{"pageNumber":"400","pageRowStart":"9975","pageSize":"25","recordCount":40807,"records":[{"id":70263825,"text":"70263825 - 2018 - A comprehensive analysis of geodetic slip rate estimates and uncertainties in California","interactions":[],"lastModifiedDate":"2025-02-25T15:47:01.183754","indexId":"70263825","displayToPublicDate":"2017-11-14T09:42:19","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A comprehensive analysis of geodetic slip rate estimates and uncertainties in California","docAbstract":"Developing a comprehensive model of tectonic continental deformation requires assessing (1) fault‐slip rates, (2) off‐fault deformation rates, and (3) realistic uncertainties. Fault‐slip rates can be estimated by modeling fault systems, based on space geodetic measurements of active surface ground displacement such as Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). Geodetic slip‐rate estimates may vary widely due to measurement and epistemic (model) uncertainties, presenting a challenge for both estimating slip rates and accurately characterizing uncertainties: models may vary in the number of faults represented and the precise location of those faults. Since 2003, 33 published geodetic deformation models have produced slip‐rate estimates within California. Variability among these models represents variability among valid model choices and may be considered a proxy for model uncertainties in geodetic slip‐rate estimates. To enable rigorous comparison between geodetic slip‐rate estimates, I combine models on a georeferenced grid and find an average standard deviation on slip rate of ∼1.5 mm/yr over 542 grid cells (average area of 1304 km2/cell). Furthermore, the average strike‐slip and tensile‐slip rates over all 33 studies, in each grid cell, may then be projected onto Unified California Earthquake Rupture Forecast (UCERF) v.3.1 faults for a single summary model of geodetic slip rates. Slip rates that do not project perfectly onto UCERF3.1 faults form a summary model of off‐modeled‐fault (OMF) deformation. Most of this OMF deformation occurs in grid cells that intersect UCERF3.1 faults, suggesting that off‐fault deformation may be, in part, a product of epistemic uncertainty in geodetic slip‐rate estimates and may be physically accommodated on, or very near, UCERF faults.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120170159","usgsCitation":"Evans, E., 2018, A comprehensive analysis of geodetic slip rate estimates and uncertainties in California: Bulletin of the Seismological Society of America, v. 108, no. 1, p. 1-18, https://doi.org/10.1785/0120170159.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-086957","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"108","issue":"1","noUsgsAuthors":false,"publicationDate":"2017-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Eileen 0000-0002-7290-5269 eevans@usgs.gov","orcid":"https://orcid.org/0000-0002-7290-5269","contributorId":167021,"corporation":false,"usgs":true,"family":"Evans","given":"Eileen","email":"eevans@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928556,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70193529,"text":"70193529 - 2018 - The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and precocious maturation of early-rearing Atlantic salmon Salmo salar","interactions":[],"lastModifiedDate":"2018-01-11T16:14:22","indexId":"70193529","displayToPublicDate":"2017-11-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":857,"text":"Aquaculture Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and precocious maturation of early-rearing Atlantic salmon Salmo salar","title":"The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and precocious maturation of early-rearing Atlantic salmon Salmo salar","docAbstract":"Swimming exercise, typically measured in body-lengths per second (BL/s), and dissolved oxygen (DO), are important environmental variables in fish culture. While there is an obvious physiological association between these two parameters, their interaction has not been adequately studied in Atlantic salmon Salmo salar. Because exercise and DO are variables that can be easily manipulated in modern aquaculture systems, we sought to assess the impact of these parameters, alone and in combination, on the performance, health and welfare of juvenile Atlantic salmon. In our study, Atlantic salmon fry were stocked into 12 circular 0.5 m3 tanks in a flow-through system and exposed to either high (1.5–2 BL/s) or low (<0.5 BL/s) swimming speeding and high (100% saturation) or low (70% saturation) DO while being raised from 10 g to approximately 350 g in weight. Throughout the study period, we assessed the impacts of exercise and DO concentration on growth, feed conversion, survival and fin condition. By study's end, both increased swimming speed and higher DO were independently associated with a statistically significant increase in growth performance (p < .05); however, no significant differences were noted in survival and feed conversion. Caudal fin damage was associated with low DO, while right pectoral fin damage was associated with higher swimming speed. Finally, precocious male sexual maturation was associated with low swimming speed. These results suggest that providing exercise and dissolved oxygen at saturation during Atlantic salmon early rearing can result in improved growth performance and a lower incidence of precocious parr.
","language":"English","publisher":"Wiley","doi":"10.1111/are.13511","usgsCitation":"Waldrop, T., Summerfelt, S.T., Mazik, P.M., and Good, C., 2018, The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and precocious maturation of early-rearing Atlantic salmon Salmo salar: Aquaculture Research, v. 49, no. 2, p. 801-808, https://doi.org/10.1111/are.13511.","productDescription":"8 p.","startPage":"801","endPage":"808","ipdsId":"IP-084451","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461119,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/are.13511","text":"Publisher Index Page"},{"id":348841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-26","publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227bb","contributors":{"authors":[{"text":"Waldrop, Thomas","contributorId":56977,"corporation":false,"usgs":true,"family":"Waldrop","given":"Thomas","affiliations":[],"preferred":false,"id":722051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Summerfelt, Steven T.","contributorId":192709,"corporation":false,"usgs":false,"family":"Summerfelt","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":722052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Good, Christopher","contributorId":200359,"corporation":false,"usgs":false,"family":"Good","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":722053,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70194077,"text":"70194077 - 2018 - Modeling the compensatory response of an invasive tree to specialist insect herbivory","interactions":[],"lastModifiedDate":"2018-01-05T14:02:43","indexId":"70194077","displayToPublicDate":"2017-11-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1016,"text":"Biological Control","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the compensatory response of an invasive tree to specialist insect herbivory","docAbstract":"The severity of the effects of herbivory on plant fitness can be moderated by the ability of plants to compensate for biomass loss. Compensation is an important component of the ecological fitness in many plants, and has been shown to reduce the effects of pests on agricultural plant yields. It can also reduce the effectiveness of biocontrol through introduced herbivores in controlling weedy invasive plants. This study used a modeling approach to predict the effect of different levels of foliage herbivory by biological control agents introduced to control the invasive tree Melaleuca quinquennervia (melaleuca) in Florida. It is assumed in the model that melaleuca can optimally change its carbon and nitrogen allocation strategies in order to compensate for the effects of herbivory. The model includes reallocation of more resources to production and maintenance of photosynthetic tissues at the expense of roots. This compensation is shown to buffer the severity of the defoliation effect, but the model predicts a limit on the maximum herbivory that melaleuca can tolerate and survive. The model also shows that the level of available limiting nutrient (e.g., soil nitrogen) may play an important role in a melaleuca’s ability to compensate for herbivory. This study has management implications for the best ways to maximize the level of damage using biological control or other means of defoliation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocontrol.2017.11.002","usgsCitation":"Zhang, B., Liu, X., DeAngelis, D.L., Zhai, L., Rayamajhi, M.B., and Ju, S., 2018, Modeling the compensatory response of an invasive tree to specialist insect herbivory: Biological Control, v. 117, p. 128-136, https://doi.org/10.1016/j.biocontrol.2017.11.002.","productDescription":"9 p.","startPage":"128","endPage":"136","ipdsId":"IP-090151","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocontrol.2017.11.002","text":"Publisher Index Page"},{"id":348850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","volume":"117","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227b4","contributors":{"authors":[{"text":"Zhang, Bo","contributorId":146526,"corporation":false,"usgs":false,"family":"Zhang","given":"Bo","email":"","affiliations":[{"id":16714,"text":"Dept. of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":722070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Xin","contributorId":146527,"corporation":false,"usgs":false,"family":"Liu","given":"Xin","email":"","affiliations":[{"id":16715,"text":"Nanjing Forestry University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":722071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":722072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhai, Lu","contributorId":147395,"corporation":false,"usgs":false,"family":"Zhai","given":"Lu","affiliations":[{"id":16839,"text":"Department of Biology, University of Miami, Coral Gables, Florida","active":true,"usgs":false}],"preferred":false,"id":722073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rayamajhi, Min B.","contributorId":191306,"corporation":false,"usgs":false,"family":"Rayamajhi","given":"Min","email":"","middleInitial":"B.","affiliations":[{"id":33268,"text":"USDA-ARS Aquatic Weed Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":722074,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ju, Shu","contributorId":200346,"corporation":false,"usgs":false,"family":"Ju","given":"Shu","email":"","affiliations":[{"id":13532,"text":"Department of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":722075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193560,"text":"70193560 - 2018 - Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains","interactions":[],"lastModifiedDate":"2018-04-02T13:56:58","indexId":"70193560","displayToPublicDate":"2017-11-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2298,"text":"Journal of Forestry Research","active":true,"publicationSubtype":{"id":10}},"title":"Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains","docAbstract":"In eastern North America, white-tailed deer (Odocoileus virginianus) can have profound influences on forest biodiversity and forest successional processes. Moderate to high deer populations in the central Appalachians have resulted in lower forest biodiversity. Legacy effects in some areas persist even following deer population reductions or declines. This has prompted managers to consider deer population management goals in light of policies designed to support conservation of biodiversity and forest regeneration while continuing to support ample recreational hunting opportunities. However, despite known relationships between herbivory intensity and biodiversity impact, little information exists on the predictability of herbivory intensity across the varied and spatially diverse habitat conditions of the central Appalachians. We examined the predictability of browsing rates across central Appalachian landscapes at four environmental scales: vegetative community characteristics, physical environment, habitat configuration, and local human and deer population demographics. In an information-theoretic approach, we found that a model fitting the number of stems browsed relative to local vegetation characteristics received most (62%) of the overall support of all tested models assessing herbivory impact. Our data suggest that deer herbivory responded most predictably to differences in vegetation quantity and type. No other spatial factors or demographic factors consistently affected browsing intensity. Because herbivory, vegetation communities, and productivity vary spatially, we suggest that effective broad-scale herbivory impact assessment should include spatially-balanced vegetation monitoring that accounts for regional differences in deer forage preference. Effective monitoring is necessary to avoid biodiversity impacts and deleterious changes in vegetation community composition that are difficult to reverse and/or may not be detected using traditional deer-density based management goals.
","language":"English","publisher":"Springer","doi":"10.1007/s11676-017-0476-6","usgsCitation":"Kniowski, A.B., and Ford, W., 2018, Predicting intensity of white-tailed deer herbivory in the Central Appalachian Mountains: Journal of Forestry Research, v. 29, no. 3, p. 841-850, https://doi.org/10.1007/s11676-017-0476-6.","productDescription":"10 p.","startPage":"841","endPage":"850","ipdsId":"IP-086612","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469161,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99324","text":"External Repository"},{"id":348769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Mountains","volume":"29","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-21","publicationStatus":"PW","scienceBaseUri":"5a60fb13e4b06e28e9c22bd8","contributors":{"authors":[{"text":"Kniowski, Andrew B.","contributorId":191558,"corporation":false,"usgs":false,"family":"Kniowski","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":719363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":719362,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193638,"text":"70193638 - 2018 - Catchment-scale determinants of nonindigenous minnow richness in the eastern United States","interactions":[],"lastModifiedDate":"2017-12-11T13:08:33","indexId":"70193638","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Catchment-scale determinants of nonindigenous minnow richness in the eastern United States","docAbstract":"Understanding the drivers of biological invasions is critical for preserving aquatic biodiversity. Stream fishes make excellent model taxa for examining mechanisms driving species introduction success because their distributions are naturally limited by catchment boundaries. In this study, we compared the relative importance of catchment-scale abiotic and biotic predictors of native and nonindigenous minnow (Cyprinidae) richness in 170 catchments throughout the eastern United States. We compared historic and contemporary cyprinid distributional data to determine catchment-wise native/nonindigenous status for 152 species. Catchment-scale model predictor variables described natural (elevation, precipitation, flow accumulation) and anthropogenic (developed land cover, number of dams) abiotic features, as well as native congener richness. Native congener richness may represent either biotic resistance via interspecific competition, or trait preadaptation according to Darwin's naturalisation hypothesis. We used generalised linear mixed models to examine evidence supporting the relative roles of abiotic and biotic predictors of cyprinid introduction success. Native congener richness was positively correlated with nonindigenous cyprinid richness and was the most important variable predicting nonindigenous cyprinid richness. Mean elevation had a weak positive effect, and effects of other abiotic factors were insignificant and less important. Our results suggest that at this spatial scale, trait preadaptation may be more important than intrageneric competition for determining richness of nonindigenous fishes.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12331","usgsCitation":"Peoples, B.K., Midway, S.R., DeWeber, J.T., and Wagner, T., 2018, Catchment-scale determinants of nonindigenous minnow richness in the eastern United States: Ecology of Freshwater Fish, v. 27, no. 1, p. 138-145, https://doi.org/10.1111/eff.12331.","productDescription":"8 p.","startPage":"138","endPage":"145","ipdsId":"IP-074166","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":461121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12331","text":"Publisher Index Page"},{"id":348724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.78125,\n 29.53522956294847\n ],\n [\n -66.62109375,\n 29.53522956294847\n ],\n [\n -66.62109375,\n 47.487513008956554\n ],\n [\n -85.78125,\n 47.487513008956554\n ],\n [\n -85.78125,\n 29.53522956294847\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-13","publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227c7","contributors":{"authors":[{"text":"Peoples, Brandon K.","contributorId":177551,"corporation":false,"usgs":false,"family":"Peoples","given":"Brandon","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":719709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Midway, Stephen R.","contributorId":172159,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":719710,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeWeber, Jefferson T.","contributorId":199675,"corporation":false,"usgs":false,"family":"DeWeber","given":"Jefferson","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":719711,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193612,"text":"70193612 - 2018 - Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework","interactions":[],"lastModifiedDate":"2017-12-11T13:07:48","indexId":"70193612","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework","title":"Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework","docAbstract":"An individual-based model framework was used to evaluate growth potential of the federally endangered pallid sturgeon (Scaphirhynchus albus) in the Missouri River. The model, developed for age-0 sturgeon, combines information on functional feeding response, bioenergetics and swimming ability to regulate consumption and growth within a virtual foraging arena. Empirical data on water temperature, water velocity and prey density were obtained from three sites in the Missouri River and used as inputs in the model to evaluate hypotheses concerning factors affecting pallid sturgeon growth. The model was also used to evaluate the impacts of environmental heterogeneity and water velocity on individual growth variability, foraging success and dispersal ability. Growth was simulated for a period of 100 days using 100 individuals (first feeding; 19 mm and 0.035 g) per scenario. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Highly heterogeneous habitats (i.e., wide range of environmental conditions) and moderate water velocities (0.3 m/s) were also found to positively affect growth rates. The model developed here provides an important management and conservation tool for evaluating growth hypotheses and(or) identifying habitats in the Missouri River that are favourable to age-0 pallid sturgeon growth.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12337","usgsCitation":"Deslauriers, D., Heironimus, L.B., Rapp, T., Graeb, B.D., Klumb, R.A., and Chipps, S.R., 2018, Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework: Ecology of Freshwater Fish, v. 27, no. 1, p. 198-208, https://doi.org/10.1111/eff.12337.","productDescription":"11 p.","startPage":"198","endPage":"208","ipdsId":"IP-080765","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348729,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-24","publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227cb","contributors":{"authors":[{"text":"Deslauriers, David","contributorId":187586,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","email":"","affiliations":[],"preferred":false,"id":719622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heironimus, Laura B.","contributorId":187587,"corporation":false,"usgs":false,"family":"Heironimus","given":"Laura","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":719623,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rapp, Tobias","contributorId":199643,"corporation":false,"usgs":false,"family":"Rapp","given":"Tobias","email":"","affiliations":[],"preferred":false,"id":719624,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graeb, Brian D. S.","contributorId":171851,"corporation":false,"usgs":false,"family":"Graeb","given":"Brian","email":"","middleInitial":"D. S.","affiliations":[{"id":26956,"text":"Departement of Natural Resource Management, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":719625,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klumb, Robert A.","contributorId":86606,"corporation":false,"usgs":true,"family":"Klumb","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":561,"text":"South Dakota Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":5089,"text":"South Dakota State University","active":true,"usgs":false},{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":719626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719621,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193580,"text":"70193580 - 2018 - Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance","interactions":[],"lastModifiedDate":"2018-02-05T15:33:08","indexId":"70193580","displayToPublicDate":"2017-11-13T00:00:00","publicationYear":"2018","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":"Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance","docAbstract":"Context
Species-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.
Objectives
We tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.
Methods
We compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.
Results
Blackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.
Conclusions
LC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.
Exposure of wildlife to Active Pharmaceutical Ingredients (APIs) is likely to occur but studies of risk are limited. One exposure pathway that has received attention is trophic transfer of APIs in a water-fish-osprey food chain. Samples of water, fish plasma and osprey plasma were collected from Delaware River and Bay, and analyzed for 21 APIs. Only 2 of 21 analytes exceeded method detection limits in osprey plasma (acetaminophen and diclofenac) with plasma levels typically 2–3 orders of magnitude below human therapeutic concentrations (HTC). We built upon a screening level model used to predict osprey exposure to APIs in Chesapeake Bay and evaluated whether exposure levels could have been predicted in Delaware Bay had we just measured concentrations in water or fish. Use of surface water and BCFs did not predict API concentrations in fish well, likely due to fish movement patterns, and partitioning and bioaccumulation uncertainties associated with these ionizable chemicals. Input of highest measured API concentration in fish plasma combined with pharmacokinetic data accurately predicted that diclofenac and acetaminophen would be the APIs most likely detected in osprey plasma. For the majority of APIs modeled, levels were not predicted to exceed 1 ng/mL or method detection limits in osprey plasma. Based on the target analytes examined, there is little evidence that APIs represent a significant risk to ospreys nesting in Delaware Bay. If an API is present in fish orders of magnitude below HTC, sampling of fish-eating birds is unlikely to be necessary. However, several human pharmaceuticals accumulated in fish plasma within a recommended safety factor for HTC. It is now important to expand the scope of diet-based API exposure modeling to include alternative exposure pathways (e.g., uptake from landfills, dumps and wastewater treatment plants) and geographic locations (developing countries) where API contamination of the environment may represent greater risk.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.09.083","usgsCitation":"Bean, T., Rattner, B.A., Lazarus, R.S., Day, D.D., Burket, S.R., Brooks, B.W., Haddad, S.P., and Bowerman, W.W., 2018, Pharmaceuticals in water, fish and osprey nestlings in Delaware River and Bay: Environmental Pollution, v. 232, p. 533-545, https://doi.org/10.1016/j.envpol.2017.09.083.","productDescription":"13 p.","startPage":"533","endPage":"545","ipdsId":"IP-086763","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":461125,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2017.09.083","text":"Publisher Index Page"},{"id":348631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware Bay, Delaware River","volume":"232","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bade4b09af898c94133","contributors":{"authors":[{"text":"Bean, Thomas G. 0000-0002-3577-1994 tbean@usgs.gov","orcid":"https://orcid.org/0000-0002-3577-1994","contributorId":195993,"corporation":false,"usgs":true,"family":"Bean","given":"Thomas G.","email":"tbean@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":717477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":717476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lazarus, Rebecca S. 0000-0003-1731-6469 rlazarus@usgs.gov","orcid":"https://orcid.org/0000-0003-1731-6469","contributorId":5594,"corporation":false,"usgs":true,"family":"Lazarus","given":"Rebecca","email":"rlazarus@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":717478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Day, Daniel D. 0000-0001-9070-7170 dday@usgs.gov","orcid":"https://orcid.org/0000-0001-9070-7170","contributorId":3985,"corporation":false,"usgs":true,"family":"Day","given":"Daniel","email":"dday@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":717479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burket, S. Rebekah","contributorId":198867,"corporation":false,"usgs":false,"family":"Burket","given":"S.","email":"","middleInitial":"Rebekah","affiliations":[{"id":35352,"text":"Department of Environmental Science, Baylor University, Waco, TX, USA","active":true,"usgs":false}],"preferred":false,"id":717480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooks, Bryan W. 0000-0002-6277-9852","orcid":"https://orcid.org/0000-0002-6277-9852","contributorId":198868,"corporation":false,"usgs":false,"family":"Brooks","given":"Bryan","email":"","middleInitial":"W.","affiliations":[{"id":35352,"text":"Department of Environmental Science, Baylor University, Waco, TX, USA","active":true,"usgs":false}],"preferred":false,"id":717481,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haddad, Samuel P.","contributorId":198869,"corporation":false,"usgs":false,"family":"Haddad","given":"Samuel","email":"","middleInitial":"P.","affiliations":[{"id":35352,"text":"Department of Environmental Science, Baylor University, Waco, TX, USA","active":true,"usgs":false}],"preferred":false,"id":717482,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bowerman, William W.","contributorId":198870,"corporation":false,"usgs":false,"family":"Bowerman","given":"William","email":"","middleInitial":"W.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":717483,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193930,"text":"70193930 - 2018 - Riparian bird density decline in response to biocontrol of Tamarix from riparian ecosystems along the Dolores River in SW Colorado, USA","interactions":[],"lastModifiedDate":"2021-08-12T14:50:01.696431","indexId":"70193930","displayToPublicDate":"2017-11-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Riparian bird density decline in response to biocontrol of Tamarix from riparian ecosystems along the Dolores River in SW Colorado, USA","title":"Riparian bird density decline in response to biocontrol of Tamarix from riparian ecosystems along the Dolores River in SW Colorado, USA","docAbstract":"Biocontrol of invasive tamarisk (Tamarix spp.) in the arid Southwest using the introduced tamarisk beetle (Diorhabda elongata) has been hypothesized to negatively affect some breeding bird species, but no studies to date have documented the effects of beetle-induced defoliation on riparian bird abundance. We assessed the effects of tamarisk defoliation by monitoring defoliation rates, changes in vegetation composition, and changes in density of six obligate riparian breeding bird species at two sites along the Dolores River in Colorado following the arrival of tamarisk beetles. We conducted bird point counts from 2010 to 2014 and modeled bird density as a function of native vegetation density and extent of defoliation using hierarchical distance sampling. Maximum annual defoliation decreased throughout the study period, peaking at 32–37% in 2009–2010 and dropping to 0.5–15% from 2011–2014. Stem density of both tamarisk and native plants declined throughout the study period until 2014. Density of all bird species declined throughout most of the study, with Song Sparrow disappearing from the study sites after 2011. Blue Grosbeak, Yellow-breasted Chat, and Yellow Warbler densities were negatively related to defoliation in the previous year, while Lazuli Bunting exhibited a positive relationship with defoliation. These findings corroborate earlier predictions of species expected to be sensitive to defoliation as a result of nest site selection. Tamarisk defoliation thus had short-term negative impacts on riparian bird species; active restoration may be needed to encourage the regrowth of native riparian vegetation, which in the longer-term may result in increased riparian bird density.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-017-1569-z","usgsCitation":"Darrah, A., and van Riper, C., 2018, Riparian bird density decline in response to biocontrol of Tamarix from riparian ecosystems along the Dolores River in SW Colorado, USA: Biological Invasions, v. 20, no. 3, p. 709-720, https://doi.org/10.1007/s10530-017-1569-z.","productDescription":"12 p.","startPage":"709","endPage":"720","ipdsId":"IP-074375","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":348552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Dolores River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.02145385742188,\n 37.85425428219824\n ],\n [\n -108.775634765625,\n 37.85425428219824\n ],\n [\n -108.775634765625,\n 38.26136726838286\n ],\n [\n -109.02145385742188,\n 38.26136726838286\n ],\n [\n -109.02145385742188,\n 37.85425428219824\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-12","publicationStatus":"PW","scienceBaseUri":"5a06c8bee4b09af898c860a9","contributors":{"authors":[{"text":"Darrah, Abigail J.","contributorId":187674,"corporation":false,"usgs":false,"family":"Darrah","given":"Abigail J.","affiliations":[{"id":35720,"text":"Audubon Mississippi, Coastal Bird Stewardship ProgramMoss PointUSA","active":true,"usgs":false},{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":721498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":721497,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198748,"text":"70198748 - 2018 - Fish Bioenergetics 4.0: An R-based modeling application","interactions":[],"lastModifiedDate":"2018-08-20T09:30:02","indexId":"70198748","displayToPublicDate":"2017-11-08T09:29:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Fish Bioenergetics 4.0: An R-based modeling application","docAbstract":"Bioenergetics modeling is a widely used tool in fisheries management and research. Although popular, currently available software (i.e., Fish Bioenergetics 3.0) has not been updated in over 20 years and is incompatible with newer operating systems (i.e., 64‐bit). Moreover, since the release of Fish Bioenergetics 3.0 in 1997, the number of published bioenergetics models has increased appreciably from 56 to 105 models representing 73 species. In this article, we provide an overview of Fish Bioenergetics 4.0 (FB4), a newly developed modeling application that consists of a graphical user interface (Shiny by RStudio) combined with a modeling package used in the R computing environment. While including the same capabilities as previous versions, Fish Bioenergetics 4.0 allows for timely updates and bug fixes and can be continuously improved based on feedback from users. In addition, users can add new or modified parameter sets for additional species and formulate and incorporate modifications such as habitat‐dependent functions (e.g., dissolved oxygen, salinity) that are not part of the default package. We hope that advances in the new modeling platform will attract a broad range of users while facilitating continued application of bioenergetics modeling to a wide spectrum of questions in fish biology, ecology, and management.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/03632415.2017.1377558","usgsCitation":"Deslauriers, D., Chipps, S.R., Breck, J.E., Rice, J., and Madenjian, C.P., 2018, Fish Bioenergetics 4.0: An R-based modeling application: Fisheries Magazine, v. 42, no. 11, p. 586-596, https://doi.org/10.1080/03632415.2017.1377558.","productDescription":"11 p.","startPage":"586","endPage":"596","ipdsId":"IP-088650","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488352,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/141352","text":"External Repository"},{"id":356613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"5b98a327e4b0702d0e843034","contributors":{"authors":[{"text":"Deslauriers, David","contributorId":187586,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","email":"","affiliations":[],"preferred":false,"id":743033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":742842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breck, James E.","contributorId":171518,"corporation":false,"usgs":false,"family":"Breck","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":743034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, James A.","contributorId":176863,"corporation":false,"usgs":false,"family":"Rice","given":"James A.","affiliations":[],"preferred":false,"id":743035,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":742843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192784,"text":"70192784 - 2018 - Evaluating trade-offs in bull trout reintroduction strategies using structured decision making","interactions":[],"lastModifiedDate":"2018-02-05T15:34:49","indexId":"70192784","displayToPublicDate":"2017-11-08T00:00:00","publicationYear":"2018","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":"Evaluating trade-offs in bull trout reintroduction strategies using structured decision making","docAbstract":"Structured decision making allows reintroduction decisions to be made despite uncertainty by linking reintroduction goals with alternative management actions through predictive models of ecological processes. We developed a decision model to evaluate the trade-offs between six bull trout (Salvelinus confluentus) reintroduction decisions with the goal of maximizing the number of adults in the recipient population without reducing the donor population to an unacceptable level. Sensitivity analyses suggested that the decision identity and outcome were most influenced by survival parameters that result in increased adult abundance in the recipient population, increased juvenile survival in the donor and recipient populations, adult fecundity rates, and sex ratio. The decision was least sensitive to survival parameters associated with the captive-reared population, the effect of naivety on released individuals, and juvenile carrying capacity of the reintroduced population. The model and sensitivity analyses can serve as the foundation for formal adaptive management and improved effectiveness, efficiency, and transparency of bull trout reintroduction decisions.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0516","usgsCitation":"Brignon, W.R., Peterson, J., Dunham, J.B., Schaller, H.A., and Schreck, C.B., 2018, Evaluating trade-offs in bull trout reintroduction strategies using structured decision making: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 2, p. 293-307, https://doi.org/10.1139/cjfas-2016-0516.","productDescription":"15 p.","startPage":"293","endPage":"307","ipdsId":"IP-085432","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0516","text":"External Repository"},{"id":348438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425b1e4b0dc0b45b45308","contributors":{"authors":[{"text":"Brignon, William R.","contributorId":193087,"corporation":false,"usgs":false,"family":"Brignon","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":716925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":716924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaller, Howard A.","contributorId":195101,"corporation":false,"usgs":false,"family":"Schaller","given":"Howard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716923,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192927,"text":"70192927 - 2018 - Wanted dead or alive: A state-space mark-recapture-recovery model incorporating multiple recovery types and state uncertainty","interactions":[],"lastModifiedDate":"2018-07-03T11:42:11","indexId":"70192927","displayToPublicDate":"2017-11-07T00:00:00","publicationYear":"2018","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":"Wanted dead or alive: A state-space mark-recapture-recovery model incorporating multiple recovery types and state uncertainty","docAbstract":"We developed a state-space mark-recapture-recovery model that incorporates multiple recovery types and state uncertainty to estimate survival of an anadromous fish species. We apply the model to a dataset of out-migrating juvenile steelhead trout (Oncorhynchus mykiss) tagged with passive integrated transponders, recaptured during outmigration, and recovered on bird colonies in the Columbia River basin (2008-2014). Recoveries on bird colonies are often ignored in survival studies because the river reach of mortality is often unknown, which we model as a form of state uncertainty. Median outmigration survival from release to the lower river (river kilometer 729 to 75) ranged from 0.27 to 0.35, depending on year. Recovery probabilities were frequently >0.20 in the first river reach following tagging, indicating that one out of five fish that died in that reach was recovered on a bird colony. Integrating dead recovery data provided increased parameter precision, estimation of where birds consumed fish, and survival estimates across larger spatial scales. More generally, these modeling approaches provide a flexible framework to integrate multiple sources of tag recovery data into mark-recapture studies.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0246","usgsCitation":"Hostetter, N.J., Gardner, B., Evans, A.F., Cramer, B.M., Payton, Q., Collis, K., and Roby, D.D., 2018, Wanted dead or alive: A state-space mark-recapture-recovery model incorporating multiple recovery types and state uncertainty: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 7, p. 1117-1127, https://doi.org/10.1139/cjfas-2016-0246.","productDescription":"11 p.","startPage":"1117","endPage":"1127","ipdsId":"IP-077533","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.354248046875,\n 45.46783598133375\n ],\n [\n -118.8116455078125,\n 45.46783598133375\n ],\n [\n -118.8116455078125,\n 47.468949677672484\n ],\n [\n -124.354248046875,\n 47.468949677672484\n ],\n [\n -124.354248046875,\n 45.46783598133375\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e842e4b09af898c8cb1e","contributors":{"authors":[{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":717365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":720947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Allen F.","contributorId":171691,"corporation":false,"usgs":false,"family":"Evans","given":"Allen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":720948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cramer, Bradley M.","contributorId":171692,"corporation":false,"usgs":false,"family":"Cramer","given":"Bradley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":720949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Payton, Quinn","contributorId":149990,"corporation":false,"usgs":false,"family":"Payton","given":"Quinn","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":720950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collis, Ken","contributorId":149991,"corporation":false,"usgs":false,"family":"Collis","given":"Ken","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":720951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717364,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192871,"text":"70192871 - 2018 - The first hop: Use of Beaufort Sea deltas by hatch-year semipalmated sandpipers","interactions":[],"lastModifiedDate":"2018-01-05T14:13:37","indexId":"70192871","displayToPublicDate":"2017-11-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"The first hop: Use of Beaufort Sea deltas by hatch-year semipalmated sandpipers","docAbstract":"River deltas along Alaska’s Beaufort Sea coast are used by hatch-year semipalmated sandpipers (Calidris pusilla) after leaving their terrestrial natal sites, but the drivers of their use of these stopover sites on the first “hop” of fall migration are unknown. We quantified sandpiper temporal distribution and abundance as related to food resources at three river deltas during the beginning of their fall migration (post-breeding period) to compare the habitat quality among these deltas. We conducted population counts, sampled invertebrates, and captured birds to collect blood samples from individuals for triglyceride and stable isotope analyses to determine fattening rates and diet. Patterns of sandpiper and invertebrate abundance were complex and varied among deltas and within seasons. River deltas were used by sandpipers from late July to late August, and peak sandpiper counts ranged from 1000 to 4000 individuals, of which 98% were hatch-year semipalmated sandpipers. Isotopic signatures from blood plasma samples indicated that birds switched from a diet of upland tundra to delta invertebrate taxa as the migration season progressed, suggesting a dependence on delta invertebrates. Despite differences in diet among deltas, we found no differences in fattening rates of juvenile sandpipers as indicated by triglyceride levels. The number of sandpipers was positively associated with abundance of Amphipoda and Oligochaeta at the Jago and Okpilak-Hulahula deltas; an isotopic mixing model indicated that sandpipers consumed Amphipoda and Oligochaeta at Jago, mostly Chironomidae at Okpilak-Hulahula and Spionidae at Canning. Regardless of the difference in sandpiper diets at the Beaufort Sea deltas, their similar fattening rates throughout the season indicate that all of these stopover sites provide a critical food resource for hatch-year sandpipers beginning their first migration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0272-8","usgsCitation":"Churchwell, R.T., Kendall, S.J., Brown, S.C., Blanchard, A.L., Hollmen, T.E., and Powell, A., 2018, The first hop: Use of Beaufort Sea deltas by hatch-year semipalmated sandpipers: Estuaries and Coasts, v. 41, no. 1, p. 280-292, https://doi.org/10.1007/s12237-017-0272-8.","productDescription":"13 p.","startPage":"280","endPage":"292","ipdsId":"IP-065128","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348404,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -146.865234375,\n 68.34654079146961\n ],\n [\n -141.0205078125,\n 68.34654079146961\n ],\n [\n -141.0205078125,\n 70.34831755984779\n ],\n [\n -146.865234375,\n 70.34831755984779\n ],\n [\n -146.865234375,\n 68.34654079146961\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-15","publicationStatus":"PW","scienceBaseUri":"5a07e844e4b09af898c8cb24","contributors":{"authors":[{"text":"Churchwell, Roy T.","contributorId":171773,"corporation":false,"usgs":false,"family":"Churchwell","given":"Roy","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":720993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, Steve J. 0000-0002-9290-5629","orcid":"https://orcid.org/0000-0002-9290-5629","contributorId":169663,"corporation":false,"usgs":false,"family":"Kendall","given":"Steve","email":"","middleInitial":"J.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":720994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":720995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blanchard, Arny L.","contributorId":173948,"corporation":false,"usgs":false,"family":"Blanchard","given":"Arny","email":"","middleInitial":"L.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":720996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hollmen, Tuula E.","contributorId":106077,"corporation":false,"usgs":true,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":717253,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192975,"text":"70192975 - 2018 - The effectiveness of surrogate taxa to conserve freshwater biodiversity","interactions":[],"lastModifiedDate":"2018-01-05T14:14:42","indexId":"70192975","displayToPublicDate":"2017-11-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"The effectiveness of surrogate taxa to conserve freshwater biodiversity","docAbstract":"Establishing protected areas has long been an effective conservation strategy, and is often based on more readily surveyed species. The potential of any freshwater taxa to be a surrogate of other aquatic groups has not been fully explored. We compiled occurrence data on 72 species of freshwater fish, amphibians, mussels, and aquatic reptiles for the Great Plains, Wyoming. We used hierarchical Bayesian multi-species mixture models and MaxEnt models to describe species distributions, and program Zonation to identify conservation priority areas for each aquatic group. The landscape-scale factors that best characterized aquatic species distributions differed among groups. There was low agreement and congruence among taxa-specific conservation priorities (<20%), meaning that no surrogate priority areas would include or protect the best habitats of other aquatic taxa. We found that common, wide-ranging aquatic species were included in taxa-specific priority areas, but rare freshwater species were not included. Thus, the development of conservation priorities based on a single freshwater aquatic group would not protect all species in the other aquatic groups.
","language":"English","publisher":"Wiley","doi":"10.1111/cobi.12967","usgsCitation":"Stewart, D., Underwood, Z.E., Rahel, F.J., and Walters, A.W., 2018, The effectiveness of surrogate taxa to conserve freshwater biodiversity: Conservation Biology, v. 32, no. 1, p. 183-194, https://doi.org/10.1111/cobi.12967.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-077166","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-14","publicationStatus":"PW","scienceBaseUri":"5a07e841e4b09af898c8cb1c","contributors":{"authors":[{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":720908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Underwood, Zachary E.","contributorId":166946,"corporation":false,"usgs":false,"family":"Underwood","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":717506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193588,"text":"70193588 - 2018 - Linking spring phenology with mechanistic models of host movement to predict disease transmission risk","interactions":[],"lastModifiedDate":"2018-02-14T14:22:11","indexId":"70193588","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2018","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":"Linking spring phenology with mechanistic models of host movement to predict disease transmission risk","docAbstract":"Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission.
Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [Cervus Canadensis] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem.
Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts.
Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands.
Synthesis and applications. Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13022","usgsCitation":"Merkle, J., Cross, P.C., Scurlock, B.M., Cole, E., Courtemanch, A.B., Dewey, S., and Kauffman, M., 2018, Linking spring phenology with mechanistic models of host movement to predict disease transmission risk: Journal of Applied Ecology, v. 55, no. 2, p. 810-819, https://doi.org/10.1111/1365-2664.13022.","productDescription":"10 p.","startPage":"810","endPage":"819","ipdsId":"IP-079776","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":469167,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13022","text":"Publisher Index Page"},{"id":438078,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7474803","text":"USGS data release","linkHelpText":"Elk movement and predicted number of brucellosis-induced abortion events in the southern Greater Yellowstone Ecosystem (1993-2015)"},{"id":348261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-19","publicationStatus":"PW","scienceBaseUri":"5a07e848e4b09af898c8cb32","contributors":{"authors":[{"text":"Merkle, Jerod","contributorId":172972,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","affiliations":[{"id":35288,"text":"Wyoming Cooperative Fish and Wildlife Research Unit, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":719500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":719499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":719501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Eric K. 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":145755,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":719503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Courtemanch, Alyson B.","contributorId":198651,"corporation":false,"usgs":false,"family":"Courtemanch","given":"Alyson","email":"","middleInitial":"B.","affiliations":[{"id":35682,"text":"Wyoming Game and Fish Department, Jackson, WY","active":true,"usgs":false}],"preferred":false,"id":719504,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dewey, Sarah","contributorId":145757,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":16229,"text":"National Park Service, Grand Teton National Park, PO Drawer 170, Moose, WY 83012 USA","active":true,"usgs":false}],"preferred":false,"id":719505,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":719502,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193860,"text":"70193860 - 2018 - Quantifying changes and influences on mottled duck density in Texas","interactions":[],"lastModifiedDate":"2018-01-24T15:46:56","indexId":"70193860","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying changes and influences on mottled duck density in Texas","docAbstract":"Understanding the relative influence of environmental and intrinsic effects on populations is important for managing and conserving harvested species, especially those species inhabiting changing environments. Additionally, climate change can increase the uncertainty associated with management of species in these changing environments, making understanding factors affecting their populations even more important. Coastal ecosystems are particularly threatened by climate change; the combined effects of increasing severe weather events, sea level rise, and drought will likely have non-linear effects on coastal marsh wildlife species and their associated habitats. A species of conservation concern that persists in these coastal areas is the mottled duck (Anas fulvigula). Mottled ducks in the western Gulf Coast are approximately 50% below target abundance numbers established by the Gulf Coast Joint Venture for Texas and Louisiana, USA. Although evidence for declines in mottled duck abundance is apparent, specific causes of the decrease remain unknown. Our goals were to determine where the largest declines in mottled duck population were occurring along the system of Texas Gulf Coast National Wildlife Refuges and quantify the relative contribution of environmental and intrinsic effects on changes to relative population density. We modeled aerial survey data of mottled duck density along the Texas Gulf Coast from 1986–2015 to quantify effects of extreme weather events on an index to mottled duck density using the United States Climate Extremes Index and Palmer Drought Severity Index. Our results indicate that decreases in abundance are best described by an increase in days with extreme 1-day precipitation from June to November (hurricane season) and an increase in drought severity. Better understanding those portions of the life cycle affected by environmental conditions, and how to manage mottled duck habitat in conjunction with these events will likely be key to persistence of the species under future environmental conditions.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21373","usgsCitation":"Ross, B., Haukos, D.A., and Walther, P., 2018, Quantifying changes and influences on mottled duck density in Texas: Journal of Wildlife Management, v. 82, p. 374-382, https://doi.org/10.1002/jwmg.21373.","productDescription":"9 p.","startPage":"374","endPage":"382","ipdsId":"IP-083236","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.00878906249999,\n 25.898761936567023\n ],\n [\n -93.482666015625,\n 25.898761936567023\n ],\n [\n -93.482666015625,\n 30.41078179084589\n ],\n [\n -99.00878906249999,\n 30.41078179084589\n ],\n [\n -99.00878906249999,\n 25.898761936567023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-25","publicationStatus":"PW","scienceBaseUri":"5a07e845e4b09af898c8cb26","contributors":{"authors":[{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720704,"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":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":720705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walther, Patrick","contributorId":42153,"corporation":false,"usgs":true,"family":"Walther","given":"Patrick","affiliations":[],"preferred":false,"id":720750,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193574,"text":"70193574 - 2018 - Discrete choice modeling of season choice for Minnesota turkey hunters","interactions":[],"lastModifiedDate":"2018-01-24T15:49:03","indexId":"70193574","displayToPublicDate":"2017-11-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Discrete choice modeling of season choice for Minnesota turkey hunters","docAbstract":"Recreational turkey hunting exemplifies the interdisciplinary nature of modern wildlife management. Turkey populations in Minnesota have reached social or biological carrying capacities in many areas, and changes to turkey hunting regulations have been proposed by stakeholders and wildlife managers. This study employed discrete stated choice modeling to enhance understanding of turkey hunter preferences about regulatory alternatives. We distributed mail surveys to 2,500 resident turkey hunters. Results suggest that, compared to season structure and lotteries, additional permits and level of potential interference from other hunters most influenced hunter preferences for regulatory alternatives. Low hunter interference was preferred to moderate or high interference. A second permit issued only to unsuccessful hunters was preferred to no second permit or permits for all hunters. Results suggest that utility is not strictly defined by harvest or an individual's material gain but can involve preference for other outcomes that on the surface do not materially benefit an individual. Discrete stated choice modeling offers wildlife managers an effective way to assess constituent preferences related to new regulations before implementing them.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21382","usgsCitation":"Schroeder, S., Fulton, D.C., Cornicelli, L., and Merchant, S., 2018, Discrete choice modeling of season choice for Minnesota turkey hunters: Journal of Wildlife Management, v. 82, p. 457-465, https://doi.org/10.1002/jwmg.21382.","productDescription":"9 p.","startPage":"457","endPage":"465","ipdsId":"IP-081175","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70193694,"text":"70193694 - 2018 - Lack of observed movement response to lead exposure of California condors","interactions":[],"lastModifiedDate":"2018-01-24T15:49:57","indexId":"70193694","displayToPublicDate":"2017-11-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Lack of observed movement response to lead exposure of California condors","docAbstract":"Lead poisoning is an important conservation concern for wildlife, and scavenging birds are especially at risk from consumption of carcasses of animals killed with lead ammunition. Because current methods to identify lead exposure require animal capture and blood collection, management would benefit from the development of a less costly and noninvasive behavioral test for illness in wild animals. We attempted to design such a test to identify lead exposure in California condors (Gymnogyps californianus) that we tracked with global positioning system (GPS) telemetry in southern California, USA, 2013–2016. We measured blood-lead concentrations in tracked birds and expected that flight behavior would be influenced by lead exposure; thus, we measured the effect of blood-lead concentrations on 2 different types of movement rates and on the proportion of time condors spent in flight. We found no effect of lead exposure on any of these 3 behavioral metrics. Our work suggests that the measurements we took of flight behaviors were not a useful tool in predicting lead exposure in the mildly to moderately exposed birds we studied. Wild birds are effective at hiding illness, especially condors who have a strong social hierarchy in which showing weakness is a disadvantage. However, focusing on behaviors other than flight, expanding the sample studied to include birds with a wider range of lead concentration values, or analyzing tissues such as feathers (rather than, or in addition to, blood) may be more useful for identification of lead exposure and other diseases that may limit wildlife populations. © 2017 This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21378","usgsCitation":"Poessel, S.A., Brandt, J., Uyeda, L., Astell, M., and Katzner, T., 2018, Lack of observed movement response to lead exposure of California condors: Journal of Wildlife Management, v. 82, p. 310-318, https://doi.org/10.1002/jwmg.21378.","productDescription":"9 p.","startPage":"310","endPage":"318","ipdsId":"IP-088092","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":348204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"82","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5a00314de4b0531197b5a73a","contributors":{"authors":[{"text":"Poessel, Sharon A. 0000-0002-0283-627X spoessel@usgs.gov","orcid":"https://orcid.org/0000-0002-0283-627X","contributorId":168465,"corporation":false,"usgs":true,"family":"Poessel","given":"Sharon","email":"spoessel@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":719938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Joseph","contributorId":127742,"corporation":false,"usgs":false,"family":"Brandt","given":"Joseph","affiliations":[{"id":7133,"text":"California Condor Recovery Program, US Fish and Wildlife Service, Ventura, CA","active":true,"usgs":false}],"preferred":false,"id":719940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uyeda, Linda","contributorId":199752,"corporation":false,"usgs":false,"family":"Uyeda","given":"Linda","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":719941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Astell, Molly","contributorId":199753,"corporation":false,"usgs":false,"family":"Astell","given":"Molly","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":719942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":719939,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192806,"text":"70192806 - 2018 - Tracing biogeochemical subsidies from glacier runoff into Alaska's coastal marine food webs","interactions":[],"lastModifiedDate":"2018-01-05T14:17:02","indexId":"70192806","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Tracing biogeochemical subsidies from glacier runoff into Alaska's coastal marine food webs","docAbstract":"Nearly half of the freshwater discharge into the Gulf of Alaska originates from landscapes draining glacier runoff, but the influence of the influx of riverine organic matter on the trophodynamics of coastal marine food webs is not well understood. We quantified the ecological impact of riverine organic matter subsidies to glacier-marine habitats by developing a multi-trophic level Bayesian three-isotope mixing model. We utilized large gradients in stable (δ13C, δ15N, δ2H) and radiogenic (Δ14C) isotopes that trace riverine and marine organic matter sources as they are passed from lower to higher trophic levels in glacial-marine habitats. We also compared isotope ratios between glacial-marine and more oceanic habitats. Based on isotopic measurements of potential baseline sources, ambient water and tissues of marine consumers, estimates of the riverine organic matter source contribution to upper trophic-level species including fish and seabirds ranged from 12% to 44%. Variability in resource use among similar taxa corresponded to variation in species distribution and life histories. For example, riverine organic matter assimilation by the glacier-nesting seabirds Kittlitz's murrelet (Brachyramphus brevirostris) was greater than that of the forest-nesting marbled murrelet (B. marmoratus). The particulate and dissolved organic carbon in glacial runoff and near surface coastal waters was aged (12100–1500 years BP 14C-age) but dissolved inorganic carbon and biota in coastal waters were young (530 years BP 14C-age to modern). Thus terrestrial-derived subsidies in marine food webs were primarily composed of young organic matter sources released from glacier ecosystems and their surrounding watersheds. Stable isotope compositions also revealed a divergence in food web structure between glacial-marine and oceanic sites. This work demonstrates linkages between terrestrial and marine ecosystems, and facilitates a greater understanding of how climate-driven changes in freshwater runoff have the potential to alter food web dynamics within coastal marine ecosystems in Alaska.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13875","usgsCitation":"Arimitsu, M.L., Hobson, K.A., Webber, D.N., Piatt, J.F., Hood, E.W., and Fellman, J.B., 2018, Tracing biogeochemical subsidies from glacier runoff into Alaska's coastal marine food webs: Global Change Biology, v. 24, no. 1, p. 387-398, https://doi.org/10.1111/gcb.13875.","productDescription":"12 p.","startPage":"387","endPage":"398","ipdsId":"IP-085458","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":469172,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/59558","text":"External Repository"},{"id":438079,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z036D9","text":"USGS data release","linkHelpText":"Biogeochemical Subsidies from Glacier Runoff into Alaska Coastal Marine Food Webs, Gulf of Alaska, 2012-2013"},{"id":348063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.95263671875,\n 59.6954703349364\n ],\n [\n -145.283203125,\n 59.6954703349364\n ],\n [\n -145.283203125,\n 61.62206526043813\n ],\n [\n -148.95263671875,\n 61.62206526043813\n ],\n [\n -148.95263671875,\n 59.6954703349364\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-23","publicationStatus":"PW","scienceBaseUri":"59fadd1fe4b0531197b13c6f","contributors":{"authors":[{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":717011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hobson, Keith A.","contributorId":190909,"corporation":false,"usgs":false,"family":"Hobson","given":"Keith","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":717012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webber, D’Arcy N.","contributorId":198740,"corporation":false,"usgs":false,"family":"Webber","given":"D’Arcy","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":717013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hood, Eran W.","contributorId":198165,"corporation":false,"usgs":false,"family":"Hood","given":"Eran","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":717015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fellman, Jason B.","contributorId":198741,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":717016,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192606,"text":"70192606 - 2018 - Small-scale genetic structure in an endangered wetland specialist: possible effects of landscape change and population recovery","interactions":[],"lastModifiedDate":"2018-01-24T15:50:38","indexId":"70192606","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Small-scale genetic structure in an endangered wetland specialist: possible effects of landscape change and population recovery","docAbstract":"The effects of anthropogenic landscape change on genetic population structure are well studied, but the temporal and spatial scales at which genetic structure can develop, especially in taxa with high dispersal capabilities like birds, are less well understood. We investigated population structure in the Hawaiian gallinule (Gallinula galeata sandvicensis), an endangered wetland specialist bird on the island of O`ahu (Hawai`i, USA). Hawaiian gallinules have experienced a gradual population recovery from near extinction in the 1950s, and have recolonized wetlands on O`ahu in the context of a rapidly urbanizing landscape. We genotyped 152 Hawaiian gallinules at 12 microsatellite loci and sequenced a 520 base-pair fragment of the ND2 region of mitochondrial DNA (mtDNA) from individuals captured at 13 wetland locations on O`ahu in 2014–2016. We observed moderate to high genetic structuring (overall microsatellite FST = 0.098, mtDNA FST = 0.248) among populations of Hawaiian gallinules occupying wetlands at very close geographic proximity (e.g., 1.5–55 km). Asymmetry in gene flow estimates suggests that Hawaiian gallinules may have persisted in 2–3 strongholds which served as source populations that recolonized more recently restored habitats currently supporting large numbers of birds. Our results highlight that genetic structure can develop in taxa that are expanding their range after severe population decline, and that biologically significant structuring can occur over small geographic distances, even in avian taxa.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-017-1020-0","usgsCitation":"van Rees, C.B., Reed, J.M., Wilson, R.E., Underwood, J., and Sonsthagen, S.A., 2018, Small-scale genetic structure in an endangered wetland specialist: possible effects of landscape change and population recovery: Conservation Genetics, v. 19, no. 1, p. 129-142, https://doi.org/10.1007/s10592-017-1020-0.","productDescription":"14 p.","startPage":"129","endPage":"142","ipdsId":"IP-086333","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":348064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.35968017578125,\n 21.21642046916312\n ],\n [\n -157.60574340820312,\n 21.21642046916312\n ],\n [\n -157.60574340820312,\n 21.749295836732088\n ],\n [\n -158.35968017578125,\n 21.749295836732088\n ],\n [\n -158.35968017578125,\n 21.21642046916312\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-24","publicationStatus":"PW","scienceBaseUri":"59fadd1fe4b0531197b13c72","contributors":{"authors":[{"text":"van Rees, Charles B.","contributorId":198604,"corporation":false,"usgs":false,"family":"van Rees","given":"Charles","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":716535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, J. Michael","contributorId":198605,"corporation":false,"usgs":false,"family":"Reed","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":716536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":716537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Underwood, Jared G.","contributorId":139332,"corporation":false,"usgs":false,"family":"Underwood","given":"Jared G.","affiliations":[],"preferred":false,"id":716538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":716534,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70194480,"text":"70194480 - 2018 - Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change","interactions":[],"lastModifiedDate":"2017-11-29T12:39:47","indexId":"70194480","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change","docAbstract":"Climate-change driven increases in water temperature pose challenges for aquatic organisms. Predictions of impacts typically do not account for fine-grained spatiotemporal thermal patterns in rivers. Patches of cooler water could serve as refuges for anadromous species like salmon that migrate during summer. We used high-resolution remotely sensed water temperature data to characterize summer thermal heterogeneity patterns for 11,308 km of second–seventh-order rivers throughout the Pacific Northwest and northern California (USA). We evaluated (1) water temperature patterns at different spatial resolutions, (2) the frequency, size, and spacing of cool thermal patches suitable for Pacific salmon (i.e., contiguous stretches ≥ 0.25 km, ≤ 15 °C and ≥ 2 °C, aooler than adjacent water), and (3) potential influences of climate change on availability of cool patches. Thermal heterogeneity was nonlinearly related to the spatial resolution of water temperature data, and heterogeneity at fine resolution (< 1 km) would have been difficult to quantify without spatially continuous data. Cool patches were generally > 2.7 and < 13.0 km long, and spacing among patches was generally > 5.7 and < 49.4 km. Thermal heterogeneity varied among rivers, some of which had long uninterrupted stretches of warm water ≥ 20 °C, and others had many smaller cool patches. Our models predicted little change in future thermal heterogeneity among rivers, but within-river patterns sometimes changed markedly compared to contemporary patterns. These results can inform long-term monitoring programs as well as near-term climate-adaptation strategies.
","language":"English","publisher":"Springer","doi":"10.1007/s00027-017-0557-9","usgsCitation":"Fullerton, A., Torgersen, C.E., Lawer, J., Steel, E.A., Ebersole, J.L., and Lee, S., 2018, Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change: Aquatic Sciences, v. 80, https://doi.org/10.1007/s00027-017-0557-9.","productDescription":"Article 3; 15p.","startPage":"15","ipdsId":"IP-090182","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":469171,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5854952","text":"External Repository"},{"id":349527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 39\n ],\n [\n -112.763671875,\n 39\n ],\n [\n -112.763671875,\n 49.081062364320736\n ],\n [\n -124.71679687499999,\n 49.081062364320736\n ],\n [\n -124.71679687499999,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","edition":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-21","publicationStatus":"PW","scienceBaseUri":"5a60fad8e4b06e28e9c227d5","contributors":{"authors":[{"text":"Fullerton, A.H.","contributorId":200991,"corporation":false,"usgs":false,"family":"Fullerton","given":"A.H.","email":"","affiliations":[],"preferred":false,"id":724027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":724026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawer, J.J.","contributorId":200992,"corporation":false,"usgs":false,"family":"Lawer","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":724028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steel, E. A.","contributorId":200993,"corporation":false,"usgs":false,"family":"Steel","given":"E.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":724029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebersole, J. L.","contributorId":74221,"corporation":false,"usgs":false,"family":"Ebersole","given":"J.","email":"","middleInitial":"L.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":724030,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, S.Y.","contributorId":200994,"corporation":false,"usgs":false,"family":"Lee","given":"S.Y.","email":"","affiliations":[],"preferred":false,"id":724031,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192464,"text":"70192464 - 2018 - Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA","interactions":[],"lastModifiedDate":"2017-10-31T14:33:38","indexId":"70192464","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA","docAbstract":"Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2017.09.028","usgsCitation":"DeLong, S.B., Youberg, A.M., DeLong, W.M., and Murphy, B.P., 2018, Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA: Geomorphology, v. 300, p. 13-30, https://doi.org/10.1016/j.geomorph.2017.09.028.","productDescription":"18 p.","startPage":"13","endPage":"30","ipdsId":"IP-070321","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469173,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2017.09.028","text":"Publisher Index Page"},{"id":347894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Chiricahua Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.2833,\n 31.9\n ],\n [\n -109.2667,\n 31.9\n ],\n [\n -109.2667,\n 31.9167\n ],\n [\n -109.2833,\n 31.9167\n ],\n [\n -109.2833,\n 31.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"300","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98ba2e4b0531197af9f84","contributors":{"authors":[{"text":"DeLong, Stephen B. 0000-0002-0945-2172 sdelong@usgs.gov","orcid":"https://orcid.org/0000-0002-0945-2172","contributorId":5240,"corporation":false,"usgs":true,"family":"DeLong","given":"Stephen","email":"sdelong@usgs.gov","middleInitial":"B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":715980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Youberg, Ann M. 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172609,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":true,"id":715981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLong, Whitney M.","contributorId":198416,"corporation":false,"usgs":false,"family":"DeLong","given":"Whitney","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":715982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Brendan P.","contributorId":198417,"corporation":false,"usgs":false,"family":"Murphy","given":"Brendan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":715983,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193072,"text":"70193072 - 2018 - Greater sage-grouse population trends across Wyoming","interactions":[],"lastModifiedDate":"2018-01-24T15:51:33","indexId":"70193072","displayToPublicDate":"2017-10-31T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Greater sage-grouse population trends across Wyoming","docAbstract":"The scale at which analyses are performed can have an effect on model results and often one scale does not accurately describe the ecological phenomena of interest (e.g., population trends) for wide-ranging species: yet, most ecological studies are performed at a single, arbitrary scale. To best determine local and regional trends for greater sage-grouse (Centrocercus urophasianus) in Wyoming, USA, we modeled density-independent and -dependent population growth across multiple spatial scales relevant to management and conservation (Core Areas [habitat encompassing approximately 83% of the sage-grouse population on ∼24% of surface area in Wyoming], local Working Groups [7 regional areas for which groups of local experts are tasked with implementing Wyoming's statewide sage-grouse conservation plan at the local level], Core Area status (Core Area vs. Non-Core Area) by Working Groups, and Core Areas by Working Groups). Our goal was to determine the influence of fine-scale population trends (Core Areas) on larger-scale populations (Working Group Areas). We modeled the natural log of change in population size (![\"math](\"http://onlinelibrary.wiley.com/store/10.1002/jwmg.21386/asset/equation/jwmg21386-math-0001.png?v=1&s=2556af55897eeca9ae5982921cf5b63fdff4c53d\")
peak M lek counts) by time to calculate the finite rate of population growth (λ) for each population of interest from 1993 to 2015. We found that in general when Core Area status (Core Area vs. Non-Core Area) was investigated by Working Group Area, the 2 populations trended similarly and agreed with the overall trend of the Working Group Area. However, at the finer scale where Core Areas were analyzed separately, Core Areas within the same Working Group Area often trended differently and a few large Core Areas could influence the overall Working Group Area trend and mask trends occurring in smaller Core Areas. Relatively close fine-scale populations of sage-grouse can trend differently, indicating that large-scale trends may not accurately depict what is occurring across the landscape (e.g., local effects of gas and oil fields may be masked by increasing larger populations).
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.21386","usgsCitation":"Edmunds, D.R., Aldridge, C.L., O’Donnell, M.S., and Monroe, A., 2018, Greater sage-grouse population trends across Wyoming: Journal of Wildlife Management, v. 82, p. 397-412, https://doi.org/10.1002/jwmg.21386.","productDescription":"16 p.","startPage":"397","endPage":"412","ipdsId":"IP-087426","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21386","text":"Publisher Index Page"},{"id":347946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"82","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-27","publicationStatus":"PW","scienceBaseUri":"59f98bb0e4b0531197af9fcf","contributors":{"authors":[{"text":"Edmunds, David R. 0000-0002-5212-8271 dedmunds@usgs.gov","orcid":"https://orcid.org/0000-0002-5212-8271","contributorId":152210,"corporation":false,"usgs":true,"family":"Edmunds","given":"David","email":"dedmunds@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":717821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science 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,{"id":70192852,"text":"70192852 - 2018 - Historical cover trends in a sagebrush steppe ecosystem from 1985 to 2013: Links with climate, disturbance, and management","interactions":[],"lastModifiedDate":"2018-08-10T13:45:32","indexId":"70192852","displayToPublicDate":"2017-10-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Historical cover trends in a sagebrush steppe ecosystem from 1985 to 2013: Links with climate, disturbance, and management","docAbstract":"Understanding the causes and consequences of component change in sagebrush steppe is crucial for evaluating ecosystem sustainability. The sagebrush (Artemisia spp.) steppe ecosystem of the northwest USA has been impacted by the invasion of exotic grasses, increasing fire return intervals, changing land management practices, and fragmentation, often lowering the overall resilience to change. We utilized contemporary and historical Landsat imagery, field data, and regression tree models to produce fractional cover maps of rangeland components (shrub, sagebrush, herbaceous, bare ground, and litter) through the last 30 years. Our main goals were to (1) investigate rangeland component trends over 30 years, (2) evaluate the magnitude and direction of trends in components and climate drivers and their relationship, and (3) assess component trends influenced by climate. Results indicated that over the study period, shrub, sage, herbaceous, and litter cover decreased, while bare ground cover increased. Measured rates of change ranged from − 0.14% decade−1 for shrub cover to 0.05% decade−1 for bare ground, whereas herbaceous and litter cover trends were negligible. Net landscape cover changes were consistent with expectations of climate change and disturbance producing a loss of biotic cover, and converting a portion of shrub and sagebrush to herbaceous cover. Overall, fire and related successional recovery was the greatest change agent for all components in terms of area and cover change, while increasing minimum temperature, at a rate of 0.66°C decade−1, was found to be the most significant climate driver.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-017-0191-3","usgsCitation":"Shi, H., Rigge, M.B., Homer, C.G., Xian, G.Z., Meyer, D., and Bunde, B., 2018, Historical cover trends in a sagebrush steppe ecosystem from 1985 to 2013: Links with climate, disturbance, and management: Ecosystems, v. 21, no. 5, p. 913-929, https://doi.org/10.1007/s10021-017-0191-3.","productDescription":"17 p.","startPage":"913","endPage":"929","ipdsId":"IP-079676","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.1904296875,\n 40.97575093157534\n ],\n [\n -118.16894531249999,\n 40.97575093157534\n ],\n [\n -118.16894531249999,\n 42.7349091465156\n ],\n [\n -120.1904296875,\n 42.7349091465156\n ],\n [\n -120.1904296875,\n 40.97575093157534\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-24","publicationStatus":"PW","scienceBaseUri":"59f83a2de4b063d5d309808a","contributors":{"authors":[{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Debbie 0000-0002-8841-697X debbie.meyer.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":192361,"corporation":false,"usgs":true,"family":"Meyer","given":"Debbie","email":"debbie.meyer.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bunde, Brett 0000-0003-0228-779X brett.bunde.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-0228-779X","contributorId":198821,"corporation":false,"usgs":true,"family":"Bunde","given":"Brett","email":"brett.bunde.ctr@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717213,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191451,"text":"fs20173069 - 2018 - Everglades Depth Estimation Network (EDEN)—A decade of serving hydrologic information to scientists and resource managers","interactions":[],"lastModifiedDate":"2021-10-26T16:14:19.190775","indexId":"fs20173069","displayToPublicDate":"2017-10-30T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3069","title":"Everglades Depth Estimation Network (EDEN)—A decade of serving hydrologic information to scientists and resource managers","docAbstract":"Introduction
The Everglades Depth Estimation Network (EDEN) provides scientists and resource managers with regional maps of daily water levels and depths in the freshwater part of the Greater Everglades landscape. The EDEN domain includes all or parts of five Water Conservation Areas, Big Cypress National Preserve, Pennsuco Wetlands, and Everglades National Park. Daily water-level maps are interpolated from water-level data at monitoring gages, and depth is estimated by using a digital elevation model of the land surface. Online datasets provide time series of daily water levels at gages and rainfall and evapotranspiration data (https://sofia.usgs.gov/eden/). These datasets are used by scientists and resource managers to guide large-scale field operations, describe hydrologic changes, and support biological and ecological assessments that measure ecosystem response to the implementation of the Comprehensive Everglades Restoration Plan. EDEN water-level data have been used in a variety of biological and ecological studies including (1) the health of American alligators as a function of water depth, (2) the variability of post-fire landscape dynamics in relation to water depth, (3) the habitat quality for wading birds with dynamic habitat selection, and (4) an evaluation of the habitat of the Cape Sable seaside sparrow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173069","collaboration":"Prepared as part of the U.S. Geological Survey Greater Everglades Priority Ecosystems Science and in collaboration with the
U.S. Army Corps of Engineers as part of the Comprehensive Everglades Restoration Plan REstoration COordination and VERification (RECOVER) Program","usgsCitation":"Patino, Eduardo, Conrads, Paul, Swain, Eric, and Beerens, James, 2018, Everglades Depth Estimation Network (EDEN)—A decade of serving hydrologic information to scientists and resource managers (ver. 1.1, January 2018): U.S. Geological Survey Fact Sheet 2017–3069, 6 p., https://doi.org/10.3133/fs20173069.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-071266","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":347419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3069/fs20173069.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3069"},{"id":347418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3069/coverthb1.jpg"},{"id":350307,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2017/3069/versionHist.txt","size":"1 MB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.29083251953124,\n 26.684275490019488\n ],\n [\n -80.45013427734375,\n 26.686729520004036\n ],\n [\n -80.56549072265625,\n 26.350036674507894\n ],\n [\n -81.68609619140624,\n 26.33280692289788\n ],\n [\n -81.70257568359375,\n 26.143110637100634\n ],\n [\n -81.91955566406249,\n 26.06418490332395\n ],\n [\n -81.134033203125,\n 25.008461758688334\n ],\n [\n -80.41168212890625,\n 25.17760219565174\n ],\n [\n -80.49407958984375,\n 25.693513062561056\n ],\n [\n -80.35400390625,\n 26.115985925333536\n ],\n [\n -80.2935791015625,\n 26.185018250078308\n ],\n [\n -80.233154296875,\n 26.362342068998764\n ],\n [\n -80.2056884765625,\n 26.524650377182763\n ],\n [\n -80.29083251953124,\n 26.684275490019488\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 30, 2017; Version 1.1","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
","tableOfContents":"- Introduction
- EDEN Water-Level Model
- EDEN Web Applications
- Looking Forward to the Next Decade
- References
- Special Acknowledgment
","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2017-10-30","revisedDate":"2018-01-05","noUsgsAuthors":false,"publicationDate":"2017-10-30","publicationStatus":"PW","scienceBaseUri":"59f83a30e4b063d5d30980ab","contributors":{"authors":[{"text":"Patino, Eduardo 0000-0003-1016-3658 epatino@usgs.gov","orcid":"https://orcid.org/0000-0003-1016-3658","contributorId":1743,"corporation":false,"usgs":true,"family":"Patino","given":"Eduardo","email":"epatino@usgs.gov","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":712329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":712331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":725420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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