conditions are poised at the Fe(III)(s)/Fe(II)(aq) stability boundary, indicating arsenic-bearing Fe (oxyhydr)oxide mineral sensitivity to pH and redox changes. Changing groundwater geochemistry can have negative implications for home water treatment (e.g., reduced arsenic removal efficiency, iron fouling), which can lead to ongoing but unrecognized hazard of arsenic exposure from domestic well water. Our results may inform arsenic mobilization processes and geochemical sensitivity in similarly complex aquifers in Southeast Asia and elsewhere.
Lawns as a landcover change substantially alter evapotranspiration, CO2, and energy exchanges and are of rising importance considering their spatial extent. We contrast eddy covariance (EC) flux measurements collected in the Denver, Colorado, USA metropolitan area in 2011 and 2012 over a lawn and a xeric tallgrass prairie. Close linkages between seasonal vegetation development, energy fluxes, and net ecosystem exchange (NEE) of CO2 were found. Irrigation of the lawn modified energy and CO2 fluxes and greatly contributed to differences observed between sites. Due to greater water inputs (precipitation + irrigation) at the lawn in this semi-arid climate, energy partitioning at the lawn was dominated by latent heat (LE) flux. As a result, evapotranspiration (ET) of the lawn was more than double that of tallgrass prairie (2011: 639(±17) mm vs. 302(±9) mm; 2012: 584(±15) mm vs. 265(±7) mm). NEE for the lawn was characterized by a longer growing season, higher daily net uptake of CO2, and growing season NEE that was also more than twice that of the prairie (2011: −173(±23) g C m−2 vs. -81(±10) g C m−2; 2012: −73(±22) g C m−2 vs. -21(±8) g C m−2). During the drought year (2012), temperature and water stress greatly influenced the direction and magnitude of CO2 flux at both sites. The results suggest that lawns in Denver can function as carbon sinks and conditionally contribute to the mitigation of carbon emissions - directly by CO2 uptake and indirectly through effects of evaporative cooling on microclimate and energy use.
Electromagnetic geophysical methods image the electrical conductivity of the subsurface. Electrical conductivity is an intrinsic material property that is sensitive to temperature, composition, porosity, volatile and/or melt content, and other physical properties relevant to the solid Earth. Therefore, imaging the electrical structure of the crust and mantle yields valuable information on the physical and chemical state of the lithosphere-asthenosphere system.
Here we explore the viability of the passive magnetotelluric (MT) method for constraining upper mantle properties. We approach this problem in four successive steps: 1) review the electrical conductivity behavior of relevant materials; 2) predict the bulk electrical conductivity structure of oceanic and continental lithosphere for a suite of representative physical states; 3) generate synthetic MT data from the conductivity predictions; 4) compare and discuss the conductivity predictions and the synthetic data with select case studies from oceanic and continental settings. Our aim is to clarify the uncertainties associated with drawing inferences from electrical conductivity observations and ultimately to provide a basis for assigning confidence levels to interpretations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.pepi.2021.106661","usgsCitation":"Naif, S., Selway, K., Murphy, B.S., Egbert, G.D., and Pommier, A., 2021, Electrical conductivity of the lithosphere-asthenosphere system: Physics of the Earth and Planetary Interiors, v. 313, 106661, 24 p., https://doi.org/10.1016/j.pepi.2021.106661.","productDescription":"106661, 24 p.","ipdsId":"IP-122999","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":383704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"313","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Naif, Samer","contributorId":252975,"corporation":false,"usgs":false,"family":"Naif","given":"Samer","email":"","affiliations":[{"id":50479,"text":"Earth and Atmospheric Sciences, Georgia Tech; Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":811217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selway, Kate","contributorId":224245,"corporation":false,"usgs":false,"family":"Selway","given":"Kate","affiliations":[],"preferred":false,"id":811218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":811219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Egbert, Gary D.","contributorId":187462,"corporation":false,"usgs":false,"family":"Egbert","given":"Gary","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":811220,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pommier, Anne","contributorId":252976,"corporation":false,"usgs":false,"family":"Pommier","given":"Anne","email":"","affiliations":[{"id":50480,"text":"Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":811221,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218236,"text":"70218236 - 2021 - Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators","interactions":[],"lastModifiedDate":"2021-04-22T18:29:27.802713","indexId":"70218236","displayToPublicDate":"2021-02-12T11:01:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators","docAbstract":"During the Pacific marine heatwave of 2014–2016, abundance and quality of several key forage fish species in the Gulf of Alaska were simultaneously reduced throughout the system. Capelin (Mallotus catervarius), sand lance (Ammodytes personatus), and herring (Clupea pallasii) populations were at historically low levels, and within this community abrupt declines in portfolio effects identify trophic instability at the onset of the heatwave. Although compensatory changes in age‐structure, size, growth or energy content of forage fish were observed to varying degrees among all these forage fish, none were able to fully mitigate adverse impacts of the heatwave, which likely included both top‐down and bottom‐up forcing. Notably, changes to the demographic structure of forage fish suggested size‐selective removals typical of top‐down regulation. At the same time, zooplankton community structure may have driven bottom‐up regulation as copepod community structure shifted towards smaller, warm‐water species, and euphausiid biomass was reduced owing to the loss of cold‐water species. Mediated by these impacts on the forage fish community, an unprecedented disruption of the normal pelagic food web was signaled by higher trophic level disruptions during 2015–2016, when seabirds, marine mammals, and groundfish experienced shifts in distribution, mass mortalities, and reproductive failures. Unlike decadal‐scale variability underlying ecosystem regime shifts, the heatwave appeared to temporarily overwhelm the ability of the forage fish community to buffer against changes imposed by warm water anomalies, thereby eliminating any ecological advantages that may have accrued from having a suite of coexisting forage species with differing life history compensations.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15556","usgsCitation":"Arimitsu, M.L., Piatt, J.F., Hatch, S., Suryan, R., Batten, S., Bishop, M.A., Campbell, R.W., Coletti, H., Cushing, D., Gorman, K., Hopcroft, R.R., Kuletz, K.J., Marsteller, C.E., McKinstry, C., McGowan, D., Moran, J., Pegau, W., Schaefer, A., Schoen, S.K., Straley, J., and von Biela, V.R., 2021, Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators: Global Change Biology, v. 27, no. 9, p. 1859-1878, https://doi.org/10.1111/gcb.15556.","productDescription":"20 p.","startPage":"1859","endPage":"1878","ipdsId":"IP-123071","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453466,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15556","text":"Publisher Index Page"},{"id":383375,"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 -135,\n 56.32872090717995\n ],\n [\n -138.1640625,\n 59.00662762374203\n ],\n [\n -143.37158203125,\n 60.18523283150752\n ],\n [\n -145.72265625,\n 60.3812902796077\n ],\n [\n -149.87548828125,\n 59.85585085709834\n ],\n [\n -152.2265625,\n 58.0546319113729\n ],\n [\n -153.91845703125,\n 56.47462805805594\n ],\n [\n -135,\n 56.32872090717995\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-03-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 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The white sucker hepatitis B virus (WSHBV) was first described in the white sucker (Catostomus commersonii), a freshwater teleost, and belongs to the genus Parahepadnavirus. At present, the host range of WSHBV and its impact on fish health are unknown, and neither genetic diversity nor association with fish health have been studied in any parahepadnavirus. Given the relevance of genomic diversity to disease outcome for the orthohepadnaviruses, we sought to characterize genomic variation in WSHBV and determine how it is structured among watersheds. We identified WSHBV-positive white sucker inhabiting tributaries of Lake Michigan, Lake Superior, Lake Erie (USA), and Lake Athabasca (Canada). Copy number in plasma and in liver tissue was estimated via qPCR. Templates from 27 virus-positive fish were amplified and sequenced using a primer-specific, circular long-range amplification method coupled with amplicon sequencing on the Illumina MiSeq. Phylogenetic analysis of the WSHBV genome identified phylogeographical clustering reminiscent of that observed with human hepatitis B virus genotypes. Notably, most non-synonymous substitutions were found to cluster in the pre-S/spacer overlap region, which is relevant for both viral entry and replication. The observed predominance of p1/s3 mutations in this region is indicative of adaptive change in the polymerase open reading frame (ORF), while, at the same time, the surface ORF is under purifying selection. Although the levels of variation we observed do not meet the criteria used to define sub/genotypes of human and avian hepadnaviruses, we identified geographically associated genome variation in the pre-S and spacer domain sufficient to define five WSHBV haplotypes. This study of WSHBV genetic diversity should facilitate the development of molecular markers for future identification of genotypes and provide evidence in future investigations of possible differential disease outcomes.
","language":"English","publisher":"MDPI","doi":"10.3390/v13020285","usgsCitation":"Adams, C., Blazer, V., Sherry, J., Cornman, R.S., and Iwanowicz, L., 2021, Phylogeographic genetic diversity in the white sucker hepatitis B Virus across the Great Lakes Region and Alberta, Canada: Viruses, v. 13, no. 2, 285, 17 p., https://doi.org/10.3390/v13020285.","productDescription":"285, 17 p.","ipdsId":"IP-109590","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":453470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v13020285","text":"Publisher Index Page"},{"id":383276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Michigan, Minnesota, Ohio, Wisconsin","otherGeospatial":"Athabasca River, Detroit River, Fox River, Lake Erie, Lake Michigan , Lake Superior, Milwaukee River, Root River, Sheboygan River, St. Louis River, Swan Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.900390625,\n 46.28622391806706\n ],\n [\n -91.62597656249999,\n 46.28622391806706\n ],\n [\n -91.62597656249999,\n 46.98025235521883\n ],\n [\n -92.900390625,\n 46.98025235521883\n ],\n [\n -92.900390625,\n 46.28622391806706\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.505859375,\n 42.68243539838623\n ],\n [\n -87.5830078125,\n 42.68243539838623\n ],\n [\n -87.5830078125,\n 44.77793589631623\n ],\n [\n -88.505859375,\n 44.77793589631623\n ],\n [\n -88.505859375,\n 42.68243539838623\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.8037109375,\n 41.178653972331674\n ],\n [\n -83.056640625,\n 41.178653972331674\n ],\n [\n -83.056640625,\n 42.5530802889558\n ],\n [\n -83.8037109375,\n 42.5530802889558\n ],\n [\n -83.8037109375,\n 41.178653972331674\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.64208984374999,\n 54.16243396806779\n ],\n [\n -113.15917968749999,\n 54.16243396806779\n ],\n [\n -113.15917968749999,\n 55.50374985927514\n ],\n [\n -115.64208984374999,\n 55.50374985927514\n ],\n [\n -115.64208984374999,\n 54.16243396806779\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Cynthia R 0000-0003-4383-530X","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":219530,"corporation":false,"usgs":false,"family":"Adams","given":"Cynthia R","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":810314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":810315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherry, Jim","contributorId":251691,"corporation":false,"usgs":false,"family":"Sherry","given":"Jim","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":810316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":810317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":810318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218174,"text":"70218174 - 2021 - Patterns and processes of pathogen exposure in gray wolves across North America","interactions":[],"lastModifiedDate":"2021-02-15T16:38:27.445147","indexId":"70218174","displayToPublicDate":"2021-02-12T10:23:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and processes of pathogen exposure in gray wolves across North America","docAbstract":"The presence of many pathogens varies in a predictable manner with latitude, with infections decreasing from the equator towards the poles. We investigated the geographic trends of pathogens infecting a widely distributed carnivore: the gray wolf (Canis lupus). Specifically, we investigated which variables best explain and predict geographic trends in seroprevalence across North American wolf populations and the implications of the underlying mechanisms. We compiled a large serological dataset of nearly 2000 wolves from 17 study areas, spanning 80° longitude and 50° latitude. Generalized linear mixed models were constructed to predict the probability of seropositivity of four important pathogens: canine adenovirus, herpesvirus, parvovirus, and distemper virus—and two parasites: Neospora caninum and Toxoplasma gondii. Canine adenovirus and herpesvirus were the most widely distributed pathogens, whereas N. caninum was relatively uncommon. Canine parvovirus and distemper had high annual variation, with western populations experiencing more frequent outbreaks than eastern populations. Seroprevalence of all infections increased as wolves aged, and denser wolf populations had a greater risk of exposure. Probability of exposure was positively correlated with human density, suggesting that dogs and synanthropic animals may be important pathogen reservoirs. Pathogen exposure did not appear to follow a latitudinal gradient, with the exception of N. caninum. Instead, clustered study areas were more similar: wolves from the Great Lakes region had lower odds of exposure to the viruses, but higher odds of exposure to N. caninum and T. gondii; the opposite was true for wolves from the central Rocky Mountains. Overall, mechanistic predictors were more informative of seroprevalence trends than latitude and longitude. Individual host characteristics as well as inherent features of ecosystems determined pathogen exposure risk on a large scale. This work emphasizes the importance of biogeographic wildlife surveillance, and we expound upon avenues of future research of cross-species transmission, spillover, and spatial variation in pathogen infection.
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J.","contributorId":236937,"corporation":false,"usgs":false,"family":"Hudson","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":810340,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70218713,"text":"70218713 - 2021 - Indicators of volcanic eruptions revealed by global M4+ earthquakes","interactions":[],"lastModifiedDate":"2021-03-08T16:13:29.870904","indexId":"70218713","displayToPublicDate":"2021-02-12T10:07:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Indicators of volcanic eruptions revealed by global M4+ earthquakes","docAbstract":"Determining whether seismicity near volcanoes is due primarily to tectonic or magmatic processes is a challenging but critical endeavor for volcanic eruption forecasting and detection, especially at poorly monitored volcanoes. Global statistics on the occurrence and timing of earthquakes near volcanoes both within and outside of eruptive periods reveal patterns in eruptive seismicity that may improve our ability to discern magmatically driven seismicity from purely tectonic seismicity. In this paper, we catalog magnitude four and greater (M4+) earthquakes near volcanoes globally and compute statistics on their occurrence with respect to various eruptive and volcanic attributes, evaluating their utility as diagnostic indicators of eruptions. Using a 2‐week time window and a 30 km radius around the volcanoes, we find that 11% of eruptions are preceded by at least one M4+ earthquake, but only 1% of such earthquakes is followed by eruption. However, earthquakes located 5–15 km from the volcano, those with normal faulting mechanisms and/or large nondouble‐couple components, and those occurring as groups are more commonly associated with eruptions, providing significant forecasting utility in some cases. Similarly, certain volcanoes are more likely to exhibit such precursors, such as those with long repose periods. We illustrate the use of these data in eruption forecasting scenarios, including rapid identification of analogous earthquake sequences at other volcanoes. When integrated within the context of multiparametric, multidisciplinary probabilistic assessments of volcanic activity, global earthquake statistics can improve eruption forecasts, and our work provides a model for use on other rapidly expanding global volcanological databases.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021294","usgsCitation":"Pesicek, J.D., Ogburn, S.E., and Prejean, S., 2021, Indicators of volcanic eruptions revealed by global M4+ earthquakes: Journal of Geophysical Research, v. 126, no. 3, e2020JB021294, 28 p., https://doi.org/10.1029/2020JB021294.","productDescription":"e2020JB021294, 28 p.","ipdsId":"IP-124151","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb021294","text":"Publisher Index Page"},{"id":384229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Pesicek, Jeremy D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":202042,"corporation":false,"usgs":true,"family":"Pesicek","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ogburn, Sarah E. 0000-0002-4734-2118","orcid":"https://orcid.org/0000-0002-4734-2118","contributorId":204751,"corporation":false,"usgs":true,"family":"Ogburn","given":"Sarah","email":"","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prejean, Stephanie 0000-0003-0510-1989 sprejean@usgs.gov","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":172404,"corporation":false,"usgs":true,"family":"Prejean","given":"Stephanie","email":"sprejean@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":811482,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218675,"text":"70218675 - 2021 - Airborne geophysical imaging of weak zones on Iliamna Volcano, Alaska: Implications for slope stability","interactions":[],"lastModifiedDate":"2021-03-05T13:52:47.045359","indexId":"70218675","displayToPublicDate":"2021-02-12T07:44:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Airborne geophysical imaging of weak zones on Iliamna Volcano, Alaska: Implications for slope stability","docAbstract":"Water‐saturated, hydrothermally altered rocks reduce the strength of volcanic edifices and increase the potential for sector collapses and far‐traveled mass flows of unconsolidated debris. Iliamna Volcano is an andesitic stratovolcano located on the western side of the Cook Inlet, ∼225 km southwest of Anchorage and is a source of repeated avalanches. The widespread snow and ice cover on Iliamna Volcano make surface alteration difficult to identify. However, intense hydrothermal alteration significantly reduces both the electrical resistivity and magnetization of volcanic rock and can therefore be identified with airborne geophysical measurements. We use airborne electromagnetic and magnetic data to map snow and ice thickness and identify underlying alteration zones at Iliamna Volcano, Alaska. Resistivities were calculated to an average depth of >300 m, and a 3‐D susceptibility model extends from the surface to the base of the volcano, about 3,000 m below the summit. Geophysical models image low resistivity (<30 ohm‐m) and low susceptibilities near the summit of Iliamna and below its older vent complex, with the low susceptibilities indicating alteration up to ∼800 m in thickness. Thin conductors (∼50–100 m thick) on the edifice slopes coincide with recorded locations of repeated debris avalanches over the past ∼60 years and are attributed to saturated zones at high elevation. Three‐dimensional slope stability models based upon the geophysically constrained alteration distribution suggest the edifice of Iliamna is unstable and could lead to collapse scars ∼400 m deep near the current and former vent complexes.
Stratigraphic, lithologic, foraminiferal, and radiocarbon analyses indicate that at least four abrupt mud-over-peat contacts are recorded across three sites (Jacoby Creek, McDaniel Creek, and Mad River Slough) in northern Humboldt Bay, California, USA (∼44.8°N, −124.2°W). The stratigraphy records subsidence during past megathrust earthquakes at the southern Cascadia subduction zone ∼40 km north of the Mendocino Triple Junction. Maximum and minimum radiocarbon ages on plant macrofossils from above and below laterally extensive (>6 km) contacts suggest regional synchroneity of subsidence. The shallowest contact has radiocarbon ages that are consistent with the most recent great earthquake at Cascadia, which occurred at 250 cal yr B.P. (1700 CE). Using Bchron and OxCal software, we model ages for the three older contacts of ca. 875 cal yr B.P., ca. 1120 cal yr B.P., and ca. 1620 cal yr B.P.
For each of the four earthquakes, we analyze foraminifera across representative mud-over-peat contacts selected from McDaniel Creek. Changes in fossil foraminiferal assemblages across all four contacts reveal sudden relative sea-level (RSL) rise (land subsidence) with submergence lasting from decades to centuries. To estimate subsidence during each earthquake, we reconstructed RSL rise across the contacts using the fossil foraminiferal assemblages in a Bayesian transfer function. The coseismic subsidence estimates are 0.85 ± 0.46 m for the 1700 CE earthquake, 0.42 ± 0.37 m for the ca. 875 cal yr B.P. earthquake, 0.79 ± 0.47 m for the ca. 1120 cal yr B.P. earthquake, and ≥0.93 m for the ca. 1620 cal yr B.P. earthquake. The subsidence estimate for the ca. 1620 cal yr B.P. earthquake is a minimum because the pre-subsidence paleoenvironment likely was above the upper limit of foraminiferal habitation. The subsidence estimate for the ca. 875 cal yr B.P. earthquake is less than (<50%) the subsidence estimates for other contacts and suggests that subsidence magnitude varied over the past four earthquake cycles in southern Cascadia.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35701.1","usgsCitation":"Padgett, J., Engelhart, S.E., Kelsey, H., Witter, R., Cahill, N., and Hemphill-Haley, E., 2021, Timing and amount of southern Cascadia earthquake subsidence over the past 1700 years at northern Humboldt Bay, California, USA: GSA Bulletin, v. 133, no. 9-10, p. 2137-2156, https://doi.org/10.1130/B35701.1.","productDescription":"20 p.","startPage":"2137","endPage":"2156","ipdsId":"IP-122222","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":453481,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/b35701.1","text":"External Repository"},{"id":400683,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Humboldt Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.57946777343751,\n 40.43440488077008\n ],\n [\n -123.81042480468749,\n 40.43440488077008\n ],\n [\n -123.81042480468749,\n 41.31082388091818\n ],\n [\n -124.57946777343751,\n 41.31082388091818\n ],\n [\n -124.57946777343751,\n 40.43440488077008\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"133","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2021-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Padgett, Jason S.","contributorId":257829,"corporation":false,"usgs":false,"family":"Padgett","given":"Jason S.","affiliations":[{"id":52130,"text":"Department of Geology, Humboldt State University, Arcata, California 95524, USA; Department of Geography, Durham University, Durham, DH1 3LE, UK","active":true,"usgs":false}],"preferred":false,"id":843182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engelhart, Simon E.","contributorId":60104,"corporation":false,"usgs":false,"family":"Engelhart","given":"Simon","email":"","middleInitial":"E.","affiliations":[{"id":6923,"text":"University of Rhode Island, Kingston, RI","active":true,"usgs":false}],"preferred":false,"id":843183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Harvey M.","contributorId":206893,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey M.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":843184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@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":843185,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false},{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":843186,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hemphill-Haley, Eileen","contributorId":194373,"corporation":false,"usgs":false,"family":"Hemphill-Haley","given":"Eileen","affiliations":[{"id":35736,"text":"Hemphill-Haley Consulting, McKinleyville, CA","active":true,"usgs":false}],"preferred":false,"id":843187,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219505,"text":"70219505 - 2021 - Partial migration and spawning movements of humpback chub in the Little Colorado River are better understood using data from autonomous PIT tag antennas","interactions":[],"lastModifiedDate":"2021-08-17T16:01:40.065816","indexId":"70219505","displayToPublicDate":"2021-02-12T06:33:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Partial migration and spawning movements of humpback chub in the Little Colorado River are better understood using data from autonomous PIT tag antennas","docAbstract":"Choosing whether or not to migrate is an important life history decision for many fishes. Here we combine data from physical captures and detections on autonomous passive integrated transponder (PIT) tag antennas to study migration in an endangered fish, the humpback chub (Gila cypha). We develop hidden Markov mark-recapture models with and without antenna detections and find that the model fit without antenna detections misses a large proportion of fish and underestimates migration and survival probabilities. We then assess survival and growth differences associated with life history strategy and migration for different demographic groups (small male, small female, large male, large female). We find large differences in survival according to life history strategy, where residents had much lower over-winter survival than migrants. However, within the migratory life history strategy, survival and growth were similar for active migrants and skipped migrants for all demographic groups. We discuss some common challenges to incorporating detections from autonomous antennas into population models and demonstrate how these data can provide insight about fish movement and life history strategies.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0291","usgsCitation":"Dzul, M.C., Kendall, W.L., Yackulic, C., Winkelman, D.L., Van Haverbeke, D.R., and Yard, M.D., 2021, Partial migration and spawning movements of humpback chub in the Little Colorado River are better understood using data from autonomous PIT tag antennas: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 8, p. 1057-1072, https://doi.org/10.1139/cjfas-2020-0291.","productDescription":"16 p.","startPage":"1057","endPage":"1072","onlineOnly":"N","ipdsId":"IP-121398","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":436513,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95KA0XI","text":"USGS data release","linkHelpText":"Humpback chub spring and fall capture histories in the Little Colorado River, 2009-2019"},{"id":384979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Little Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.28851318359375,\n 35.67737855391475\n ],\n [\n -111.29425048828125,\n 35.67737855391475\n ],\n [\n -111.29425048828125,\n 36.43896124085945\n ],\n [\n -112.28851318359375,\n 36.43896124085945\n ],\n [\n -112.28851318359375,\n 35.67737855391475\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William Louis 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":257230,"corporation":false,"usgs":false,"family":"Kendall","given":"William","email":"","middleInitial":"Louis","affiliations":[{"id":51981,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, 201 J.V.K. Wagar Building 1484 Campus Delivery, Fort Collins, CO 80523, USA","active":true,"usgs":false}],"preferred":false,"id":813825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":813827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Haverbeke, David Randall","contributorId":257231,"corporation":false,"usgs":false,"family":"Van Haverbeke","given":"David","email":"","middleInitial":"Randall","affiliations":[{"id":51983,"text":"Arizona Fish and Wildlife Conservation Office, U.S. Fish and Wildlife Service, 2500 S Pine Knoll Dr., Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":813828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":169281,"corporation":false,"usgs":true,"family":"Yard","given":"Michael","email":"myard@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":813829,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70225729,"text":"70225729 - 2021 - Nutrients and warming alter mountain lake benthic algal structure and function","interactions":[],"lastModifiedDate":"2021-11-05T11:34:43.374212","indexId":"70225729","displayToPublicDate":"2021-02-12T06:32:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Nutrients and warming alter mountain lake benthic algal structure and function","docAbstract":"In recent years, benthic algae have been increasing in abundance in the littoral zones of oligotrophic lakes, but causality has been hard to assign. We used field and laboratory experiments to explore the implications of increasing water temperature and nutrient availability for benthic algal assemblages and ecosystem processes in a Colorado alpine lake. We tested the effect of nutrient enrichment on the relative abundance of algal taxonomic groups in situ using nutrient diffusing substrata. We manipulated temperature and nutrient concentrations in laboratory assays to assess their interactive effects on ecosystem function of chlorophyte-dominated benthic assemblages. Nutrient enrichment with both N and P favored Chlorophyta (green algae) in field experiments and produced the highest overall algal biomass. In the absence of nutrient enrichment, the relative abundance of Bacillariophyta (diatoms) was substantially greater than that of Chlorophyta and cyanobacteria. In laboratory assays, N uptake increased but net ecosystem production decreased with warming temperatures, resulting in reduced N-use efficiency. Even though dissolved organic C (DOC) substantially increased in solution after all laboratory incubations, lower DOC concentrations in the assays with added P and warmer temperatures suggest nutrients and warming stimulated heterotrophic microorganisms as well as primary producers. Our results demonstrate that nutrient availability stimulates Chlorophyta in benthic algal assemblages and that the increase in chlorophytes may alter ecosystem processes with ongoing, rapid environmental change, including N cycling and metabolic functions in oligotrophic lake littoral habitats.
Concentrations, loads, and yields of nitrate plus nitrite, total nitrogen, and total phosphorus were assessed in the Iowa River upstream from the Coralville Reservoir in east-central Iowa. The results of this study describe baseline nutrient transport during two historical reference periods, 1980–96 and 2006–10, that can be used to evaluate the progress of the implementation of reduction strategies in the Middle Iowa River Basin. Where available, nutrient data during the more recent period 2011–18 are also described. Data included nutrient concentrations and streamflow from multiple Federal, State, and Tribal agencies, and loads were computed using multiple techniques to provide valuable insights, which would otherwise not be possible.
Despite an upward trend for mean annual and base streamflow (the trend in high streamflow was not significant), average nutrient loads and yields in the Iowa River were smaller in the recent period (2011–18) than in either historical reference period. Notably smaller loads during the 2012 drought, however, caused pronounced skewed average loads for 2011–18. Comparisons among periods were difficult to make because of a short period of data upstream from Marshalltown, Iowa, at the upstream boundary of the study area and a lack of recent data near Marengo, Iowa, at the downstream boundary of the study area. Though spring and summer loads were a disproportionate part of annual loads, up to 90 percent, seasonal load comparisons to determine load reduction were more sensitive to one or the other historical period than was assessment of annual loads. Runoff-transport relations may provide an additional tool to assess load reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205148","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Garrett, J.D., and Kalkhoff, S.J., 2021, Nutrient concentrations, loads, and yields in the Middle Iowa River Basin, Iowa: U.S. Geological Survey Scientific Investigations Report 2020–5148, 22 p., https://doi.org/10.3133/sir20205148.","productDescription":"Report: vii, 22 p.; 1 Table; Dataset","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116761","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":383240,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.csv","text":"Table 1.1","size":"23.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383239,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148_table1.1.xlsx","text":"Table 1.1","size":"28.1 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5148 Table 1.1","linkHelpText":"— Tributary sites in the Middle Iowa River Basin, upstream of Coralville Reservoir"},{"id":383241,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":383238,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5148/sir20205148.pdf","text":"Report","description":"SIR 2020–5148"},{"id":383237,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5148/coverthb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Middle Iowa River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.065673828125,\n 41.380930388318\n ],\n [\n -90.911865234375,\n 41.529141988723104\n ],\n [\n -90.9613037109375,\n 41.79179268262892\n ],\n [\n -91.2249755859375,\n 42.020732852644294\n ],\n [\n -91.5655517578125,\n 42.17968819665961\n ],\n [\n -91.900634765625,\n 42.34636533160187\n ],\n [\n -92.142333984375,\n 42.66224137632748\n ],\n [\n -92.3291015625,\n 42.984558134256076\n ],\n [\n -92.5323486328125,\n 43.18114705939968\n ],\n [\n -92.7685546875,\n 43.20917969039356\n ],\n [\n -92.9058837890625,\n 43.08894918346591\n ],\n [\n -92.8564453125,\n 42.807491865911544\n ],\n [\n -92.6641845703125,\n 42.55712670332118\n ],\n [\n -92.46093749999999,\n 42.28137302193453\n ],\n [\n -92.1148681640625,\n 42.00848901572399\n ],\n [\n -91.8731689453125,\n 41.70982942509964\n ],\n [\n -91.6644287109375,\n 41.40565583808169\n ],\n [\n -91.4117431640625,\n 41.1455697310095\n ],\n [\n -91.175537109375,\n 41.000629848685385\n ],\n [\n -91.0052490234375,\n 40.9964840143779\n ],\n [\n -90.911865234375,\n 41.017210578228436\n ],\n [\n -90.94482421875,\n 41.104190944576466\n ],\n [\n -90.99426269531249,\n 41.21585377825921\n ],\n [\n -91.04919433593749,\n 41.25716209782705\n ],\n [\n -91.065673828125,\n 41.380930388318\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The Harford County Department of Public Works and the U.S. Geological Survey have been working cooperatively to monitor continuous streamflow at several streamgages in Harford County, Maryland, including Bynum Run and Winters Run. A perceived recent uptick in the number of flooding events in the Bynum Run and Winters Run watersheds have led to questions about the relative frequency and magnitude of floods experienced by county residents. Precipitation, stage (water elevation), and peak flow analyses and trends were evaluated. Although there was no one contributor to point to for the perceived increase in flooding, it is most likely attributable to a combination of precipitation, stage, and peak flow. There have been numerous rainfall events with exceedingly long return intervals, but none were statistically out of the ordinary. The stages of the streams at higher flows are slightly higher (less than 0.5 feet) than historical stages, but likely are not great enough to cause a significant increase in flooding. The ratings (stage discharge relationship) for the streams have changed slightly. The latest ratings indicate erosion and deposition in the streambed over the years of observation, but again these alone do not result in more flooding. These factors taken together may point to an observational bias for incidental flooding. With the increase in land development, there may simply be more observations of flooding in the county.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215007","collaboration":"Prepared in cooperation with the Harford County Department of Public Works","usgsCitation":"Nealen, C.W., and Doheny, E.J., 2021, Precipitation, peak streamflow, and inundation in the Bynum Run and Winters Run watersheds in Harford County, Maryland: U.S. Geological Survey Scientific Investigations Report 2021–5007, 12 p., https://doi.org/10.3133/sir20215007.","productDescription":"vi, 12 p.","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-095939","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":383193,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5007/sir20215007.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5007"},{"id":383192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5007/coverthb.jpg"}],"country":"United States","state":"Maryland","county":"Harford County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.5032958984375,\n 39.2492708462234\n ],\n [\n -75.89355468749999,\n 39.50404070558415\n ],\n [\n -75.882568359375,\n 39.7240885773337\n ],\n [\n -76.8658447265625,\n 39.72831341029745\n ],\n [\n -76.5032958984375,\n 39.2492708462234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Pacific pink salmon (Oncorhynchus gorbuscha) invasions, thought to originate from populations introduced and established in Russia, occurred along the Norwegian coast in 2017 and 2019. Despite several thousand pink salmon entering and establishing in northern Norwegian rivers, current understanding of the ecological effect of the species in northern Europe is limited. Scavengers feeding on pacific salmon carcasses are important vectors for the transport of marine derived energy and nutrients to terrestrial ecosystems in the Pacific Northwest, North America, where the salmon naturally occur. However the role of terrestrial and aquatic scavengers in the consumption and removal of pink salmon beyond the salmon’s native range is unknown. This study has identified terrestrial and sub-aquatic vertebrate scavengers on pink salmon carcasses in a sub-arctic river in northern Norway. Avian scavengers filmed by a camera placed near sites baited with pink salmon carcasses included the Eurasian magpie (Pica pica), hooded crow (Corvus cornix), common raven (Corvus corax), the European herring gull (Larus argentatus), redwing (Turdus iliacus) and goosander (Mergus merganser). However, the largest carcass weight was removed by red foxes (Vulpes vulpes). Carcasses entering Vesterelv River in 2019 were estimated to provide energy and nutrients to the river ecosystem an order of magnitude lower than in the Pacific Northwest. This study provides some of the first information in northern Europe on the mechanisms and quantification of energy and nutrient transfer from the ocean to riparian environments via introduced Pacific pink salmon. Results help to begin to determine the ecological effect of pink salmon and the development of appropriate management strategies.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-020-02419-x","usgsCitation":"Dunlop, K.M., Wipfli, M.S., Muladal, R., and Wierzbinski, G., 2021, Terrestrial and semi-aquatic scavengers on invasive Pacific pink salmon (Oncorhynchus gorbuscha) carcasses in a riparian ecosystem in northern Norway.: Biological Invasions, v. 23, p. 973-979, https://doi.org/10.1007/s10530-020-02419-x.","productDescription":"7 p.","startPage":"973","endPage":"979","ipdsId":"IP-116215","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453492,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-020-02419-x","text":"Publisher Index Page"},{"id":395864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Norway","otherGeospatial":"Finnmark, Vesterelv","volume":"23","noUsgsAuthors":false,"publicationDate":"2020-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunlop, Kathy M.","contributorId":275858,"corporation":false,"usgs":false,"family":"Dunlop","given":"Kathy","email":"","middleInitial":"M.","affiliations":[{"id":56901,"text":"imr","active":true,"usgs":false}],"preferred":false,"id":834369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muladal, Rune","contributorId":275859,"corporation":false,"usgs":false,"family":"Muladal","given":"Rune","email":"","affiliations":[{"id":38108,"text":"NA","active":true,"usgs":false}],"preferred":false,"id":834370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wierzbinski, Grzegorz","contributorId":275860,"corporation":false,"usgs":false,"family":"Wierzbinski","given":"Grzegorz","email":"","affiliations":[{"id":38108,"text":"NA","active":true,"usgs":false}],"preferred":false,"id":834371,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218011,"text":"ofr20211006 - 2021 - Aeromagnetic map of Burney and the surrounding area, northeastern California","interactions":[],"lastModifiedDate":"2021-02-12T12:50:25.298438","indexId":"ofr20211006","displayToPublicDate":"2021-02-11T13:58:26","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":"2021-1006","displayTitle":"Aeromagnetic Map of Burney and the Surrounding Area, Northeastern California","title":"Aeromagnetic map of Burney and the surrounding area, northeastern California","docAbstract":"An aeromagnetic survey was conducted to improve understanding of the geology and structure in the area around Burney, northeastern California. The new data are a substantial improvement over existing data and reveal a prominent north northwest-trending magnetic grain that allows extension of mapped faults, delineation of plutons within the Mesozoic basement in the northern Sierra Nevada, and linear anomalies that limit the amount of strike-slip offset along various faults in the area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211006","usgsCitation":"Langenheim, V.E., 2021, Aeromagnetic map of Burney and the surrounding area, northeastern California: U.S. Geological Survey Open-File Report 2021–1006, 8 p., 1 sheet, scale 1:250:000, https://doi.org/10.3133/ofr20211006.","productDescription":"Report: iv, 8 p.; 1 Sheet: 30.37 x 34.42 inches; Data Release","numberOfPages":"8","ipdsId":"IP-111186","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":383220,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PUFYDD","linkHelpText":"Aeromagnetic data, grid data, and magnetization boundaries of a survey flown in the Burney region, northeastern California"},{"id":383219,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2021/1006/ofr20211006_sheet.pdf","text":"Sheet","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":383217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1006/covrthb.jpg"},{"id":383218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1006/ofr20211006_pamphlet.pdf","text":"Pamphlet","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.607421875,\n 39.57182223734374\n ],\n [\n -120.0146484375,\n 39.57182223734374\n ],\n [\n -120.0146484375,\n 41.541477666790286\n ],\n [\n -122.607421875,\n 41.541477666790286\n ],\n [\n -122.607421875,\n 39.57182223734374\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
This whitepaper addresses to two focal areas – (3) Insight gleaned from complex data using Artificial Intelligence (AI), and other advanced techniques (primary), and (2) Predictive modeling through the use of AI techniques and AI-derived model components (secondary). This topic is directly relevant to four DOE Earth and Environmental Systems Science Division Grand Challenges: integrated water cycle, biogeochemistry, drivers and responses in the Earth system, and data-model integration.
","language":"English","publisher":"Department of Energy","doi":"10.2172/1769795","usgsCitation":"Varadharajan, C., Kumar, V., Willard, J., Zwart, J.A., Sadler, J.M., Weierbach, H., Perciano, T., Mueller, J., Hendrix, V., and Christianson, D., 2021, Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality: Technical Report, 5 p., https://doi.org/10.2172/1769795.","productDescription":"5 p.","ipdsId":"IP-126904","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":453494,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1769795","text":"External Repository"},{"id":421340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Varadharajan, Charuleka","contributorId":242712,"corporation":false,"usgs":false,"family":"Varadharajan","given":"Charuleka","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":883289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":883290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883292,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weierbach, Helen","contributorId":290549,"corporation":false,"usgs":false,"family":"Weierbach","given":"Helen","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883293,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perciano, Talita 0000-0002-2388-1803","orcid":"https://orcid.org/0000-0002-2388-1803","contributorId":290546,"corporation":false,"usgs":false,"family":"Perciano","given":"Talita","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883294,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mueller, Juliane 0000-0001-8627-1992","orcid":"https://orcid.org/0000-0001-8627-1992","contributorId":290539,"corporation":false,"usgs":false,"family":"Mueller","given":"Juliane","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883295,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hendrix, Valerie 0000-0001-9061-8952","orcid":"https://orcid.org/0000-0001-9061-8952","contributorId":290533,"corporation":false,"usgs":false,"family":"Hendrix","given":"Valerie","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":883296,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christianson, Danielle","contributorId":265829,"corporation":false,"usgs":false,"family":"Christianson","given":"Danielle","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":883297,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}