In unglaciated terrain, the imprint of past glacial periods is difficult to discern. The topographic signature of periglacial processes, such as solifluction lobes, may be erased or hidden by time and vegetation, and thus their import diminished. Belowground, periglacial weathering, particularly frost cracking, may have imparted a profound influence on weathering and erosion rates during past climate regimes. By combining a mechanical frost-weathering model with the full suite of Last Glacial Maximum climate simulations, we elucidate the meters-deep magnitude and continent-spanning expanse of frost weathering across unglaciated North America at ∼21 ka. The surprising extent of modeled frost weathering suggests, by proxy, the broad legacy of diverse periglacial processes. Complementing previous studies that championed the role of precipitation-driven changes in Critical Zone evolution, our results imply an additional strong temperature control on surficial process efficacy across much of modern North America, both during glacial periods and modern climes.
Insular species, particularly birds, experience high levels of speciation and endemism. Similarly, island birds experience extreme levels of extinction. Based on a 2012 taxonomic assessment, historically there were four reed-warbler species in the Mariana Islands, the Guam Reed-warbler Acrocephalus luscinia (Guam), the Nightingale Reed-warbler Acrocephalus hiwae (Saipan and Alamagan), the Aguijuan Reed-warbler A. nijoi (Aguiguan or Aguijuan), and the Pagan Reed-warbler A. yamashinae (Pagan). Between 2008 and 2010 we surveyed for three of these species on Alamagan, Aguiguan, and Pagan. Our results indicate that reed-warblers are extinct on Aguiguan, likely extinct on Pagan, and only the Nightingale Reed-warbler on Alamagan and Saipan remains. We estimated the global population at between 1,019 and 6,356 birds (95% CI; mean estimate 3,688), which has declined by more than 1,000 birds since the first quantitative surveys were conducted in 1982, i.e. a 24% decline in 28 years. Camp et al. (2009) describe the status of the Nightingale Reed-warbler on Saipan, which has also declined. We estimated the Alamagan population to be between 428 and 1,762 birds in 2010 (mean estimate 946). Thus, the Alamagan population is ~25 % of the global population, and it has declined slightly since 2000. This decline was not significant but is concerning, especially given a similar decline on Saipan. Restoration and protection of tall-stature native and secondary forest could benefit the Alamagan population, as would similar conservation on Saipan that includes wetland habitat. After suitable restoration of forest and wetland habitats on Aguiguan, Guam and Pagan, individuals from Alamagan and Saipan could serve as founder populations. Careful consideration of the extent and habitat preference of individuals translocated to Tinian, where an unknown reed-warbler species previously occurred, is warranted.
In the San Joaquin Valley (SJV), California, about 10% of drinking water wells since 2010 had arsenic concentrations above the US maximum contaminant level of 10 μg/L. High concentrations of arsenic are often associated with high pH (greater than 7.8) or reduced geochemical conditions. Although most wells have low arsenic (<3 μg/L) and do not have changing arsenic concentrations, this study found that most wells with concentrations above 10 μg/L had arsenic trends. Overall, about 24% of wells had time-series trends since 2010 and 59% had paired-sample trends since 2000. Most wells had decreasing arsenic trends, even in wells with higher arsenic concentrations. These wells often had co-detections of increasing nitrate and sulfate trends that reflect oxic groundwater likely derived from agricultural recharge. Wells with increasing arsenic trends were deeper or located in the valley trough where aquifer materials are more fine-grained and where reducing conditions favor arsenic mobility. Wells with arsenic trends also tend to be clustered near areas of higher well density. Groundwater pumping in these areas has likely increased the contribution of younger, more oxic groundwater in wells with declining arsenic or, less frequently, increased the contribution of higher pH or reduced groundwater in wells with rising arsenic. Projections of arsenic trends indicate that 37 wells with high arsenic presently will be below 10 μg/L in ten years. Unfortunately, these improvements will be largely offset by 31 wells that are expected to increase above 10 μg/L in addition to expected rises in nitrate in wells where arsenic decreased. This study shows how human-altered flow systems can impact the natural geochemical character of water in both beneficial and deleterious ways.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.145223","usgsCitation":"Haugen, E.A., Jurgens, B., Arroyo-Lopez, J.A., and Bennett, G.L., 2021, Groundwater development leads to decreasing arsenic concentrations in the San Joaquin Valley, California: Science of the Total Environment, v. 771, 145223, 14 p., https://doi.org/10.1016/j.scitotenv.2021.145223.","productDescription":"145223, 14 p.","ipdsId":"IP-118584","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":453817,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2021.145223","text":"Publisher Index Page"},{"id":436558,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OZ50BM","text":"USGS data release","linkHelpText":"Water Quality data compiled for Groundwater development leads to decreasing arsenic concentrations in the San Joaquin Valley, California"},{"id":383224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70218003/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.16870117187501,\n 35.092945313732635\n ],\n [\n -118.54248046874999,\n 35.71975793933433\n ],\n [\n -119.5751953125,\n 37.23907530202184\n ],\n [\n -121.387939453125,\n 39.07890809706475\n ],\n [\n -121.56372070312499,\n 39.40224434029275\n ],\n [\n -122.574462890625,\n 39.223742741391305\n ],\n [\n -121.761474609375,\n 38.12591462924157\n ],\n [\n -121.14624023437499,\n 37.47485808497102\n ],\n [\n -120.465087890625,\n 36.518465989675875\n ],\n [\n -120.21240234375001,\n 35.88905007936091\n ],\n [\n -119.674072265625,\n 35.263561862152095\n ],\n [\n -119.16870117187501,\n 35.092945313732635\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"771","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haugen, Emily A. 0000-0002-0263-9911","orcid":"https://orcid.org/0000-0002-0263-9911","contributorId":211480,"corporation":false,"usgs":true,"family":"Haugen","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arroyo-Lopez, Jose Alfredo 0000-0002-7835-2730","orcid":"https://orcid.org/0000-0002-7835-2730","contributorId":250663,"corporation":false,"usgs":true,"family":"Arroyo-Lopez","given":"Jose","email":"","middleInitial":"Alfredo","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, George L. V V 0000-0002-6239-1604 georbenn@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-1604","contributorId":1373,"corporation":false,"usgs":true,"family":"Bennett","given":"George","suffix":"V","email":"georbenn@usgs.gov","middleInitial":"L. V","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810201,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223444,"text":"70223444 - 2021 - Migration of injected wastewater with high levels of ammonia in a saline aquifer in south Florida","interactions":[],"lastModifiedDate":"2021-08-30T12:05:28.839956","indexId":"70223444","displayToPublicDate":"2021-01-18T10:31:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Migration of injected wastewater with high levels of ammonia in a saline aquifer in south Florida","docAbstract":"Treated wastewater with high levels of ammonia has been injected, since March 1983 into the deep saline units of the Lower Floridan aquifer (LFA) from a treatment plant near the east coast of Miami-Dade County in southeastern Florida. Monitoring wells in the plant recorded ammonia concentrations above ambient levels at hydrogeologic units located about 1000 ft (304.8 m) above injection depths between 2500 and 2800 ft (762 and 853 m) below sea level. A solute-transport model was developed to assess the horizontal and vertical extent of the injected ammonia, with ammonia moving from the injected zone into the overlying units: the upper semiconfining unit, the uppermost permeable zone of the LFA, and the middle semiconfining units of the Avon Park Formation. Ammonia is assumed to be transported under the effects of local heterogeneity in a porous limestone aquifer with high-salinity ambient groundwater and via upward migration through quasi-vertical pathways. A flow model of the migration of the injected ammonia was calibrated with PEST using head, salinity, and ammonia concentration data measured from 1983 to 2013. Borehole geophysical data support the high permeability of the uppermost permeable zone in the LFA. Average simulated head, normalized salinity, and ammonia concentration residuals over all monitoring wells were −1.37 ft, 0.01, and −0.67 mg/L, respectively. Model results are consistent with undetectable ammonia concentrations in the Upper Floridan aquifer.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13076","usgsCitation":"Sepulveda, N., and Lohmann, M., 2021, Migration of injected wastewater with high levels of ammonia in a saline aquifer in south Florida: Groundwater, v. 59, no. 4, p. 597-613, https://doi.org/10.1111/gwat.13076.","productDescription":"17 p.","startPage":"597","endPage":"613","ipdsId":"IP-107330","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":436559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EWI8N0","text":"USGS data release","linkHelpText":"Data Sets for Simulation of Migration of Injected Wastewater with High Levels of Ammonia in a Saline Aquifer in South Florida, using SEAWAT v 4"},{"id":388589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.9088134765625,\n 25.175116531621764\n ],\n [\n -79.42291259765625,\n 25.175116531621764\n ],\n [\n -79.42291259765625,\n 26.04444515079636\n ],\n [\n -80.9088134765625,\n 26.04444515079636\n ],\n [\n -80.9088134765625,\n 25.175116531621764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":822044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lohmann, Melinda A. 0000-0003-1472-159X","orcid":"https://orcid.org/0000-0003-1472-159X","contributorId":216660,"corporation":false,"usgs":true,"family":"Lohmann","given":"Melinda A.","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":822045,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217749,"text":"70217749 - 2021 - Poecivirus is present in individuals with beak deformities in seven species of North American birds","interactions":[],"lastModifiedDate":"2021-04-08T14:49:00.142143","indexId":"70217749","displayToPublicDate":"2021-01-18T10:12:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Poecivirus is present in individuals with beak deformities in seven species of North American birds","docAbstract":"Avian keratin disorder (AKD), a disease of unknown etiology characterized by debilitating beak overgrowth, has increasingly affected wild bird populations since the 1990s. A novel picornavirus, poecivirus, is closely correlated with disease status in Black-capped Chickadees (Poecile atricapillus) in Alaska. However, our knowledge of the relationship between poecivirus and beak deformities in other species and other geographic areas remains limited. The growing geographic scope and number of species affected by AKD-like beak deformities require a better understanding of the causative agent to evaluate the population-level impacts of this epizootic. Here, we tested eight individuals from six avian species with AKD-consistent deformities for the presence of poecivirus: Mew Gull (Larus canus), Hairy Woodpecker (Picoides villosus), Black-billed Magpie (Pica hudsonia), American Crow (Corvus brachyrhynchos), Red-breasted Nuthatch (Sitta canadensis), and Blackpoll Warbler (Setophaga striata). The birds were sampled in Alaska and Maine (1999−2016). We used targeted PCR followed by Sanger sequencing to test for the presence of poecivirus in each specimen and to obtain viral genome sequence from virus-positive host individuals. We detected poecivirus in all individuals tested, but not in negative controls (water and tissue samples). Furthermore, we used unbiased metagenomic sequencing to test for the presence of other pathogens in six of these specimens (Hairy Woodpecker, two American Crows, two Red-breasted Nuthatches, Blackpoll Warbler). This analysis yielded additional viral sequences from several specimens, including the complete coding region of poecivirus from one Red-breasted Nuthatch, which we confirmed via targeted PCR followed by Sanger sequencing. This study demonstrates that poecivirus is present in individuals with AKD-consistent deformities from six avian species other than Black-capped Chickadee. While further investigation will be required to explore whether there exists a causal link between this virus and AKD, this study demonstrates that poecivirus is not geographically restricted to Alaska, but rather occurs elsewhere in North America.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-20-00017","usgsCitation":"Zylberberg, M., Van Hemert, C.R., Handel, C.M., Liu, R., and DeRisi, J.L., 2021, Poecivirus is present in individuals with beak deformities in seven species of North American birds: Journal of Wildlife Diseases, v. 57, no. 2, p. 273-281, https://doi.org/10.7589/JWD-D-20-00017.","productDescription":"9 p.","startPage":"273","endPage":"281","ipdsId":"IP-112325","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":453821,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/jwd-d-20-00017","text":"Publisher Index Page"},{"id":436560,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YQCHSR","text":"USGS data release","linkHelpText":"Data Associated with Poecivirus Testing of Individual Birds with Beak Deformities"},{"id":382845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.6201171875,\n 43.13306116240612\n ],\n [\n -69.43359375,\n 44.02442151965934\n ],\n [\n -67.32421875,\n 44.49650533109348\n ],\n [\n -66.9287109375,\n 45.089035564831036\n ],\n [\n -67.7197265625,\n 45.79816953017265\n ],\n [\n -67.763671875,\n 47.010225655683485\n ],\n [\n -68.73046875,\n 47.249406957888446\n ],\n [\n -69.0380859375,\n 47.517200697839414\n ],\n [\n -70.57617187499999,\n 45.644768217751924\n ],\n [\n -71.2353515625,\n 45.336701909968134\n ],\n [\n -70.7958984375,\n 43.389081939117496\n ],\n [\n -70.6201171875,\n 43.13306116240612\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.4736328125,\n 54.49556752187406\n ],\n [\n -129.9462890625,\n 56.07203547180089\n ],\n [\n -135.439453125,\n 59.82273188377389\n ],\n [\n -137.373046875,\n 58.88194208135912\n ],\n [\n -139.130859375,\n 60.34869562531862\n ],\n [\n -140.9326171875,\n 60.30518536282736\n ],\n [\n -141.0205078125,\n 69.65708627301174\n ],\n [\n -157.10449218749997,\n 71.46912418989677\n ],\n [\n -166.640625,\n 68.83180177092166\n ],\n [\n -168.3984375,\n 65.53117097417717\n ],\n [\n -166.5087890625,\n 61.58549218152362\n ],\n [\n -167.6953125,\n 60.13056361691419\n ],\n [\n -158.8623046875,\n 57.68066002977235\n ],\n [\n -165.10253906249997,\n 54.648412502316695\n ],\n [\n -174.7265625,\n 52.214338608258196\n ],\n [\n -174.1552734375,\n 51.56341232867588\n ],\n [\n -152.40234375,\n 56.92099675839107\n ],\n [\n -147.0849609375,\n 59.80063426102869\n ],\n [\n -140.4052734375,\n 59.60109549032134\n ],\n [\n -135.263671875,\n 55.52863052257191\n ],\n [\n -131.1767578125,\n 54.265224078605684\n ],\n [\n -130.4736328125,\n 54.49556752187406\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zylberberg, Maxine","contributorId":181767,"corporation":false,"usgs":false,"family":"Zylberberg","given":"Maxine","email":"","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":809464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Hemert, Caroline R. 0000-0002-6858-7165 cvanhemert@usgs.gov","orcid":"https://orcid.org/0000-0002-6858-7165","contributorId":3592,"corporation":false,"usgs":true,"family":"Van Hemert","given":"Caroline","email":"cvanhemert@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":809465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":809466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Rachel","contributorId":248590,"corporation":false,"usgs":false,"family":"Liu","given":"Rachel","email":"","affiliations":[{"id":49956,"text":"University of California San Francisco","active":true,"usgs":false}],"preferred":false,"id":809467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeRisi, Joseph L.","contributorId":172863,"corporation":false,"usgs":false,"family":"DeRisi","given":"Joseph","email":"","middleInitial":"L.","affiliations":[{"id":27105,"text":"University of California San Francisco; Howard Hughes Medical Institute","active":true,"usgs":false}],"preferred":false,"id":809468,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218672,"text":"70218672 - 2021 - Field trials to test new trap technologies for monitoring Culex populations and the efficacy of the biopesticide formulation VectoMax® FG for control of larval Culex quinquefasciatus in the Alaka'i Plateau, Kaua'i, Hawaii","interactions":[],"lastModifiedDate":"2021-03-04T14:19:00.460784","indexId":"70218672","displayToPublicDate":"2021-01-18T08:15:54","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":5948,"text":"Hawaii Cooperative Studies Unit Technical Report Series","active":true,"publicationSubtype":{"id":4}},"seriesNumber":"96","title":"Field trials to test new trap technologies for monitoring Culex populations and the efficacy of the biopesticide formulation VectoMax® FG for control of larval Culex quinquefasciatus in the Alaka'i Plateau, Kaua'i, Hawaii","docAbstract":"Mosquito-borne avian malaria Plasmodium relictum is a key limiting factor for endemic Hawaiian forest birds. In the past decade, populations of Kaua‘i’s endemic forest birds have been in a steep decline due to an increase in malaria transmission. To evaluate the use of available biopesticides for short-term mosquito control we tested the efficacy of the biopesticide VectoMax® FG against Culex quinquefasciatus larvae in naturally occurring perched stream pools, seeps, and ground pools in forest bird habitat in Kaua‘i’s remote Alaka‘i Plateau. We also tested the efficacy of conventional and newer traps and attractants for the capture of adult Culex quinquefasciatus in Hawaiian rain forests and monitored adult mosquito populations at the Kaua‘i field site. During field trials conducted on Hawai‘i Island we captured more Culex quinquefasciatus in gravid traps than in host-seeking traps. Among the host-seeking traps, Biogents BG-Sentinel 2 traps baited with CO2 and BG-Lure caught more Culex quinquefasciatus and Aedes japonicus japonicus than CDC (Centers for Disease Control and Prevention) traps baited with compressed CO2, CDC traps baited with dry ice, or Biogents BG-Sentinel 2 traps baited with BG-Lure and octenol but not CO2. Both Biogents BG-Sentinel 2 and CDC miniature traps baited with compressed CO2 or dry ice captured significantly more Culex quinquefasciatus than Biogents BG-Sentinel 2 traps baited with octenol and BG-Lure but without CO2. We also found that gravid traps baited with timothy hay infusions caught significantly more Culex quinquefasciatus than traps baited with either a commercial gravid mosquito attractant or an infusion made with pelleted rabbit feed. Traps baited with an infusion of timothy hay and donkey dung were the most effective for Culex quinquefasciatus. On Kaua‘i, we operated Biogents BG-Sentinel 2 traps baited with CO2 and gravid traps and captured 29 mosquitoes in 182 trap-nights from October–November 2016 and 126 mosquitoes in 254 trap-nights from September–October 2017. Contrary to our findings on Hawai‘i Island, most mosquitoes (96%) were captured in Biogents BG-Sentinel 2 traps indicating considerable site-to-site variability in trap efficacy. Weekly adult trapping on Kaua‘i indicates Culex quinquefasciatus populations peaked in October but provided no reliable evidence that larval control had any significant effect on adult populations. Overall, VectoMax® FG was very effective at larval control reducing larval abundance by 95% at 48 hours and out to 1-week post-treatment. Treatment was most effective (100% at 1-week post-treatment) in perched pools when early instar larvae were present and least effective in seeps when pupae and fourth instar larvae were most common. Although post-treatment counts fluctuated dramatically, we observed no evidence of population level impacts to the two most common non-target invertebrates: the water strider Microvelia vagans and endemic damselfly naiads (Megalagrion sp.). VectoMax® FG appears to be an effective and safe biopesticide for the local control of Culex quinquefasciatus larvae in forest bird habitat in the Alaka‘i Plateau. Further studies will be necessary to determine if local larval control significantly reduces adult mosquito abundance and, ultimately, avian malaria transmission, and if there are long term, non-target effects associated with repeated use of VectoMax® FG in natural Hawaiian waterways.
Recurring slope lineae (RSL) are dark linear markings on Mars that regrow annually and likely originate from the flow of either liquid water or granular material. Following the great dust storm (or planet-encircling dust event, PEDE) of Mars year (MY) 34, Mars Reconnaissance Orbiter/High Resolution Imaging Science Experiment has seen many more candidate RSL than in typical Mars years. They have been imaged at more than 285 unique locations from August 2018 (when the atmosphere was clearing as the PEDE decayed) to August 2019, about half (157) of which are locations where RSL have not been documented previously. In MY34, 150 active RSL sites were identified in the southern middle latitudes (SML, -60° to -30°), whereas an average of 36 active sites were observed in each previous year (MY28–33). Post-PEDE RSL are also present during southern summer over a wider range of latitude, slope aspect, and Ls (areocentric longitude of the sun) than in prior years. These RSL sites usually show evidence for recent dust deposition: obscuration of relatively dark areas, an overall brighter and redder surface than in prior years, and dust devil tracks, which indicate dust lifting by several mechanisms. We speculate that dust-lifting processes may initiate and sustain RSL activity. The RSL may form from flows of dust (perhaps clumped) and/or sand that is destabilized by dust movement or directly mobilized by dust devils. If this is the case, then the otherwise puzzling recurrence and year-to-year variability of RSL activity can be at least partly explained. The dust replenishment varies from year to year, which could explain interannual variations in RSL activity.
Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.
The Hayward fault in California's San Francisco Bay area produces large earthquakes, with the last occurring in 1868. We examine how physics‐based dynamic rupture modeling can be used to numerically simulate large earthquakes on not only the Hayward fault, but also its connected companions to the north and south, the Rodgers Creek and Calaveras faults. Equipped with a wealth of images of this fault system, including those of its 3D geology and 3D geometry, in addition to inferences about its interseismic creep‐rate pattern and rock‐friction behavior, we use a finite‐element computer code to perform 3D dynamic earthquake rupture simulations. We find that the rock properties affect the locations and amount of slip produced in our simulated large earthquakes. Crucial factors that control rupture behavior in our modeling are the earthquake nucleation locations, the fault geometry, and the data that reveal where the fault system is creeping or locked. Our findings suggest that large Rodgers Creek‐Hayward‐Calaveras‐Northern Calaveras (RC‐H‐C‐NC) fault‐system earthquakes may result from dynamic rupture that starts in a locked part of the fault system, but is then stopped by the creeping parts, leading to high‐magnitude‐6 earthquakes; or, from dynamic rupture that starts in a locked part of the fault system, then cascades through some of the creeping parts, leading to magnitude‐7 earthquakes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020577","usgsCitation":"Harris, R.A., Barall, M., Lockner, D.A., Moore, D.E., Ponce, D.A., Graymer, R., Funning, G.J., Morrow, C.A., Kyriakopoulos, C., and Eberhart-Phillips, D., 2021, A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek‐Hayward‐Calaveras Fault System, California: JGR Solid Earth, v. 126, e2020JB020577, 28 p., https://doi.org/10.1029/2020JB020577.","productDescription":"e2020JB020577, 28 p.","ipdsId":"IP-120122","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb020577","text":"Publisher Index Page"},{"id":384448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Francisco","otherGeospatial":"San Andres Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.98095703125,\n 37.18657859524883\n ],\n [\n -121.77246093750001,\n 37.18657859524883\n ],\n [\n -121.77246093750001,\n 38.38472766885085\n ],\n [\n -122.98095703125,\n 38.38472766885085\n ],\n [\n -122.98095703125,\n 37.18657859524883\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-03-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":812382,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":198670,"corporation":false,"usgs":false,"family":"Barall","given":"Michael","affiliations":[],"preferred":false,"id":812383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":812384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Diane E. 0000-0002-8641-1075 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0000-0003-4910-5682","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":207816,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":812387,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Funning, Gareth J. 0000-0002-8247-0545","orcid":"https://orcid.org/0000-0002-8247-0545","contributorId":172418,"corporation":false,"usgs":false,"family":"Funning","given":"Gareth","email":"","middleInitial":"J.","affiliations":[{"id":6984,"text":"UC Riverside","active":true,"usgs":false}],"preferred":false,"id":812388,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrow, Carolyn A. 0000-0003-3500-6181 cmorrow@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-6181","contributorId":3206,"corporation":false,"usgs":true,"family":"Morrow","given":"Carolyn","email":"cmorrow@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":812389,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kyriakopoulos, Christodoulos 0000-0001-9283-2282","orcid":"https://orcid.org/0000-0001-9283-2282","contributorId":255461,"corporation":false,"usgs":false,"family":"Kyriakopoulos","given":"Christodoulos","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":812390,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Eberhart-Phillips, Donna 0000-0003-0392-8659","orcid":"https://orcid.org/0000-0003-0392-8659","contributorId":190650,"corporation":false,"usgs":false,"family":"Eberhart-Phillips","given":"Donna","email":"","affiliations":[],"preferred":false,"id":812391,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237711,"text":"70237711 - 2021 - Assessing the feasibility of managed aquifer recharge in California","interactions":[],"lastModifiedDate":"2022-10-21T13:20:08.072357","indexId":"70237711","displayToPublicDate":"2021-01-16T06:40:52","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":"Assessing the feasibility of managed aquifer recharge in California","docAbstract":"With aquifers around the world stressed by over-extraction, water managers are increasingly turning to managed aquifer recharge (MAR), directly replenishing groundwater resources through injection wells, recharge basins, or other approaches. While there has been progress in understanding the geological and infrastructure-related considerations to make MAR more effective, critical evaluations of its institutional design and implementation are limited. This study assesses MAR projects, using a case study of projects proposed by groundwater sustainability agencies (GSAs) in California to comply with the state's Sustainable Groundwater Management Act of 2014; these projects will almost double the number of MAR projects in the United States. We draw on content analysis of groundwater sustainability plans that propose these projects. We first assess the types of recharge projects proposed and the stated aims of the projects, to assess when and why agencies are turning to MAR as a solution. We find that recharge basins are by far the most common approach, and that GSAs hope these basins will improve water table levels, reduce subsidence, and improve water quality. We then analyze potential barriers to project implementation and assess the projects' ability to achieve the stated goals. Primary concerns identified include a potential lack of available water, a potentially challenging legal framework, and minimal consideration of funding and cumulative land needs. To conclude, we discuss broader considerations for ensuring that MAR is an effective water management tool.
Coral reefs worldwide are experiencing rapid degradation in response to climate and land-use change, namely effects of warming sea-surface temperatures, contaminant runoff, and overfishing. Extensive coral bleaching caused by the steady rise of sea-surface temperatures is projected to increase, but our understanding and ability to predict where corals may be most resilient to this effect is limited owing to a lack of knowledge of nearshore habitat conditions and the role of compromised coral health in preconditioning bleaching vulnerability. On high islands and most atolls, fresh to brackish groundwater discharges to the coast through the beach face and seafloor, where it mixes with marine waters and commonly creates cool estuarine nearshore waters that are important to wildlife and ecosystem services that benefit people. Here, we summarize results of a study to evaluate the ecosystem services and effects of groundwater on coral reef health and the potential role of groundwater to maintain cold-water refugia that can buffer corals from thermal stress during temperature maxima. Across 75 kilometers of the west coastline of the Island of Hawaiʻi, paired time-series and discrete measurements of water quality, coral-community and colony size structures, and coral health indicators, including bleaching, at 33 stations grouped into 12 study areas were made from July 2010 to December 2013. The results show that nearshore water temperatures are depressed by groundwater across extensive areas of the nearshore. Persistent cold-water refugia ranging from 1 to 5 degrees Celsius below surrounding marine water temperatures are shown to be associated with identified groundwater inputs. Significant correlations were found between metrics of coral health and water temperature. Because areas of temperature refugia were notable along the west coast of the Island of Hawaiʻi and are identified by ecologists as increasingly important to valued wildlife, improved understanding of groundwater flux to the long-term resilience of coral reefs is likely important. In particular, evaluating the extent that the magnitude and timing of groundwater discharge across the nearshore mitigate thermal bleaching stress may help inform the fate of coral reefs projected to experience rising sea-surface temperatures worldwide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201128","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Grossman, E.E., Marrack, L., and vanArendonk, N.R., 2021, Nearshore water quality and coral health indicators along the west coast of the Island of Hawaiʻi, 2010–2014: U.S. Geological Survey Open-File Report 2020–1128, 45 p., https://doi.org/10.3133/ofr20201128.","productDescription":"Report: vii, 45 p.; Data Releases","numberOfPages":"45","onlineOnly":"Y","ipdsId":"IP-112588","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":382234,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74X569K","linkHelpText":"Coral cover and health determined from seafloor photographs and diver observations, West Hawai'i, 2010-2011"},{"id":382235,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154FJQ","linkHelpText":"Nearshore water properties and estuary conditions along the coral reef coastline of west Hawaii Island (2010-2014)"},{"id":382232,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1128/covrthb.jpg"},{"id":382233,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1128/ofr20201128.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawaii, Kaloko-Honokōhau National Historical Park, Puʻuhonua O Hōnaunau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.05006217956543,\n 19.666513211037795\n ],\n [\n -156.01581573486328,\n 19.666513211037795\n ],\n [\n -156.01581573486328,\n 19.6935061404277\n ],\n [\n -156.05006217956543,\n 19.6935061404277\n ],\n [\n -156.05006217956543,\n 19.666513211037795\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.91865539550778,\n 19.406980567050198\n ],\n [\n -155.90157508850095,\n 19.406980567050198\n ],\n [\n -155.90157508850095,\n 19.42357528523296\n ],\n [\n -155.91865539550778,\n 19.42357528523296\n ],\n [\n -155.91865539550778,\n 19.406980567050198\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Coastal and Marine Science Center
2885 Mission St.
Santa Cruz, CA 95060
The recovery of large carnivore species from over‐exploitation can have socioecological effects; thus, reliable estimates of potential abundance and distribution represent a valuable tool for developing management objectives and recovery criteria. For sea otters (Enhydra lutris), as with many apex predators, equilibrium abundance is not constant across space but rather varies as a function of local habitat quality and resource dynamics, thereby complicating the extrapolation of carrying capacity (K) from one location to another. To overcome this challenge, we developed a state‐space model of density‐dependent population dynamics in southern sea otters (E. l. nereis), in which K is estimated as a continuously varying function of a suite of physical, biotic, and oceanographic variables, all described at fine spatial scales. We used a theta‐logistic process model that included environmental stochasticity and allowed for density‐independent mortality associated with shark bites. We used Bayesian methods to fit the model to time series of survey data, augmented by auxiliary data on cause of death in stranded otters. Our model results showed that the expected density at K for a given area can be predicted based on local bathymetry (depth and distance from shore), benthic substrate composition (rocky vs. soft sediments), presence of kelp canopy, net primary productivity, and whether or not the area is inside an estuary. In addition to density‐dependent reductions in growth, increased levels of shark‐bite mortality over the last decade have also acted to limit population expansion. We used the functional relationships between habitat variables and equilibrium density to project estimated values of K for the entire historical range of southern sea otters in California, USA, accounting for spatial variation in habitat quality. Our results suggest that California could eventually support 17,226 otters (95% CrI = 9,739–30,087). We also used the fitted model to compute candidate values of optimal sustainable population abundance (OSP) for all of California and for regions within California. We employed a simulation‐based approach to determine the abundance associated with the maximum net productivity level (MNPL) and propose that the upper quartile of the distribution of MNPL estimates (accounting for parameter uncertainty) represents an appropriate threshold value for OSP. Based on this analysis, we suggest a candidate value for OSP (for all of California) of 10,236, which represents 59.4% of projected K.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21985","usgsCitation":"Tinker, M., Yee, J.L., Laidre, K.L., Hatfield, B.B., Harris, M.D., Tomoleoni, J.A., Bell, T.W., Saarman, E., Carswell, L., and Miles, A.K., 2021, Habitat features predict carrying capacity of a recovering marine carnivore: Journal of Wildlife Management, v. 85, no. 2, p. 303-323, https://doi.org/10.1002/jwmg.21985.","productDescription":"21 p.","startPage":"303","endPage":"323","ipdsId":"IP-122195","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":453835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21985","text":"Publisher Index Page"},{"id":382279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -118.27880859375001,\n 33.815666308702774\n ],\n [\n -118.740234375,\n 34.125447565116126\n ],\n [\n -119.091796875,\n 34.23451236236987\n ],\n [\n -119.61914062499999,\n 34.50655662164561\n ],\n [\n -120.36621093749999,\n 34.56085936708384\n ],\n [\n -120.69580078125001,\n 35.31736632923788\n ],\n [\n -121.728515625,\n 36.474306755095235\n ],\n [\n -121.70654296874999,\n 36.94989178681327\n ],\n [\n -122.34374999999999,\n 37.43997405227057\n ],\n [\n -121.75048828124999,\n 37.54457732085582\n ],\n [\n -121.97021484374999,\n 37.96152331396614\n ],\n [\n -120.7177734375,\n 38.03078569382294\n ],\n [\n -121.28906250000001,\n 38.39333888832238\n ],\n [\n -122.58544921875,\n 38.238180119798635\n ],\n [\n -123.06884765625,\n 38.08268954483802\n ],\n [\n -122.82714843749999,\n 37.666429212090605\n ],\n [\n -122.54150390625,\n 37.125286284966805\n ],\n [\n -122.01416015625,\n 36.77409249464195\n ],\n [\n -122.1240234375,\n 36.43896124085945\n ],\n [\n -121.33300781249999,\n 35.51434313431818\n ],\n [\n -120.87158203125,\n 34.88593094075317\n ],\n [\n -120.78369140624999,\n 34.470335121217474\n ],\n [\n -120.12451171875,\n 33.687781758439364\n ],\n [\n -118.27880859375001,\n 33.815666308702774\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinker, M. Tim 0000-0002-3314-839X","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":207839,"corporation":false,"usgs":true,"family":"Tinker","given":"M. Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":808385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laidre, Kristin L.","contributorId":191798,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Brian B. 0000-0003-1432-2660 brian_hatfield@usgs.gov","orcid":"https://orcid.org/0000-0003-1432-2660","contributorId":147917,"corporation":false,"usgs":true,"family":"Hatfield","given":"Brian","email":"brian_hatfield@usgs.gov","middleInitial":"B.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Michael D.","contributorId":127460,"corporation":false,"usgs":false,"family":"Harris","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":808389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bell, Tom W.","contributorId":149016,"corporation":false,"usgs":false,"family":"Bell","given":"Tom","email":"","middleInitial":"W.","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":808391,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saarman, Emily","contributorId":247807,"corporation":false,"usgs":false,"family":"Saarman","given":"Emily","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":808392,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carswell, Lilian P.","contributorId":221789,"corporation":false,"usgs":false,"family":"Carswell","given":"Lilian P.","affiliations":[{"id":40429,"text":"USFWS - Ventura FWO","active":true,"usgs":false}],"preferred":false,"id":808393,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808394,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70227447,"text":"70227447 - 2021 - Movements of marine and estuarine turtles during Hurricane Michael","interactions":[],"lastModifiedDate":"2022-01-17T16:16:36.898138","indexId":"70227447","displayToPublicDate":"2021-01-15T10:08:41","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":"Movements of marine and estuarine turtles during Hurricane Michael","docAbstract":"Natural disturbances are an important driver of population dynamics. Because it is difficult to observe wildlife during these events, our understanding of the strategies that species use to survive these disturbances is limited. On October 10, 2018, Hurricane Michael made landfall on Florida’s northwest coast. Using satellite and acoustic telemetry, we documented movements of 6 individual turtles: one loggerhead sea turtle, one Kemp’s ridley sea turtle, three green sea turtles and one diamondback terrapin, in a coastal bay located less than 30 km from hurricane landfall. Post-storm survival was confirmed for all but the Kemp’s ridley; the final condition of that individual remains unknown. No obvious movements were observed for the remaining turtles however the loggerhead used a larger home range in the week after the storm. This study highlights the resiliency of turtles in response to extreme weather conditions. However, long-term impacts to these species from habitat changes post-hurricane are unknown.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-021-81234-3","usgsCitation":"Lamont, M.M., Johnson, D., and Catizone, D.J., 2021, Movements of marine and estuarine turtles during Hurricane Michael: Scientific Reports, v. 11, p. 1-11, https://doi.org/10.1038/s41598-021-81234-3.","productDescription":"1577, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-118507","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-81234-3","text":"Publisher Index Page"},{"id":394437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","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 -91.42822265625,\n 18.083200903334312\n ],\n [\n -80.88134765625,\n 18.083200903334312\n ],\n [\n -80.88134765625,\n 30.751277776257812\n ],\n [\n -91.42822265625,\n 30.751277776257812\n ],\n [\n -91.42822265625,\n 18.083200903334312\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Darren 0000-0002-0502-6045","orcid":"https://orcid.org/0000-0002-0502-6045","contributorId":203921,"corporation":false,"usgs":true,"family":"Johnson","given":"Darren","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830937,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":830938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227769,"text":"70227769 - 2021 - Using grazing to manage herbaceous structure for a heterogeneity-dependent bird","interactions":[],"lastModifiedDate":"2022-01-31T15:19:36.502867","indexId":"70227769","displayToPublicDate":"2021-01-15T09:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Using grazing to manage herbaceous structure for a heterogeneity-dependent bird","docAbstract":"Grazing management recommendations often sacrifice the intrinsic heterogeneity of grasslands by prescribing uniform grazing distributions through smaller pastures, increased stocking densities, and reduced grazing periods. The lack of patch-burn grazing in semi-arid landscapes of the western Great Plains in North America requires alternative grazing management strategies to create and maintain heterogeneity of habitat structure (e.g., animal unit distribution, pasture configuration), but knowledge of their effects on grassland fauna is limited. The lesser prairie-chicken (Tympanuchus pallidicinctus), an imperiled, grassland-obligate, native to the southern Great Plains, is an excellent candidate for investigating effects of heterogeneity-based grazing management strategies because it requires diverse microhabitats among life-history stages in a semi-arid landscape. We evaluated influences of heterogeneity-based grazing management strategies on vegetation structure, habitat selection, and nest and adult survival of lesser prairie-chickens in western Kansas, USA. We captured and monitored 116 female lesser prairie-chickens marked with very high frequency (VHF) or global positioning system (GPS) transmitters and collected landscape-scale vegetation and grazing data during 2013–2015. Vegetation structure heterogeneity increased at stocking densities ≤0.26 animal units/ha, where use by nonbreeding female lesser prairie-chickens also increased. Probability of use for nonbreeding lesser prairie-chickens peaked at values of cattle forage use values near 37% and steadily decreased with use ≥40%. Probability of use was positively affected by increasing pasture area. A quadratic relationship existed between growing season deferment and probability of use. We found that 70% of nests were located in grazing units in which grazing pressure was <0.8 animal unit months/ha. Daily nest survival was negatively correlated with grazing pressure. We found no relationship between adult survival and grazing management strategies. Conservation in grasslands expressing flora community composition appropriate for lesser prairie-chickens can maintain appropriate habitat structure heterogeneity through the use of low to moderate stocking densities (<0.26 animal units/ha), greater pasture areas, and site-appropriate deferment periods. Alternative grazing management strategies (e.g., rest-rotation, season-long rest) may be appropriate in grasslands requiring greater heterogeneity or during intensive drought. Grazing management favoring habitat heterogeneity instead of uniform grazing distributions will likely be more conducive for preserving lesser prairie-chicken populations and grassland biodiversity.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.21984","usgsCitation":"Kraft, J.D., Haukos, D.A., Bain, M.R., Rice, M.B., Robinson, S., Sullins, D.S., Hagen, C., Pitman, J., Lautenbach, J., Plumb, R., and Lautenbach, J., 2021, Using grazing to manage herbaceous structure for a heterogeneity-dependent bird: Journal of Wildlife Management, v. 85, no. 2, p. 354-368, https://doi.org/10.1002/jwmg.21984.","productDescription":"15 p.","startPage":"354","endPage":"368","ipdsId":"IP-092108","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/jwmg.21984","text":"External Repository"},{"id":395138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.953125,\n 37.01132594307015\n ],\n [\n -98.382568359375,\n 37.01132594307015\n ],\n [\n -98.382568359375,\n 39.29179704377487\n ],\n [\n -101.953125,\n 39.29179704377487\n ],\n [\n -101.953125,\n 37.01132594307015\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kraft, John D.","contributorId":172789,"corporation":false,"usgs":false,"family":"Kraft","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":832156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bain, Matthew R.","contributorId":272571,"corporation":false,"usgs":false,"family":"Bain","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":33811,"text":"TNC","active":true,"usgs":false}],"preferred":false,"id":832157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":832158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Samantha","contributorId":272573,"corporation":false,"usgs":false,"family":"Robinson","given":"Samantha","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullins, Dan S.","contributorId":272574,"corporation":false,"usgs":false,"family":"Sullins","given":"Dan","email":"","middleInitial":"S.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hagen, Christian A.","contributorId":272575,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":832161,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pitman, James","contributorId":176512,"corporation":false,"usgs":false,"family":"Pitman","given":"James","affiliations":[],"preferred":false,"id":832162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lautenbach, Joseph","contributorId":272577,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Joseph","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832163,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Plumb, Reid","contributorId":272578,"corporation":false,"usgs":false,"family":"Plumb","given":"Reid","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832164,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lautenbach, Jonathan","contributorId":272579,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Jonathan","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":832165,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70217305,"text":"70217305 - 2021 - Seed production patterns of surviving Sierra Nevada conifers show minimal change following drought","interactions":[],"lastModifiedDate":"2021-01-18T13:39:10.353799","indexId":"70217305","displayToPublicDate":"2021-01-15T07:37:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Seed production patterns of surviving Sierra Nevada conifers show minimal change following drought","docAbstract":"Reproduction is a key component of ecological resilience in forest ecosystems, so understanding how seed production is influenced by extreme drought is key to understanding forest recovery trajectories. If trees respond to mortality-inducing drought by preferentially allocating resources for reproduction, the recovery of the stand to pre-drought conditions may be enhanced accordingly. We used a 20-year annual seed capture data set to investigate whether seed production by three tree genera commonly found in the Sierra Nevada (Abies, Pinus, and Calocedrus) was correlated with variation in local weather, which included an extreme drought spanning multiple years. We tested whether average seed production differed during the drought years, and whether annual seed counts could be explained by three weather variables: spring temperature, annual precipitation, and summer climatic water deficit (CWD). We fit models testing for four separate effects: (1) a priming year model (weather 1 year prior to reproductive bud initiation), (2) a bud initiation model (weather in the year of reproductive bud initiation), (3) a pollination year model (weather in the year of pollination), and (4) maturation year model (weather in the year of seed maturation). For genera with two-year reproductive cycles, the pollination and maturation models were combined. We found support for the summer CWD Abies maturation year model, which suggested higher seed outputs immediately following dry summer conditions. The spring temperature pollination year model was selected for Pinus, which suggested that seed output is higher following warm spring weather during pollination. The annual precipitation priming year model was selected for Calocedrus, which showed a negative association between seed production and wetter conditions two years prior to seed production. More parent tree basal area resulted in higher seed output for all genera, though the confidence intervals overlapped 0 for Calocedrus. Permutation tests sugested there was no systematic difference in mean seed production during the drought after accounting for live tree basal area, regardless of genus. These results highlight the variability in response across genera, and suggest that the influence of seed production on forest recovery following drought-related mortality may depend on affected species and the timing of the mortality event within the masting cycle. A greater understanding of species-level masting to drought stress is needed to more precisely predict community-level recovery following drought.
Understanding the carbon transport within aquatic environments is crucial to quantifying global and local carbon budgets, yet limited empirical data currently (2021) exist. This report documents methodology and provides data for quantifying the aquatic export of carbon from a cypress swamp within Big Cypress National Preserve and is part of a larger carbon budget study. The U.S. Geological Survey operated two continuous monitoring stations, 022889001 and 022909471, that measured flow volume and water quality within the Big Cypress National Preserve in South Florida from September 2015 to October 2017. Station 022889001 represented the flow into the study area and station 022909471 represented the flow out of the study area. Site-specific regression models were developed by using continuously measured specific conductance and concomitant, discretely collected dissolved organic carbon, dissolved inorganic carbon, and particulate carbon samples to calculate total carbon (TC) concentrations at 15-minute intervals.
Calculated TC concentrations typically increased as flow was decreasing and decreased as flow was increasing. TC loads were calculated by multiplying concentrations and flow volume, and the difference between the load calculations for input/output locations of the swamp flow system was used to determine the aquatic carbon export from the study area.
Calculated monthly TC loads ranged from 0 metric tons in spring 2017 at both stations to 3,145 and 7,821 metric tons in September 2017 at 022889001 and 022909471, respectively. During 2016, the annual loads were 10,479 and 15,243 metric tons at 022889001 and 022909471, respectively. Calculated monthly aquatic TC exports from the study area ranged from −0.7 gram of carbon per square meter in May 2016 to 44.1 grams of carbon per square meter during September 2017. The carbon export from the study area varied monthly, increased as flow increased, and was greatly influenced by Hurricane Irma in September 2017. The aquatic TC export from the Sweetwater Strand study area was 42.0 grams of carbon per square meter per year in 2016, which is substantially (about 15 times) larger than the estimated overall mean riverine carbon export per square meter for the eastern United States; however, it was also less than the monthly export of carbon in September 2017. The monthly aquatic carbon export from the study area in September 2017 alone was greater than the aquatic carbon export from all of 2016, which is largely the result of the substantial increase in flow attributed to Hurricane Irma.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201136","collaboration":"Greater Everglades Priority Ecosystem Science Program","usgsCitation":"Booth, A.C., 2021, Development and application of surrogate models, calculated loads, and aquatic export of carbon based on specific conductance, Big Cypress National Preserve, South Florida, 2015–17: U.S. Geological Survey Open-File Report 2020–1136, 14 p., https://doi.org/10.3133/ofr20201136.","productDescription":"Report: v, 14 p.; Data Release; 2 Appendixes","onlineOnly":"Y","ipdsId":"IP-112929","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":382104,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.rtf","text":"Appendix 2","size":"960 kB","description":"OFR 2020-1136 Appendix 2 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida (rtf file)"},{"id":382062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1136/coverthb.jpg"},{"id":382063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1136/ofr20201136.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136"},{"id":382064,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EXZLJT","text":"USGS data release","linkHelpText":"Calculated carbon concentrations, loads, and export in Big Cypress National Preserve, South Florida, 2015-2017"},{"id":382101,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.pdf","text":"Appendix 1","size":"424 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 1 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida"},{"id":382102,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix2.pdf","text":"Appendix 2","size":"356 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1136 Appendix 2 pdf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022909471: Loop Road Culverts Monroe Station to Florida Trail, Florida"},{"id":382103,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1136/appendix1.rtf","text":"Appendix 1","size":"2.91 MB","description":"OFR 2020-1136 Appendix 1 rtf file","linkHelpText":"Model Archive for Total Carbon Concentration at U.S. Geological Survey Station 022889001: Tamiami Canal 11 Mile Road to Monroe Station, Florida (rtf file)"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.22604370117186,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 25.812254545273433\n ],\n [\n -80.8978271484375,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 26.058016587844723\n ],\n [\n -81.22604370117186,\n 25.812254545273433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Although Arctic ringed seals Phoca hispida hispida are currently abundant and broadly distributed, their numbers are projected to decline substantially by the year 2100 due to climate warming. While understanding population structure could provide insight into the impact of environmental changes on this subspecies, detecting demographically important levels of exchange can be difficult in taxa with high abundance. We used a next-generation sequencing approach (DArTseq) to genotype ~5700 single nucleotide polymorphisms in 79 seals from 4 Pacific Arctic regions. Comparison of the 2 most geographically separated strata (eastern Bering vs. northeastern Chukchi-Beaufort Seas) revealed a statistically significant level of genetic differentiation (FST = 0.001, p = 0.005) that, while small, was 1 to 2 orders of magnitude greater than expected based on divergence estimated for similarly sized populations connected by low (1% yr-1) dispersal. A relatively high proportion (72 to 88%) of individuals within these strata could be genetically assigned to their stratum of origin. These results indicate that demographically important structure may be present among Arctic ringed seals breeding in different areas, increasing the risk that declines in the number of seals breeding in areas most negatively affected by environmental warming could occur.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01087","usgsCitation":"Lang, A.R., Boveng, P.L., Quakenbush, L., Robertson, K., Lauf, M., Rode, K.D., Ziel, H., and Taylor, B., 2021, Re-examination of population structure in Arctic ringed seals using DArTseq genotyping: Endangered Species Research, v. 44, p. 11-31, https://doi.org/10.3354/esr01087.","productDescription":"21 p.","startPage":"11","endPage":"31","ipdsId":"IP-104727","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453844,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01087","text":"Publisher Index Page"},{"id":382277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": 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]\n}","volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lang, Aimee R.","contributorId":247810,"corporation":false,"usgs":false,"family":"Lang","given":"Aimee","email":"","middleInitial":"R.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boveng, Peter L.","contributorId":171523,"corporation":false,"usgs":false,"family":"Boveng","given":"Peter","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":808401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quakenbush, L.","contributorId":243091,"corporation":false,"usgs":false,"family":"Quakenbush","given":"L.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":808402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Robertson, K.","contributorId":247811,"corporation":false,"usgs":false,"family":"Robertson","given":"K.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lauf, M.","contributorId":247812,"corporation":false,"usgs":false,"family":"Lauf","given":"M.","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":808405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ziel, H.","contributorId":247813,"corporation":false,"usgs":false,"family":"Ziel","given":"H.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":808406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Taylor, B .L.","contributorId":181914,"corporation":false,"usgs":false,"family":"Taylor","given":"B .L.","affiliations":[],"preferred":false,"id":808407,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218755,"text":"70218755 - 2021 - The weight of cities: Urbanization effects on Earth’s subsurface","interactions":[],"lastModifiedDate":"2021-03-12T14:56:28.755208","indexId":"70218755","displayToPublicDate":"2021-01-14T08:55:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7751,"text":"AGU Advances","active":true,"publicationSubtype":{"id":10}},"title":"The weight of cities: Urbanization effects on Earth’s subsurface","docAbstract":"Across the world, people increasingly choose to live in cities. By 2050, 70% of Earth's population will live in large urban areas. Upon considering a large city, questions arise such as, how much does that weigh? What are its effects on the landscape? Does it cause measurable subsidence? Here I calculate the weight of San Francisco Bay region urbanization, where 7.75 million people live at, or near the coast. It is difficult to account for everything that is in a city. I assume that most of the weight is buildings and their contents, which allows the use of base outline and height data to approximate their mass, which is cumulatively 1.6·1012 kg. I build a series of finite element models to study effects of pressure exerted by the weight distribution. Within the elastic realm, I look at compression, flexure, isostatic compensation, stress change, dilatation, and fluid flow changes. Within the nonlinear realm I show example calculations of primary and secondary settlement of soils under load. The combined modeled subsidence from building loads is at least 5–80 mm, with the largest contributions coming from nonlinear settlement and creep in soils. A general result is closing of pore space and redirection of pore fluids. While the calculated subsidence of the Bay Area is relatively small compared with other sources of elevation change such as pumping and recharge of aquifers, all sources of subsidence are concerning given an expected 200–300 mm sea level rise at San Francisco by the year 2050.
Water-quality effects after remediating abandoned draining mine tunnels using structural bulkheads were examined in two study areas in Colorado, USA. A bulkhead was installed in the Dinero mine tunnel in 2009 to improve water quality in Lake Fork Creek, a tributary to the upper Arkansas River. Although bulkhead installation improved pH, and manganese and zinc concentrations and loads at the Dinero mine tunnel, water-quality degradation was observed at the nearby Nelson tunnel. Only manganese concentrations improved in Lake Fork Creek downstream from the tunnel. To improve water quality in Cement Creek, a tributary of the Animas River, multiple bulkheads were installed in mine tunnels during 1996–2003 and a water treatment plant operated from 1989 to 2003 to treat drainage from several draining tunnels. After bulkhead installation and cessation of active water treatment (about 2003), water quality (pH and dissolved copper, manganese, and zinc concentrations) degraded at the mouth of Cement Creek. The patterns and timing were similar to post-bulkhead increased discharge and trace-metal loads at non-bulkheaded tunnels indicating the bulkheads might have been the cause. Pre-1989 water-quality data for Cement Creek are scarce, although limited historical data indicate possible, slight improvement in only manganese concentrations after bulkhead installation. Increased zinc loads in Lake Fork Creek and decreased pH through time in Cement Creek may indicate increased groundwater discharge to the streams after bulkhead installation. In these two study areas, bulkheads did not substantially improve downstream water quality.
The Bureau of Land Management (BLM) requested assistance from the U.S. Geological Survey (USGS) to conduct an assessment study to identify areas that may have economic potential for the future extraction of lignite and leonardite resources in the Williston Basin in North Dakota. The study will be used by the BLM to assist with the preparation of a revised resource management plan for the Williston Basin, in accordance with BLM planning policies.
The assessment of the economic potential of lignite resources required the establishment of criteria defining an economic lignite deposit. In consultation with the BLM, criteria were established to delineate drill holes that contained economic lignite beds. The criteria established are a minimum lignite bed thickness, a minimum cumulative lignite thickness, a maximum cumulative stripping ratio, and a maximum overburden. Likewise, an assessment of the economic potential of leonardite deposits required the establishment of criteria delineating drill holes that contained economic leonardite deposits. The criteria established are a minimum leonardite bed thickness, a minimum cumulative leonardite thickness, and a maximum overburden.
The drill hole data utilized in this study were obtained from the National Coal Resources Data System database and from several coal companies. Data from more than 20,000 drill holes, both proprietary and nonproprietary, were used to compile areas of economic potential for lignite or leonardite.
Areas delineated as having lignite or leonardite resources with economic potential, based on the established criteria, were present in 24 counties in the western portion of North Dakota. Areas of economic potential were delineated using a visual best-fit method without croplines. Areas defined as having economic potential for certain lignite beds or leonardite deposits may extend beyond known croplines in this study.
Stratigraphically, the lignite and leonardite deposits in the Williston Basin in North Dakota are mostly found in the Paleocene Fort Union Formation. Thick (greater than 20 feet) and laterally extensive (greater than 5 square miles) lignite beds are present in the Fort Union Formation throughout the Sentinel Butte and Tongue River Members. Lignite beds are also present in the Ludlow Member of the Fort Union Formation, although they are not as numerous or thick as they are in the overlying Sentinel Butte and Tongue River Members. As a result of lateral facies changes and migrating fluvial channel complexes in the Fort Union Formation, lignite beds of varying thickness occupy different stratigraphic horizons vertically throughout the Williston Basin.
The calculation of volumes for lignite and leonardite resources was not part of the scope of this study requested by the BLM, but a future study by the USGS may involve a comprehensive assessment of lignite resources and reserves in the Williston Basin. This future study could combine geologic data compiled in this study with geologic data from a previously unpublished 2019 assessment study by the USGS in the Williston Basin in eastern Montana. This future USGS study could also include the calculation of volumes for lignite resources and reserves, based on economic models derived using analogs from active mining operations in the Williston Basin and available spot market or contract coal prices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201135","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shaffer, B.N., 2021, An assessment of the economic potential of lignite and leonardite resources in the Williston Basin, North Dakota: U.S. Geological Survey Open-File Report 2020–1135, 14 p., https://doi.org/10.3133/ofr20201135.","productDescription":"vi, 14 p.","onlineOnly":"Y","ipdsId":"IP-120360","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":436582,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436581,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93GGU6P","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Mercer and Oliver Counties, North Dakota"},{"id":436580,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436579,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NWIHEE","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in McLean County, North Dakota"},{"id":436578,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436577,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94V9WV8","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Billings County, North Dakota"},{"id":436576,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436575,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90636SP","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Golden Valley County, North Dakota"},{"id":436574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FHHH4T","text":"USGS data release","linkHelpText":"Drill hole data for coal beds in the Paleocene Fort Union Formation in the Williston Basin in Dunn County, North Dakota"},{"id":382138,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1135/coverthb.jpg"},{"id":382139,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1135/ofr20201135.pdf","text":"Report","size":"6.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1135"}],"country":"United States","state":"North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 45.89000815866184\n ],\n [\n -99.931640625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 45.89000815866184\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Quantitative reconstructions of vegetation abundance from sediment-derived pollen systems provide unique insights into past ecological conditions. Recently, the use of pollen accumulation rates (PAR, grains cm−2 year−1) has shown promise as a bioproxy for plant abundance. However, successfully reconstructing region-specific vegetation dynamics using PAR requires that accurate assessments of pollen deposition processes be quantitatively linked to spatially-explicit measures of plant abundance. Our study addressed these methodological challenges. Modern PAR and vegetation data were obtained from seven lakes in the western Klamath Mountains, California. To determine how to best calibrate our PAR-biomass model, we first calculated the spatial area of vegetation where vegetation composition and patterning is recorded by changes in the pollen signal using two metrics. These metrics were an assemblage-level relevant source area of pollen (aRSAP) derived from extended R-value analysis (sensu Sugita, 1993) and a taxon-specific relevant source area of pollen (tRSAP) derived from PAR regression (sensu Jackson, 1990). To the best of our knowledge, aRSAP and tRSAP have not been directly compared. We found that the tRSAP estimated a smaller area for some taxa (e.g. a circular area with a 225 m radius for Pinus) than the aRSAP (a circular area with a 625 m radius). We fit linear models to relate PAR values from modern lake sediments with empirical, distance-weighted estimates of aboveground live biomass (AGLdw) for both the aRSAP and tRSAP distances. In both cases, we found that the PARs of major tree taxa – Pseudotsuga, Pinus, Notholithocarpus, and TCT (Taxodiaceae, Cupressaceae, and Taxaceae families) – were statistically significant and reasonably precise estimators of contemporary AGLdw. However, predictions weighted by the distance defined by aRSAP tended to be more precise. The relative root-mean squared error for the aRSAP biomass estimates was 9% compared to 12% for tRSAP. Our results demonstrate that calibrated PAR-biomass relationships provide a robust method to infer changes in past plant biomass.
","language":"English","publisher":"SAGE Publishing","doi":"10.1177/0959683620988038","usgsCitation":"Knight, C.A., Baskaran, M., Bunting, M.J., Champagne, M.R., Potts, M.D., Wahl, D., Wanket, J., and Battles, J.J., 2021, Linking modern pollen accumulation rates to biomass: Quantitative vegetation reconstruction in the western Klamath Mountains, NW California, USA: The Holocene, v. 31, no. 5, p. 814-829, https://doi.org/10.1177/0959683620988038.","productDescription":"16 p.","startPage":"814","endPage":"829","ipdsId":"IP-122720","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":453850,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hull-repository.worktribe.com/output/3679635","text":"External Repository"},{"id":382454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Western Klamath Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.365234375,\n 40.052847601823984\n ],\n [\n -121.4208984375,\n 40.052847601823984\n ],\n [\n -121.4208984375,\n 42.220381783720605\n ],\n [\n -124.365234375,\n 42.220381783720605\n ],\n [\n -124.365234375,\n 40.052847601823984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Knight, Clarke A. 0000-0003-0002-6959","orcid":"https://orcid.org/0000-0003-0002-6959","contributorId":248212,"corporation":false,"usgs":false,"family":"Knight","given":"Clarke","email":"","middleInitial":"A.","affiliations":[{"id":49825,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California 94720 USA","active":true,"usgs":false}],"preferred":false,"id":808617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baskaran, Mark","contributorId":87867,"corporation":false,"usgs":false,"family":"Baskaran","given":"Mark","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":808618,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bunting, M. Jane 0000-0002-3152-5745","orcid":"https://orcid.org/0000-0002-3152-5745","contributorId":248213,"corporation":false,"usgs":false,"family":"Bunting","given":"M.","email":"","middleInitial":"Jane","affiliations":[{"id":49826,"text":"Department of Geography, Geology and Environment, University of Hull, Cottingham Road, Hull, HU6 7RX UK","active":true,"usgs":false}],"preferred":false,"id":808619,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champagne, Marie Rhondelle 0000-0001-8236-3910","orcid":"https://orcid.org/0000-0001-8236-3910","contributorId":248214,"corporation":false,"usgs":true,"family":"Champagne","given":"Marie","email":"","middleInitial":"Rhondelle","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potts, Matthew D. 0000-0001-7442-3944","orcid":"https://orcid.org/0000-0001-7442-3944","contributorId":248215,"corporation":false,"usgs":false,"family":"Potts","given":"Matthew","email":"","middleInitial":"D.","affiliations":[{"id":49825,"text":"Department of Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, California 94720 USA","active":true,"usgs":false}],"preferred":false,"id":808621,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":808622,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wanket, James","contributorId":248216,"corporation":false,"usgs":false,"family":"Wanket","given":"James","email":"","affiliations":[{"id":49829,"text":"Department of Geography, California State University, Sacramento, Sacramento, California 95819 USA","active":true,"usgs":false}],"preferred":false,"id":808623,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":808624,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217337,"text":"70217337 - 2021 - Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","interactions":[],"lastModifiedDate":"2021-02-04T14:31:23.035113","indexId":"70217337","displayToPublicDate":"2021-01-13T11:02:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States","docAbstract":"This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b05835","usgsCitation":"Lombard, M.A., Daniel, J., Jeddy, Z., Hay, L., and Ayotte, J.D., 2021, Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States: Environmental Science & Technology, v. 55, no. 3, p. 1822-1831, https://doi.org/10.1021/acs.est.9b05835.","productDescription":"10 p.","startPage":"1822","endPage":"1831","ipdsId":"IP-109293","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":453853,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.9b05835","text":"Publisher Index Page"},{"id":436586,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TU0R2T","text":"USGS data release","linkHelpText":"Datasets for assessing the impact of drought on arsenic exposure from private domestic wells in the 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\"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"55","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":808395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Johnni","contributorId":247808,"corporation":false,"usgs":false,"family":"Daniel","given":"Johnni","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeddy, Zuha","contributorId":247809,"corporation":false,"usgs":false,"family":"Jeddy","given":"Zuha","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":808397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":808398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808399,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222946,"text":"70222946 - 2021 - B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","interactions":[],"lastModifiedDate":"2021-08-10T13:59:41.764808","indexId":"70222946","displayToPublicDate":"2021-01-13T08:57:02","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}},"displayTitle":"B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","title":"B-positive: A robust estimator of aftershock magnitude distribution in transiently incomplete catalogs","docAbstract":"The earthquake magnitude-frequency distribution is characterized by the b-value, which describes the relative frequency of large versus small earthquakes. It has been suggested that changes in b-value after an earthquake can be used to discriminate whether that earthquake is part of a foreshock sequence or a more typical mainshock-aftershock sequence, with a decrease in b-value heralding a larger earthquake to come. However, the measurement of b-value during an active aftershock sequence is strongly biased by short-term incompleteness of the earthquake catalog and by data-windowing, and these biases have the same direction as the proposed signal. Here I develop a new estimator of the b-value that is insensitive to transient changes in catalog completeness and that does not require data windowing. The new estimator “b-positive” is based on the positive-only subset of the differences in magnitude between successive earthquakes, which are described by a double-exponential (Laplace) distribution with the same b-value as the magnitude distribution itself. The b-positive estimator greatly improves the robustness of continuous b-value measurements during active earthquake sequences, as well as in historical catalogs with unknown or variable completeness. The new estimator confirms some of the observations of Gulia and Wiemer (2019), although at a reduced level, showing a decrease and recovery of the b-value during several recent foreshock sequences that cannot be attributed simply to measurement bias. However, the unbiased b-value changes may be too subtle to use in a real-time earthquake alarm system.
Dense, vitric, dacitic pyroclasts (dacite lithics) from the 1991 preclimactic explosions of Mt. Pinatubo were analyzed for their vesicular and crystal textures and dissolved H2O and CO2 contents. Micron-scale heterogeneities in groundmass glass volatile contents (0.9 wt% differences in H2O within 500 μm) are observed and argue that parts of the dacite lithics equilibrated at different depths before finally being constructed. Greater vesicularities and larger and greater number densities of vesicles are observed in groundmass glass around phenocrysts compared to groundmass glass away from phenocrysts, similar to textures produced in experiments that sintered bimodal distributions of particles. Furthermore, increasingly greater proportions of stretched and distorted vesicles are observed in lithics from the later explosions, which parallels the increasingly shorter reposes between explosions. Finally, micron-sized crystal fragments are ubiquitous in groundmass glass of all dacite lithics. The textures, together with the variable volatile contents, lead us to propose a model that the dacite lithics formed by rapid and repetitive sintering of ash particles derived from a variety of depths on the conduit walls above the fragmentation level. We speculate that sintering of conduit material produced impermeable layers that retarded gas flow through the conduit, causing pressure to build until the cap failed and the next explosion occurred.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-020-01427-y","usgsCitation":"Wang, Y., Gardner, J., and Hoblitt, R., 2021, Formation of dense pyroclasts by sintering of ash particles during the preclimactic eruptions of Mt. Pinatubo in 1991: Bulletin of Volcanology, v. 83, 6, 13 p., https://doi.org/10.1007/s00445-020-01427-y.","productDescription":"6, 13 p.","ipdsId":"IP-123722","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":401291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Philippines","otherGeospatial":"Mount Pinatubo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 120.28038024902344,\n 15.101957550324563\n ],\n [\n 120.41015624999999,\n 15.101957550324563\n ],\n [\n 120.41015624999999,\n 15.208662610868245\n ],\n [\n 120.28038024902344,\n 15.208662610868245\n ],\n [\n 120.28038024902344,\n 15.101957550324563\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yining","contributorId":292117,"corporation":false,"usgs":false,"family":"Wang","given":"Yining","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":843815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, James E.","contributorId":292118,"corporation":false,"usgs":false,"family":"Gardner","given":"James E.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":843816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoblitt, Richard P. 0000-0001-5850-4760","orcid":"https://orcid.org/0000-0001-5850-4760","contributorId":292119,"corporation":false,"usgs":false,"family":"Hoblitt","given":"Richard P.","affiliations":[{"id":62834,"text":"USGS Volcano Science Center","active":true,"usgs":false}],"preferred":false,"id":843817,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}