The U.S. Department of Interior National Park Service is charged with both monitoring avian communities and evaluating the influence of visitors to National Parks on sensitive species; however, this task is challenging considering that sampling programs often involve multiple species, each with differing behavior, habitat requirements, and detectability. Our objectives were to build a model to describe the status of waterbirds in Glacier Bay National Park, Alaska, USA, and assess effects of area closures on these species. We used a Bayesian multistate occupancy model to describe the status of multiple species and make the best possible use of existing survey data. We modeled up to 5 states per species and evaluated predictors of occupancy, nesting, and abundance, as well as survey-related predictors of state-dependent detection probability. We found that occupancy probability varied across species and habitats (islands vs. glacial outwashes). For most species, occupancy probability was substantially greater at sites occupied in the year previous (site persistence). We found weak evidence that area closures affected the occurrence of species in the study, but this was largely because most sites were closed for the entirety of the study period. The probability of detecting occurrence, nesting, and abundance varied across species and survey methods (ground vs. vessel). Detection parameters provided valuable information for enhancing the efficiency of future surveys, by identifying preferred survey methods and sampling periods for specific waterbird species. © 2020 The Wildlife Society.
Dynamically triggered offshore aftershocks, caused by passing seismic waves from main shocks located on land, are currently not considered in tsunami warnings. The M7.0 2010 Haiti earthquake epicenter was located on land 27 km north of the Caribbean Sea and its focal mechanism was oblique strike-slip. Nevertheless, a tsunami recorded on a Caribbean Deep-Ocean Assessment and Reporting of Tsunami (DART) buoy and a tide gauge produced runup heights of 1–3 m along Haiti southeast coast. Earthquake finite-fault model inversions of the DART waveform suggest that a reverse fault doublet with magnitudes of M6.8 and M6.5 located 85 km southwest of the epicenter may have excited the tsunami. This doublet collocates with dynamically triggered aftershocks, derived from back-projection analysis, that occurred 20-60 s after the main shock of the Haiti earthquake. The aftershocks are within a region of maximum dynamic strain predicted by the main shock, on a possibly tectonically active submarine ridge southwest of Haiti's Southern Peninsula. The agreement between the tsunami finite-fault source models and the seismic and tectonic evidence suggests that earthquakes on land, even strike-slip faults, can generate tsunamis by dynamically triggering offshore aftershocks.
Environmental change associated with anthropogenic disturbance can lower habitat quality, especially for sensitive species such as many amphibians. Variation in environmental quality may affect an organism’s physiological health and, ultimately, survival and fitness. Using multiple health measures can aid in identifying populations at increased risk of declines. Our objective was to measure environmental variables at multiple spatial scales and their effect on three indicators of health in ornate chorus frog (Pseudacris ornata) tadpoles to identify potential correlates of population declines. To accomplish this, we measured a glucocorticoid hormone (corticosterone; CORT) profile associated with the stress response, as well as the skin mucosal immune function (combined function of skin secretions and skin bacterial community) and bacterial communities of tadpoles from multiple ponds. We found that water quality characteristics associated with environmental variation, including higher water temperature, conductivity and total dissolved solids, as well as percent developed land nearby, were associated with elevated CORT release rates. However, mucosal immune function, although highly variable, was not significantly associated with water quality or environmental factors. Finally, we examined skin bacterial diversity as it aids in immunity and is affected by environmental variation. We found that skin bacterial diversity differed between ponds and was affected by land cover type, canopy cover and pond proximity. Our results indicate that both local water quality and land cover characteristics are important determinants of population health for ornate chorus frogs. Moreover, using these proactive measures of health over time may aid in early identification of at-risk populations that could prevent further declines and aid in management decisions.
","language":"English","publisher":"The Society for Experimental Biology","doi":"10.1093/conphys/coaa047","usgsCitation":"Goff, C.B., Walls, S., Rodriguez, D., and Gabor, C.S., 2020, Changes in physiology and microbial diversity in larval ornate chorus frogs are associated with habitat quality: Conservation Physiology, v. 8, no. 1, coaa047, 19 p., https://doi.org/10.1093/conphys/coaa047.","productDescription":"coaa047, 19 p.","ipdsId":"IP-109179","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456407,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coaa047","text":"Publisher Index Page"},{"id":436929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UBF9SM","text":"USGS data release","linkHelpText":"Corticosterone release rates, water quality, microbiome, and mucosome data for analysis of Pseudacris ornata sites"},{"id":411709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Goff, Cory B.","contributorId":300720,"corporation":false,"usgs":false,"family":"Goff","given":"Cory","email":"","middleInitial":"B.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861287,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walls, Susan 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":216235,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":861288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, David","contributorId":300721,"corporation":false,"usgs":false,"family":"Rodriguez","given":"David","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861289,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gabor, Caitlin S.","contributorId":300722,"corporation":false,"usgs":false,"family":"Gabor","given":"Caitlin","email":"","middleInitial":"S.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":861290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274789,"text":"70274789 - 2020 - Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary","interactions":[],"lastModifiedDate":"2026-04-09T15:01:46.432427","indexId":"70274789","displayToPublicDate":"2020-06-15T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":23798,"text":"Frontiers Earth Science - Biogeoscience","active":true,"publicationSubtype":{"id":10}},"title":"Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary","docAbstract":"Environmental research has been shifting toward a new normal in which a primary focus is to capture change that may be accelerating. In this study, we collected particulate samples in the northern San Francisco Bay Estuary (SFBE) in the fall of 2011 through the spring of 2012 in order to assess vascular plant contributions across both time and space and to compare our findings with a similar set of samples from 1990 to 1992. Across the ∼20-year span, we detected (1) decreasing C:Na ratios (averages ± SD of 12.5 ± 2.5 vs. 8.8 ± 1.4, significant t-test with p < 0.0001); (2) distinct shifts in chlorophyll vs. salinity, with higher chlorophyll concentrations shifting toward freshwater; and (3) greater relative proportions of vascular plant carbon that also appears less degraded (as indicated by lignin measurements) shifting from freshwater toward higher salinities. Lignin compositional data (syringyl:vanillyl and cinnamyl:vanillyl) suggest that increased lignin content in the more saline samples could be derived from wetland materials, while a two-endmember mixing model indicates that a significant portion of the particulate organic carbon (POC) in the western sites (50–60% as an upper bound, 13–15% as a lower bound) could be wetland-derived. This has potential implications for the lower food web, given recent work that demonstrates selective feeding by copepods on wetland detrital material in the northern SFBE. The latter has ramifications for proposed wetland restoration within the SFBE and Sacramento River/San Joaquin River Delta system, namely, that restored wetlands could confer important benefits toward the food web. Equally important is to prioritize continued monitoring of particulate organic matter cycling in the SFBE system to make sure that changing conditions are accounted for in any management decision.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2020.00185","usgsCitation":"Hernes, P.J., Dyda, R.Y., and Bergamaschi, B.A., 2020, Reassessing particulate organic carbon dynamics in the highly disturbed San Francisco Bay Estuary: Frontiers Earth Science - Biogeoscience, v. 8, 185, 13 p., https://doi.org/10.3389/feart.2020.00185.","productDescription":"185, 13 p.","ipdsId":"IP-117634","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":502493,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.00185","text":"Publisher Index Page"},{"id":502352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River Delta, San Francisco Bay Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.2443083713161,\n 38.39872273873195\n ],\n [\n -122.2443083713161,\n 37.81288212710655\n ],\n [\n -121.45817059994386,\n 37.81288212710655\n ],\n [\n -121.45817059994386,\n 38.39872273873195\n ],\n [\n -122.2443083713161,\n 38.39872273873195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Hernes, Peter J.","contributorId":139730,"corporation":false,"usgs":false,"family":"Hernes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":959148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyda, Rachael Y. 0000-0002-4616-7231","orcid":"https://orcid.org/0000-0002-4616-7231","contributorId":369567,"corporation":false,"usgs":false,"family":"Dyda","given":"Rachael","middleInitial":"Y.","affiliations":[{"id":28024,"text":"UCDavis","active":true,"usgs":false}],"preferred":false,"id":959149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":959150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217553,"text":"70217553 - 2020 - Investigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series","interactions":[],"lastModifiedDate":"2021-01-21T21:00:37.352527","indexId":"70217553","displayToPublicDate":"2020-06-13T14:57:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series","docAbstract":"To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly (
In the Northern Gulf of Mexico, salt marshes are threatened by sea level rise, erosion, and loss of protective barrier islands. These barrier islands provide critical habitat for wildlife, including globally significant populations of marsh and shorebirds. We investigated salt marsh restoration on two Louisiana barrier islands using presence of 8 marsh bird species as an index to evaluate restoration success. Land loss was extensive for both islands prior to restoration, with submerged marsh restored by backfilling sediment into the marsh platform. Restoration methods were similar between the two islands, although Raccoon Island was built to a higher elevation (1.1 m) than Whiskey Island (0.8m). Avian presence was estimated via passive acoustic monitoring and point counts. To evaluate restoration success, we modeled influence of habitat covariates on index species presence in restored and reference (intact) sites over three breeding seasons and modeled occupancy for 6 species. On Whiskey Island, index richness was higher in restored sites. Marsh specialists Seaside Sparrows (Ammospiza maritima ) and Least Bitterns (Ixobrychus exilis ) had higher occupancy in restored areas on Whiskey, while generalist species showed no response to site. These results are likely due to a strong association between habitat and vegetation type, with restored sites dominated by Spartina alterniflora and reference sites by Avicennia germinans . On Raccoon Island, species richness was low across all sites. Our results suggest that restoration efforts were successful in creating salt marsh habitat on Whiskey but not Raccoon as of the time of our study.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13222","usgsCitation":"Byerly, P.A., Waddle, H., Premeaux, A.R., and Leberg, P.L., 2020, Effects of barrier island salt marsh restoration on marsh bird occurrence in the Northern Gulf of Mexico: Restoration Ecology, v. 28, no. 6, p. 1610-1620, https://doi.org/10.1111/rec.13222.","productDescription":"11 p.","startPage":"1610","endPage":"1620","ipdsId":"IP-118357","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":377330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Isles Derniers, Raccoon Island, Whiskey Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.96954345703125,\n 29.014745722129636\n ],\n [\n -90.65711975097656,\n 29.014745722129636\n ],\n [\n -90.65711975097656,\n 29.09517707913941\n ],\n [\n -90.96954345703125,\n 29.09517707913941\n ],\n [\n -90.96954345703125,\n 29.014745722129636\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Byerly, Paige A.","contributorId":237930,"corporation":false,"usgs":false,"family":"Byerly","given":"Paige","email":"","middleInitial":"A.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":222187,"corporation":false,"usgs":true,"family":"Waddle","given":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":795564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Premeaux, Alexis R.","contributorId":237932,"corporation":false,"usgs":false,"family":"Premeaux","given":"Alexis","email":"","middleInitial":"R.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795565,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leberg, Paul L.","contributorId":237934,"corporation":false,"usgs":false,"family":"Leberg","given":"Paul","email":"","middleInitial":"L.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":795566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210797,"text":"70210797 - 2020 - Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain","interactions":[],"lastModifiedDate":"2020-06-25T15:19:50.029027","indexId":"70210797","displayToPublicDate":"2020-06-13T09:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain","docAbstract":"Conservation status and management priorities are often informed by population trends. Trend estimates can be derived from population surveys or models, but both methods are associated with sources of uncertainty. Many Arctic-breeding shorebirds are thought to be declining based on migration and/or overwintering population surveys, but data are lacking to estimate the trends of some shorebird species. In addition, for most species, little is known about the stage(s) at which population bottlenecks occur, such as breeding vs. nonbreeding periods. We used previously published and unpublished estimates of vital rates to develop the first large-scale population models for 6 species of Arctic-breeding shorebirds in North America, including separate estimates for 3 subspecies of Dunlin. We used the models to estimate population trends and identify life stages at which population growth may be limited. Our model for the arcticola subspecies of Dunlin agreed with previously published information that the subspecies is severely declining. Our results also linked the decline to the subspecies’ low annual survival rate, thus potentially implicating factors during the nonbreeding period in the East Asian-Australasian Flyway. However, our trend estimates for all species showed high uncertainty, highlighting the need for more accurate and precise estimates of vital rates. Of the vital rates, annual survival had the strongest influence on population trend in all taxa. Improving the accuracy, precision, and spatial and temporal coverage of estimates of vital rates, especially annual survival, would improve demographic model-based estimates of population trends and help direct management to regions or seasons where birds are subject to higher mortality.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duaa026","usgsCitation":"Weiser, E.L., Lanctot, R., Brown, S.C., Gates, H., Bety, J., Boldenow, M.L., Brook, R.W., Brown, G.S., English, W.B., Flemming, S.A., Franks, S., Gilchrist, H.G., Giroux, M., Johnson, A.C., Kendall, S., Kennedy, L.V., Koloski, L., Kwon, E., Lamarre, J., Lank, D.B., Latty, C.J., Lecomte, N., Liebezeit, J.R., McGuire, R., McKinnon, L., Nol, E., Payer, D.C., Perz, J., Rausch, J., Robards, M.D., Saalfeld, S.T., Senner, N.R., Smith, P., Soloviev, M., Solovyeva, D.V., Ward, D.H., Wood, P., and Sandercock, B., 2020, Annual adult survival drives trends in Arctic-breeding shorebirds but knowledge gaps in other vital rates remain: The Condor, v. 1222, duaa026, 14 p., https://doi.org/10.1093/condor/duaa026.","productDescription":"duaa026, 14 p.","ipdsId":"IP-114598","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":456413,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duaa026","text":"Publisher Index Page"},{"id":436931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DZZ1OB","text":"USGS data release","linkHelpText":"Arctic Shorebird Population Model"},{"id":375919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1222","noUsgsAuthors":false,"publicationDate":"2020-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":791464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":791470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":791471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, H. River","contributorId":84256,"corporation":false,"usgs":true,"family":"Gates","given":"H. River","affiliations":[],"preferred":false,"id":791472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bêty, Joël","contributorId":169335,"corporation":false,"usgs":false,"family":"Bêty","given":"Joël","affiliations":[],"preferred":false,"id":791473,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boldenow, Megan L.","contributorId":203662,"corporation":false,"usgs":false,"family":"Boldenow","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":36677,"text":"Department of Biology and Wildlife, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":791474,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brook, Rodney W.","contributorId":92083,"corporation":false,"usgs":false,"family":"Brook","given":"Rodney","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":791475,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Glen S.","contributorId":216260,"corporation":false,"usgs":false,"family":"Brown","given":"Glen","email":"","middleInitial":"S.","affiliations":[{"id":39382,"text":"Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":791476,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"English, Willow B.","contributorId":169341,"corporation":false,"usgs":false,"family":"English","given":"Willow","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":791477,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flemming, Scott A.","contributorId":207034,"corporation":false,"usgs":false,"family":"Flemming","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":791478,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Franks, Samantha E.","contributorId":92979,"corporation":false,"usgs":true,"family":"Franks","given":"Samantha E.","affiliations":[],"preferred":false,"id":791479,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gilchrist, H. Grant","contributorId":177911,"corporation":false,"usgs":false,"family":"Gilchrist","given":"H.","email":"","middleInitial":"Grant","affiliations":[],"preferred":false,"id":791480,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Giroux, Marie-Andree","contributorId":169343,"corporation":false,"usgs":false,"family":"Giroux","given":"Marie-Andree","email":"","affiliations":[],"preferred":false,"id":791481,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Johnson, Andrew C.","contributorId":169346,"corporation":false,"usgs":false,"family":"Johnson","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":true,"id":791482,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kendall, 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proposal, which does not adequately consider the lessons learnt from the 2020 Aichi Biodiversity Targets. Whilst having a single simple overarching target is appealing, we believe a positively-framed target will garner support, rather than one that aims to, at best, limit negative impacts. The Convention on Biological Diversity’s zero draft states that future targets should be clear, consistent and SMART (Specific, Measurable, Achievable, Relevant and Timely). Extinction is problematic as a standalone target: it can take decades to demonstrate and therefore cannot be measured over a relevant time-period, and is biased towards terrestrial vertebrates. The proposal is not scalable across nations, nor is it equitable,one of the key aspirations of the zero draft. Many industrialised countries are unlikely to find the targets challenging because their most vulnerable species have largely gone extinct; tropical species-rich countries, where much biodiversity is yet to be catalogued, will find the targets demanding and unachievable in the short- or medium-term. Despite the authors’ statement to the contrary, species extinction is not necessarily relevant to other aspects of biodiversity, such as ecosystems or genetic diversity. A species may be reduced to a small fraction of its former extent without going extinct. However, its ecosystem will be altered, and its contribution to ecosystem functions and the socio-economic benefits it provided will be lost. The focus on extinction is not novel and has not been particularly successful to date, as demonstrated by the decline of emblematic species such as rhinoceroses. Alternatively, composite indicators can be used to capture biodiversity’s three fundamental components (ecosystems, species and genetic diversity). In conclusion, we cannot support a target that fails to represent the diversity in biodiversity and, in the authors’ words, could be met despite “wholesale and damaging changes to life on Earth.”","language":"English","publisher":"AAAS","doi":"10.1126/science.aba6592","usgsCitation":"O'Brien, D., Hunter, M., Breed, M., Bertola, L., Ogden, R., Palma da Silva, C., Paz-Vinas, I., Segelbacher, G., Hoban, S.M., and Jaffe, R., 2020, Proposed species extinction target fails to capture the diversity in biodiversity: Science, v. 368, no. 6496, p. 1193-1195, https://doi.org/10.1126/science.aba6592.","productDescription":"3 p.","startPage":"1193","endPage":"1195","ipdsId":"IP-120746","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":456416,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://discovery.ucl.ac.uk/id/eprint/10099553/","text":"External Repository"},{"id":377939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"368","issue":"6496","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Brien, David","contributorId":192192,"corporation":false,"usgs":false,"family":"O'Brien","given":"David","affiliations":[],"preferred":false,"id":797386,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":207584,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":797387,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breed, Martin","contributorId":239609,"corporation":false,"usgs":false,"family":"Breed","given":"Martin","affiliations":[{"id":47928,"text":"College of Science and Engineering, Flinders University","active":true,"usgs":false}],"preferred":false,"id":797388,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bertola, Laura","contributorId":239610,"corporation":false,"usgs":false,"family":"Bertola","given":"Laura","affiliations":[{"id":38178,"text":"City College of New York","active":true,"usgs":false}],"preferred":false,"id":797389,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogden, Rob","contributorId":239611,"corporation":false,"usgs":false,"family":"Ogden","given":"Rob","email":"","affiliations":[{"id":47931,"text":"Royal (Dick) School of Veterinary Studies & the Roslin Institute, University of Edinburgh","active":true,"usgs":false}],"preferred":false,"id":797390,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Palma da Silva, Clarisse","contributorId":239613,"corporation":false,"usgs":false,"family":"Palma da Silva","given":"Clarisse","email":"","affiliations":[{"id":47933,"text":"Departamento de Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas – Unicamp","active":true,"usgs":false}],"preferred":false,"id":797392,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paz-Vinas, Ivan","contributorId":239614,"corporation":false,"usgs":false,"family":"Paz-Vinas","given":"Ivan","email":"","affiliations":[{"id":47934,"text":"Laboratoire Ecologie Fonctionnelle et Environnement, Université de Toulouse","active":true,"usgs":false}],"preferred":false,"id":797393,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Segelbacher, Gernot","contributorId":206584,"corporation":false,"usgs":false,"family":"Segelbacher","given":"Gernot","email":"","affiliations":[{"id":37345,"text":"University of Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":797394,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hoban, Sean M. 0000-0002-0348-8449","orcid":"https://orcid.org/0000-0002-0348-8449","contributorId":206582,"corporation":false,"usgs":false,"family":"Hoban","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":37343,"text":"The Morton Arboretum","active":true,"usgs":false}],"preferred":false,"id":797395,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jaffe, Rodolfo","contributorId":239612,"corporation":false,"usgs":false,"family":"Jaffe","given":"Rodolfo","email":"","affiliations":[{"id":47932,"text":"Instituto Tecnológico Vale; Department of Ecology, University of São Paulo","active":true,"usgs":false}],"preferred":false,"id":797391,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70213314,"text":"70213314 - 2020 - Historical museum collections and contemporary population studies implicate roads and introduced predatory bullfrogs in the decline of western pond turtles","interactions":[],"lastModifiedDate":"2020-09-17T15:59:49.96803","indexId":"70213314","displayToPublicDate":"2020-06-12T10:46:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Historical museum collections and contemporary population studies implicate roads and introduced predatory bullfrogs in the decline of western pond turtles","docAbstract":"The western pond turtle (WPT), recently separated into two paripatrically distributed species (Emys pallida and Emys marmorata), is experiencing significant reductions in its range and population size. In addition to habitat loss, two potential causes of decline are female-biased road mortality and high juvenile mortality from non-native predatory bullfrogs (Rana catesbeiana). However, quantitative analyses of these threats have never been conducted for either species of WPT. We used a combination of historical museum samples and published and unpublished field studies shared with us through personal communications with WPT field researchers (B. Shaffer, P. Scott, R. Fisher, C. Brown, R. Dagit, L. Patterson, T. Engstrom, 2019, personal communications) to quantify the effect of roads and bullfrogs on WPT populations along the west coast of the United States. Both species of WPT shift toward increasingly male biased museum collections over the last century, a trend consistent with increasing, female-biased road mortality. Recent WPT population studies revealed that road density and proximity were significantly associated with increasingly male-biased sex ratios, further suggesting female-biased road mortality. The mean body size of museum collections of E. marmorata, but not E. pallida, has increased over the last 100 years, consistent with reduced recruitment and aging populations that could be driven by invasive predators. Contemporary WPT population sites that co-occur with bullfrogs had significantly greater average body sizes than population sites without bullfrogs, suggesting strong bullfrog predation on small WPT hatchlings and juveniles. Overall, our findings indicate that both species of WPT face demographic challenges which would have been difficult to document without the use of both historical data from natural history collections and contemporary demographic field data. Although correlational, our analyses suggest that female-biased road mortality and predation on small turtles by non-native bullfrogs are occurring, and that conservation strategies reducing both may be important for WPT recovery.
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These data also contain valuable information concerning dens, nests, roosts, and other central places that are often associated with important life history events and may exhibit unique characteristics; however, using satellite telemetry data to study central places is complicated by common nuances like locational error and animal movement. We coupled a novel modeling framework that accounts for these nuances with an Argos satellite telemetry dataset to examine the spatiotemporal behavior associated with harbor seal haul-out sites on Kodiak Island, Alaska, USA. The methodology incorporates an observation model that accommodates multiple sources of uncertainty in telemetry data and a flexible Bayesian nonparametric model to uncover latent clustering in the telemetry locations. We also contribute extensions to examine the effect of covariates on site selection and to obtain population-level inference concerning central place use. Harbor seal haul-out sites generally occurred in inlets and bays, areas that are isolated from the open water of the Gulf of Alaska. Most individuals selected haul-out sites that were protected from wave exposure. The effects of bathymetry and shoreline complexity on haul-out site selection were variable among individual seals, as were the effects of time of day, time since low tide, and day of year on temporal patterns of haul-out use. As repositories of satellite telemetry data on a wide variety of species accumulate, so do opportunities for using this information to learn about the locations of central places, as well as the temporal patterns in their use. The model-based approach we describe offers a practical and rigorous means for gaining insight concerning these sensitive locations, knowledge of which is important for the effective management and conservation of many species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3123","usgsCitation":"Brost, B.M., Hooten, M., and Small, R., 2020, Model-based clustering reveals patterns in central place use of a marine top predator: Ecosphere, e03123, 15 p., https://doi.org/10.1002/ecs2.3123.","productDescription":"e03123, 15 p.","ipdsId":"IP-079248","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":456420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3123","text":"Publisher Index Page"},{"id":394975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.171142578125,\n 56.32262930069559\n ],\n [\n -151.885986328125,\n 57.76865857271793\n ],\n [\n -152.479248046875,\n 58.019737000187305\n ],\n [\n -153.74267578125,\n 58.04300405858762\n ],\n [\n -155.115966796875,\n 57.320589769167135\n ],\n [\n -154.171142578125,\n 56.32262930069559\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Brost, Brian M.","contributorId":272252,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":831864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":831863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Small, Robert J.","contributorId":272253,"corporation":false,"usgs":false,"family":"Small","given":"Robert J.","affiliations":[{"id":56329,"text":"akfg","active":true,"usgs":false}],"preferred":false,"id":831865,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210718,"text":"70210718 - 2020 - Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA","interactions":[],"lastModifiedDate":"2020-08-06T19:30:06.543616","indexId":"70210718","displayToPublicDate":"2020-06-12T09:48:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns in hydrologic response, a new three-component metric for hydrograph analysis and implications for ecohydrology, Northwest Volcanic Aquifer Study Area, USA","docAbstract":"Oregon, California, Idaho, Nevada and Utah
Spatial patterns of hydrologic response were examined for the Northwest Volcanic Aquifer Study Area (NVASA). The utility of established hydrograph-separation methods for assessing hydrologic response in permeable volcanic terranes was assessed and a new three-component metric for hydrograph analysis was developed. The new metric, which partitions streamflow into subcomponents defined by the timescales of hydrologic response (e.g., fast-runoff, intermediate-interflow and slow-baseflow), was used to gain a fundamental understanding of the regional hydrology, investigate sub-regional differences, influencing factors, and ecohydrological implications.
The combined effects of NVASA’s physiography, climate and geology create a strongly coupled surface-groundwater system that produces copious baseflow and limited quantities of runoff and interflow. Patterns of hydrologic response are influenced by the type and rate of precipitation and permeability of the underlying geology. Under variable precipitation conditions the hydrologic response of volcanic terranes with similar permeability and subsurface-storage capacity can be significantly different. From a water management and ecohydrology perspective, understanding regional patterns of hydrologic response and sub-regional differences is fundamental. Results indicate that minimum-flow methods provide the most conservative estimate of baseflow and may be the most robust for filtering out snowmelt bias in baseflow estimates. Baseflow contributes ∼75% of the perennial streamflow across the NVASA and represents a critical component of the regional water supply that provides critical cold-water habitat.
Karst is a landscape formed from the dissolution of soluble rock or rock containing minerals that are easily dissolved from within the rock. The landscape is characterized by sinkholes, caves, losing streams, springs, and underground drainage systems, which rapidly move water through the karst. The two forms of karst in New York State include carbonate karst, which forms in carbonate rock (limestone, marble, and dolostone), and evaporite karst, which forms in rock that contains the evaporite minerals gypsum and halite.
Past and recent studies of karst across the State have shown that areas of focused recharge in karstic carbonate rock allow contaminants to enter aquifer systems with little attenuation. Focused areas of recharge need to be identified to help prevent such contamination from sources on or adjacent to the karst. The New York State Departments of Environmental Conservation and Health are collaborating with the agricultural community to make farmers and farm-planning advisors more aware of karst and how to manage daily farming activities to reduce their impact on surface water and groundwater resources, especially in karst areas. There is also a need to make regulators, planners, and the general public aware of New York’s karst resources and to properly protect and manage these resources to protect the quality of groundwater and surface water that can flow into, through, and from karst bedrock.
Using publicly available geospatial data, karst bedrock and closed depressions over or near karst rock were identified across New York. Carbonate, evaporite, and marble geologic units were selected from a statewide 1:250,000-scale bedrock geology dataset. The selected geologic units were intersected with 7.5-minute quadrangle maps to define the study area.
The U.S. Geological Survey has compiled an inventory of closed depressions from statewide digital contour data, scanned 7.5-minute topographic maps known as a digital raster graphics, and light detection and ranging (lidar) digital elevation models. Analysis of the data resulted in the identification of 5,023 closed depressions statewide. The inventory was conducted to eliminate duplication of results from analysis of the three data sources. A series of overlay analyses was conducted using the closed depressions and thematic data known to be key factors in determining the probability of a closed depression contributing to focused groundwater recharge; the thematic data include bedrock geology, soil type, soil infiltration rate, and land cover.
Though the extent of karst development is important in understanding the interaction between surface water and groundwater in karst terrains, some of the worst cases of groundwater contamination in karst can occur where only minor karst features might be present. The presence of karst—be it a short section of a solutioned fracture or an extensive cave system—requires careful consideration, forward-looking environmental planning, and consistent water-quality protection to preserve New York State’s water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205030","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Kappel, W.M., Reddy, J.E., and Root, J.C., 2020, Statewide assessment of karst aquifers in New York with an inventory of closed-depression and focused-recharge features: U.S. Geological Survey Scientific Investigations Report 2020–5030, 74 p., https://doi.org/10.3133/sir20205030.","productDescription":"Report: viii, 74 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090019","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":375401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5030/coverthb.jpg"},{"id":375404,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HGN5IJ","text":"USGS data release","linkHelpText":"Data for statewide assessment of New York’s karst aquifers with an inventory of closed-depression and focused-recharge features"},{"id":375534,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5030/sir20205030.pdf","text":"Report","size":"19.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5030"},{"id":375482,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5030/sir20205030_table1.pdf","text":"Table 1","size":"140 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Stratigraphic column of New York State bedrock indicating those units in which karst features might be present"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Hydraulic fracturing (HF) is a technique that is used for extracting petroleum resources from impermeable host rocks. In this process, fluid injected under high pressure causes fractures to propagate. This technique has been transformative for the hydrocarbon industry, unlocking otherwise stranded resources; however, environmental concerns make HF controversial. One concern is HF‐induced seismicity, since fluids driven under high pressure also have the potential to reactivate faults. Controversy has inevitably followed these HF‐induced earthquakes, with economic and human losses from ground shaking at one extreme and moratoriums on resource development at the other. Here, we review the state of knowledge of this category of induced seismicity. We first cover essential background information on HF along with an overview of published induced earthquake cases to date. Expanding on this, we synthesize the common themes and interpret the origin of these commonalities, which include recurrent earthquake swarms, proximity to well bore, rapid response to stimulation, and a paucity of reported cases. Next, we discuss the unanswered questions that naturally arise from these commonalities, leading to potential research themes: consistent recognition of cases, proposed triggering mechanisms, geologically susceptible conditions, identification of operational controls, effective mitigation efforts, and science‐informed regulatory management. HF‐induced seismicity provides a unique opportunity to better understand and manage earthquake rupture processes; overall, understanding HF‐induced earthquakes is important in order to avoid extreme reactions in either direction.
Channels change in response to natural or anthropogenic fluctuations in streamflow and/or sediment supply and measurements of channel change are critical to many river management applications. Whereas repeated field surveys are costly and time‐consuming, remote sensing can be used to detect channel change at multiple temporal and spatial scales. Repeat images have been widely used to measure long‐term channel change, but these measurements are only significant if the magnitude of change exceeds the uncertainty. Existing methods for characterizing uncertainty have two important limitations. First, while the use of a spatially variable image co‐registration error avoids the assumption that errors are spatially uniform, this type of error, as originally formulated, can only be applied to linear channel adjustments, which provide less information on channel change than polygons of erosion and deposition. Second, previous methods use a level‐of‐detection (LoD) threshold to remove non‐significant measurements, which is problematic because real changes that occurred but were smaller than the LoD threshold would be removed. In this study, we present a new method of quantifying uncertainty associated with channel change based on probabilistic, spatially varying estimates of co‐registration error and digitization uncertainty that obviates a LoD threshold. The spatially distributed probabilistic (SDP) method can be applied to both linear channel adjustments and polygons of erosion and deposition, making this the first uncertainty method generalizable to all metrics of channel change. Using a case study from the Yampa River, Colorado, we show that the SDP method reduced the magnitude of uncertainty and enabled us to detect smaller channel changes as significant. Additionally, the distributional information provided by the SDP method allowed us to report the magnitude of channel change with an appropriate level of confidence in cases where a simple LoD approach yielded an indeterminate result.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4926","usgsCitation":"Leonard, C., Legleiter, C.J., Lea, D.M., and Schmidt, J.C., 2020, Measuring channel planform change from image time series: A generalizable, spatially distributed, probabilistic method for quantifying uncertainty: Earth Surface Processes and Landforms, v. 45, no. 11, p. 2727-2744, https://doi.org/10.1002/esp.4926.","productDescription":"18 p.","startPage":"2727","endPage":"2744","ipdsId":"IP-113525","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":436932,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SEBJ3X","text":"USGS data release","linkHelpText":"Aerial photographs from the Yampa and Little Snake Rivers in northwest Colorado used to characterize channel changes occurring between 1954 and 1961"},{"id":378500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-07-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Leonard, Christina","contributorId":195596,"corporation":false,"usgs":false,"family":"Leonard","given":"Christina","email":"","affiliations":[],"preferred":true,"id":799076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":799077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lea, Devin M.","contributorId":240907,"corporation":false,"usgs":false,"family":"Lea","given":"Devin","email":"","middleInitial":"M.","affiliations":[{"id":48159,"text":"Department of Geography, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":799078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":799079,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210999,"text":"70210999 - 2020 - Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA)","interactions":[],"lastModifiedDate":"2020-08-26T19:19:54.479689","indexId":"70210999","displayToPublicDate":"2020-06-12T08:27:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA)","docAbstract":"This research examined the influences of outflow characteristics affecting riverbank stability. The 130 km stretch of the lower Osage River downstream from Bagnell Dam (Missouri, USA) provided an excellent case study for this purpose. The integrated BSTEM model with the HEC-RAS model was accurately calibrated and validated with data from the U.S. Geological Survey (USGS). Then, the outflow characteristics (peak flow duration, flow drawdown rate, and low flow duration) were investigated individually. The results of this study showed that: 1) Riverbank stability is little affected by the duration time of the peak flow, especially on the reaches far from the dam. 2) Sudden flow drawdown significantly reduces riverbank stability. However, the impact of the drawdown rate decreases with distance from the dam. 3) The duration of the low flow after peak flow influences the riverbank stability value proportional to the distance from the dam. The time of low flow before failure increases as the distance from the dam increases.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02626667.2020.1772974","usgsCitation":"Mohammed-Ali, W., Mendoza, C., and Holmes, R.R., 2020, Influence of hydropower outflow characteristics affecting riverbank stability: The lower Osage River case (Missouri, USA): Hydrological Sciences Journal, v. 65, no. 10, p. 1784-1793, https://doi.org/10.1080/02626667.2020.1772974.","productDescription":"10 p.","startPage":"1784","endPage":"1793","ipdsId":"IP-110034","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":376250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Lower Osage River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.7081298828125,\n 38.13887716726548\n ],\n [\n -92.1697998046875,\n 38.13887716726548\n ],\n [\n -92.1697998046875,\n 38.302869955150044\n ],\n [\n -92.7081298828125,\n 38.302869955150044\n ],\n [\n -92.7081298828125,\n 38.13887716726548\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Mohammed-Ali, Wesam","contributorId":225556,"corporation":false,"usgs":false,"family":"Mohammed-Ali","given":"Wesam","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":792383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Cesar","contributorId":225557,"corporation":false,"usgs":false,"family":"Mendoza","given":"Cesar","email":"","affiliations":[{"id":37501,"text":"Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":792384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmes, Robert R. Jr. 0000-0002-5060-3999 bholmes@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":1624,"corporation":false,"usgs":true,"family":"Holmes","given":"Robert","suffix":"Jr.","email":"bholmes@usgs.gov","middleInitial":"R.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":false,"id":793358,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224298,"text":"70224298 - 2020 - Assessment of fire fuel load dynamics in shrubland ecosystems in the western United States using MODIS products","interactions":[],"lastModifiedDate":"2021-09-21T13:14:01.451306","indexId":"70224298","displayToPublicDate":"2020-06-12T08:11:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of fire fuel load dynamics in shrubland ecosystems in the western United States using MODIS products","docAbstract":"Kodiak Island in southern Alaska is one of the premier examples globally for the study of forearc magmatism. This location contains two Paleocene intrusive belts that formed due to the subduction of a migrating spreading ridge and slab-window: the Kodiak batholith and the trenchward magmatic belt. These magmatic rocks are part of the Sanak-Baranof belt, which extends for greater than 2,100 km along the southern Alaskan margin and vary in age from 61 to 50 Ma west to east.
Trenchward-belt rocks, with an 40Ar/39Ar age of 60.2±0.9 Ma, intrude into the Paleocene Ghost Rocks Formation and are composed of granitoids, basaltic dikes, and small gabbroic plutons that lie along or southward of the Kalsin Bay Fault. Such intrusions were emplaced at shallow levels and have abundant evidence of incomplete intermingling of basaltic and granitic magmas. These textures indicate trenchward-belt intrusions that froze before complete assimilation, leaving behind features such as abundant locally stoped blocks, gabbroic pods within granitic intrusions, and microstructural evidence such as strongly embayed olivine and pyroxene phenocrysts in granitoid bodies.
The Kodiak batholith and satellite intrusions extend for over 110 km along the axis of Kodiak Island and vary in width from 2 to 6 km. These intrude into the Late Cretaceous Kodiak Formation. U-Pb ages on zircon from the intrusions range from 59.2±0.2 Ma in the southwest to 58.4±0.2 Ma near its northwest tip. We interpret these ages as tracking the location of a migrating triple junction and associated slab-window. The batholith is composed of granite and granodiorite, with lesser amounts of tonalite and diorite. The center of the Kodiak batholith contains high-inclusion zones with abundant residual host rock fragments that were carried up from 5–10 km below current exposure levels. These high-inclusion zones contain biotite aggregates, pure quartz clots, and large xenocrysts of sillimanite, kyanite, andalusite, and garnet. This is a higher-pressure mineral assemblage than exists in the batholith metamorphic aureole. Gravity observations and modeling are consistent with the high-inclusion zones extending downward for 5–10 km. The Kodiak batholith results from a migrating triple junction and slab-window that led to high degrees of partial melting within the Kodiak accretionary prism.
Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Invasive predatory lake trout Salvelinus namaycush were discovered in Yellowstone Lake in 1994 and caused a precipitous decrease in abundance of native Yellowstone cutthroat trout Oncorhynchus clarkii bouvieri. Suppression efforts (primarily gillnetting) initiated in 1995 did not curtail lake trout population growth or lakewide expansion. An adaptive management strategy was developed in 2010 that specified desired conditions indicative of ecosystem recovery. Population modeling was used to estimate effects of suppression efforts on the lake trout and establish effort benchmarks to achieve negative population growth (λ < 1). Partnerships enhanced funding support, and a scientific review panel provided guidance to increase suppression gillnetting effort to >46,800 100-m net nights; this effort level was achieved in 2012 and led to a reduction in lake trout biomass. Total lake trout biomass declined from 432,017 kg in 2012 to 196,675 kg in 2019, primarily because of a 79% reduction in adults. Total abundance declined from 925,208 in 2012 to 673,983 in 2019 but was highly variable because of recruitment of age-2 fish. Overall, 3.35 million lake trout were killed by suppression efforts from 1995 to 2019. Cutthroat trout abundance remained below target levels, but relative condition increased, large individuals (> 400 mm) became more abundant, and individual weights doubled, probably because of reduced density. Continued actions to suppress lake trout will facilitate further recovery of the cutthroat trout population and integrity of the Yellowstone Lake ecosystem.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes5020018","usgsCitation":"Koel, T., Arnold, J.L., Bigelow, P., Brenden, T.O., Davis, J.D., Detjens, C.R., Doepke, P., Ertel, B.D., Glassic, H., Gresswell, R.E., Guy, C., MacDonald, D.J., Ruhl, M.E., Stuth, T.J., Sweet, D.P., Syslo, J.M., Thomas, N.A., Tronstad, L., White, P.J., and Zale, A.V., 2020, Yellowstone Lake ecosystem restoration: A case study for invasive fish management: Fishes, v. 5, no. 2, 18, 63 p., https://doi.org/10.3390/fishes5020018.","productDescription":"18, 63 p.","ipdsId":"IP-118729","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":456433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes5020018","text":"Publisher Index Page"},{"id":396739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.9619140625,\n 44.01652134387754\n ],\n [\n -109.6875,\n 44.01652134387754\n ],\n [\n -109.6875,\n 44.95702412512118\n ],\n [\n -110.9619140625,\n 44.95702412512118\n ],\n [\n -110.9619140625,\n 44.01652134387754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Koel, Todd M.","contributorId":272054,"corporation":false,"usgs":false,"family":"Koel","given":"Todd M.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arnold, Jeffrey L.","contributorId":278609,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bigelow, Patricia E.","contributorId":276048,"corporation":false,"usgs":false,"family":"Bigelow","given":"Patricia E.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenden, Travis O.","contributorId":126759,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis","email":"","middleInitial":"O.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":837116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Jeffery D.","contributorId":287835,"corporation":false,"usgs":false,"family":"Davis","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":837117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Detjens, Colleen R.","contributorId":270712,"corporation":false,"usgs":false,"family":"Detjens","given":"Colleen","email":"","middleInitial":"R.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Doepke, Philip D.","contributorId":278610,"corporation":false,"usgs":false,"family":"Doepke","given":"Philip 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Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":837184,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Guy, Christopher S","contributorId":120991,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher S","affiliations":[],"preferred":false,"id":837185,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"MacDonald, Drew J.","contributorId":270660,"corporation":false,"usgs":false,"family":"MacDonald","given":"Drew","email":"","middleInitial":"J.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":837186,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ruhl, Michael E.","contributorId":287915,"corporation":false,"usgs":false,"family":"Ruhl","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837187,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stuth, Todd J.","contributorId":287916,"corporation":false,"usgs":false,"family":"Stuth","given":"Todd","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":837188,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sweet, David P.","contributorId":287917,"corporation":false,"usgs":false,"family":"Sweet","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":837189,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Syslo, John M.","contributorId":276045,"corporation":false,"usgs":false,"family":"Syslo","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":837190,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Thomas, Nathan A.","contributorId":270658,"corporation":false,"usgs":false,"family":"Thomas","given":"Nathan","email":"","middleInitial":"A.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":837191,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":837192,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"White, Patrick J.","contributorId":169530,"corporation":false,"usgs":false,"family":"White","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":837193,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837194,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70210608,"text":"70210608 - 2020 - Increased drought severity tracks warming in the United States’ largest river basin","interactions":[],"lastModifiedDate":"2020-09-18T14:53:21.021876","indexId":"70210608","displayToPublicDate":"2020-06-11T13:03:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Increased drought severity tracks warming in the United States’ largest river basin","docAbstract":"Across the Upper Missouri River Basin, the recent drought of 2000 to 2010, known as the “turn-of-the-century drought,” was likely more severe than any in the instrumental record including the Dust Bowl drought. However, until now, adequate proxy records needed to better understand this event with regard to long-term variability have been lacking. Here we examine 1,200 y of streamflow from a network of 17 new tree-ring–based reconstructions for gages across the upper Missouri basin and an independent reconstruction of warm-season regional temperature in order to place the recent drought in a long-term climate context. We find that temperature has increasingly influenced the severity of drought events by decreasing runoff efficiency in the basin since the late 20th century (1980s) onward. The occurrence of extreme heat, higher evapotranspiration, and associated low-flow conditions across the basin has increased substantially over the 20th and 21st centuries, and recent warming aligns with increasing drought severities that rival or exceed any estimated over the last 12 centuries. Future warming is anticipated to cause increasingly severe droughts by enhancing water deficits that could prove challenging for water management.","language":"English","publisher":"Proceedings of the National Academies of Science","doi":"10.1073/pnas.1916208117","usgsCitation":"Martin, J.T., Pederson, G.T., Woodhouse, C.A., Cook, E.R., McCabe, G.J., Anchukaitis, K.J., Wise, E.K., Erger, P., Dolan, L.S., McGuire, M., Gangopadhyay, S., Chase, K.J., Littell, J., Gray, S., St. George, S., Friedman, J.M., Sauchyn, D.J., St. Jacques, J., and King, J., 2020, Increased drought severity tracks warming in the United States’ largest river basin: PNAS, v. 117, no. 21, p. 11328-11336, https://doi.org/10.1073/pnas.1916208117.","productDescription":"9 p.","startPage":"11328","endPage":"11336","ipdsId":"IP-102315","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and 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Center","active":true,"usgs":true}],"preferred":true,"id":790805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":790806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":790807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Edward R.","contributorId":225235,"corporation":false,"usgs":false,"family":"Cook","given":"Edward","email":"","middleInitial":"R.","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":790808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":790809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anchukaitis, Kevin J.","contributorId":195005,"corporation":false,"usgs":false,"family":"Anchukaitis","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":790810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wise, Erika K.","contributorId":202071,"corporation":false,"usgs":false,"family":"Wise","given":"Erika","email":"","middleInitial":"K.","affiliations":[{"id":27051,"text":"University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":790811,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erger, Patrick","contributorId":218753,"corporation":false,"usgs":false,"family":"Erger","given":"Patrick","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":790896,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dolan, Larry S.","contributorId":225236,"corporation":false,"usgs":false,"family":"Dolan","given":"Larry","email":"","middleInitial":"S.","affiliations":[{"id":39458,"text":"Montana Department of Natural Resources and Conservation","active":true,"usgs":false}],"preferred":false,"id":790812,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McGuire, Marketa","contributorId":218755,"corporation":false,"usgs":false,"family":"McGuire","given":"Marketa","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":790813,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":790814,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":790815,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":790816,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Gray, Stephen T. 0000-0002-0959-3418 sgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-3418","contributorId":209851,"corporation":false,"usgs":true,"family":"Gray","given":"Stephen","email":"sgray@usgs.gov","middleInitial":"T.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":790817,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"St. George, Scott","contributorId":218756,"corporation":false,"usgs":false,"family":"St. George","given":"Scott","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":790818,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790819,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sauchyn, David J.","contributorId":218758,"corporation":false,"usgs":false,"family":"Sauchyn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":790820,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"St. Jacques, Jeannine-Marie","contributorId":195063,"corporation":false,"usgs":false,"family":"St. Jacques","given":"Jeannine-Marie","affiliations":[],"preferred":false,"id":790821,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"King, John C.","contributorId":225237,"corporation":false,"usgs":false,"family":"King","given":"John C.","affiliations":[{"id":41082,"text":"Lone Pine Research","active":true,"usgs":false}],"preferred":false,"id":790822,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70210607,"text":"ofr20201064 - 2020 - Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report","interactions":[],"lastModifiedDate":"2020-06-12T16:03:59.858553","indexId":"ofr20201064","displayToPublicDate":"2020-06-11T13:00:59","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1064","displayTitle":"Juvenile Lost River and Shortnose Sucker Year-Class Formation, Survival, and Growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 Monitoring Report","title":"Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report","docAbstract":"Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth; (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake. The U.S. Geological Survey monitoring program, which began in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Juvenile sucker year-class strength and apparent survival were low in 2018 in Upper Klamath Lake. Most juvenile sucker mortality occurs within the first year of life. The Upper Klamath Lake year-class strength indices for Lost River and shortnose suckers in 2018 were the lowest they had been since the start of monitoring in 2015. The annual catch rates of shortnose sucker remained consistently low, whereas Lost River sucker catch rates varied. The capture of only four age-1 and older suckers from Upper Klamath Lake during the 2018 sampling season indicated low annual survival of the 2017 cohort.
Annual production indices of juvenile suckers in Clear Lake are highly variable and potentially affected by seasonal connections to spawning habitat in Willow Creek. A total of seven age-0 shortnose or Klamath largescale suckers (Catostomus snyderi) were captured from Clear Lake in 2018, which was a relatively wet year, indicating that a small cohort was formed or that there was a delay in the recruitment of age-0 suckers. The 2018 sampling continued to detect recruitment of juveniles from the 2015 cohort to the lake. Given the dysconnectivity between Willow Creek and Clear Lake during the 2015 spawning season, the continued recruitment of young fish of this cohort to the lake may be attributed to reproduction by resident suckers in Willow Creek. Suckers younger than age-3 in Clear Lake could be identified as either shortnose or Klamath largescale suckers. A stream resident life history, if it were occurring, is consistent with these fish being Klamath largescale suckers. Survival of all distinguishable taxa of juvenile suckers is much higher in Clear Lake than in Upper Klamath Lake, with non-trivial numbers of suckers surviving to join spawning aggregations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201064","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Bart, R.J., Burdick, S.M., Hoy, M.S., and Ostberg, C.O., 2020, Juvenile Lost River and shortnose sucker year-class formation, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2018 monitoring report: U.S. Geological Survey Open-File Report 2020–1064, 33 p., https://doi.org/10.3133/ofr20201064.","productDescription":"vi, 33 p.","onlineOnly":"Y","ipdsId":"IP-116680","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":375530,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1064/ofr20201064.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1064"},{"id":375529,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1064/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Clear Lake Reservoir, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25747680664064,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.789744876718984\n ],\n [\n -121.04324340820312,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.94519164538106\n ],\n [\n -121.25747680664064,\n 41.789744876718984\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1075439453125,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.224449701009725\n ],\n [\n -121.76834106445311,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.593532625649935\n ],\n [\n -122.1075439453125,\n 42.224449701009725\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
We test the hypothesis that ocean seafloor pressures impart stresses that alter the initiation or termination of transient slow slip events (SSEs) on shallow submarine and near-coastal faults, using simulated seafloor pressures and a new catalog of SSEs in the Hikurangi subduction zone. We show that seafloor pressures may be represented by an average time history over the ~100-km dimensions of the study area. We account for SSE uncertainties and the multiplicity of processes that affect SSEs statistically by estimating the probabilities of rejecting the null hypothesis that SSE initiation or termination pressures are those to be expected by chance sampling of known (modeled) seafloor pressures, with low probabilities indicating some causal connection. No impact of ocean pressure changes on SSE initiation is detectable, but a correlation with their terminations is suggested. SSE slip that weakens the fault and makes it more sensitive to small stress changes may explain results.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GL087273","usgsCitation":"Gomberg, J.S., Baxter, P.J., Smith, E.G., Ariyoshi, K., and Chiswell, S., 2020, The ocean's impact on slow slip events: Geophysical Research Letters, v. 47, no. 14, e2020GL087273, 15 p., https://doi.org/10.1029/2020GL087273.","productDescription":"e2020GL087273, 15 p.","ipdsId":"IP-115199","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499853,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/ffe5bbfe0ddb4ed785934362b7777064","text":"External Repository"},{"id":480845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 177.28639581617597,\n -38.17149200548941\n ],\n [\n 177.28639581617597,\n -40.523586910552204\n ],\n [\n 180.53561304652231,\n -40.523586910552204\n ],\n [\n 180.53561304652231,\n -38.17149200548941\n ],\n [\n 177.28639581617597,\n -38.17149200548941\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"14","noUsgsAuthors":false,"publicationDate":"2020-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baxter, Peter J.","contributorId":201839,"corporation":false,"usgs":false,"family":"Baxter","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":924648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Euan G. C.","contributorId":194943,"corporation":false,"usgs":false,"family":"Smith","given":"Euan","email":"","middleInitial":"G. C.","affiliations":[],"preferred":false,"id":924649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ariyoshi, Keisuke","contributorId":349718,"corporation":false,"usgs":false,"family":"Ariyoshi","given":"Keisuke","affiliations":[{"id":40272,"text":"Japan Agency for Marine-Earth Science and Technology","active":true,"usgs":false}],"preferred":false,"id":924650,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiswell, Steve","contributorId":242932,"corporation":false,"usgs":false,"family":"Chiswell","given":"Steve","email":"","affiliations":[{"id":48587,"text":"National Institute of Water & Atmospheric Research Ltd","active":true,"usgs":false}],"preferred":false,"id":924651,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227037,"text":"70227037 - 2020 - Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate","interactions":[],"lastModifiedDate":"2021-12-28T15:37:37.953059","indexId":"70227037","displayToPublicDate":"2020-06-11T09:34:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Drought reshuffles plant phenology and reduces the foraging benefit of green-wave surfing for a migratory ungulate","docAbstract":"To increase resource gain, many herbivores pace their migration with the flush of nutritious plant green-up that progresses across the landscape (termed “green-wave surfing”). Despite concerns about the effects of climate change on migratory species and the critical role of plant phenology in mediating the ability of ungulates to surf, little is known about how drought shapes the green wave and influences the foraging benefits of migration. With a 19 year dataset on drought and plant phenology across 99 unique migratory routes of mule deer (Odocoileus hemionus) in western Wyoming, United States, we show that drought shortened the duration of spring green-up by approximately twofold (2.5 weeks) and resulted in less sequential green-up along migratory routes. We investigated the possibility that some routes were buffered from the effects of drought (i.e., routes that maintained long green-up duration irrespective of drought intensity). We found no evidence of drought-buffered routes. Instead, routes with the longest green-up in non-drought years also were the most affected by drought. Despite phenological changes along the migratory route, mule deer closely followed drought-altered green waves during migration. Migrating deer did not experience a trophic mismatch with the green wave during drought. Instead, the shorter window of green-up caused by drought reduced the opportunity to accumulate forage resources during rapid spring migrations. Our work highlights the synchronization of phenological events as an important mechanism by which climate change can negatively affect migratory species by reducing the temporal availability of key food resources. For migratory herbivores, climate change poses a new and growing threat by altering resource phenology and diminishing the foraging benefit of migration.
Heterospecific breeding associations may benefit individuals by mitigating predation risk but may also create costs if they increase competition for resources or are more easily detectable by predators. Our understanding of the interactions among hetero‐ and conspecifics is often lacking in mixed species colonies. Here, we test how the presence of hetero‐ and conspecifics influence nest and chick survival for two listed (under the U.S. Endangered Species Act) migratory species breeding on the Missouri River, USA. We monitored 2507 piping plover Charadrius melodus nests and 3245 chicks as well as 1060 least tern Sternula antillarum nests and 1374 chicks on Lake Sakakawea, the Garrison River Reach and the Gavins Point Reach for varying years between 2007 and 2016. Piping plover nest and chick survival improved with the presence and abundance of least terns, but least terns only benefited from piping plover presence for certain study areas and breeding stages. Piping plover nest survival was also improved by the presence and abundance of conspecifics on the Garrison River Reach and was negatively influenced by conspecific presence on Lake Sakakawea. Least tern chick survival improved with the presence of other least terns only on the Gavins Point Reach. Ultimately, the heterospecific breeding association between plovers and terns is mutualistic but asymmetric and is moderated by habitat, abundance of conspecifics and breeding stage. Our results highlight that spatiotemporal variation in the interactions among individuals breeding in groups precludes simple generalizations and suggests that management focused on one species may restrict benefits to that focal species if nest site requirements for heterospecifics are not also included.