{"pageNumber":"349","pageRowStart":"8700","pageSize":"25","recordCount":40797,"records":[{"id":70227770,"text":"70227770 - 2019 - A dam passage performance standard model for American shad","interactions":[],"lastModifiedDate":"2022-01-31T15:26:22.693319","indexId":"70227770","displayToPublicDate":"2018-07-30T09:20:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A dam passage performance standard model for American shad","docAbstract":"
Objectives for recovery of alosines commonly involve improving fish passage at dams during migration. However, a quantitative basis for dam passage performance standards is largely absent. We describe development of a stochastic life-history-based simulation model for American shad, Alosa sapidissima, to estimate effects of dam passage and migratory delay on abundance, spatial distribution of spawning adults, and demographic structuring in space and time. We used the Penobscot River, Maine, USA, as a case study to examine sensitivity of modeled population metrics and probability of achieving specific management goals to inputs. Spawner abundance and percentage of repeat spawners were most sensitive to survival and migration delay at dams, marine survival, and temperature cues for migratory events. Recovery objectives related to abundance and spatial distribution of spawners were achievable under multiple scenarios, but high rates of upstream and downstream passage were necessary. The simulation indicated trade-offs between upstream and downstream passage efficacy whereby increased downstream passage was required to maintain or increase population abundance in conjunction with increased upstream passage. This model provides a quantitative support tool for managers to inform ecologically based decisions about a suite of management scenarios to facilitate recovery and sustainability of diadromous fish populations.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.1139/cjfas-2018-0008","usgsCitation":"Stitch, D.S., Sheehan, T., and Zydlewski, J.D., 2019, A dam passage performance standard model for American shad: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 5, p. 762-779, https://doi.org/10.1139/cjfas-2018-0008.","productDescription":"18 p.","startPage":"762","endPage":"779","ipdsId":"IP-092496","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468115,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0008","text":"External Repository"},{"id":395139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.62060546875,\n 44.24519901522129\n ],\n [\n -67.52197265625,\n 45.321254361171476\n ],\n [\n -67.939453125,\n 45.96642454131025\n ],\n [\n -68.2470703125,\n 46.392411189814645\n ],\n [\n -69.85107421874999,\n 46.46813299215554\n ],\n [\n -70.37841796875,\n 45.9511496866914\n ],\n [\n -70.51025390625,\n 45.537136680398596\n ],\n [\n -69.76318359375,\n 45.61403741135093\n ],\n [\n -69.6533203125,\n 45.24395342262324\n ],\n [\n -69.14794921875,\n 44.49650533109348\n ],\n [\n -69.06005859375,\n 44.24519901522129\n ],\n [\n -68.62060546875,\n 44.24519901522129\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stitch, Daniel S.","contributorId":272580,"corporation":false,"usgs":false,"family":"Stitch","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":52997,"text":"State University of New York College at Oneonta","active":true,"usgs":false}],"preferred":false,"id":832167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Timothy F.","contributorId":272581,"corporation":false,"usgs":false,"family":"Sheehan","given":"Timothy F.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":832168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":832166,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70206273,"text":"70206273 - 2019 - Managing the vanishing North American hunter: A novel framework to address declines in hunters and hunter-generated conservation funds","interactions":[],"lastModifiedDate":"2019-10-29T08:21:46","indexId":"70206273","displayToPublicDate":"2018-07-30T08:20:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1910,"text":"Human Dimensions of Wildlife: An International Journal","active":true,"publicationSubtype":{"id":10}},"title":"Managing the vanishing North American hunter: A novel framework to address declines in hunters and hunter-generated conservation funds","docAbstract":"As long as the funding mechanism supporting state wildlife conservation relies heavily on hunter-generated funds, declines in hunter participation are a threat to the conservation of both game and non-game species. To address options to bolster wildlife agency profit from the sale of hunting licenses, we developed a stage-based, stochastic population model of a hunter population, and demonstrate its utility within a decision-making framework to inform state wildlife agency decisions. We evaluated hypothetical youth and adult recruitment-focused outreach programs over 10 years to increase license sale profit. Using our model as the core of a decision analysis, state agencies can set hunter population or license profit targets, and evaluate management actions designed to achieve those objectives. We anticipate that our approach will provide a valuable framework for anticipating the future of hunting and hunting-generated conservation funds, and can be extended to other user groups, including target shooters and anglers.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/10871209.2018.1499155","usgsCitation":"Price-Tack, J., McGowan, C.P., Ditchkoff, S., Morse, W., and Robinson, O.J., 2019, Managing the vanishing North American hunter: A novel framework to address declines in hunters and hunter-generated conservation funds: Human Dimensions of Wildlife: An International Journal, v. 23, no. 6, p. 515-532, https://doi.org/10.1080/10871209.2018.1499155.","productDescription":"18 p.","startPage":"515","endPage":"532","ipdsId":"IP-088223","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":490064,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Managing_the_vanishing_North_American_hunter_a_novel_framework_to_address_declines_in_hunters_and_hunter-generated_conservation_funds/6877256","text":"External Repository"},{"id":368691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Price-Tack, J.L.","contributorId":220074,"corporation":false,"usgs":false,"family":"Price-Tack","given":"J.L.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":774046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":774045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ditchkoff, S.S.","contributorId":220075,"corporation":false,"usgs":false,"family":"Ditchkoff","given":"S.S.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":774047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morse, W.C.","contributorId":220076,"corporation":false,"usgs":false,"family":"Morse","given":"W.C.","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":774048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Orin J.","contributorId":220077,"corporation":false,"usgs":false,"family":"Robinson","given":"Orin","middleInitial":"J.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":774049,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208892,"text":"70208892 - 2019 - Multi-measurement approach for establishing the base of gas hydrate occurrence in the Krishna-Godavari Basin for sites cored during Expedition NGHP-02 in the offshore of India","interactions":[],"lastModifiedDate":"2020-03-04T15:05:41","indexId":"70208892","displayToPublicDate":"2018-07-26T14:57:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Multi-measurement approach for establishing the base of gas hydrate occurrence in the Krishna-Godavari Basin for sites cored during Expedition NGHP-02 in the offshore of India","docAbstract":"

The 2015 National Gas Hydrate Program of India's second expedition, NGHP-02, acquired logging and coring datasets for constraining the base of the gas hydrate occurrence zone (deepest GH) and the theoretical base of gas hydrate stability zone (BGHS). These data are used here for two primary goals: to constrain the deepest occurrence of gas hydrate relative to predicted stability limits and the observed BSR, and to characterize the nature of the contact between gas hydrate-bearing sediment and the underlying gas hydrate-free sediment. A consensus depth for the deepest GH is derived for each NGHP-02 coring site from downhole indicators of gas hydrate occurrence obtained from well-log electrical resistivity and acoustic data, pressure core compressional wave velocity measurements, and conventional core measurements of anomalously low temperatures. To establish the theoretical BGHS, models of gas hydrate phase stability with depth are compared with downhole temperature profiles derived from: 1) assuming a constant geothermal gradient consistent with downhole temperature measurements, and 2) assuming constant heat flow using a geotherm through the downhole temperature measurements and incorporating thermal conductivity calculated from borehole logging data. Although the deepest NGHP-02 GH occurrences are controlled at several sites by a lithologic boundary, most sites have deepest GH occurrences within a single coarse-grained lithology. Cutoffs within a single coarse-grained lithology, which occur for the primary NGHP-02 Area B gas hydrate reservoir, will inhibit pore-pressure drawdowns used to extract methane from gas hydrate as an energy resource.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.07.026","usgsCitation":"Waite, W., Ruppel, C.D., Collett, T.S., Schultheiss, P., Holland, M., Shukla, K., and Kumar, P., 2019, Multi-measurement approach for establishing the base of gas hydrate occurrence in the Krishna-Godavari Basin for sites cored during Expedition NGHP-02 in the offshore of India: Marine and Petroleum Geology, v. 108, p. 296-320, https://doi.org/10.1016/j.marpetgeo.2018.07.026.","productDescription":"25 p.","startPage":"296","endPage":"320","ipdsId":"IP-097865","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1703491","text":"Publisher Index Page"},{"id":372916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Bay of Bengal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 89.12109375,\n 20.24158281954221\n ],\n [\n 86.63818359375,\n 21.657428197370653\n ],\n [\n 81.80419921875,\n 17.035777250427195\n ],\n [\n 82.3974609375,\n 15.644196600866072\n ],\n [\n 89.12109375,\n 20.24158281954221\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":195778,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn","email":"cruppel@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":783893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultheiss, P.","contributorId":79657,"corporation":false,"usgs":true,"family":"Schultheiss","given":"P.","affiliations":[],"preferred":false,"id":783894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holland, M.","contributorId":17380,"corporation":false,"usgs":true,"family":"Holland","given":"M.","email":"","affiliations":[],"preferred":false,"id":783895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shukla, K.M.","contributorId":168911,"corporation":false,"usgs":false,"family":"Shukla","given":"K.M.","email":"","affiliations":[{"id":25388,"text":"ONGC","active":true,"usgs":false}],"preferred":false,"id":783896,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kumar, P.","contributorId":45476,"corporation":false,"usgs":true,"family":"Kumar","given":"P.","affiliations":[],"preferred":false,"id":783897,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206134,"text":"70206134 - 2019 - Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference","interactions":[],"lastModifiedDate":"2019-10-23T15:52:00","indexId":"70206134","displayToPublicDate":"2018-07-25T15:46:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference","docAbstract":"

Background

Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models.

We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference.

Results

We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation.

Conclusion

The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

","language":"English","publisher":"Springer","doi":"10.1186/s40462-018-0129-1","collaboration":"Colorado State University","usgsCitation":"Hooten, M., Brian D. Gerber, Christopher P. Peck, Mindy B. Rice, Anthony D. Apa, Gammonley, J.H., and Amy J. Davis, 2019, Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference: Movement Ecology, v. 6, 14, https://doi.org/10.1186/s40462-018-0129-1.","productDescription":"14","ipdsId":"IP-086823","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468116,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-018-0129-1","text":"Publisher Index Page"},{"id":368535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","contributors":{"authors":[{"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":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":773684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brian D. Gerber","contributorId":219968,"corporation":false,"usgs":false,"family":"Brian D. Gerber","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":773685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christopher P. Peck","contributorId":219969,"corporation":false,"usgs":false,"family":"Christopher P. Peck","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":773686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mindy B. Rice","contributorId":219970,"corporation":false,"usgs":false,"family":"Mindy B. Rice","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anthony D. Apa","contributorId":219971,"corporation":false,"usgs":false,"family":"Anthony D. Apa","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gammonley, James H.","contributorId":219972,"corporation":false,"usgs":false,"family":"Gammonley","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":773689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amy J. Davis","contributorId":219973,"corporation":false,"usgs":false,"family":"Amy J. Davis","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":773690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206810,"text":"70206810 - 2019 - Lions and leopards coexist without spatial, temporal or demographic effects of interspecific competition","interactions":[],"lastModifiedDate":"2019-11-22T10:25:23","indexId":"70206810","displayToPublicDate":"2018-07-16T10:23:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Lions and leopards coexist without spatial, temporal or demographic effects of interspecific competition","docAbstract":"1. Although interspecific competition plays a principle role in shaping species behaviour and demography, little is known about the population-level outcomes of competition between large carnivores, and the mechanisms that facilitate coexistence.\n2. We conducted a multi-landscape analysis of two widely distributed, threatened large carnivore competitors to offer insight into coexistence strategies and assist with species-level conservation. \n3. We evaluated how interference competition affects occupancy, temporal activity and population density of a dominant competitor, the lion (Panthera leo), and its subordinate competitor, the leopard (Panthera pardus). We collected camera-trap data over three years in ten study sites covering 5,070 km2. We used multispecies occupancy modelling to assess spatial responses in varying environmental and prey conditions and competitor presence, and examined temporal overlap and the relationship between lion and leopard densities across sites and years. \n4. Results showed that both lion and leopard occupancy was independent of – rather than conditional on – their competitor’s presence across all environmental covariates. Marginal occupancy probability for leopard was higher in areas with more bushy, ‘hideable’ habitat, human (tourist) activity and topographic ruggedness, whereas lion occupancy decreased with increasing hideable habitat and increased with higher abundance of very large prey. Temporal overlap was high between carnivores and there was no significant relationship between species densities. \n4. Lions pose a threat to the survival of individual leopards, but they exerted no tractable influence on leopard spatial or temporal dynamics. Furthermore, lions did not appear to suppress leopard populations, suggesting that intraguild competitors can coexist in the same areas without population decline. Aligned conservation strategies that promote functioning ecosystems, rather than target individual species, are therefore suggested to achieve cost- and space-effective conservation.","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12883","usgsCitation":"Fuller, A.K., Miller, J., Pittman, R., Mann, G., and Balme, G., 2019, Lions and leopards coexist without spatial, temporal or demographic effects of interspecific competition: Journal of Animal Ecology, v. 87, no. 6, p. 1709-1726, https://doi.org/10.1111/1365-2656.12883.","productDescription":"18 p.","startPage":"1709","endPage":"1726","ipdsId":"IP-089044","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468118,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12883","text":"Publisher Index Page"},{"id":369459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":775837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Jennifer","contributorId":197539,"corporation":false,"usgs":false,"family":"Miller","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":775838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pittman, Ross","contributorId":220824,"corporation":false,"usgs":false,"family":"Pittman","given":"Ross","email":"","affiliations":[{"id":40281,"text":"Institute for Communities and Wildlife in Africa","active":true,"usgs":false}],"preferred":false,"id":775839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mann, Gareth","contributorId":220825,"corporation":false,"usgs":false,"family":"Mann","given":"Gareth","email":"","affiliations":[{"id":40281,"text":"Institute for Communities and Wildlife in Africa","active":true,"usgs":false}],"preferred":false,"id":775840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Balme, Guy","contributorId":220826,"corporation":false,"usgs":false,"family":"Balme","given":"Guy","email":"","affiliations":[{"id":40281,"text":"Institute for Communities and Wildlife in Africa","active":true,"usgs":false}],"preferred":false,"id":775841,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204422,"text":"70204422 - 2019 - Importance of riparian forest corridors for the ocelot in agricultural landscapes","interactions":[],"lastModifiedDate":"2019-07-23T08:51:11","indexId":"70204422","displayToPublicDate":"2018-07-09T08:50:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Importance of riparian forest corridors for the ocelot in agricultural landscapes","docAbstract":"Worldwide, private lands have attracted increased attention from conservationists, not only because most of the globe is privately owned, but also because private lands can be an asset to the protected area conservation strategy. In Brazil, the riverine Areas of Permanent Protection (APPs) is a key instrument of the Forest Code to protect native vegetation on private lands. Although APPs were conceived to function as potential wildlife corridors, this putative role has been rarely assessed. Further, recent debatable changes in the Forest Code have decreased the extent of APPs. Given this lack of information and the declining area being protected along with the growing demand for agricultural and biofuel production, which stimulate additional deforestation, it is timely to assess the role of APPs in wildlife conservation. We did this analyzing how ocelot (Leopardus pardalis) occurrence is influenced by covariates in 3 cerrado landscapes dominated by sugarcane and managed forests of eucalyptus and pine trees. We collected detection/non-detection data by camera trapping during 2 dry seasons (2013 and 2014) at 208 stations (6606 camera-days). We estimated ocelot detection and mean relative abundance using a single-species/single-season occupancy model that accounts for heterogeneous detection probability induced by variation in abundance. Modeling results showed that percentage of native forest was the most important covariate to explain ocelot mean relative abundance. This parameter was also affected positively by APPs, with ocelots being more abundant inside than outside APPs and, unexpectedly, by sugarcane. Given study design, however, the positive effect of this crop likely reflects the contact zone between sugarcane and native forest. Our findings show that landscape composition affects ocelot abundance and highlight the importance of APPs and Legal Reserves in agricultural landscapes. We conclude that, in such landscapes, compliance to the Forest Code by private land owners is key to supporting ocelot occurrence.","language":"English","publisher":"Oxford Academic ","doi":"10.1093/jmammal/gyy075","usgsCitation":"Paolino, R., Royle, A., Versiani, N., Rodrigues, T.F., Pasqualotto, N., Krepschi, V., and Adriano Chiarello, 2019, Importance of riparian forest corridors for the ocelot in agricultural landscapes: Journal of Mammalogy, v. 99, no. 4, p. 874-884, https://doi.org/10.1093/jmammal/gyy075.","productDescription":"11 p.","startPage":"874","endPage":"884","ipdsId":"IP-092001","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyy075","text":"Publisher Index Page"},{"id":365833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365832,"type":{"id":15,"text":"Index Page"},"url":"https://academic.oup.com/jmammal/article-abstract/99/4/874/5050937"}],"volume":"99","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Paolino, Roberta","contributorId":217469,"corporation":false,"usgs":false,"family":"Paolino","given":"Roberta","email":"","affiliations":[{"id":38961,"text":"Universidade de São Paulo","active":true,"usgs":false}],"preferred":false,"id":766836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":766835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Versiani, Natalia","contributorId":217470,"corporation":false,"usgs":false,"family":"Versiani","given":"Natalia","email":"","affiliations":[{"id":38961,"text":"Universidade de São Paulo","active":true,"usgs":false}],"preferred":false,"id":766837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodrigues, Thiago F.","contributorId":217471,"corporation":false,"usgs":false,"family":"Rodrigues","given":"Thiago","email":"","middleInitial":"F.","affiliations":[{"id":39648,"text":"Universidade Estadual Paulista (UNESP)","active":true,"usgs":false}],"preferred":false,"id":766838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pasqualotto, Nielson","contributorId":217472,"corporation":false,"usgs":false,"family":"Pasqualotto","given":"Nielson","email":"","affiliations":[{"id":38961,"text":"Universidade de São Paulo","active":true,"usgs":false}],"preferred":false,"id":766839,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krepschi, Victor","contributorId":217473,"corporation":false,"usgs":false,"family":"Krepschi","given":"Victor","email":"","affiliations":[{"id":38961,"text":"Universidade de São Paulo","active":true,"usgs":false}],"preferred":false,"id":766840,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Adriano Chiarello","contributorId":217474,"corporation":false,"usgs":false,"family":"Adriano Chiarello","affiliations":[{"id":38961,"text":"Universidade de São Paulo","active":true,"usgs":false}],"preferred":false,"id":766841,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197990,"text":"70197990 - 2019 - Modeling framework to estimate spawning and hatching locations of pelagically-spawned eggs","interactions":[],"lastModifiedDate":"2019-03-26T16:24:40","indexId":"70197990","displayToPublicDate":"2018-07-05T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Modeling framework to estimate spawning and hatching locations of pelagically-spawned eggs","docAbstract":"

Identifying spawning and hatching locations is vital to controlling invasive fish and conserving imperiled fish, which can be difficult for pelagically-spawning species with semi-buoyant eggs. In freshwater systems, this reproductive strategy is common among cyprinid species, such as Chinese carp species currently threatening the Great Lakes. Following the confirmation that one of these species, Grass Carp (Ctenopharyngodon idella), was spawning in a Great Lakes tributary, we developed a modeling framework to combine field data with hydraulic models to calculate the most probable spawning and hatching locations for collected eggs. Our results indicate that the estimated spawning location encompassed habitat consistent with spawning sites in Grass Carp’s native range. Additionally, all eggs were identified to have hatched in the river, increasing the likelihood of successful recruitment. This modeling framework can be used to estimate spawning and hatching locations for Chinese carp species, as well as all pelagic, riverine spawners. Spawning and hatching locations provide key information to researchers about the reproductive requirements of species and to agencies about how best to manage populations for control or restoration.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0047","usgsCitation":"Embke, H.S., Kocovsky, P., Garcia, T., Mayer, C.M., and Qian, S.S., 2019, Modeling framework to estimate spawning and hatching locations of pelagically-spawned eggs: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 4, p. 597-607, https://doi.org/10.1139/cjfas-2018-0047.","productDescription":"11 p.","startPage":"597","endPage":"607","ipdsId":"IP-087557","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":501079,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/92211","text":"External Repository"},{"id":355500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e544e4b060350a15d077","contributors":{"authors":[{"text":"Embke, Holly S. 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":173026,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"S.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":false,"id":739500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":739499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":739501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Christine M.","contributorId":50814,"corporation":false,"usgs":true,"family":"Mayer","given":"Christine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":739502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qian, Song S.","contributorId":198934,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":739503,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203663,"text":"70203663 - 2019 - Predicting species-habitat relationships: Does body size matter?","interactions":[],"lastModifiedDate":"2019-05-30T15:35:23","indexId":"70203663","displayToPublicDate":"2018-07-01T15:34:22","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting species-habitat relationships: Does body size matter?","docAbstract":"Context.\nAllometric scaling laws are foundational to structuring processes from cellular to ecosystem levels. The idea that allometric relationships underlie species characteristic selection scales, the spatial scales at which species respond to landscape features, has recently been investigated, however, supporting empirical evidence is scarce.\n\nObjectives.\nLack of pattern can be explained by inaccurate estimation, low power, confounding factors, or absence of a relationship. In this paper, we evaluate the relationship between body size and species characteristic selection scales after overcoming limitations of previous study designs.\n\nMethods.\nWe conducted 1328 avian point counts across the state of Nebraska using the robust sampling design to account for imperfect detection. We used Bayesian latent indicator scale selection with N-mixture models to estimate species’ characteristic selection scales of six habitat features in 86 species. We propagated the uncertainty associated with assigning characteristic scales to a model of the relationship between body size and characteristic spatial scales.\n\nResults.\nSpecies characteristic scales varied across habitat predictors, and varied in the uncertainty associated with selecting single characteristic scales. After propagating uncertainty our results do not support a relationship between species’ body size and the spatial scales at which they respond to landscape features.\n\nConclusions.\nAs species abundance integrates birth, death, immigration, and emigration processes, each of which are influenced by ecological processes manifesting at various scales, we question whether a general allometric relationship should be expected. Our results suggest that selection may act on responses to specific environmental features, rather than response to spatial scale per se.","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0648-6","usgsCitation":"Stuber, E., Gruber, L., and Fontaine, J.J., 2019, Predicting species-habitat relationships: Does body size matter?: Landscape Ecology, v. 33, no. 7, p. 1049-1060, https://doi.org/10.1007/s10980-018-0648-6.","productDescription":"12 p.","startPage":"1049","endPage":"1060","ipdsId":"IP-071453","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":364262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"7","publishingServiceCenter":{"id":3,"text":"Helena PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, E.F.","contributorId":205137,"corporation":false,"usgs":false,"family":"Stuber","given":"E.F.","email":"","affiliations":[{"id":37031,"text":"Nebraska Cooperative Fish & Wildlife Research Unit, University of Nebraska-Lincoln, Lincoln, Nebraska","active":true,"usgs":false}],"preferred":false,"id":763458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gruber, L.","contributorId":215936,"corporation":false,"usgs":false,"family":"Gruber","given":"L.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":763459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":763457,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204574,"text":"70204574 - 2019 - Effects of landscape characteristics on annual survival of Lesser Prairie-Chickens","interactions":[],"lastModifiedDate":"2019-08-08T11:24:13","indexId":"70204574","displayToPublicDate":"2018-07-01T13:00:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Effects of landscape characteristics on annual survival of Lesser Prairie-Chickens","docAbstract":"

Agriculture and development have caused landscape change throughout the southwestern Great Plains in the range of the lesser prairie-chicken (Tympanuchus pallidicinctus). Landscape alteration within the lesser prairie-chicken range may contribute to range contraction and population losses through decreases in survival rates. Our objectives were to determine if: (1) landscape configuration (i.e., the spatial arrangement of habitat) or composition (i.e., the amount of habitat), at the study-site scale, affected annual survival of females, (2) relationships exist between landscape context (i.e., landscape configuration and composition) and weekly survival to assess effects of landscape composition and configuration on lesser prairie-chicken populations, and (3) anthropogenic features influenced daily mortality risk. We captured 170 female lesser prairie-chickens and used very-high-frequency and GPS (Global Positioning System) transmitters to track their movement and survival for 2 y. We used known-fate survival models to test if landscape configuration or composition within three sites in Kansas were related to differences in female survival among sites. In addition we tested for relationships between weekly survival and landscape configuration or composition within home ranges. Finally, we used Andersen-Gill models to test the influence of distance to anthropogenic features on daily mortality risk. Differences in survival were evident between sites with differing landscape compositions as annual survival in Northwestern Kansas (Ŝ= 0.27) was half that of Clark County, Kansas (Ŝ= 0.56), which corresponded with 41.9% more grassland on the landscape in Clark County; landscape configuration did not measurably differ among sites. Survival was greater for prairie-chickens with home-ranges that had greater patch richness and in areas with 30% crop and 57% grassland. Female lesser prairie-chickens also experienced greater mortality risk closer to fences at patch edges. Further conversion of grassland landscapes occupied by lesser prairie-chickens should be avoided to reduce habitat loss and fragmentation thresholds that could affect survival. We suggest continued encouragement of Conservation Reserve Program enrollment in western areas of the lesser prairie-chicken range to maintain or increase the amount of grassland to increase annual survival.

","language":"English","publisher":"BioOne","doi":"10.1674/0003-0031-180.1.66","usgsCitation":"Robinson, S.G., Haukos, D.A., Plumb, R.T., Kraft, J.D., Sullins, D.S., Lautenbach, J.M., Lautenbach, J.D., Sandercock, B.K., Christian A. Hagen, Bartuszevige, A.M., and Rice, M.B., 2019, Effects of landscape characteristics on annual survival of Lesser Prairie-Chickens: American Midland Naturalist, v. 180, p. 66-86, https://doi.org/10.1674/0003-0031-180.1.66.","productDescription":"21 p.","startPage":"66","endPage":"86","ipdsId":"IP-085818","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":352,"text":"Kansas Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":460603,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11250/2559517","text":"External Repository"},{"id":366273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.041015625,\n 37.02886944696474\n ],\n [\n -97.93212890625,\n 37.02886944696474\n ],\n [\n -97.93212890625,\n 39.35978526869001\n ],\n [\n -102.041015625,\n 39.35978526869001\n ],\n [\n -102.041015625,\n 37.02886944696474\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"180","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Samantha G.","contributorId":172786,"corporation":false,"usgs":false,"family":"Robinson","given":"Samantha","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":767708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":767613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumb, Reid T.","contributorId":172787,"corporation":false,"usgs":false,"family":"Plumb","given":"Reid","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":767709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraft, John D.","contributorId":172789,"corporation":false,"usgs":false,"family":"Kraft","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":767710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullins, Daniel S.","contributorId":166689,"corporation":false,"usgs":false,"family":"Sullins","given":"Daniel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":767711,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lautenbach, Joseph M.","contributorId":172788,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":767712,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lautenbach, Jonathan D.","contributorId":172790,"corporation":false,"usgs":false,"family":"Lautenbach","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":767713,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sandercock, Brett K.","contributorId":95816,"corporation":false,"usgs":true,"family":"Sandercock","given":"Brett","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":767714,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Christian A. Hagen","contributorId":217299,"corporation":false,"usgs":false,"family":"Christian A. Hagen","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":767715,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bartuszevige, Anne M.","contributorId":172827,"corporation":false,"usgs":false,"family":"Bartuszevige","given":"Anne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":767716,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rice, Mindy B.","contributorId":214399,"corporation":false,"usgs":false,"family":"Rice","given":"Mindy","email":"","middleInitial":"B.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767717,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70223490,"text":"70223490 - 2019 - Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats","interactions":[],"lastModifiedDate":"2021-08-30T13:11:53.375779","indexId":"70223490","displayToPublicDate":"2018-07-01T08:09:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats","docAbstract":"

With the declines in abundance and changing distribution of white-nose syndrome–affected bat species, increased reliance on acoustic monitoring is now the new “normal.” As such, the ability to accurately identify individual bat species with acoustic identification programs has become increasingly important. We assessed rates of disagreement between the three U.S. Fish and Wildlife Service–approved acoustic identification software programs (Kaleidoscope Pro 4.2.0, Echoclass 3.1, and Bat Call Identification 2.7d) and manual visual identification using acoustic data collected during summers from 2003 to 2017 at Fort Drum, New York. We assessed the percentage of agreement between programs through pairwise comparisons on a total nightly count level, individual file level (e.g., individual echolocation pass call file), and grouped maximum likelihood estimate level (e.g., probability values that a species is misclassified as present when in fact it is absent) using preplanned contrasts, Akaike Information Criterion, and annual confusion matrices. Interprogram agreement on an individual file level was low, as measured by Cohen's Kappa (0.2–0.6). However, site-night level pairwise comparative analysis indicated that program agreement was higher (40–90%) using single season occupancy metrics. In comparing analytical outcomes of our different datasets (i.e., how comparable programs and visual identification are regarding the relationship between environmental conditions and bat activity), we determined high levels of congruency in the relative rankings of the model as well as the relative level of support for each individual model. This indicated that among individual software packages, when analyzing bat calls, there was consistent ecological inference beyond the file-by-file level at the scales used by managers. Depending on objectives, we believe our results can help users choose automated software and maximum likelihood estimate thresholds more appropriate for their needs and allow for better cross-comparison of studies using different automated acoustic software.

","language":"English","publisher":"Allen Press","doi":"10.3996/102018-JFWM-090","usgsCitation":"Ford, W., Nocera, T., Silvis, A., and Dobony, C., 2019, Let’s agree to disagree: Comparing auto-acoustic identification programs for northeastern bats: Journal of Fish and Wildlife Management, v. 10, no. 2, p. 346-361, https://doi.org/10.3996/102018-JFWM-090.","productDescription":"16 p.","startPage":"346","endPage":"361","ipdsId":"IP-101166","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468122,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/102018-jfwm-090","text":"Publisher Index Page"},{"id":388654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":822153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nocera, Tomás","contributorId":264895,"corporation":false,"usgs":false,"family":"Nocera","given":"Tomás","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":822154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":264896,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","affiliations":[{"id":54472,"text":"RES Inc.","active":true,"usgs":false}],"preferred":false,"id":822155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dobony, Christopher A.","contributorId":264897,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher A.","affiliations":[{"id":54576,"text":"DoD","active":true,"usgs":false}],"preferred":false,"id":822156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203772,"text":"70203772 - 2019 - The Santa Cruz Basin submarine landslide complex, southern California: Repeated failure of uplifted basin sediment","interactions":[],"lastModifiedDate":"2019-08-16T09:27:31","indexId":"70203772","displayToPublicDate":"2018-06-30T11:04:30","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The Santa Cruz Basin submarine landslide complex, southern California: Repeated failure of uplifted basin sediment","docAbstract":"

The Santa Cruz Basin (SCB) is one of several fault-bounded basins within the California Continental Borderland that has drawn interest over the years for its role in the tectonic evolution of the region, but also because it contains a record of a variety of modes of sedimentary mass transport (i.e., open slope vs. canyon-confined systems). Here, we present a suite of new high-resolution marine geophysical data that demonstrate the extent and significance of the SCB submarine landslide complex in terms of late Miocene to present basin evolution and regional geohazard assessment. The new data reveal that submarine landslides cover an area of ~160 km2 along the eastern flank of the Santa Rosa–Cortes Ridge and have emplaced a minimum of 9 to 16 km3 of mass transport deposits along the floor of the SCB during the Quaternary. The failures occur along an onlapping wedge of Pliocene sediment that was uplifted and tilted during the later stages of basin development. The uplifted and steepened Pliocene strata were preconditioned for failure so that parts of the section failed episodically throughout the Quaternary—most likely during large earthquakes. Once failed, the material initially translated as a block glide along a defined failure surface. As transport continued several kilometers across a steep section of the lower slope, the material separated into distinctive proximal and distal components. The failed masses mobilized into debris flows that show evidence for dynamic separation into less and more mobile components that disturbed and eroded underlying stratigraphy in areas most proximal to the source area. The most highly mobilized components and those with the lowest viscosity and yield strength produced flows that blanket the underlying stratigraphy along the distal reaches of deposition. The estimated volumes of individual landslides within the complex (0.1–2.6 km3), the runout distance measured from the headwalls (>20 km), and evidence for relatively high velocity during initial mobilization all suggest that slides in the SCB may have been tsunamigenic. Because many slopes in the California Continental Borderland are either sediment starved or have experienced sediment bypass during the Quaternary, we propose that uplift and rotation of Pliocene deposits are important preconditioning factors for slope failure that need to be systematically evaluated as potential tsunami initiators.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From the Mountains to the Abyss--The California Borderland as an archive of southern California geologic evolution","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.2110/sepmsp.110.05","usgsCitation":"Brothers, D., Maier, K.L., Kluesner, J., Conrad, J.E., and Chaytor, J., 2019, The Santa Cruz Basin submarine landslide complex, southern California: Repeated failure of uplifted basin sediment, chap. of From the Mountains to the Abyss--The California Borderland as an archive of southern California geologic evolution, 18 p., https://doi.org/10.2110/sepmsp.110.05.","productDescription":"18 p.","ipdsId":"IP-075723","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":364590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"California Continental Borderland, Santa Cruz Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.12451171875,\n 33.30298618122413\n ],\n [\n -119.14672851562499,\n 33.30298618122413\n ],\n [\n -119.14672851562499,\n 33.925129700072\n ],\n [\n -120.12451171875,\n 33.925129700072\n ],\n [\n -120.12451171875,\n 33.30298618122413\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brothers, Daniel S. 0000-0001-7702-157X","orcid":"https://orcid.org/0000-0001-7702-157X","contributorId":210199,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":764059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maier, Katherine L. 0000-0003-2908-3340 kcoble@usgs.gov","orcid":"https://orcid.org/0000-0003-2908-3340","contributorId":4926,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine","email":"kcoble@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":764060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":764061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":764062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":764063,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198795,"text":"70198795 - 2019 - State-space models to infer movements and behavior of fish detected in a spatial array of acoustic receivers ","interactions":[],"lastModifiedDate":"2019-03-26T16:22:56","indexId":"70198795","displayToPublicDate":"2018-06-25T13:50:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"State-space models to infer movements and behavior of fish detected in a spatial array of acoustic receivers ","docAbstract":"

We developed state-space models for inferring movements and behaviors of fish implanted with acoustic transmitters and detected within a spatial array of stationary acoustic receivers. In these models fish movements and behavior switching are specified using a hidden Markov model of the changes in an individual's latent activity center. The observed number of detections at each acoustic receiver is modeled as a function of the distance between the receiver and a fish's activity center. To illustrate these models, we analyzed the detections of individual Gulf sturgeon that moved within a spatial array of acoustic receivers placed in the Suwannee River, Florida. Our models of these detections provided estimates of the locations of individual sturgeon and the periods when individuals switched between spawning and resting behaviors. We anticipate that these models will be used to analyze acoustic surveys of other species and to help design new surveys.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0067 ","usgsCitation":"Price, M.E., and Dorazio, R., 2019, State-space models to infer movements and behavior of fish detected in a spatial array of acoustic receivers : Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 4, p. 543-550, https://doi.org/10.1139/cjfas-2018-0067 .","productDescription":"8 p.","startPage":"543","endPage":"550","ipdsId":"IP-099255 ","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":501072,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/91211","text":"External Repository"},{"id":356592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2a3e4b0702d0e842fa6","contributors":{"authors":[{"text":"Price, Melissa E. 0000-0002-4276-0855 mprice@usgs.gov","orcid":"https://orcid.org/0000-0002-4276-0855","contributorId":5875,"corporation":false,"usgs":true,"family":"Price","given":"Melissa","email":"mprice@usgs.gov","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":742991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorazio, Robert 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":149286,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":742992,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203036,"text":"70203036 - 2019 - Mapping protected groundwater adjacent to oil and gas fields, San Joaquin Valley, California","interactions":[],"lastModifiedDate":"2019-04-17T09:24:31","indexId":"70203036","displayToPublicDate":"2018-06-14T09:23:28","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Mapping protected groundwater adjacent to oil and gas fields, San Joaquin Valley, California","docAbstract":"

Airborne electromagnetic (AEM) surveys are a major component of a regional study of groundwater quality adjacent to oil and gas fields in the San Joaquin Valley of California, USA. AEM resistivity models are being used to delineate groundwater salinity in an effort to locate groundwater adjacent to oil and gas fields that could have future beneficial use. AEM models are also being used to improve our understanding of the hydrogeologic controls that may influence fluid transport between oil and gas operations and protected groundwater.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"7th annual conference on Airborne electromagnetics","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"7th annual conference on Airborne electromagnetics","conferenceDate":"June 17-20, 2018","conferenceLocation":"Kolding, Denmark","language":"English","publisher":"AEM","usgsCitation":"Ball, L.B., Gillespie, J., Minsley, B., Davis, T., and Landon, M.K., 2019, Mapping protected groundwater adjacent to oil and gas fields, San Joaquin Valley, California, in 7th annual conference on Airborne electromagnetics, Kolding, Denmark, June 17-20, 2018.","ipdsId":"IP-095178","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":362996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362995,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.conferencemanager.dk/AEM2018/abstracts-presentations-posters.html"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 35.75\n ],\n [\n -119.5,\n 35.75\n ],\n [\n -119.5,\n 37.5\n ],\n [\n -121.5,\n 37.5\n ],\n [\n -121.5,\n 35.75]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":760891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":760892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, Burke 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":211849,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":760893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Tracy 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":176921,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197422,"text":"70197422 - 2019 - Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state","interactions":[],"lastModifiedDate":"2019-02-21T14:58:45","indexId":"70197422","displayToPublicDate":"2018-06-04T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state","title":"Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state","docAbstract":"

Arid and semiarid ecosystems make up approximately 41% of Earth’s terrestrial surface and are suggested to regulate the trend and interannual variability of the global terrestrial carbon (C) sink. Biological soil crusts (biocrusts) are common dryland soil surface communities of bryophytes, lichens, and/or cyanobacteria that bind the soil surface together and that may play an important role in regulating the climatic sensitivity of the dryland C cycle. Major uncertainties exist in our understanding of the interacting effects of changing temperature and moisture on CO2 uptake (photosynthesis) and loss (respiration) from biocrust and sub-crust soil, particularly as related to biocrust successional state. Here, we used a mesocosm approach to assess how biocrust successional states related to climate treatments. We subjected bare soil (Bare), early successional lightly pigmented cyanobacterial biocrust (Early), and late successional darkly pigmented moss-lichen biocrust (Late) to either ambient or + 5°C above ambient soil temperature for 84 days. Under ambient temperatures, Late biocrust mesocosms showed frequent net uptake of CO2, whereas Bare soil, Early biocrust, and warmed Late biocrust mesocosms mostly lost CO2 to the atmosphere. The inhibiting effect of warming on CO2 exchange was a result of accelerated drying of biocrust and soil. We used these data to parameterize, via Bayesian methods, a model of ecosystem CO2 fluxes, and evaluated the model with data from an autochamber CO2 system at our field site on the Colorado Plateau in SE Utah. In the context of the field experiment, the data underscore the negative effect of warming on fluxes both biocrust CO2 uptake and loss—which, because biocrusts are a dominant land cover type in this ecosystem, may extend to ecosystem-scale C cycling.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-018-0250-4","usgsCitation":"Tucker, C., Ferrenberg, S., and Reed, S.C., 2019, Climatic sensitivity of dryland soil CO2 fluxes differs dramatically with biological soil crust successional state: Ecosystems, v. 22, no. 1, p. 15-32, https://doi.org/10.1007/s10021-018-0250-4.","productDescription":"18 p.","startPage":"15","endPage":"32","ipdsId":"IP-083628","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":354689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-30","publicationStatus":"PW","scienceBaseUri":"5b46e575e4b060350a15d191","contributors":{"authors":[{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":737103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":737104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":737105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203182,"text":"70203182 - 2019 - In situ distributions of magnetic susceptibility in some igneous rocks","interactions":[],"lastModifiedDate":"2019-06-25T14:31:08","indexId":"70203182","displayToPublicDate":"2018-05-31T14:28:41","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"In situ distributions of magnetic susceptibility in some igneous rocks","docAbstract":"Measurements of in-situ magnetic susceptibility were compiled from mainly Precambrian crystalline basement rocks beneath the Colorado Plateau and ranges in Arizona, Colorado, and New Mexico. The susceptibility meter used samples about 33 cubic centimeters of rock and measures variations in the modal distribution of magnetic minerals that form a minor component volumetrically in these coarsely crystalline granitic to granodioritic rocks. Recent measurements include 50-150 measurements on each outcrop and show that the distribution of magnetic susceptibilities is highly variable, multimodal and strongly non-Gaussian so that a mean value has little significance. Rock bodies with the most multimodal distributions generally have complex tectonic histories including metamorphism and multiple tectonic events. Variations between outcrops within the same rock body are large; however, where distributions overlap, measurements appear to fill gaps within modal peaks. Histograms of measurements are a better representation of the magnetic susceptibility distribution for a given rock body than mean and standard deviation. The best effective magnetic susceptibility estimate for an outcrop can be obtained by computing themagnetic force of the measurements 3-5 m above the outcrop and finding the constant susceptibility that gives an equal integral of the force. The multifractal distribution of the minor minerals in the rocks explains the observed multimodal distributions of magnetic susceptibility at millimeter to meter scales.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Horizons in Earth Science Research. Volume 18","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Nova Science Publishers, Inc.","usgsCitation":"Gettings, M.E., 2019, In situ distributions of magnetic susceptibility in some igneous rocks, chap. 6 of Horizons in Earth Science Research. Volume 18, p. 183-208.","productDescription":"16 p.","startPage":"183","endPage":"208","ipdsId":"IP-093170","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":365029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363214,"type":{"id":15,"text":"Index Page"},"url":"https://novapublishers.com/shop/horizons-in-earth-science-research-volume-18/"}],"country":"United States","state":"Arizona, Colorado, New Mexico","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gettings, Mark E. 0000-0002-2910-2321 mgetting@usgs.gov","orcid":"https://orcid.org/0000-0002-2910-2321","contributorId":602,"corporation":false,"usgs":true,"family":"Gettings","given":"Mark","email":"mgetting@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":761533,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70197371,"text":"70197371 - 2019 - Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change","interactions":[],"lastModifiedDate":"2019-03-04T11:28:08","indexId":"70197371","displayToPublicDate":"2018-05-31T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change","docAbstract":"

Land cover is an important determinant of aquatic habitat and is projected to shift with climate changes, yet climate-driven land cover changes are rarely factored into climate assessments. To quantify impacts and uncertainty of coupled climate and land cover change on warm-water fish species’ distributions, we used an ensemble model approach to project distributions of 14 species. For each species, current range projections were compared to 27 scenario-based projections and aggregated to visualize uncertainty. Multiple regression and model selection techniques were used to identify drivers of range change. Novel, or no-analogue, climates were assessed to evaluate transferability of models. Changes in total probability of occurrence ranged widely across species, from a 63% increase to a 65% decrease. Distributional gains and losses were largely driven by temperature and flow variables and underscore the importance of habitat heterogeneity and connectivity to facilitate adaptation to changing conditions. Finally, novel climate conditions were driven by mean annual maximum temperature, which stresses the importance of understanding the role of temperature on fish physiology and the role of temperature-mitigating management practices.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0002","usgsCitation":"Bouska, K.L., Whitledge, G.W., Lant, C., and Schoof, J., 2019, Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 3, p. 415-425, https://doi.org/10.1139/cjfas-2018-0002.","productDescription":"11 p.","startPage":"415","endPage":"425","ipdsId":"IP-093466","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468124,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2018-0002","text":"External Repository"},{"id":354616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"76","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d72e4b092d9651e1af6","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736888,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whitledge, Gregory W.","contributorId":73110,"corporation":false,"usgs":true,"family":"Whitledge","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":736889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lant, Christopher","contributorId":205317,"corporation":false,"usgs":false,"family":"Lant","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":736890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoof, Justin","contributorId":205318,"corporation":false,"usgs":false,"family":"Schoof","given":"Justin","email":"","affiliations":[],"preferred":false,"id":736891,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197333,"text":"70197333 - 2019 - Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia","interactions":[],"lastModifiedDate":"2019-12-21T09:06:03","indexId":"70197333","displayToPublicDate":"2018-05-30T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia","docAbstract":"Sinabung Volcano (Sumatra, Indonesia) awoke from over 1200 years of dormancy with multiple phreatic explosions in 2010. After a period of quiescence, Sinabung activity resumed in 2013, producing frequent explosions, lava dome extrusion, and pyroclastic flows from dome collapses, becoming one of the world's most active volcanoes and displacing over 20,000 citizens. This study presents a compilation of the geochemical datasets collected by the Indonesian Center for Volcanology and Geological Hazard Mitigation (CVGHM) from 2010 - current (2016), which provides insights into the evolution of the eruption. Based on observations of SO2 emissions, ash componentry, leachate chemistry, and bulk ash geochemistry, the eruption can be split into five distinct phases. The initial stage of phreatic summit explosions occurred from August - October 2010, during which background SO2 emissions averaged ~550 ± 180 t/d (1 s.d.). An eruptive pause (phase two) starting in October 2010 abruptly ended in September 2013 with a resumption of conduit-clearing eruptions. This third phase had a relatively modest background SO2 emission rate (avg. ~410 ± 275 t/d) and produced ash consisting entirely of accidental ejecta with high S/Cl leachate ratios (up to 30), suggestive of deep-sourced magma and the incorporation of hydrothermal sulfur-bearing phases. The most intense phase of the eruption (phase four) occurred from December 2013 to February 2014, when juvenile magma first reached the surface. This period included dozens of large eruptions per day, high SO2 emission rates (average: 1,120 ± 1,030 t/d, peak: ~3,800 t/d), the onset of lava dome extrusion, and a dramatic drop in S/Cl ash leachates to ratios < 5, all reflecting increased degassing from shallow magma and the clearing out of sulfurous phases from the old hydrothermal system. From late February 2014 through the time of writing (September 2016), Sinabung settled into a relatively steady state of lower activity (phase five). Ash emissions now consist of dominantly juvenile material, and background SO2 emission rates have been progressively decreasing to an average of ~250 - 300 t/d. Starting August 2016, SO2 emissions started being measured in a continuous manner using a network of permanent scanning DOAS instruments. We find that long-term SO2 emission rates have been gradually declining at Sinabung since early 2014, consistent with an apparent decrease in magma supply. Our degassing model suggests that large explosions and pyroclastic flows could continue in the near-term owing to conduit plugging and dome collapses, remaining a major threat until the magma supply rate decreases further and the eruption ends.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.11.018","usgsCitation":"Primulyana, S., Kern, C., Lerner, A., Saing, U., Kunrat, S., Alfianti, H., and Marlia, M., 2019, Gas and ash emissions associated with the 2010–present activity of Sinabung Volcano, Indonesia: Journal of Volcanology and Geothermal Research, v. 382, p. 184-196, https://doi.org/10.1016/j.jvolgeores.2017.11.018.","productDescription":"13 p.","startPage":"184","endPage":"196","ipdsId":"IP-080511","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.11.018","text":"Publisher Index Page"},{"id":354587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","state":"Sumatra","otherGeospatial":"Mount Sinabung","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 94.04296874999999,\n 6.140554782450308\n ],\n [\n 97.03125,\n -1.0546279422758742\n ],\n [\n 101.7333984375,\n -1.0546279422758742\n ],\n [\n 101.0302734375,\n 4.565473550710278\n ],\n [\n 97.03125,\n 7.885147283424331\n ],\n [\n 94.04296874999999,\n 6.140554782450308\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"382","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155df3e4b092d9651e1b92","contributors":{"authors":[{"text":"Primulyana, Sofyan","contributorId":194978,"corporation":false,"usgs":false,"family":"Primulyana","given":"Sofyan","email":"","affiliations":[],"preferred":false,"id":736704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lerner, Allan","contributorId":205264,"corporation":false,"usgs":false,"family":"Lerner","given":"Allan","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":736705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saing, Ugan","contributorId":205265,"corporation":false,"usgs":false,"family":"Saing","given":"Ugan","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736706,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunrat, Syegi","contributorId":205266,"corporation":false,"usgs":false,"family":"Kunrat","given":"Syegi","email":"","affiliations":[{"id":37069,"text":"CVGHM, Portland State University","active":true,"usgs":false}],"preferred":false,"id":736707,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alfianti, Hilma","contributorId":205267,"corporation":false,"usgs":false,"family":"Alfianti","given":"Hilma","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736708,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marlia, Mitha","contributorId":205268,"corporation":false,"usgs":false,"family":"Marlia","given":"Mitha","email":"","affiliations":[{"id":37068,"text":"CVGHM","active":true,"usgs":false}],"preferred":false,"id":736709,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202954,"text":"70202954 - 2019 - The epidemiology of avian pox and interaction with avian malaria in Hawaiian forest birds","interactions":[],"lastModifiedDate":"2019-04-09T17:19:01","indexId":"70202954","displayToPublicDate":"2018-05-22T17:18:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"The epidemiology of avian pox and interaction with avian malaria in Hawaiian forest birds","docAbstract":"

Despite the purported role of avian pox (Avipoxvirus spp.) in the decline of endemic Hawaiian birds, few studies have been conducted on the dynamics of this disease, its impact on free‐living avian populations, or its interactions with avian malaria (Plasmodium relictum). We conducted four longitudinal studies of 3–7 yr in length and used generalized linear models to evaluate cross‐sectional prevalence of active pox infection and individuals with healed deformities that had recovered from pox. Our goal was to understand how species, season, elevation, malaria infection, and other biological characteristics influenced pox infection in ʻApapane, Hawaiʻi ʻAmakihi, ʻIʻiwi, and Japanese White‐eye across low‐, mid‐, and high‐elevation forests on the island of Hawaiʻi. We also used multi‐state capture‐recapture (longitudinal) models to estimate pox infection rates, recovery rates, and potential pox‐related mortality. Pox infection rates were typically highest in low‐elevation forests, followed by mid‐elevation forests, and lowest in high‐elevation forests. We also found seasonal changes in pox prevalence throughout the annual cycle; typically increasing from spring through summer, peaking in fall, and declining in winter. These seasonal changes occurred in low‐ and mid‐elevation forests, but not in high elevations where pox infection was low. Seasonal and elevation patterns of pox infection are like those for avian malaria, strongly implicating mosquito vectors, rather than other biting arthropods or contact transmission, as the primary source of transmitting both diseases. Most native Hawaiian birds recovered from pox infection within 6 months; frequently without permanent lesions. Contrary to our expectations, we found no direct evidence that pox is a substantial mortality factor in any of the three native bird species we studied. Birds with chronic malaria infection were more likely to have both active pox infection and healed pox lesions suggesting a synergistic interaction that may influence the evolution of pox virulence. Because pox infection can be assessed visually, and birds have a high recovery rate, this disease may be a sensitive indicator of the seasonal and annual risk of transmission of malaria in Hawaiʻi.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1311","usgsCitation":"Samuel, M., Woodworth, B.L., Atkinson, C.T., Hart, P.J., and Lapointe, D., 2019, The epidemiology of avian pox and interaction with avian malaria in Hawaiian forest birds: Ecological Monographs, v. 88, no. 4, p. 621-637, https://doi.org/10.1002/ecm.1311.","productDescription":"17 p.","startPage":"621","endPage":"637","ipdsId":"IP-066385","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":468127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecm.1311","text":"Publisher Index Page"},{"id":362864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Samuel, Michael 0000-0002-4267-2724 msamuel@usgs.gov","orcid":"https://orcid.org/0000-0002-4267-2724","contributorId":214727,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":760641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodworth, Bethany L.","contributorId":214728,"corporation":false,"usgs":false,"family":"Woodworth","given":"Bethany","email":"","middleInitial":"L.","affiliations":[{"id":38381,"text":"University of New England","active":true,"usgs":false}],"preferred":false,"id":760642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":760643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":760644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":760645,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197206,"text":"70197206 - 2019 - Modeling the relationship between water level, wild rice abundance, and waterfowl abundance at a central North American wetland","interactions":[],"lastModifiedDate":"2019-03-26T16:25:47","indexId":"70197206","displayToPublicDate":"2018-05-22T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the relationship between water level, wild rice abundance, and waterfowl abundance at a central North American wetland","docAbstract":"

Recent evidence suggests wild rice (Zizania palustris), an important resource for migrating waterfowl, is declining in parts of central North America, providing motivation to rigorously quantify the relationship between waterfowl and wild rice. A hierarchical mixed-effects model was applied to data on waterfowl abundance for 16 species, wild rice stem density, and two measures of water depth (true water depth at vegetation sampling locations and water surface elevation). Results provide evidence for an effect of true water depth (TWD) on wild rice abundance (posterior mean estimate for TWD coefficient, β TWD = 0.92, 95% confidence interval = 0.11—1.74), but not for an effect of wild rice stem density or water surface elevation on local waterfowl abundance (posterior mean values for relevant parameters overlapped 0). Refined protocols for sampling design and more consistent sampling frequency to increase data quality should be pursued to overcome issues that may have obfuscated relationships evaluated here.

","language":"English","publisher":"Springer","doi":"10.1007/s13157-018-1025-6","usgsCitation":"Aagaard, K., Eash, J.D., Ford, W., Heglund, P., McDowell, M., and Thogmartin, W.E., 2019, Modeling the relationship between water level, wild rice abundance, and waterfowl abundance at a central North American wetland: Wetlands, v. 39, no. 1, p. 149-160, https://doi.org/10.1007/s13157-018-1025-6.","productDescription":"12 p.","startPage":"149","endPage":"160","ipdsId":"IP-070237","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":354399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-26","publicationStatus":"PW","scienceBaseUri":"5b155d7ae4b092d9651e1b48","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eash, Josh D.","contributorId":100933,"corporation":false,"usgs":true,"family":"Eash","given":"Josh","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":736227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, Walt","contributorId":205151,"corporation":false,"usgs":false,"family":"Ford","given":"Walt","email":"","affiliations":[],"preferred":false,"id":736228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heglund, Patricia J.","contributorId":51248,"corporation":false,"usgs":true,"family":"Heglund","given":"Patricia J.","affiliations":[],"preferred":false,"id":736229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDowell, Michelle","contributorId":205152,"corporation":false,"usgs":false,"family":"McDowell","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":736230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":736231,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204878,"text":"70204878 - 2019 - Synchrony — An emergent property of recreational fisheries","interactions":[],"lastModifiedDate":"2019-08-21T15:17:07","indexId":"70204878","displayToPublicDate":"2018-05-21T15:16:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Synchrony — An emergent property of recreational fisheries","docAbstract":"Recreational fisheries are traditionally managed at local scales, but more effective management could be achieved using a cross‐scale approach. To do this, we must first understand how local processes scale up to influence landscape patterns between anglers and resources. We highlight how population‐based synchrony methods, used in conjunction with a complex‐adaptive‐systems framework, can reveal emergent spatial properties within social‐ecological systems such as recreational fisheries. Herein, we quantified the level of spatial synchrony in angler behaviour, defined the relationship between angler synchrony and distance among waterbodies, and highlighted social‐ecological attributes contributing to these patterns. We leveraged a 111 waterbody‐year (34 waterbodies, 5‐year collection period) recreational fisheries dataset from Nebraska, USA to address these objectives. Intra‐annual patterns in angler behaviour were moderately synchronous across large spatial scales and predominately unrelated to distance among waterbodies. Large‐scale synchronous patterns in angler behaviour emerged from local‐scale interactions between angler heterogeneity and waterbody diversity. Spatial synchrony in angler behaviour is an emergent property that resulted from local‐level processes that scaled up to form large‐scale patterns. We posit that angler utility in combination with waterbodies sharing these desired utility components caused spatial synchrony among anglers with similar preferences or specializations. The level of spatial synchrony in angler behaviour will therefore depend on the degree of angler heterogeneity and waterbody diversity on the landscape, with high or low levels of both leading to low and high levels of spatial synchrony respectively. Synthesis and applications. Synchrony‐based methods proved useful for unveiling an emergent property in recreational fisheries that is beneficial for effective cross‐scale management. It may not be appropriate to extrapolate information and apply uniform management actions among local waterbodies because angler behaviour was not synchronous at small scales. Rather, anglers respond uniquely to waterbody diversity and therefore substitute waterbodies may be dispersed throughout the landscape. Creating boat access, for example could yield unintended consequences for a particular angler group and cause local and regional shifts in angler behaviour. Evaluating appropriate management options will require a cross‐scale monitoring approach that captures angler heterogeneity and waterbody diversity at multiple scales. Recreational fisheries are traditionally managed at local scales, but more effective management could be achieved using a cross‐scale approach. To do this, we must first understand how local processes scale up to influence landscape patterns between anglers and resources. We highlight how population‐based synchrony methods, used in conjunction with a complex‐adaptive‐systems framework, can reveal emergent spatial properties within social‐ecological systems such as recreational fisheries. Herein, we quantified the level of spatial synchrony in angler behaviour, defined the relationship between angler synchrony and distance among waterbodies, and highlighted social‐ecological attributes contributing to these patterns. We leveraged a 111 waterbody‐year (34 waterbodies, 5‐year collection period) recreational fisheries dataset from Nebraska, USA to address these objectives. Intra‐annual patterns in angler behaviour were moderately synchronous across large spatial scales and predominately unrelated to distance among waterbodies. Large‐scale synchronous patterns in angler behaviour emerged from local‐scale interactions between angler heterogeneity and waterbody diversity. Spatial synchrony in angler behaviour is an emergent property that resulted from local‐level processes that scaled up to form large‐scale patterns. We posit that angler","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.13164","usgsCitation":"Pope, K.L., 2019, Synchrony — An emergent property of recreational fisheries: Journal of Applied Ecology, v. 55, no. 6, p. 2986-2996, https://doi.org/10.1111/1365-2664.13164.","productDescription":"11 p.","startPage":"2986","endPage":"2996","ipdsId":"IP-086746","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":366808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":768861,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70196987,"text":"70196987 - 2019 - Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon","interactions":[],"lastModifiedDate":"2019-01-28T09:35:59","indexId":"70196987","displayToPublicDate":"2018-05-14T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon","docAbstract":"

We applied an empirical model to predict hatching and emergence timing for 25 western Alaska sockeye salmon (Oncorhynchus nerka) populations in four lake-nursery systems to explore current patterns and potential responses of early life history phenology to warming water temperatures. Given experienced temperature regimes during development, we predicted hatching to occur in as few as 58 d to as many as 260 d depending on spawning timing and temperature. For a focal lake spawning population, our climate-lake temperature model predicted a water temperature increase of 0.7 to 1.4 °C from 2015 to 2099 during the incubation period, which translated to a 16 d to 30 d earlier hatching timing. The most extreme scenarios of warming advanced development by approximately a week earlier than historical minima and thus climatic warming may lead to only modest shifts in phenology during the early life history stage of this population. The marked variation in the predicted timing of hatching and emergence among populations in close proximity on the landscape may serve to buffer this metapopulation from climate change.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0468","usgsCitation":"Sparks, M.M., Falke, J.A., Quinn, T.P., Adkison, M.D., Schindler, D.E., Bartz, K.K., Young, D.B., and Westley, P.A., 2019, Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 1, p. 123-135, https://doi.org/10.1139/cjfas-2017-0468.","productDescription":"13 p.","startPage":"123","endPage":"135","ipdsId":"IP-092007","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6bde4b0da30c1bfbd8e","contributors":{"authors":[{"text":"Sparks, Morgan M.","contributorId":200252,"corporation":false,"usgs":false,"family":"Sparks","given":"Morgan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":735277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":735278,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adkison, Milo D.","contributorId":100791,"corporation":false,"usgs":false,"family":"Adkison","given":"Milo","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735279,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schindler, Daniel E.","contributorId":83485,"corporation":false,"usgs":true,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":735280,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":735281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Daniel","contributorId":58468,"corporation":false,"usgs":false,"family":"Young","given":"Daniel","affiliations":[{"id":35763,"text":"National Park Service, Lake Clark National Park and Preserve, Port Alsworth, AK","active":true,"usgs":false}],"preferred":false,"id":735282,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Westley, Peter A. H.","contributorId":190530,"corporation":false,"usgs":false,"family":"Westley","given":"Peter","email":"","middleInitial":"A. H.","affiliations":[],"preferred":false,"id":735283,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198751,"text":"70198751 - 2019 - Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids","interactions":[],"lastModifiedDate":"2019-02-11T15:14:09","indexId":"70198751","displayToPublicDate":"2018-05-08T15:54:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids","docAbstract":"

Understanding how environmental factors interact to determine the abundance and distribution of animals is a primary goal of ecology, and fundamental to the conservation of wildlife populations. Studies of these relationships, however, often assume static environmental conditions, and rarely consider effects of competition with ecologically similar species. In many parts of their shared ranges, grizzly bears Ursus arctos and American black bears U. americanus have nearly complete dietary overlap and share similar life history traits. We therefore tested the hypothesis that density patterns of both bear species would reflect seasonal variation in available resources, with areas of higher primary productivity supporting higher densities of both species. We also hypothesized that interspecific competition would influence seasonal density patterns. Specifically, we predicted that grizzly bear density would be locally reduced due to the ability of black bears to more efficiently exploit patchy food resources such as seasonally abundant fruits. To test our hypotheses, we used detections of 309 grizzly and 597 black bears from two independent genetic sampling methods in spatially‐explicit capture–recapture (SECR) models. Our results suggest grizzly bear density was lower in areas of high black bear density during spring and summer, although intraspecific densities were also important, particularly during the breeding season. Black bears had lower densities in areas of high grizzly bear density in spring; however, density of black bears in early and late summer was best explained by primary productivity. Our results are consistent with the hypothesis that smaller‐bodied, more abundant black bears may influence the density patterns of behaviorally‐dominant grizzly bears through exploitative competition. We also suggest that seasonal variation in resource availability be considered in efforts to relate environmental conditions to animal density.

","language":"English","publisher":"Wiley","doi":"10.1111/ecog.03556","usgsCitation":"Stetz, J.B., Mitchell, M.S., and Kendall, K.C., 2019, Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids: Ecography, v. 42, no. 2, p. 237-248, https://doi.org/10.1111/ecog.03556.","productDescription":"12 p.","startPage":"237","endPage":"248","ipdsId":"IP-089876","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.7576904296875,\n 47.98072994347796\n ],\n [\n -113.038330078125,\n 47.98072994347796\n ],\n [\n -113.038330078125,\n 48.996438064932285\n ],\n [\n -114.7576904296875,\n 48.996438064932285\n ],\n [\n -114.7576904296875,\n 47.98072994347796\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-25","publicationStatus":"PW","scienceBaseUri":"5b98a2c6e4b0702d0e842fe4","contributors":{"authors":[{"text":"Stetz, Jeffrey B.","contributorId":15493,"corporation":false,"usgs":true,"family":"Stetz","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":743542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":742846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":742847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204360,"text":"70204360 - 2019 - On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models","interactions":[],"lastModifiedDate":"2020-02-19T13:43:22","indexId":"70204360","displayToPublicDate":"2018-05-01T11:34:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models","docAbstract":"

We clarify relationships between conditional (CAR) and simultaneous (SAR) autoregressive models. We review the literature on this topic and find that it is mostly incomplete. Our main result is that a SAR model can be written as a unique CAR model, and while a CAR model can be written as a SAR model, it is not unique. In fact, we show how any multivariate Gaussian distribution on a finite set of points with a positive-definite covariance matrix can be written as either a CAR or a SAR model. We illustrate how to obtain any number of SAR covariance matrices from a single CAR covariance matrix by using Givens rotation matrices on a simulated example. We also discuss sparseness in the original CAR construction, and for the resulting SAR weights matrix. For a real example, we use crime data in 49 neighborhoods from Columbus, Ohio, and show that a geostatistical model optimizes the likelihood much better than typical first-order CAR models. We then use the implied weights from the geostatistical model to estimate CAR model parameters that provides the best overall optimization.

","language":"English","publisher":"Wiley","doi":"10.1016/j.spasta.2018.04.006","usgsCitation":"Hoef, J.M., Hanksb, E.M., and Hooten, M., 2019, On the relationship between conditional (CAR) and simultaneous (SAR) autoregressive models: Spatial Statistics, v. 25, p. 68-85, https://doi.org/10.1016/j.spasta.2018.04.006.","productDescription":"18 p.","startPage":"68","endPage":"85","ipdsId":"IP-080788","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://arxiv.org/abs/1710.07000","text":"Publisher Index Page"},{"id":365775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hoef, Jay M. Ver","contributorId":217288,"corporation":false,"usgs":false,"family":"Hoef","given":"Jay","email":"","middleInitial":"M. Ver","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":766520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanksb, Ephraim M.","contributorId":217289,"corporation":false,"usgs":false,"family":"Hanksb","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[{"id":24698,"text":"PSU","active":true,"usgs":false}],"preferred":false,"id":766521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":766519,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196639,"text":"70196639 - 2019 - Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013","interactions":[],"lastModifiedDate":"2019-10-09T08:27:37","indexId":"70196639","displayToPublicDate":"2018-04-23T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013","docAbstract":"

We conducted travel time tomography using P- and S-wave arrival times of volcanic-tectonic (VT) events that occurred between November and December 2013 to determine the three-dimensional (3D) seismic velocity structure (Vp, Vs, and Vp/Vs) beneath Sinabung volcano, Indonesia in order to delineate geological subsurface structure and to enhance our understanding of the volcanism itself. This was a time period when phreatic explosions became phreatomagmatic and then magma migrated to the surface forming a summit lava dome. We used 4846 VT events with 16,138 P- and 16,138 S-wave arrival time phases recorded by 6 stations for the tomographic inversion. The relocated VTs collapse into three clusters at depths from the surface to sea level, from 2 to 4 km below sea level, and from 5 to 8.5 km below sea level. The tomographic inversion results show three prominent regions of high Vp/Vs (~ 1.8) beneath Sinabung volcano at depths consistent with the relocated earthquake clusters. We interpret these anomalies as intrusives associated with previous eruptions and possibly surrounding the magma conduit, which we cannot resolve with this study. One anomalous region might contain partial melt, at sea level and below the eventual eruption site at the summit. Our results are important for the interpretation of a conceptual model of the “plumbing system” of this hazardous volcano.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2017.09.018","usgsCitation":"Nugraha, A.D., Indrastuti, N., Kusnandar, R., Gunawan, H., McCausland, W.A., Aulia, A.N., and Harlianti, U., 2019, Joint 3-D tomographic imaging of Vp, Vs and Vp/Vs and hypocenter relocation at Sinabung volcano, Indonesia from November to December 2013: Journal of Volcanology and Geothermal Research, v. 382, p. 210-223, https://doi.org/10.1016/j.jvolgeores.2017.09.018.","productDescription":"14 p.","startPage":"210","endPage":"223","ipdsId":"IP-084224","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2017.09.018","text":"Publisher Index Page"},{"id":353660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Sinabung Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 98.3167,\n 3.1\n ],\n [\n 98.5,\n 3.1\n ],\n [\n 98.5,\n 3.3\n ],\n [\n 98.3167,\n 3.3\n ],\n [\n 98.3167,\n 3.1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"382","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe70","contributors":{"authors":[{"text":"Nugraha, Andri Dian","contributorId":202043,"corporation":false,"usgs":false,"family":"Nugraha","given":"Andri","email":"","middleInitial":"Dian","affiliations":[{"id":36333,"text":"Institut Teknologi Bandung","active":true,"usgs":false}],"preferred":false,"id":733856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Indrastuti, Novianti","contributorId":204389,"corporation":false,"usgs":false,"family":"Indrastuti","given":"Novianti","email":"","affiliations":[{"id":36928,"text":"Center for Volcanology and Geological Hazard Mitigation, Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kusnandar, Ridwan","contributorId":204390,"corporation":false,"usgs":false,"family":"Kusnandar","given":"Ridwan","email":"","affiliations":[{"id":36929,"text":"Meteorological, Climatological, and Geophysical Agency, Denpasar, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunawan, Hendra","contributorId":194977,"corporation":false,"usgs":false,"family":"Gunawan","given":"Hendra","email":"","affiliations":[],"preferred":false,"id":733859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":733855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aulia, Atin Nur","contributorId":204391,"corporation":false,"usgs":false,"family":"Aulia","given":"Atin","email":"","middleInitial":"Nur","affiliations":[{"id":36930,"text":"Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institute of Technology Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harlianti, Ulvienin","contributorId":204392,"corporation":false,"usgs":false,"family":"Harlianti","given":"Ulvienin","email":"","affiliations":[{"id":36930,"text":"Geophysical Engineering, Faculty of Mining and Petroleum Engineering, Institute of Technology Bandung, Indonesia","active":true,"usgs":false}],"preferred":false,"id":733861,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227896,"text":"70227896 - 2019 - Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","interactions":[],"lastModifiedDate":"2022-02-02T17:14:09.501322","indexId":"70227896","displayToPublicDate":"2018-04-17T11:00:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","title":"Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","docAbstract":"

The specificity and accuracy of inferred fish origin and movement relies on describing spatial heterogeneity and temporal stability of environmental signatures. But the cost and logistics of sample collection often precludes the complete quantification of environmental signature temporal stability and spatial heterogeneity. We used repeated sampling and a novel approach (Bayesian ridge regression, BRR) to quantify the temporal stability and spatial heterogeneity of 87Sr/86Sr, respectively. We explained 86% of observed variation in 87Sr/86Sr using a BRR model and estimated 87Sr/86Sr throughout the Upper North Platte River Basin with high accuracy (±0.00106). Year to year variation in 87Sr/86Sr signatures ranged from 0.00007 to 0.00073 (SD), while seasonal variation ranged from 0.00091 to 0.00134 (SD). We then assessed the specificity and discussed the accuracy of inferring movement using three scenarios of described spatial heterogeneity. Our results indicate reliable inference of fish movement requires comprehensive quantification of spatial heterogeneity and temporal variation in environmental signatures.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0124","usgsCitation":"Ciepiela, L.R., and Walters, A.W., 2019, Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 6, p. 928-936, https://doi.org/10.1139/cjfas-2018-0124.","productDescription":"9 p.","startPage":"928","endPage":"936","ipdsId":"IP-094459","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501331,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/93571","text":"External Repository"},{"id":395283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Upper North Platte River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.138671875,\n 40.74725696280421\n ],\n [\n -106,\n 40.74725696280421\n ],\n [\n -106,\n 42.48830197960227\n ],\n [\n -107.138671875,\n 42.48830197960227\n ],\n [\n -107.138671875,\n 40.74725696280421\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ciepiela, Lindsy R.","contributorId":273061,"corporation":false,"usgs":false,"family":"Ciepiela","given":"Lindsy","email":"","middleInitial":"R.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":832549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832548,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}