{"pageNumber":"343","pageRowStart":"8550","pageSize":"25","recordCount":40794,"records":[{"id":70201782,"text":"70201782 - 2019 - The missing dead: The lost role of animal remains in nutrient cycling in North American Rivers","interactions":[],"lastModifiedDate":"2019-01-30T13:57:15","indexId":"70201782","displayToPublicDate":"2019-01-30T13:57:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5453,"text":"Food Webs","active":true,"publicationSubtype":{"id":10}},"title":"The missing dead: The lost role of animal remains in nutrient cycling in North American Rivers","docAbstract":"<p><span>While&nbsp;leaf litter, wood, and other plant remnants are known to play a central role in lotic ecosystems, animal remains (carcasses, bones, shells) have received less attention. We propose a simple classification scheme for animal remains in rivers based on origin (authochthonous vs. allochthonous) and frequency (pulsed vs continuous). We then present case studies in which we estimate the former&nbsp;</span>biomass<span>&nbsp;of several taxonomic groups that are now diminished in abundance to determine whether their remains could have historically constituted a significant flux of nutrients in rivers of North America. We focus on bones and shells, which decompose slowly and could provide long-term reservoirs of nutrients. We find that carcasses of&nbsp;alligator snapping turtles, once abundant in southeastern rivers, could have provided an amount of phosphorus equivalent to about 1% of total phosphorus (TP) load at median flow, and more at low flows.&nbsp;Mussel&nbsp;shells could have contributed a similar amount (0.8% of TP) but the contribution of beaver carcasses, even at former abundances, was likely small. In contrast, a single documented mass drowning of&nbsp;bison&nbsp;in the Assiniboine River could have contributed half the annual TP load for that river. Such drownings could have been a common occurrence prior to the loss of most wild terrestrial megafauna in North America. We conclude that animal remnants, particularly allochthonous remains from terrestrial animals, formerly played a substantial role in nutrient cycling. Existing models of ecosystem function under reference conditions are incomplete without consideration of these lost animal legacies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fooweb.2018.e00106","usgsCitation":"Wenger, S., Subalusky, A.L., and Freeman, M., 2019, The missing dead: The lost role of animal remains in nutrient cycling in North American Rivers: Food Webs, v. 18, p. 1-6, https://doi.org/10.1016/j.fooweb.2018.e00106.","productDescription":"article e00106; 6 p.","startPage":"1","endPage":"6","ipdsId":"IP-101338","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fooweb.2018.e00106","text":"Publisher Index Page"},{"id":360823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":755366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Subalusky, Amanda L.","contributorId":211950,"corporation":false,"usgs":false,"family":"Subalusky","given":"Amanda","email":"","middleInitial":"L.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":755367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228077,"text":"70228077 - 2019 - Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution","interactions":[],"lastModifiedDate":"2022-02-03T14:30:04.950797","indexId":"70228077","displayToPublicDate":"2019-01-30T08:16:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution","docAbstract":"Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red-eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated-detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit only improved insignificantly when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red-eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. Our results estimating a weak correlation between vital rates and temporal changes in covariates indicate that we have yet to identify the most relevant components of global change changing the distributions of these species and, more significantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.","language":"English","doi":"10.1002/ece3.4890","usgsCitation":"Clement, M., Nichols, J., Collazo, J.A., Terando, A., Hines, J.E., and Williams, S.G., 2019, Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution: Ecology and Evolution, v. 9, no. 4, p. 1985-2003, https://doi.org/10.1002/ece3.4890.","productDescription":"19 p.","startPage":"1985","endPage":"2003","ipdsId":"IP-097244","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":467961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4890","text":"Publisher Index Page"},{"id":395341,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Clement, Matthew J. 0000-0003-4231-7949","orcid":"https://orcid.org/0000-0003-4231-7949","contributorId":274483,"corporation":false,"usgs":false,"family":"Clement","given":"Matthew J.","affiliations":[{"id":54519,"text":"U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":833022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols, James D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":264235,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":833023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terando, Adam 0000-0002-9280-043X","orcid":"https://orcid.org/0000-0002-9280-043X","contributorId":205908,"corporation":false,"usgs":true,"family":"Terando","given":"Adam","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":833025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":833026,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Steven G. 0000-0003-3760-6818","orcid":"https://orcid.org/0000-0003-3760-6818","contributorId":215501,"corporation":false,"usgs":false,"family":"Williams","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":39268,"text":"North Carolina State University, NC Cooperative Fish & Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":833027,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70201773,"text":"70201773 - 2019 - Linking the agricultural landscape of the Midwest to stream health with structural equation modeling","interactions":[],"lastModifiedDate":"2019-01-29T14:36:01","indexId":"70201773","displayToPublicDate":"2019-01-29T14:35:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Linking the agricultural landscape of the Midwest to stream health with structural equation modeling","docAbstract":"<p><span>Multiple physical and chemical stressors can simultaneously affect the biological condition of streams. To better understand the complex interactions of land-use practices, water quality, and ecological integrity of streams, the U.S. Geological Survey National Water Quality Assessment Project is conducting regional-scale assessments of stream condition across the United States. In the summer of 2013, weekly water samples were collected from 100 streams in the Midwestern United States. Employing watershed theory, we used structural equation modeling (SEM) to represent a general hypothesis for how 16 variables (previously identified to be important to stream condition) might be inter-related. Again, using SEM, we evaluated the ability of this “stressor network” to explain variations in multimetrics of algal, invertebrate, and fish community health, trimming away any environmental variables not contributing to an explanation of the ecological responses. Seven environmental variables—agricultural and urban land use, sand content of soils, basin area, percent riparian area as forest, channel erosion, and relative bed stability—were found to be important for all three-community metrics. The algal and invertebrate models included water-chemistry variables not included in the fish model. Results suggest that ecological integrity of Midwest streams are affected by both agricultural and urban land uses and by the natural geologic setting, as indicated by the sand content of soils. Chemicals related to crops (pesticides and nutrients) and residential uses (pyrethroids) were found to be more strongly related to ecological integrity than were natural factors (riparian forest, watershed soil character).</span></p>","language":"English","publisher":"ACS","doi":"10.1021/acs.est.8b04381","usgsCitation":"Schmidt, T., Van Metre, P.C., and Carlisle, D.M., 2019, Linking the agricultural landscape of the Midwest to stream health with structural equation modeling: Environmental Science & Technology, v. 53, no. 1, p. 452-462, https://doi.org/10.1021/acs.est.8b04381.","productDescription":"11 p.","startPage":"452","endPage":"462","ipdsId":"IP-099323","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.8b04381","text":"Publisher Index Page"},{"id":360798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":755306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":755307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":755308,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70201776,"text":"70201776 - 2019 - Hydrogen isotopes in high 3He/4He submarine basalts: Primordial vs. recycled water and the veil of mantle enrichment","interactions":[],"lastModifiedDate":"2019-01-29T14:28:46","indexId":"70201776","displayToPublicDate":"2019-01-29T14:28:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hydrogen isotopes in high <sup>3</sup>He/<sup>4</sup>He submarine basalts: Primordial vs. recycled water and the veil of mantle enrichment","title":"Hydrogen isotopes in high 3He/4He submarine basalts: Primordial vs. recycled water and the veil of mantle enrichment","docAbstract":"<p><span>The&nbsp;hydrogen isotope&nbsp;value (</span><i>δ</i><span>D) of water indigenous to the mantle is masked by the early degassing and&nbsp;recycling&nbsp;of surface water through Earth's history. High&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He ratios in some&nbsp;ocean island basalts, however, provide a clear geochemical signature of deep, primordial mantle that has been isolated within the Earth's interior from melting, degassing, and convective mixing with the&nbsp;upper mantle. Hydrogen isotopes were measured in high&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He submarine&nbsp;basalt&nbsp;glasses from the Southeast Indian Ridge (SEIR) at the Amsterdam–St. Paul (ASP) Plateau (</span><i>δ</i><span>D = −51 to −90‰,&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He = 7.6 to 14.1 R</span><sub>A</sub><span>) and in submarine glasses from Loihi&nbsp;seamount&nbsp;south of the island of Hawaii (</span><i>δ</i><span>D = −70 to −90‰,&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He = 22.5 to 27.8 R</span><sub>A</sub><span>). These results highlight two contrasting patterns of&nbsp;</span><i>δ</i><span>D for high&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He lavas: one trend toward high&nbsp;</span><i>δ</i><span>D of approximately −50‰, and another converging at&nbsp;</span><i>δ</i><span>D = −75‰. These same patterns are evident in a global compilation of previously reported&nbsp;</span><i>δ</i><span>D and&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He results. We suggest that the high&nbsp;</span><i>δ</i><span>D values result from water recycled during&nbsp;subduction&nbsp;that is carried into the source region of&nbsp;mantle plumes&nbsp;at the core–mantle boundary where it is mixed with primordial mantle, resulting in high&nbsp;</span><i>δ</i><span>D and moderately high&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He. Conversely, lower&nbsp;</span><i>δ</i><span>D values of −75‰, in basalts from Loihi seamount and also&nbsp;trace element&nbsp;depleted mid-ocean ridge basalts, imply a primordial Earth hydrogen isotopic value of −75‰ or lower.&nbsp;</span><i>δ</i><span>D values down to −100‰ also occur in the most trace element-depleted mid-ocean ridge basalts, typically in association with&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr ratios near 0.703. These lower&nbsp;</span><i>δ</i><span>D values may be a result of multi-stage melting history of the upper mantle where minor D/H&nbsp;fractionation&nbsp;could be associated with hydrogen retention in nominally anhydrous residual minerals. Collectively, the predominance of&nbsp;</span><i>δ</i><span>D around −75‰ in the majority of mid-ocean ridge basalts and in high&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He Loihi basalts is consistent with an origin of water on Earth that was dominated by&nbsp;accretion&nbsp;of chondritic material.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.12.012","usgsCitation":"Loewen, M., Graham, D.W., Bindeman, I.N., Lupton, J.E., and Garcia, M.O., 2019, Hydrogen isotopes in high 3He/4He submarine basalts: Primordial vs. recycled water and the veil of mantle enrichment: Earth and Planetary Science Letters, v. 508, p. 62-73, https://doi.org/10.1016/j.epsl.2018.12.012.","productDescription":"12 p.","startPage":"62","endPage":"73","ipdsId":"IP-098999","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467966,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2018.12.012","text":"Publisher Index Page"},{"id":360796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"508","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Loewen, Matthew W.","contributorId":168854,"corporation":false,"usgs":false,"family":"Loewen","given":"Matthew W.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":755301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, David W.","contributorId":167398,"corporation":false,"usgs":false,"family":"Graham","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":755302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":755303,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lupton, John E.","contributorId":211938,"corporation":false,"usgs":false,"family":"Lupton","given":"John","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":755304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garcia, Michael O.","contributorId":51636,"corporation":false,"usgs":true,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":755305,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201752,"text":"70201752 - 2019 - Compounding effects of climate change reduce population viability of a montane amphibian","interactions":[],"lastModifiedDate":"2019-03-04T11:15:22","indexId":"70201752","displayToPublicDate":"2019-01-29T13:58:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Compounding effects of climate change reduce population viability of a montane amphibian","docAbstract":"<p><span>Anthropogenic climate change presents challenges and opportunities to the growth, reproduction, and survival of individuals throughout their life cycles. Demographic compensation among life‐history stages has the potential to buffer populations from decline, but alternatively, compounding negative effects can lead to accelerated population decline and extinction. In montane ecosystems of the U.S. Pacific Northwest, increasing temperatures are resulting in a transition from snow‐dominated to rain‐dominated precipitation events, reducing snowpack. For ectotherms such as amphibians, warmer winters can reduce the frequency of critical minimum temperatures and increase the length of summer growing seasons, benefiting post‐metamorphic stages, but may also increase metabolic costs during winter months, which could decrease survival. Lower snowpack levels also result in wetlands that dry sooner or more frequently in the summer, increasing larval desiccation risk. To evaluate how these challenges and opportunities compound within a species’ life history, we collected demographic data on Cascades frog (</span><i>Rana cascadae</i><span>) in Olympic National Park in Washington state to parameterize stage‐based stochastic matrix population models under current and future (A1B, 2040s, and 2080s) environmental conditions. We estimated the proportion of reproductive effort lost each year due to drying using watershed‐specific hydrologic models, and coupled this with an analysis that relates 15 yr of&nbsp;</span><i>R.&nbsp;cascadae</i><span>&nbsp;abundance data with a suite of climate variables. We estimated the current population growth (λ</span><sub>s</sub><span>) to be 0.97 (95% CI 0.84–1.13), but predict that λ</span><sub>s</sub><span>&nbsp;will decline under continued climate warming, resulting in a 62% chance of extinction by the 2080s because of compounding negative effects on early and late life history stages. By the 2080s, our models predict that larval mortality will increase by 17% as a result of increased pond drying, and adult survival will decrease by 7% as winter length and summer precipitation continue to decrease. We find that reduced larval survival drives initial declines in the 2040s, but further declines in the 2080s are compounded by decreases in adult survival. Our results demonstrate the need to understand the potential for compounding or compensatory effects within different life history stages to exacerbate or buffer the effects of climate change on population growth rates through time.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1832","usgsCitation":"Kissel, A.M., Palen, W.J., Ryan, M.E., and Adams, M.J., 2019, Compounding effects of climate change reduce population viability of a montane amphibian: Ecological Applications, v. 29, no. 2, p. 1-12, https://doi.org/10.1002/eap.1832.","productDescription":"e01832; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-092187","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":360793,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda M.","contributorId":211917,"corporation":false,"usgs":false,"family":"Kissel","given":"Amanda","email":"","middleInitial":"M.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":755199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palen, Wendy J.","contributorId":211918,"corporation":false,"usgs":false,"family":"Palen","given":"Wendy","email":"","middleInitial":"J.","affiliations":[{"id":36678,"text":"Simon Fraser University","active":true,"usgs":false}],"preferred":false,"id":755200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Maureen E.","contributorId":208314,"corporation":false,"usgs":false,"family":"Ryan","given":"Maureen","email":"","middleInitial":"E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":755201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":755198,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70215867,"text":"70215867 - 2019 - Iterative models for early detection of invasive species across spread pathways","interactions":[],"lastModifiedDate":"2020-11-02T13:00:31.325277","indexId":"70215867","displayToPublicDate":"2019-01-29T12:10:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Iterative models for early detection of invasive species across spread pathways","docAbstract":"<p><span>Species distribution models can be used to direct early detection of invasive species, if they include proxies for invasion pathways. Due to the dynamic nature of invasion, these models violate assumptions of stationarity across space and time. To compensate for issues of stationarity, we iteratively update regionalized species distribution models annually for European gypsy moth (</span><span class=\"html-italic\">Lymantria dispar dispar</span><span>) to target early detection surveys for the USDA APHIS gypsy moth program. We defined regions based on the distances from the invasion spread front where shifts in variable importance occurred and included models for the non-quarantine portion of the state of Maine, a short-range region, an intermediate region, and a long-range region. We considered variables that represented potential gypsy moth movement pathways within each region, including transportation networks, recreational activities, urban characteristics, and household movement data originating from gypsy moth infested areas (U.S. Postal Service address forwarding data). We updated the models annually, linked the models to an early detection survey design, and validated the models for the following year using predicted risk at new positive detection locations. Human-assisted pathways data, such as address forwarding, became increasingly important predictors of gypsy moth detection in the intermediate-range geographic model as more predictor data accumulated over time (relative importance = 5.9%, 17.36%, and 35.76% for 2015, 2016, and 2018, respectively). Receiver operating curves showed increasing performance for iterative annual models (area under the curve (AUC) = 0.63, 0.76, and 0.84 for 2014, 2015, and 2016 models, respectively), and boxplots of predicted risk each year showed increasing accuracy and precision of following year positive detection locations. The inclusion of human-assisted pathway predictors combined with the strategy of iterative modeling brings significant advantages to targeting early detection of invasive species. We present the first published example of iterative species distribution modeling for invasive species in an operational context.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/f10020108","usgsCitation":"Cook, G., Jarnevich, C.S., Warden, M., Downing, M., Withrow, J., and Leinwand, I., 2019, Iterative models for early detection of invasive species across spread pathways: Forests, v. 10, no. 2, 108, 21 p., https://doi.org/10.3390/f10020108.","productDescription":"108, 21 p.","ipdsId":"IP-013042","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f10020108","text":"Publisher Index Page"},{"id":379981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Minnesota, Wisconsin, Illinois, Indiana, Ohio, West Virginia, Virginia, Pennsylvania, Delaware, Maryland, New Jersey, Connecticut, Rhode Island, Massachusetts, Maine, New Hampshire, Vermont, New York","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.59277343749999,\n              46.6795944656402\n            ],\n            [\n              -93.779296875,\n              45.49094569262732\n            ],\n            [\n              -91.7578125,\n              43.197167282501276\n            ],\n            [\n              -88.9013671875,\n              41.73852846935917\n            ],\n            [\n              -86.5283203125,\n              39.90973623453719\n            ],\n            [\n              -82.8369140625,\n              39.67337039176558\n            ],\n            [\n              -80.8154296875,\n              37.33522435930639\n            ],\n            [\n              -77.51953125,\n              37.26530995561875\n            ],\n            [\n              -76.0693359375,\n              36.63316209558658\n            ],\n            [\n              -67.1044921875,\n              44.809121700077355\n            ],\n            [\n              -67.763671875,\n              45.767522962149876\n            ],\n            [\n              -68.02734375,\n              47.368594345213374\n            ],\n            [\n              -69.12597656249999,\n              47.45780853075031\n            ],\n            [\n              -71.3232421875,\n              45.336701909968134\n            ],\n            [\n              -75.1025390625,\n              44.96479793033101\n            ],\n            [\n              -76.5966796875,\n              43.99281450048989\n            ],\n            [\n              -79.1015625,\n              43.16512263158296\n            ],\n            [\n              -81.5185546875,\n              41.60722821271717\n            ],\n            [\n              -82.96875,\n              42.16340342422401\n            ],\n            [\n              -82.2216796875,\n              43.54854811091286\n            ],\n            [\n              -82.79296874999999,\n              45.55252525134013\n            ],\n            [\n              -84.462890625,\n              46.37725420510028\n            ],\n            [\n              -88.505859375,\n              48.28319289548349\n            ],\n            [\n              -92.59277343749999,\n              46.6795944656402\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Cook, Gericke","contributorId":197522,"corporation":false,"usgs":false,"family":"Cook","given":"Gericke","email":"","affiliations":[],"preferred":false,"id":803599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":803545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warden, Melissa","contributorId":244250,"corporation":false,"usgs":false,"family":"Warden","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":803600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Marla","contributorId":244251,"corporation":false,"usgs":false,"family":"Downing","given":"Marla","email":"","affiliations":[],"preferred":false,"id":803601,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Withrow, John","contributorId":244252,"corporation":false,"usgs":false,"family":"Withrow","given":"John","affiliations":[],"preferred":false,"id":803602,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leinwand, I.","contributorId":70300,"corporation":false,"usgs":true,"family":"Leinwand","given":"I.","affiliations":[],"preferred":false,"id":803603,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237804,"text":"70237804 - 2019 - Size distributions of Arctic waterbodies reveal consistent relations in their statistical moments in space and time","interactions":[],"lastModifiedDate":"2022-10-24T14:56:05.970198","indexId":"70237804","displayToPublicDate":"2019-01-29T09:39:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Size distributions of Arctic waterbodies reveal consistent relations in their statistical moments in space and time","docAbstract":"<p><span>Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (&lt;5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km</span><sup>2</sup><span>&nbsp;(100 m</span><sup>2</sup><span>) to 1 km</span><sup>2</sup><span>. We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (</span><i>R</i><sup>2</sup><span>&nbsp;= 0.97,&nbsp;</span><i>p</i><span>&nbsp;&lt; 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2019.00005","usgsCitation":"Muster, S., Riley, W.J., Roth, K., Langer, M., Cresto Aleina, F., Koven, C.D., Lange, S., Bartsch, A., Grosse, G., Wilson, C.J., Jones, B.M., and Boike, J., 2019, Size distributions of Arctic waterbodies reveal consistent relations in their statistical moments in space and time: Frontiers Earth Science Journal, v. 7, 5,15 p., https://doi.org/10.3389/feart.2019.00005.","productDescription":"5,15 p.","ipdsId":"IP-084407","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":467968,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2019.00005","text":"Publisher Index Page"},{"id":408644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              108.02929484206624,\n              58.497272859032904\n            ],\n            [\n              108.02929484206624,\n              56.16625800333617\n            ],\n            [\n              111.88799714527761,\n              56.16625800333617\n            ],\n            [\n              111.88799714527761,\n              58.497272859032904\n            ],\n            [\n              108.02929484206624,\n              58.497272859032904\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              165,\n              78\n            ],\n            [\n              120,\n              78\n            ],\n            [\n              120,\n              65.49833107237572\n            ],\n            [\n              165,\n              65.49833107237572\n            ],\n            [\n              165,\n              78\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              75,\n              74.73823961066213\n            ],\n            [\n              64,\n              74.73823961066213\n            ],\n            [\n              64,\n              60\n            ],\n            [\n              75,\n              60\n            ],\n            [\n              75,\n              74.73823961066213\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.03449315842829,\n              63.61693192201446\n            ],\n            [\n              -118.20091651300666,\n              63.61693192201446\n            ],\n            [\n              -118.20091651300666,\n              62.07366763085378\n            ],\n            [\n              -113.03449315842829,\n              62.07366763085378\n            ],\n            [\n              -113.03449315842829,\n              63.61693192201446\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -127.82796056158378,\n              71.25879525215814\n            ],\n            [\n              -138.9851564025692,\n              71.25879525215814\n            ],\n            [\n              -138.9851564025692,\n              67.56438558510419\n            ],\n            [\n              -127.82796056158378,\n              67.56438558510419\n            ],\n            [\n              -127.82796056158378,\n              71.25879525215814\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -159.43270869663417,\n              71.53350273958918\n            ],\n            [\n              -159.43270869663417,\n              69.03513268745462\n            ],\n            [\n              -148.96276137401355,\n              69.03513268745462\n            ],\n            [\n              -148.96276137401355,\n              71.53350273958918\n            ],\n            [\n              -159.43270869663417,\n              71.53350273958918\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -166.60838181019525,\n              66.81085427741448\n            ],\n            [\n              -166.60838181019525,\n              65.1283425766598\n            ],\n            [\n              -160.4414549557404,\n              65.1283425766598\n            ],\n            [\n              -160.4414549557404,\n              66.81085427741448\n            ],\n            [\n              -166.60838181019525,\n              66.81085427741448\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.386785751183,\n              61.495175256826315\n            ],\n            [\n              -168.386785751183,\n              59.50507030029536\n            ],\n            [\n              -160.07410536581588,\n              59.50507030029536\n            ],\n            [\n              -160.07410536581588,\n              61.495175256826315\n            ],\n            [\n              -168.386785751183,\n              61.495175256826315\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2019-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Muster, Sina","contributorId":194628,"corporation":false,"usgs":false,"family":"Muster","given":"Sina","email":"","affiliations":[],"preferred":false,"id":855690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riley, William J. 0000-0002-4615-2304","orcid":"https://orcid.org/0000-0002-4615-2304","contributorId":194645,"corporation":false,"usgs":false,"family":"Riley","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":855693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roth, Kurt","contributorId":194629,"corporation":false,"usgs":false,"family":"Roth","given":"Kurt","email":"","affiliations":[],"preferred":false,"id":855691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langer, Moritz","contributorId":194630,"corporation":false,"usgs":false,"family":"Langer","given":"Moritz","email":"","affiliations":[],"preferred":false,"id":855692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cresto Aleina, Fabio","contributorId":194632,"corporation":false,"usgs":false,"family":"Cresto Aleina","given":"Fabio","email":"","affiliations":[],"preferred":false,"id":855694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koven, Charles D.","contributorId":199593,"corporation":false,"usgs":false,"family":"Koven","given":"Charles","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":855695,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lange, Stephan","contributorId":194631,"corporation":false,"usgs":false,"family":"Lange","given":"Stephan","email":"","affiliations":[],"preferred":false,"id":855696,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bartsch, Annett","contributorId":194633,"corporation":false,"usgs":false,"family":"Bartsch","given":"Annett","email":"","affiliations":[],"preferred":false,"id":855697,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":855698,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wilson, C. J.","contributorId":88242,"corporation":false,"usgs":true,"family":"Wilson","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":855699,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":855700,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Boike, Julia","contributorId":194646,"corporation":false,"usgs":false,"family":"Boike","given":"Julia","email":"","affiliations":[],"preferred":false,"id":855701,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70201735,"text":"70201735 - 2019 - Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin","interactions":[],"lastModifiedDate":"2019-01-28T13:30:46","indexId":"70201735","displayToPublicDate":"2019-01-28T13:30:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin","docAbstract":"<p><span>Freshwater biodiversity is declining, despite national and international efforts to manage and protect&nbsp;freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively&nbsp;balance ecological&nbsp;and societal needs. However, this raises the question of how social and ecological objectives can be included in an&nbsp;integrated management&nbsp;plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and&nbsp;ESS&nbsp;supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the&nbsp;Artificial Intelligence&nbsp;for Ecosystem Services (ARIES) platform (with ESS supply defined as&nbsp;</span>carbon storage<span>&nbsp;and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level&nbsp;purchasing power parity&nbsp;(PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requirements for effectively managing a balance between biodiversity and ESS supply and demand in freshwater ecosystems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.11.348","usgsCitation":"Domisch, S., Kakouei, K., Martinez-Lopez, J., Bagstad, K.J., Magrach, A., Balbi, S., Villa, F., Funk, A., Hein, T., Borgwardt, F., Hermoso, V., Jahnig, S.C., and Langhans, S.D., 2019, Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin: Science of the Total Environment, v. 656, p. 797-807, https://doi.org/10.1016/j.scitotenv.2018.11.348.","productDescription":"11 p.","startPage":"797","endPage":"807","ipdsId":"IP-100074","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467973,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.11.348","text":"Publisher Index Page"},{"id":360746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Danube River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              8,\n              42\n            ],\n            [\n              30,\n              42\n            ],\n            [\n              30,\n              50\n            ],\n            [\n              8,\n              50\n            ],\n            [\n              8,\n              42\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"656","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c5022c2e4b0708288f7e7df","contributors":{"authors":[{"text":"Domisch, Sami 0000-0002-8127-9335","orcid":"https://orcid.org/0000-0002-8127-9335","contributorId":211857,"corporation":false,"usgs":false,"family":"Domisch","given":"Sami","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":755078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kakouei, Karan 0000-0001-8665-6841","orcid":"https://orcid.org/0000-0001-8665-6841","contributorId":211859,"corporation":false,"usgs":false,"family":"Kakouei","given":"Karan","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":755080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":755082,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magrach, Ainhoa 0000-0003-2155-7556","orcid":"https://orcid.org/0000-0003-2155-7556","contributorId":208482,"corporation":false,"usgs":false,"family":"Magrach","given":"Ainhoa","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":755083,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":755084,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":755085,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Funk, Andrea","contributorId":210646,"corporation":false,"usgs":false,"family":"Funk","given":"Andrea","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":755086,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hein, Thomas 0000-0002-7767-4607","orcid":"https://orcid.org/0000-0002-7767-4607","contributorId":210649,"corporation":false,"usgs":false,"family":"Hein","given":"Thomas","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":755087,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Borgwardt, Florian","contributorId":210647,"corporation":false,"usgs":false,"family":"Borgwardt","given":"Florian","email":"","affiliations":[{"id":38121,"text":"University of Natural Resources and Life Sciences, Vienna","active":true,"usgs":false}],"preferred":false,"id":755088,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hermoso, Virgilio 0000-0003-3205-5033","orcid":"https://orcid.org/0000-0003-3205-5033","contributorId":211861,"corporation":false,"usgs":false,"family":"Hermoso","given":"Virgilio","email":"","affiliations":[{"id":38333,"text":"Centre Tecnologic Forestal de Catalunya","active":true,"usgs":false}],"preferred":false,"id":755089,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jahnig, Sonja C.","contributorId":211858,"corporation":false,"usgs":false,"family":"Jahnig","given":"Sonja","email":"","middleInitial":"C.","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":755079,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Langhans, Simone D.","contributorId":211860,"corporation":false,"usgs":false,"family":"Langhans","given":"Simone","email":"","middleInitial":"D.","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":755081,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70201738,"text":"70201738 - 2019 - Landscape genetics reveal broad and fine‐scale population structure due to landscape features and climate history in the northern leopard frog (Rana pipiens) in North Dakota","interactions":[],"lastModifiedDate":"2019-02-21T14:45:11","indexId":"70201738","displayToPublicDate":"2019-01-28T13:10:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Landscape genetics reveal broad and fine‐scale population structure due to landscape features and climate history in the northern leopard frog (<i>Rana pipiens</i>) in North Dakota","title":"Landscape genetics reveal broad and fine‐scale population structure due to landscape features and climate history in the northern leopard frog (Rana pipiens) in North Dakota","docAbstract":"<p><span>Prehistoric climate and landscape features play large roles structuring wildlife populations. The amphibians of the northern Great Plains of North America present an opportunity to investigate how these factors affect colonization, migration, and current population genetic structure. This study used 11 microsatellite loci to genotype 1,230 northern leopard frogs (</span><i>Rana pipiens</i><span>) from 41 wetlands (30 samples/wetland) across North Dakota. Genetic structure of the sampled frogs was evaluated using Bayesian and multivariate clustering methods. All analyses produced concordant results, identifying a major east–west split between two&nbsp;</span><i>R. pipiens</i><span>&nbsp;population clusters separated by the Missouri River. Substructuring within the two major identified population clusters was also found. Spatial principal component analysis (sPCA) and variance partitioning analysis identified distance, river basins, and the Missouri River as the most important landscape factors differentiating&nbsp;</span><i>R.&nbsp;pipiens</i><span>&nbsp;populations across the state. Bayesian reconstruction of coalescence times suggested the major east–west split occurred ~13–18&nbsp;kya during a period of glacial retreat in the northern Great Plains and substructuring largely occurred ~5–11&nbsp;kya during a period of extreme drought cycles. A range‐wide species distribution model (SDM) for&nbsp;</span><i>R.&nbsp;pipiens</i><span>&nbsp;was developed and applied to prehistoric climate conditions during the Last Glacial Maximum (21&nbsp;kya) and the mid‐Holocene (6&nbsp;kya) from the CCSM4 climate model to identify potential refugia. The SDM indicated potential refugia existed in South Dakota or further south in Nebraska. The ancestral populations of&nbsp;</span><i>R.&nbsp;pipiens</i><span>&nbsp;in North Dakota may have inhabited these refugia, but more sampling outside the state is needed to reconstruct the route of colonization. Using microsatellite genotype data, this study determined that colonization from glacial refugia, drought dynamics in the northern Great Plains, and major rivers acting as barriers to gene flow were the defining forces shaping the regional population structure of&nbsp;</span><i>R.&nbsp;pipiens</i><span>&nbsp;in North Dakota.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4745","usgsCitation":"Waraniak, J.M., Fisher, J., Purcell, K., Mushet, D.M., and Stockwell, C.A., 2019, Landscape genetics reveal broad and fine‐scale population structure due to landscape features and climate history in the northern leopard frog (Rana pipiens) in North Dakota: Ecology and Evolution, v. 9, no. 3, p. 1041-1060, https://doi.org/10.1002/ece3.4745.","productDescription":"20 p.","startPage":"1041","endPage":"1060","ipdsId":"IP-098834","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467975,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4745","text":"Publisher Index Page"},{"id":360742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"9","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-15","publicationStatus":"PW","scienceBaseUri":"5c5022c2e4b0708288f7e7e7","contributors":{"authors":[{"text":"Waraniak, Justin M.","contributorId":211882,"corporation":false,"usgs":false,"family":"Waraniak","given":"Justin","email":"","middleInitial":"M.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":755121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Justin D. L.","contributorId":211883,"corporation":false,"usgs":false,"family":"Fisher","given":"Justin D. L.","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":755122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Purcell, Kevin","contributorId":211884,"corporation":false,"usgs":false,"family":"Purcell","given":"Kevin","affiliations":[{"id":12471,"text":"North Dakota State University","active":true,"usgs":false}],"preferred":false,"id":755123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":755120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stockwell, Craig A.","contributorId":194252,"corporation":false,"usgs":false,"family":"Stockwell","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":755124,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201716,"text":"70201716 - 2019 - Evidence for interactions among environmental stressors in the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2019-01-28T11:37:28","indexId":"70201716","displayToPublicDate":"2019-01-28T11:37:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for interactions among environmental stressors in the Laurentian Great Lakes","docAbstract":"<p><span>Co-occurrence of environmental stressors is ubiquitous in ecosystems, but cumulative effects are difficult to predict for effective indicator development. Individual stressors can amplify (synergies) or lessen (antagonisms) each other's impacts or have fully independent effects (additive). Here we use the Laurentian Great Lakes, where a multitude of stressors have been studied for decades, as a case study for considering insights from both a systematic literature review and an expert elicitation (or structured expert judgment) to identify stressor interactions. In our literature search for pairs of stressors and interaction-related keywords, relatively few studies (9%, or 6/65) supported additive interactions with independent stressor effects. Instead, both antagonisms (42%, or 27/65) and synergies (49%, or 32/65) were common. We found substantial evidence for interactions of invasive dreissenid mussels with nutrient loading and between pairs of invasive species (predominantly dreissenids × round goby), yet both sets of records included mixtures of synergies and antagonisms. Complete quantification of individual and joint effects of stressors was rare, but effect sizes for dreissenid mussels × nutrient loading supported an antagonism. Our expert elicitation included discussion in focus groups and a follow-up survey. This process highlighted the potential for synergies of nutrient loading with dreissenid mussels and climate change as seen from the literature review. The elicitation also identified additional potential interactions less explored in the literature, particularly synergies of nutrient loading with hypoxia and wetland loss. To stimulate future research, we built a conceptual model describing interactions among dreissenid mussels, climate change, and nutrient loading. Our case study illustrates the value of considering results from both elicitations and systematic reviews to overcome data limitations. The simultaneous occurrence of synergies and antagonisms in a single ecosystem underscores the challenge of predicting the cumulative effects of stressors to guide indicator development and other management and restoration decisions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.01.010","usgsCitation":"Smith, S.D., Bunnell, D.B., Burton, G., Ciborowski, J.J., Davidson, A.D., Dickinson, C.E., Eaton, L.A., Esselman, P.C., Evans, M.A., Kashian, D.R., Manning, N., McIntyre, P.B., Nalepa, T.F., Perez-Fuentetaja, A., Steinman, A.D., Uzarski, D.G., and Allan, J.D., 2019, Evidence for interactions among environmental stressors in the Laurentian Great Lakes: Ecological Indicators, v. 101, p. 203-211, https://doi.org/10.1016/j.ecolind.2019.01.010.","productDescription":"9 p.","startPage":"203","endPage":"211","ipdsId":"IP-093690","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":360726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Laurentian Great Lakes","volume":"101","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c5022c3e4b0708288f7e7ee","contributors":{"authors":[{"text":"Smith, Sigrid D. P.","contributorId":211810,"corporation":false,"usgs":false,"family":"Smith","given":"Sigrid","email":"","middleInitial":"D. P.","affiliations":[],"preferred":false,"id":754961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":195888,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","email":"dbunnell@usgs.gov","middleInitial":"B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burton, G.A. Jr.","contributorId":91959,"corporation":false,"usgs":true,"family":"Burton","given":"G.A.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":754962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciborowski, Jan J. H.","contributorId":211812,"corporation":false,"usgs":false,"family":"Ciborowski","given":"Jan","email":"","middleInitial":"J. H.","affiliations":[],"preferred":false,"id":754963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davidson, Alisha D.","contributorId":211813,"corporation":false,"usgs":false,"family":"Davidson","given":"Alisha","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":754964,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dickinson, Caitlin E.","contributorId":211814,"corporation":false,"usgs":false,"family":"Dickinson","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":754965,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eaton, Lauren A.","contributorId":211815,"corporation":false,"usgs":false,"family":"Eaton","given":"Lauren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":754966,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":5965,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754967,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":754968,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kashian, Donna R.","contributorId":205602,"corporation":false,"usgs":false,"family":"Kashian","given":"Donna","email":"","middleInitial":"R.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":754969,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Manning, Nathan F.","contributorId":211818,"corporation":false,"usgs":false,"family":"Manning","given":"Nathan F.","affiliations":[],"preferred":false,"id":754970,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McIntyre, Peter B.","contributorId":166828,"corporation":false,"usgs":false,"family":"McIntyre","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":24540,"text":"Center for Limnology, University of Wisconsin, Madison, Wisconsin, 53706, USA.","active":true,"usgs":false}],"preferred":false,"id":754971,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nalepa, Thomas F.","contributorId":211819,"corporation":false,"usgs":false,"family":"Nalepa","given":"Thomas","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":754972,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perez-Fuentetaja, Alicia","contributorId":211820,"corporation":false,"usgs":false,"family":"Perez-Fuentetaja","given":"Alicia","email":"","affiliations":[],"preferred":false,"id":754973,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Steinman, Alan D.","contributorId":190417,"corporation":false,"usgs":false,"family":"Steinman","given":"Alan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":754974,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Uzarski, Donald G.","contributorId":211821,"corporation":false,"usgs":false,"family":"Uzarski","given":"Donald","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":754975,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Allan, J. David","contributorId":211822,"corporation":false,"usgs":false,"family":"Allan","given":"J.","email":"","middleInitial":"David","affiliations":[],"preferred":false,"id":754976,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70201717,"text":"70201717 - 2019 - Paleocene–Eocene Thermal Maximum prolonged by fossil carbon oxidation","interactions":[],"lastModifiedDate":"2019-01-28T11:33:31","indexId":"70201717","displayToPublicDate":"2019-01-28T11:33:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Paleocene–Eocene Thermal Maximum prolonged by fossil carbon oxidation","docAbstract":"<p><span>A hallmark of the rapid and massive release of carbon during the Palaeocene–Eocene Thermal Maximum is the global negative carbon isotope excursion. The delayed recovery of the carbon isotope excursion, however, indicates that CO</span><sub>2</sub><span>&nbsp;inputs continued well after the initial rapid onset, although there is no consensus about the source of this secondary carbon. Here we suggest this secondary input might have derived partly from the oxidation of remobilized sedimentary fossil carbon. We measured the biomarker indicators of thermal maturation in shelf records from the US Mid-Atlantic coast, constructed biomarker mixing models to constrain the amount of fossil carbon in US Mid-Atlantic and Tanzania coastal records, estimated the fossil carbon accumulation rate in coastal sediments and determined the range of global CO</span><sub>2</sub><span>&nbsp;release from fossil carbon reservoirs. This work provides evidence for an order of magnitude increase in fossil carbon delivery to the oceans that began ~10–20 kyr after the event onset and demonstrates that the oxidation of remobilized fossil carbon released between 10</span><sup>2</sup><span>&nbsp;and 10</span><sup>4</sup><span>&nbsp;PgC as CO</span><sub>2</sub><span>&nbsp;during the body of the Palaeocene–Eocene Thermal Maximum. The estimated mass is sufficient to have sustained the elevated atmospheric CO</span><sub>2</sub><span>&nbsp;levels required by the prolonged global carbon isotope excursion. Even after considering uncertainties in the sedimentation rates, these results indicate that the enhanced erosion, mobilization and oxidation of ancient sedimentary carbon contributed to the delayed recovery of the climate system for many thousands of years.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41561-018-0277-3","usgsCitation":"Lyons, S.L., Baczynski, A.A., Babila, T.L., Bralower, T.J., Hajek, E.A., Kump, L.R., Polites, E.G., Self-Trail, J., Trampush, S.M., Vornlocher, J.R., Zachos, J.C., and Freeman, K.H., 2019, Paleocene–Eocene Thermal Maximum prolonged by fossil carbon oxidation: Nature Geoscience, v. 12, p. 54-60, https://doi.org/10.1038/s41561-018-0277-3.","productDescription":"7 p.","startPage":"54","endPage":"60","ipdsId":"IP-099139","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":360725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-20","publicationStatus":"PW","scienceBaseUri":"5c5022c3e4b0708288f7e7f2","contributors":{"authors":[{"text":"Lyons, Shelby L.","contributorId":211823,"corporation":false,"usgs":false,"family":"Lyons","given":"Shelby","email":"","middleInitial":"L.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baczynski, Allison A.","contributorId":211824,"corporation":false,"usgs":false,"family":"Baczynski","given":"Allison","email":"","middleInitial":"A.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Babila, Tali L.","contributorId":211825,"corporation":false,"usgs":false,"family":"Babila","given":"Tali","email":"","middleInitial":"L.","affiliations":[{"id":38326,"text":"Earth & Planetary Sciences Department, University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":754979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bralower, Timothy J.","contributorId":211826,"corporation":false,"usgs":false,"family":"Bralower","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hajek, Elizabeth A.","contributorId":195146,"corporation":false,"usgs":false,"family":"Hajek","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":754981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kump, Lee R.","contributorId":195147,"corporation":false,"usgs":false,"family":"Kump","given":"Lee","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":754982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Polites, Ellen G.","contributorId":211827,"corporation":false,"usgs":false,"family":"Polites","given":"Ellen","email":"","middleInitial":"G.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754983,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":754988,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trampush, Sheila M.","contributorId":195148,"corporation":false,"usgs":false,"family":"Trampush","given":"Sheila","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":754984,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vornlocher, Jamie R.","contributorId":211828,"corporation":false,"usgs":false,"family":"Vornlocher","given":"Jamie","email":"","middleInitial":"R.","affiliations":[{"id":38327,"text":"School of Geosciences, University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":754985,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zachos, James C.","contributorId":211829,"corporation":false,"usgs":false,"family":"Zachos","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":38326,"text":"Earth & Planetary Sciences Department, University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":754986,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Freeman, Katherine H.","contributorId":211830,"corporation":false,"usgs":false,"family":"Freeman","given":"Katherine","email":"","middleInitial":"H.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754987,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70203104,"text":"70203104 - 2019 - Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?","interactions":[],"lastModifiedDate":"2023-03-24T16:35:52.034587","indexId":"70203104","displayToPublicDate":"2019-01-23T11:03:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5259,"text":"SOIL","active":true,"publicationSubtype":{"id":10}},"title":"Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?","docAbstract":"Ecosystem shifts related to climate change are anticipated for the next decades to centuries based on a number of conceptual and experimentally derived models of plant structure and function. Belowground, the potential responses of soil systems are less well known. We used geochemical steady state models, soil density fractionation, and soil radiocarbon data to constrain changes in soil carbon based on measurements from detrital (free light), aggregate-bound (occluded) and complexed or chemically bound (mineral associated) carbon pools and for bulk soil. We explored a space-for-time sequence of soils along a cold-to-warm climatic gradient from Alaskan Black Spruce forest soil with permafrost (Gelisols; 50 cm Mean Annual Temperature −1.5 ºC), Alaskan White Spruce forest soil lacking permafrost (Inceptisols; 50 cm MAT +3 ºC ), and Iowa Grassland soil lacking permafrost (Mollisols; 50 cm MAT +9 ºC) developed on similar geologic substrates (wind-blown loess deposits). These temperature ranges were also representative of temperatures at 50 cm soil depth from model output by the Community Land Model for the years 2014, 2100, and 2300 for Interior Alaska. Fitting an exponential equation to depth trends in soil C down to 2 m depths, we found that depth distributions of organic C were related mainly to depths of rooting and changes in bulk density. Using output from the geochemical steady state model, the direction and magnitude of the C loss or gain upon ecosystem shift was dictated by the C stocks of initial and final ecosystems. Radiocarbon measurements specific to each soil fraction (free light, occluded, and mineral associated) allowed us to constrain the timing of the potential loss or gain of C in each fraction driven by climatic shifts. Thawing from the Gelisol to Inceptisol in loess parent materials from present day to year 2100 resulted in small net gains to soil C, reflecting the net balance between loss of detrital and gain into occluded and mineral associated C. Greater warming and shifts from Inceptisol to Mollisol analogous to predicted warming from circa 2100 to 2300 resulted in net C losses from both occluded and mineral associated C, although small gains to the free light C fraction occurred throughout the depth profile. Gains to occluded and mineral associated C post- thaw likely reflect aggregate formation and physical protection of C as well as formation of organo-mineral compounds that accompany microbial processing. Greater warming and shifts from Inceptisol to Mollisol, which are analogous to predicted warming circa 2100 to 2300, resulted in net C losses from both occluded and mineral associated C resulting from enhanced decomposition, small gains to the free light C fraction occurred throughout the transition to Mollisol reflecting deeper rooting of the tallgrass prairie system.","language":"English","publisher":"European Geosciences Union (EGU)","doi":"10.5194/soil-2018-41","usgsCitation":"Harden, J.W., O’Donnell, J., Heckman, K., Sulman, B., Koven, C., Ping, C., and Michaelson, G., 2019, Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?: SOIL, 22 p., https://doi.org/10.5194/soil-2018-41.","productDescription":"22 p.","ipdsId":"IP-103776","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467986,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/soil-2018-41","text":"External Repository"},{"id":363102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":761184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, J.A.","contributorId":214930,"corporation":false,"usgs":false,"family":"O’Donnell","given":"J.A.","email":"","affiliations":[{"id":39140,"text":"Arctic Network, National Park Service, Anchorage, Alaska","active":true,"usgs":false}],"preferred":false,"id":761185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heckman, K.A.","contributorId":197919,"corporation":false,"usgs":false,"family":"Heckman","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":761186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sulman, B.N.","contributorId":214931,"corporation":false,"usgs":false,"family":"Sulman","given":"B.N.","email":"","affiliations":[{"id":37400,"text":"Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee","active":true,"usgs":false}],"preferred":false,"id":761187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koven, C.D.","contributorId":199628,"corporation":false,"usgs":false,"family":"Koven","given":"C.D.","email":"","affiliations":[],"preferred":false,"id":761188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ping, C.L.","contributorId":199629,"corporation":false,"usgs":false,"family":"Ping","given":"C.L.","affiliations":[],"preferred":false,"id":761189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michaelson, G.J.","contributorId":199630,"corporation":false,"usgs":false,"family":"Michaelson","given":"G.J.","email":"","affiliations":[],"preferred":false,"id":761190,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70228344,"text":"70228344 - 2019 - Dynamic wildlife occupancy models using automated acoustic monitoring data","interactions":[],"lastModifiedDate":"2022-02-09T23:22:28.985825","indexId":"70228344","displayToPublicDate":"2019-01-19T17:17:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Dynamic wildlife occupancy models using automated acoustic monitoring data","docAbstract":"Automated acoustic monitoring of wildlife has been used to characterize populations of sound-producing species across large spatial scales. However, false negatives and false positives produced by automated detection systems can compromise the utility of these data for researchers and land managers, particularly for research programs endeavoring to describe colonization and extinction dynamics that inform land use decision-making. To investigate the suitability of automated acoustic monitoring for dynamic occurrence models, we simulated underlying occurrence dynamics, calling patterns, and the automated acoustic detection process for a hypothetical species under a range of scenarios. We investigated an automated species detection aggregation method that considered a suite of options for creating encounter histories. From these encounter histories, we generated parameter estimates and computed bias for occurrence, colonization, and extinction rates using a dynamic occupancy modeling framework that accounts for false positives via small amounts of manual confirmation. We were able to achieve relatively unbiased estimates for all three state parameters under all scenarios, even when the automated detection system was simulated to be poor, given particular encounter history aggregation choices. However, some encounter history aggregation choices resulted in unreliable estimates; we provide caveats for avoiding these scenarios. Given specific choices during the detection aggregation process, automated acoustic monitoring data may provide an effective means for tracking species occurrence, colonization, and extinction patterns through time, with the potential to inform adaptive management at multiple spatial scales.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1854","usgsCitation":"Balantic, C., and Donovan, T.M., 2019, Dynamic wildlife occupancy models using automated acoustic monitoring data: Ecological Applications, v. 29, no. 3, e01854, 14 p., https://doi.org/10.1002/eap.1854.","productDescription":"e01854, 14 p.","ipdsId":"IP-098271","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.1854","text":"Publisher Index Page"},{"id":395749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Balantic, Cathleen","contributorId":275248,"corporation":false,"usgs":false,"family":"Balantic","given":"Cathleen","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":833876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833877,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70223291,"text":"70223291 - 2019 - Does incorporating gear selectivity during macroscale investigations of fish growth reduce size-selective sampling bias in parameter estimates?","interactions":[],"lastModifiedDate":"2021-08-20T13:30:36.240789","indexId":"70223291","displayToPublicDate":"2019-01-19T08:28:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Does incorporating gear selectivity during macroscale investigations of fish growth reduce size-selective sampling bias in parameter estimates?","docAbstract":"<div>Understanding of fish growth, the spatial variability in individual growth, and the potential drivers of such variability is a fundamental component of many ecological investigations. However, sampling gears are always size-selective, and this selectivity can result in biased parameter estimates that can lead to, for example, biased stock assessments that use growth estimates. Using seven flathead catfish (<i>Pylodictis olivaris</i>) populations from across the USA as an example, we investigated to what degree the incorporation of gear selectivity in growth models reduces size-selective bias in the estimation of growth parameters during macroscale investigations of fish growth. We developed a series of simulation scenarios by combining different sampling methods to obtain fish samples and different gear selectivity assumptions to estimate parameters. Results showed that the efficacy of incorporating gear selectivity in growth models to reduce size-selective sampling bias during macroscale investigations depends on multiple factors, including (<i>i</i>) the size distribution of small and large fish in the sample (which is a function of sampling methods), and (<i>ii</i>) consistency of sampling methods across populations. Incorporation of gear selectivity may reduce bias when data are lacking for large fish and when sampling methods are inconsistent across populations. Demographics of the sampled populations and the growth parameter of interest can also affect the utility of directly incorporating gear selectivity into growth models. Because multiple factors can influence the efficacy of incorporating gear selectivity into growth models, the decision to do so likely needs to be made on a case-by-case basis. This study extends the existing gear selectivity research by focusing on macroscale fish growth investigations across multiple populations and provides guidance on how to handle gear selectivity assumptions during such investigations.</div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0355","usgsCitation":"Wagner, T., and Li, Y., 2019, Does incorporating gear selectivity during macroscale investigations of fish growth reduce size-selective sampling bias in parameter estimates?: Canadian Journal Fisheries and Aquatic Sciences, v. 76, no. 11, p. 2089-2101, https://doi.org/10.1139/cjfas-2018-0355.","productDescription":"13 p.","startPage":"2089","endPage":"2101","ipdsId":"IP-101549","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":501103,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/96174","text":"External Repository"},{"id":388227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":821626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Yan","contributorId":264515,"corporation":false,"usgs":false,"family":"Li","given":"Yan","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":821627,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70203034,"text":"70203034 - 2019 - Biological and mineralogical controls over cycling of low molecular weight organic compounds along a soil chronosequence","interactions":[],"lastModifiedDate":"2019-04-15T09:53:29","indexId":"70203034","displayToPublicDate":"2019-01-18T09:51:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3416,"text":"Soil Biology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Biological and mineralogical controls over cycling of low molecular weight organic compounds along a soil chronosequence","docAbstract":"Low molecular weight organic compounds (LMWOC) represent a small but critical component of soil organic matter (SOM) for microbial growth and metabolism. The fate of these compounds is largely under microbial control, yet outside the cell, intrinsic soil properties can also significantly influence their turnover and retention. Using a chronosequence representing 1200 ka of pedogenic development, we compared physicochemical vs biological controls on the turnover and retention of fast-cycling carbon (C), e.g. glucose (GLU) and p-hydroxybenzoic acid (PHBA). Along the chronosequence, we observed mineralogical gradients whereby amorphous constituents were greatest in intermediate-aged sites, while older sites demonstrated soils with more ordered and less reactive mineralogy. Soil microbial community composition varied along the soil chronosequence and we observed reductions in total biomass and fungal biomass from younger to older sites, but this did not affect the turnover of LMWOC. Microbial utilization of LMWOC was substrate- and soil-dependent; amorphous Fe and Al oxides reduced the respiration of PHBA but respiration from glucose remained less affected. Variation in soil mineralogy did not significantly alter recovery of PHBA within microbial biomass or fungal vs. bacterial biomarkers, suggesting that reduced respiration of the phenolic resulted from direct mineral interaction with ionizable functional groups rather than changes to microbial allocation of PHBA. We conclude patterns of soil carbon storage observed across chronosequences are moderated by mineralogical effects on microbial access to LMWOC, independent of variation in microbial community composition.\nKeywords: 13C; Glucose; Microbial biomass C; Organo-mineral interactions; p-Hydroxybenzoic acid; Selective dissolution mineralogical analyses","language":"English","publisher":"Elsevier","doi":"10.1016/j.soilbio.2019.01.013","usgsCitation":"McFarland, J., Waldrop, M.P., Strawn, D., Creamer, C., Lawrence, C.R., and Haw, M., 2019, Biological and mineralogical controls over cycling of low molecular weight organic compounds along a soil chronosequence: Soil Biology and Biochemistry, v. 133, p. 16-27, https://doi.org/10.1016/j.soilbio.2019.01.013.","productDescription":"12 p.","startPage":"16","endPage":"27","ipdsId":"IP-091057","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":460515,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.soilbio.2019.01.013","text":"Publisher Index Page"},{"id":362945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"133","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":760878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":760879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strawn, Daniel 0000-0001-9073-7169","orcid":"https://orcid.org/0000-0001-9073-7169","contributorId":214820,"corporation":false,"usgs":false,"family":"Strawn","given":"Daniel","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":760880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":760881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":760882,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haw, Monica 0000-0001-5847-6448","orcid":"https://orcid.org/0000-0001-5847-6448","contributorId":201931,"corporation":false,"usgs":true,"family":"Haw","given":"Monica","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":760883,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70201727,"text":"70201727 - 2019 - Development of perennial thaw zones in boreal hillslopes enhances potential mobilization of permafrost carbon","interactions":[],"lastModifiedDate":"2019-01-28T14:33:47","indexId":"70201727","displayToPublicDate":"2019-01-17T14:33:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Development of perennial thaw zones in boreal hillslopes enhances potential mobilization of permafrost carbon","docAbstract":"<p><span>Permafrost thaw alters subsurface flow in boreal regions that in turn influences the magnitude, seasonality, and chemical composition of streamflow. Prediction of these changes is challenged by incomplete knowledge of timing, flowpath depth, and amount of groundwater discharge to streams in response to thaw. One important phenomenon that may affect flow and transport through boreal hillslopes is development of lateral perennial thaw zones (PTZs), the existence of which is here supported by geophysical observations and cryohydrogeologic modeling. Model results link thaw to enhanced and seasonally-extended baseflow, which have implications for mobilization of soluble constituents. Results demonstrate the sensitivity of PTZ development to organic layer thickness and near-surface factors that mediate heat exchange at the atmosphere/ground-surface interface. Study findings suggest that PTZs serve as a detectable precursor to accelerated permafrost degradation. This study provides important contextual insight on a fundamental thermo-hydrologic process that can enhance terrestrial-to-aquatic transfer of permafrost carbon, nitrogen, and mercury previously sequestered in thawing watersheds.</span></p>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aaf0cc","usgsCitation":"Walvoord, M.A., Voss, C., Ebel, B., and Minsley, B.J., 2019, Development of perennial thaw zones in boreal hillslopes enhances potential mobilization of permafrost carbon: Environmental Research Letters, v. 14, no. 1, p. 1-11, https://doi.org/10.1088/1748-9326/aaf0cc.","productDescription":"Article 015003; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-098066","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467989,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaf0cc","text":"Publisher Index Page"},{"id":437601,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HWCOBP","text":"USGS data release","linkHelpText":"Model Archive for coupled energy and fluid flow simulations generalized to boreal hillslopes"},{"id":360760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"14","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-17","publicationStatus":"PW","scienceBaseUri":"5c5022c3e4b0708288f7e800","contributors":{"authors":[{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":755034,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70223290,"text":"70223290 - 2019 - Temperature–not flow–predicts native fish reproduction with Implications for climate change","interactions":[],"lastModifiedDate":"2021-08-20T14:10:26.124351","indexId":"70223290","displayToPublicDate":"2019-01-17T09:05:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Temperature–not flow–predicts native fish reproduction with Implications for climate change","docAbstract":"<p><span>Habitat alterations and introduction of nonnative fishes reduced the distributions of the Flannelmouth Sucker&nbsp;</span><i>Catostomus latipinnis</i><span>, Bluehead Sucker&nbsp;</span><i>C. discobolus</i><span>, and Roundtail Chub&nbsp;</span><i>Gila robusta</i><span>&nbsp;to less than 50% of their historical ranges. Climate change models generally predict decreased streamflows and increased water temperatures that may further affect these species. Understanding the effects of flow and water temperature on their life histories should lead to better assessments of climate change impacts on extant populations and more informed management for species conservation. Basinwide larval fish sampling and hatch dates derived from otolith daily increment counts showed that water temperature was the dominant environmental factor cueing reproduction in the upper White River basin, Colorado. Reproduction for all three species began in spring, occurring first at warmer, lower-elevation, downstream locations and progressing upriver to higher elevations as water temperatures increased. Warmer water temperatures in tributaries initiated earlier reproductive activity compared to adjacent cooler main-stem habitat. Presence of larvae in samples and estimated hatch dates demonstrated a distinct, predictable upstream progression of reproduction associated with warming water and clear upstream limits to reproduction for all three species. Larval presence and hatching dates revealed earlier reproductive activity in 2012 than in 2013, driven by lower flow and earlier stream warming. A regression model predicted stream temperature during fish spawning seasons under different climate change scenarios and showed expanded upstream limits of thermally suitable reproductive habitat and earlier reproduction for our study species. The long-term implications of climate change are unknown, but managers should strive to perpetuate the valuable and relatively pristine native fish community in the upper White River drainage as a vestige of those that formerly existed throughout the Colorado River basin.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10151","usgsCitation":"Fraser, G., Bestgen, K., Winkelman, D.L., and Thompson, K.G., 2019, Temperature–not flow–predicts native fish reproduction with Implications for climate change: Transactions of the American Fisheries Society, v. 148, no. 3, p. 509-527, https://doi.org/10.1002/tafs.10151.","productDescription":"19 p.","startPage":"509","endPage":"527","ipdsId":"IP-101495","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467991,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10151","text":"Publisher Index Page"},{"id":388233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"White River headwaters","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.951416015625,\n              39.78532331459258\n            ],\n            [\n              -107.193603515625,\n              39.78532331459258\n            ],\n            [\n              -107.193603515625,\n              40.233411907115055\n            ],\n            [\n              -108.951416015625,\n              40.233411907115055\n            ],\n            [\n              -108.951416015625,\n              39.78532331459258\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"148","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Fraser, Gregory S.","contributorId":264508,"corporation":false,"usgs":false,"family":"Fraser","given":"Gregory S.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":821623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestgen, Kevin R.","contributorId":264509,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin R.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":821624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Kevin G.","contributorId":264512,"corporation":false,"usgs":false,"family":"Thompson","given":"Kevin","email":"","middleInitial":"G.","affiliations":[{"id":54484,"text":"co pw","active":true,"usgs":false}],"preferred":false,"id":821625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70203149,"text":"70203149 - 2019 - Sediment oxygen demand: A review of in situ methods","interactions":[],"lastModifiedDate":"2019-04-24T08:49:15","indexId":"70203149","displayToPublicDate":"2019-01-17T08:47:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Sediment oxygen demand: A review of in situ methods","docAbstract":"<p><span>Sediment oxygen demand (SOD) plays a fundamental role in biological and chemical processes within the benthic layer of a water body. Land use, including agricultural land use, can affect SOD. However, a wide variety of approaches have been used for in situ SOD chamber construction and data collection, and modelers frequently use SOD values from the literature, without consideration of the differences in methods. Here, we review existing literature on SOD chambers (32 papers, 1974–2016), compare the differences between in situ and laboratory methods, evaluate the effects of in situ chamber mixing, and discuss common challenges associated with deployment. A cohesive in situ sealed chamber design for use with a multiparameter water-quality instrument is presented as an effort toward standardizing SOD methodology, an important consideration that may facilitate integration of SOD data sets among multiple research efforts.</span></p>","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2018.06.0251","usgsCitation":"Coenen, E., Christensen, V.G., Bartsch, L., Kreiling, R.M., and Richardson, W.B., 2019, Sediment oxygen demand: A review of in situ methods: Journal of Environmental Quality, v. 48, no. 2, p. 403-411, https://doi.org/10.2134/jeq2018.06.0251.","productDescription":"9 p.","startPage":"403","endPage":"411","ipdsId":"IP-091254","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":363167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coenen, Erin N. 0000-0003-2470-3854","orcid":"https://orcid.org/0000-0003-2470-3854","contributorId":211159,"corporation":false,"usgs":true,"family":"Coenen","given":"Erin N.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartsch, Lynn 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":214995,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201965,"text":"70201965 - 2019 - The 4.2 ka event, ENSO, and coral reef development","interactions":[],"lastModifiedDate":"2019-02-04T16:03:19","indexId":"70201965","displayToPublicDate":"2019-01-16T16:03:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"The 4.2 ka event, ENSO, and coral reef development","docAbstract":"<p><span>Variability of sea-surface temperature related to shifts in the mode of the El Niño–Southern Oscillation (ENSO) has been implicated as a possible forcing mechanism for the global-scale changes in tropical and subtropical precipitation known as the 4.2 ka event. We review records of coral reef development and paleoceanography from the tropical eastern Pacific (TEP) to evaluate the potential impact of the 4.2 ka event on coral reefs. Our goal is to identify the regional climatic and oceanographic drivers of a 2500-year shutdown of vertical reef accretion in the TEP after 4.2 ka. The 2500-year hiatus represents&nbsp;</span><span class=\"inline-formula\">∼40</span><span> % of the Holocene history of reefs in the TEP and appears to have been tied to increased variability of ENSO. When ENSO variability abated approximately 1.7–1.6 ka, coral populations recovered and vertical accretion of reef framework resumed apace. There is some evidence that the 4.2 ka event suppressed coral growth and reef accretion elsewhere in the Pacific Ocean as well. Although the ultimate causality behind the global 4.2 ka event remains elusive, correlations between shifts in ENSO variability and the impacts of the 4.2 ka event suggest that ENSO could have played a role in climatic changes at that time, at least in the tropical and subtropical Pacific. We outline a framework for testing hypotheses of where and under what conditions ENSO may be expected to have impacted coral reef environments around 4.2 ka. Although most studies of the 4.2 ka event have focused on terrestrial environments, we suggest that understanding the event in marine systems may prove to be the key to deciphering its ultimate cause.</span></p>","language":"English","publisher":"EGU","doi":"10.5194/cp-15-105-2019","usgsCitation":"Toth, L., and Aronson, R.B., 2019, The 4.2 ka event, ENSO, and coral reef development: Climate of the Past, v. 15, p. 105-119, https://doi.org/10.5194/cp-15-105-2019.","productDescription":"15 p.","startPage":"105","endPage":"119","ipdsId":"IP-100232","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-15-105-2019","text":"Publisher Index Page"},{"id":360988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":756357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":756358,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215986,"text":"70215986 - 2019 - Fire legacies in eastern ponderosa pine forests","interactions":[],"lastModifiedDate":"2020-11-03T13:59:00.469885","indexId":"70215986","displayToPublicDate":"2019-01-16T07:49:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Fire legacies in eastern ponderosa pine forests","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Disturbance legacies structure communities and ecological memory, but due to increasing changes in disturbance regimes, it is becoming more difficult to characterize disturbance legacies or determine how long they persist. We sought to quantify the characteristics and persistence of material legacies (e.g., biotic residuals of disturbance) that arise from variation in fire severity in an eastern ponderosa pine forest in North America. We compared forest stand structure and understory woody plant and bird community composition and species richness across unburned, low‐, moderate‐, and high‐severity burn patches in a 27‐year‐old mixed‐severity wildfire that had received minimal post‐fire management. We identified distinct tree densities (high: 14.3&nbsp;±&nbsp;7.4 trees per ha, moderate: 22.3&nbsp;±&nbsp;12.6, low: 135.3&nbsp;±&nbsp;57.1, unburned: 907.9&nbsp;±&nbsp;246.2) and coarse woody debris cover (high: 8.5&nbsp;±&nbsp;1.6% cover per 30&nbsp;m transect, moderate: 4.3&nbsp;±&nbsp;0.7, low: 2.3&nbsp;±&nbsp;0.6, unburned: 1.0&nbsp;±&nbsp;0.4) among burn severities. Understory woody plant communities differed between high‐severity patches, moderate‐ and low‐severity patches, and unburned patches (all<span>&nbsp;</span><i>p</i>&nbsp;&lt;&nbsp;0.05). Bird communities differed between high‐ and moderate‐severity patches, low‐severity patches, and unburned patches (all<span>&nbsp;</span><i>p</i>&nbsp;&lt;&nbsp;0.05). Bird species richness varied across burn severities: low‐severity patches had the highest (5.29&nbsp;±&nbsp;1.44) and high‐severity patches had the lowest (2.87&nbsp;±&nbsp;0.72). Understory woody plant richness was highest in unburned (5.93&nbsp;±&nbsp;1.10) and high‐severity (5.07&nbsp;±&nbsp;1.17) patches, and it was lower in moderate‐ (3.43&nbsp;±&nbsp;1.17) and low‐severity (3.43&nbsp;±&nbsp;1.06) patches. We show material fire legacies persisted decades after the mixed‐severity wildfire in eastern ponderosa forest, fostering distinct structures, communities, and species in burned versus unburned patches and across fire severities. At a patch scale, eastern and western ponderosa system responses to mixed‐severity fires were consistent.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4879","usgsCitation":"Roberts, C.P., Donovan, V.M., Wonkka, C., Powell, L., Allen, C.R., Angeler, D., Wedin, D., and Twidwell, D., 2019, Fire legacies in eastern ponderosa pine forests: Ecology and Evolution, v. 9, no. 4, p. 1869-1879, https://doi.org/10.1002/ece3.4879.","productDescription":"11 p.","startPage":"1869","endPage":"1879","ipdsId":"IP-103565","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4879","text":"Publisher Index Page"},{"id":380071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Pine Ridge region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.08447265624999,\n              42.24478535602799\n            ],\n            [\n              -102.41455078125,\n              42.24478535602799\n            ],\n            [\n              -102.41455078125,\n              43.01268088642034\n            ],\n            [\n              -104.08447265624999,\n              43.01268088642034\n            ],\n            [\n              -104.08447265624999,\n              42.24478535602799\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, C. P.","contributorId":189791,"corporation":false,"usgs":false,"family":"Roberts","given":"C.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":803675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donovan, V. M.","contributorId":244281,"corporation":false,"usgs":false,"family":"Donovan","given":"V.","email":"","middleInitial":"M.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wonkka, C.","contributorId":244282,"corporation":false,"usgs":false,"family":"Wonkka","given":"C.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803677,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, L.","contributorId":244283,"corporation":false,"usgs":false,"family":"Powell","given":"L.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","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":803679,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angeler, D. G.","contributorId":240686,"corporation":false,"usgs":false,"family":"Angeler","given":"D. G.","affiliations":[{"id":12665,"text":"University of Cape Town","active":true,"usgs":false}],"preferred":false,"id":803680,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wedin, D.","contributorId":244284,"corporation":false,"usgs":false,"family":"Wedin","given":"D.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803681,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twidwell, D.","contributorId":244285,"corporation":false,"usgs":false,"family":"Twidwell","given":"D.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803682,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70205059,"text":"70205059 - 2019 - Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","interactions":[],"lastModifiedDate":"2019-08-29T09:01:06","indexId":"70205059","displayToPublicDate":"2019-01-14T08:59:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5038,"text":"International Journal of Climate Change: Impacts and Responses","seriesDoiName":"10.18848/1835-7156/CGP","printIssn":"1835-7156","active":true,"publicationSubtype":{"id":10}},"title":"Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","docAbstract":"Droughts in Tanzania pose challenges to agriculture, water resources, and hydropower production, all of which impact livelihoods.  Tanzania experienced below average precipitation during 1999-2014 during two important seasons: December to February (DJF) in the south and during March to June (MAMJ) in the northeast.  We explore DJF and MAMJ precipitation in the areas with drying trends and examine their relationships with anomalous sea surface temperatures (SST) in the Indo-Pacific and corresponding circulation patterns. It is found that at seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. The dominant influence for droughts in DJF is from eastern Pacific SST while for droughts in MAMJ it is from West Pacific SST. A bivariate regression model with West Pacific and Niño3.4 region SST as predictors is found to recreate multidecadal DJF variability after the 1950s and the extreme drying in MAMJ during the 2000s. The regression model coefficients also indicate differential eastern vs. western Pacific forcing for DJF vs. MAMJ. Thus we suggest that recent La Niña-like conditions, characterized by an enhanced Pacific SST gradient due to cooling in the eastern Pacific and warming in the western Pacific, played a substantial role in Tanzania’s recent multi-season drying trends. SST change scenarios (difference between 2023-2037 and 2000-2014 means) based on CMIP5 projections and observed trends illustrate the uncertainty about future precipitation outcomes and also the potential implications of contrasting linkages to eastern vs. western Pacific SSTs. These scenarios are mainly optimistic for the DJF southern Tanzania trend area, because it appears dominated by Niño3.4 cooling at both seasonal and decadal time scales. Conversely, our scenarios are quite pessimistic for the MAMJ northeastern Tanzania trend area, because we find a dominant negative influence of warming West Pacific SST.","language":"English","publisher":"Wiley","doi":"10.1002/joc.6003","usgsCitation":"Harrison, L., Funk, C., McNally, A., Shukla, S., and Husak, G., 2019, Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends: International Journal of Climate Change: Impacts and Responses, v. 39, no. 6, p. 3057-3075, https://doi.org/10.1002/joc.6003.","productDescription":"19 p.","startPage":"3057","endPage":"3075","ipdsId":"IP-101903","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/joc.6003","text":"Publisher Index Page"},{"id":367045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367039,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1002/joc.6003"}],"country":"Tanzania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[33.90371,-0.95],[34.07262,-1.05982],[37.69869,-3.09699],[37.7669,-3.67712],[39.20222,-4.67677],[38.74054,-5.90895],[38.79977,-6.47566],[39.44,-6.84],[39.47,-7.1],[39.19469,-7.7039],[39.25203,-8.00781],[39.18652,-8.48551],[39.53574,-9.11237],[39.9496,-10.0984],[40.31659,-10.3171],[39.521,-10.89688],[38.42756,-11.2852],[37.82764,-11.26879],[37.47129,-11.56876],[36.77515,-11.59454],[36.51408,-11.72094],[35.3124,-11.43915],[34.55999,-11.52002],[34.28,-10.16],[33.94084,-9.69367],[33.73972,-9.41715],[32.75938,-9.2306],[32.19186,-8.93036],[31.55635,-8.76205],[31.15775,-8.59458],[30.74,-8.34],[30.2,-7.08],[29.62,-6.52],[29.41999,-5.94],[29.51999,-5.41998],[29.34,-4.49998],[29.75351,-4.45239],[30.11632,-4.09012],[30.50554,-3.56858],[30.75224,-3.35931],[30.74301,-3.03431],[30.52766,-2.80762],[30.46967,-2.41383],[30.75831,-2.28725],[30.81613,-1.69891],[30.4191,-1.13466],[30.76986,-1.01455],[31.86617,-1.02736],[33.90371,-0.95]]]},\"properties\":{\"name\":\"United Republic of Tanzania\"}}]}","volume":"39","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":769796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@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":769795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":769798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769799,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70203154,"text":"70203154 - 2019 - The Laurentian Great Lakes: A case study in ecological disturbance and climate change","interactions":[],"lastModifiedDate":"2019-04-24T09:56:47","indexId":"70203154","displayToPublicDate":"2019-01-13T09:53:20","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The Laurentian Great Lakes: A case study in ecological disturbance and climate change","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Climate change effects are already significant, but can also magnify other ecological problems. This can be clearly seen in the Laurentian Great Lakes, which have suffered habitat degradation, fishery overharvest and dramatic alterations by invasive species. Thermal changes are expected to cause extensive loss of suitable fish habitat, and changing precipitation patterns will aggravate the problems with our highly modified lotic and lentic systems. A brief summary of the historic ecological context provided by the Great Lakes case is presented, followed by the descriptions of selected tools that help to understand and evaluate both ecological and climate change problems. Species distribution models and habitat classification combined with climate change predictions can identify the distribution and extent of optimal habitats, and identify which are most vulnerable to climate change. Ecological flow modelling can help to identify when critical flow changes are likely. Mechanistic simulation modelling specifies understanding of how aquatic systems function and can reveal cause and effect relationships. These tools can be used to help managers to protect optimal habitat, resist climate change effects to other habitats and adapt cultural systems to climate‐altered aquatic systems.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/fme.12317","usgsCitation":"McKenna, J.E., 2019, The Laurentian Great Lakes: A case study in ecological disturbance and climate change: Fisheries Management and Ecology, p. 1-14, https://doi.org/10.1111/fme.12317.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-094732","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":363175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92,\n              40\n            ],\n            [\n              -74,\n              40\n            ],\n            [\n              -74,\n              49.5\n            ],\n            [\n              -92,\n              49.5\n            ],\n            [\n              -92,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":195894,"corporation":false,"usgs":true,"family":"McKenna","given":"James","suffix":"Jr.","email":"jemckenna@usgs.gov","middleInitial":"E.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":761414,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70203580,"text":"70203580 - 2019 - Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model","interactions":[],"lastModifiedDate":"2019-05-24T08:14:50","indexId":"70203580","displayToPublicDate":"2019-01-13T07:45:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3647,"text":"Transportation Research Record","active":true,"publicationSubtype":{"id":10}},"title":"Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Stormwater practitioners need quantitative information about the quality and volume of highway runoff to assess and mitigate potential adverse effects of runoff on the Nation’s receiving waters. The U.S. Geological Survey developed the Highway Runoff Database (HRDB) in cooperation with the FHWA to provide practice-ready information to meet these information needs on the local or national scale. This paper describes the datasets that are available in version 1.1 of the HRDB and demonstrates how data and statistics from the HRDB can be used with the Stochastic Empirical Loading and Dilution Model (SELDM) to simulate highway runoff. The HRDB includes 249 sites, 6,849 runoff events, and 106,869 event mean concentrations (EMCs) collected during the 1975–2017 period. It includes data from 16 States in the conterminous United States and from Hawaii. The EMCs in the HRDB include measurements for 415 different water-quality constituents. These water-quality measurements include 32,944 trace-metal; 27,496 organic; 15,684 nutrient; 13,016 physical property; 10,307 major inorganic; 6,773 sediment; and 649 other constituent values. There are large variations in the data. For example, EMCs for total suspended solids and total phosphorus range from 0.4 to 5,440 mg/L and 0.004 to 22 mg/L, respectively; geometric means range from 1.58 to 1,379 mg/L and 0.017 to 2.82 mg/L for these constituents, respectively. The example simulations indicate that risks for adverse effects of runoff can vary by orders of magnitude; the HRDB and SELDM facilitate selection of representative statistics from available datasets.</p></div></div>","language":"English","publisher":"SAGE","doi":"10.1177/0361198118822821","usgsCitation":"Granato, G., and Jones, S.C., 2019, Simulating runoff quality with the highway-runoff database and the Stochastic Empirical Loading and Dilution Model: Transportation Research Record, v. 2673, no. 1, p. 136-142, https://doi.org/10.1177/0361198118822821.","productDescription":"7 p.","startPage":"136","endPage":"142","ipdsId":"IP-101884","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":467997,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0361198118822821","text":"Publisher Index Page"},{"id":437607,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94VL32J","text":"USGS data release","linkHelpText":"Highway-Runoff Database (HRDB) Version 1.1"},{"id":364106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"2673","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Granato, Gregory E. 0000-0002-2561-9913","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":203250,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":763203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":763204,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70204959,"text":"70204959 - 2019 - Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.","interactions":[],"lastModifiedDate":"2025-05-14T13:34:40.144004","indexId":"70204959","displayToPublicDate":"2019-01-11T09:02:39","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.","docAbstract":"This study documented surface distributions of live and dead foraminiferal assemblages in the low-gradient tidal marshes of the barrier island and estuarine complex of the eastern Mississippi Sound (Grand Bay, Pascagoula River, Fowl River, Dauphin Island). A total of 71,833 specimens representing 38 species were identified from a gradient of different elevation zones across the study area. We identified five live assemblages and nine biofacies for the dead assemblages from estuarine, low marsh, middle marsh, high marsh, and upland transition environments. Although dissolution of calcareous tests was observed in the dead assemblages, characteristic species and abundance patterns dependent on elevation in the intertidal zone were similar between living assemblages and dead biofacies. The assemblages from the eastern Mississippi Sound estuaries were dominated by Ammonia tepida, Cribroelphidium poeyanum, C. excavatum, and Paratrochammina simplissima. The low marshes were dominated by Ammotium salsum, Ammobaculites exiguus, and Miliammina fusca. The dominant species in the middle marshes was Arenoparrella mexicana. The most abundant species in the high marshes was Entzia macrescens. The upland–marsh transition zones were dominated by Trochamminita irregularis and Pseudothurammina limnetis. Canonical correspondence analysis was applied to assess the relationship between a priori defined biofacies and measured environmental data (elevation, grain size, organic matter, and salinity) to test the hypothesis that distribution of foraminiferal assemblages is driven by elevation and hence flooding frequency. Salinity was the second most important explanatory variable of dead assemblages. Riverine freshwater from the Pascagoula River markedly influenced the live and dead assemblages in the Pascagoula River marsh, which was represented by low diversity and densities and dominance by Ammoastuta inepta. The relationship between the measured environmental variables and assemblage distributions can be used in future Mississippi Sound paleo-environmental studies.","language":"English","publisher":"GeoScienceWorld","doi":"10.2113/gsjfr.49.1.29","usgsCitation":"Haller, C., Smith, C., Hallock, P., Hine, A.C., Osterman, L., and McCloskey, T., 2019, Distribution of modern salt-marsh Foraminifera from the eastern Mississippi Sound, U.S.A.: Journal of Foraminiferal Research, v. 49, no. 1, p. 29-47, https://doi.org/10.2113/gsjfr.49.1.29.","productDescription":"19 p.; Data Release","startPage":"29","endPage":"47","ipdsId":"IP-091945","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":437608,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P901T47X","text":"USGS data release","linkHelpText":"Sedimentary data from the lower Pascagoula River, Mississippi, USA"},{"id":366948,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.4124755859375,\n              30.637912028341123\n            ],\n            [\n              -89.7308349609375,\n              30.477082932837682\n            ],\n            [\n              -89.4891357421875,\n              29.954934549656144\n            ],\n            [\n              -88.0224609375,\n              30.012030680358613\n            ],\n            [\n              -88.4124755859375,\n              30.637912028341123\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"49","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haller, Christian","contributorId":200685,"corporation":false,"usgs":false,"family":"Haller","given":"Christian","affiliations":[],"preferred":false,"id":769279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallock, Pamela 0000-0002-1813-0482","orcid":"https://orcid.org/0000-0002-1813-0482","contributorId":215416,"corporation":false,"usgs":false,"family":"Hallock","given":"Pamela","email":"","affiliations":[{"id":39241,"text":"College of Marine Science, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":769280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hine, Albert C.","contributorId":218440,"corporation":false,"usgs":false,"family":"Hine","given":"Albert","email":"","middleInitial":"C.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":769281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterman, Lisa 0000-0002-8603-5217 osterman@usgs.gov","orcid":"https://orcid.org/0000-0002-8603-5217","contributorId":218441,"corporation":false,"usgs":true,"family":"Osterman","given":"Lisa","email":"osterman@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769282,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCloskey, Terrence 0000-0003-3979-3821","orcid":"https://orcid.org/0000-0003-3979-3821","contributorId":218442,"corporation":false,"usgs":true,"family":"McCloskey","given":"Terrence","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769283,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215768,"text":"70215768 - 2019 - Activity center selection by northern spotted owls","interactions":[],"lastModifiedDate":"2020-10-30T15:56:29.492902","indexId":"70215768","displayToPublicDate":"2019-01-10T10:46:38","publicationYear":"2019","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":"Activity center selection by northern spotted owls","docAbstract":"<p><span>The federally threatened northern spotted owl (</span><i>Strix occidentalis caurina</i><span>) has been intensively studied across its range, and habitat needs for the species have influenced forest management in northwestern North America for decades. Dense forest canopies are often reported in the scientific literature and agency management plans as an important habitat attribute for spotted owls, though the means of measuring forest canopy and interpreting species requirements vary across studies and more importantly, among management plans. We used light detection and ranging (lidar) measurements of canopy cover, canopy surface heterogeneity, and upper canopy surface connectivity, and an index of the presence of a competitive invasive species, the barred owl (</span><i>S. varia</i><span>), in multinomial discrete choice models using a Bayesian framework to evaluate selection of forest cover types by spotted owls in Oregon, USA, 2008–2015. We designated yearly activity centers based on the most biologically significant observation during the nesting season (Mar–Aug), generally centered on the nest tree. Spotted owls selected activity centers with more canopy cover and higher heterogeneity of the canopy surface within 100 m than was available within their territories. The average proportion of canopy cover within 100 m of a spotted owl activity center was 0.79 ± 0.12 (SD; range = 0.34–0.99). The presence of barred owls did not explain variability in selection of spotted owl activity centers, but barred owls might not affect third‐order habitat selection within territories, or our index was too spatially coarse to detect these effects on spotted owl resource selection. We demonstrate that lidar provides researchers and managers with a tool that can accurately measure forest canopies over large areas, and assist in mapping spotted owl habitat.&nbsp;</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21632","usgsCitation":"Sovern, S., Lesmeister, D.B., Dugger, K., Pruett, M., Davis, R.J., and Jenkins, J.M., 2019, Activity center selection by northern spotted owls: Journal of Wildlife Management, v. 83, no. 3, p. 714-727, https://doi.org/10.1002/jwmg.21632.","productDescription":"14 p.","startPage":"714","endPage":"727","ipdsId":"IP-095389","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21632","text":"Publisher Index Page"},{"id":379968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.288330078125,\n              42.09822241118974\n            ],\n            [\n              -121.70654296874999,\n              42.09822241118974\n            ],\n            [\n              -121.70654296874999,\n              45.166547157856016\n            ],\n            [\n              -124.288330078125,\n              45.166547157856016\n            ],\n            [\n              -124.288330078125,\n              42.09822241118974\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"83","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Sovern, Stan G.","contributorId":244122,"corporation":false,"usgs":false,"family":"Sovern","given":"Stan G.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":803355,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lesmeister, Damon B. 0000-0003-1102-0122","orcid":"https://orcid.org/0000-0003-1102-0122","contributorId":205006,"corporation":false,"usgs":false,"family":"Lesmeister","given":"Damon","email":"","middleInitial":"B.","affiliations":[{"id":37019,"text":"USDA Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":803356,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":803357,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pruett, M. Shane","contributorId":244123,"corporation":false,"usgs":false,"family":"Pruett","given":"M. Shane","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":803358,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Raymond J.","contributorId":150574,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803359,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Julianna M.","contributorId":244124,"corporation":false,"usgs":false,"family":"Jenkins","given":"Julianna","email":"","middleInitial":"M.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":803360,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
]}