{"pageNumber":"1036","pageRowStart":"25875","pageSize":"25","recordCount":184914,"records":[{"id":70181775,"text":"70181775 - 2017 - Detecting spatial regimes in ecosystems","interactions":[],"lastModifiedDate":"2017-02-14T10:28:26","indexId":"70181775","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Detecting spatial regimes in ecosystems","docAbstract":"<p><span>Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.12709","usgsCitation":"Sundstrom, S.M., Eason, T., Nelson, R.J., Angeler, D., Barichievy, C., Garmestani, A.S., Graham, N.A., Granholm, D., Gunderson, L., Knutson, M., Nash, K.L., Spanbauer, T., Stow, C., and Allen, C.R., 2017, Detecting spatial regimes in ecosystems: Ecology Letters, v. 20, no. 1, p. 19-32, https://doi.org/10.1111/ele.12709.","productDescription":"14 p.","startPage":"19","endPage":"32","ipdsId":"IP-079617","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461805,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ele.12709","text":"External Repository"},{"id":335306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"58a2d3b6e4b0c82512869a05","chorus":{"doi":"10.1111/ele.12709","url":"http://dx.doi.org/10.1111/ele.12709","publisher":"Wiley-Blackwell","authors":"Sundstrom Shana M., Eason Tarsha, Nelson R. John, Angeler David G., Barichievy Chris, Garmestani Ahjond S., Graham Nicholas A.J., Granholm Dean, Gunderson Lance, Knutson Melinda, Nash Kirsty L., Spanbauer Trisha, Stow Craig A., Allen Craig R.","journalName":"Ecology Letters","publicationDate":"12/20/2016","auditedOn":"12/27/2016","publiclyAccessibleDate":"12/20/2016"},"contributors":{"authors":[{"text":"Sundstrom, Shana M.","contributorId":7159,"corporation":false,"usgs":true,"family":"Sundstrom","given":"Shana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":668483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eason, Tarsha","contributorId":82220,"corporation":false,"usgs":true,"family":"Eason","given":"Tarsha","email":"","affiliations":[],"preferred":false,"id":668503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, R. John","contributorId":98215,"corporation":false,"usgs":true,"family":"Nelson","given":"R.","email":"","middleInitial":"John","affiliations":[],"preferred":false,"id":668504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":668505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barichievy, Chris","contributorId":17119,"corporation":false,"usgs":true,"family":"Barichievy","given":"Chris","email":"","affiliations":[],"preferred":false,"id":668506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":668507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graham, Nicholas A.J.","contributorId":101990,"corporation":false,"usgs":true,"family":"Graham","given":"Nicholas","email":"","middleInitial":"A.J.","affiliations":[],"preferred":false,"id":668508,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Granholm, Dean","contributorId":85087,"corporation":false,"usgs":true,"family":"Granholm","given":"Dean","email":"","affiliations":[],"preferred":false,"id":668509,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gunderson, Lance","contributorId":30797,"corporation":false,"usgs":true,"family":"Gunderson","given":"Lance","affiliations":[],"preferred":false,"id":668510,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Knutson, Melinda","contributorId":27929,"corporation":false,"usgs":true,"family":"Knutson","given":"Melinda","affiliations":[],"preferred":false,"id":668511,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nash, Kirsty L.","contributorId":40897,"corporation":false,"usgs":true,"family":"Nash","given":"Kirsty","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":668512,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Spanbauer, Trisha","contributorId":146435,"corporation":false,"usgs":false,"family":"Spanbauer","given":"Trisha","email":"","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":668513,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":668514,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"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":668515,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70196710,"text":"70196710 - 2017 - Effect of N fertilization and tillage on nitrous oxide (N2O) loss from soil under wheat production","interactions":[],"lastModifiedDate":"2018-04-26T17:06:39","indexId":"70196710","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"displayTitle":"Effect of N fertilization and tillage on nitrous oxide (N<sub>2</sub>O) loss from soil under wheat production","title":"Effect of N fertilization and tillage on nitrous oxide (N2O) loss from soil under wheat production","docAbstract":"Nitrous oxide (N2O-N) is one of the most important gases in the atmosphere because it is 300 times more powerful than carbon dioxide in its ability to trap heat, and is a key chemical agent of ozone depletion. The amount of N2O-N emitted from agricultural fields can be quite high, depending on the complex interplay between N fertility and residue management, plant N uptake, microbial processes, environmental conditions, and wet-up and dry-down events. High N fertilizer rates generally increase yields, but may disproportionately increase N2O-N losses due to prolonged residence time in soil when not used by the crop, and incomplete decomposition of excess N-compounds by microbes. Tillage could also affect N2O-N losses through changes in soil moisture content. Though nitrogen monoxide (NO) is one form of N lost from the soil, especially under conventional tillage, this study objective was to quantify N2O loss in wheat fields from applied urea on soil under no-till (NT) versus incorporated urea under conventional till (CT).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Carrington Research Extension Center Annual Report, A report of agricultural research and extension in central North Dakota, Vol 58","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"North Dakota State University","usgsCitation":"Bansal, S., Aberle, E., Teboh, J., Yuja, S., Liebig, M., Meier, J., and Boyd, A., 2017, Effect of N fertilization and tillage on nitrous oxide (N2O) loss from soil under wheat production, 2 p.","productDescription":"2 p.","startPage":"20","endPage":"21","ipdsId":"IP-092627","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":353761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353760,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.ag.ndsu.edu/CarringtonREC/documents/annual-reports/2017-annual-report#page=21"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4c8","contributors":{"authors":[{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aberle, Ezra","contributorId":204469,"corporation":false,"usgs":false,"family":"Aberle","given":"Ezra","email":"","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":734074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teboh, Jasper","contributorId":204470,"corporation":false,"usgs":false,"family":"Teboh","given":"Jasper","email":"","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":734075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yuja, Szilvia","contributorId":204471,"corporation":false,"usgs":false,"family":"Yuja","given":"Szilvia","email":"","affiliations":[{"id":12459,"text":"NDSU","active":true,"usgs":false}],"preferred":false,"id":734076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liebig, Mark","contributorId":146788,"corporation":false,"usgs":false,"family":"Liebig","given":"Mark","email":"","affiliations":[],"preferred":false,"id":734077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meier, Jacob 0000-0002-8822-8434","orcid":"https://orcid.org/0000-0002-8822-8434","contributorId":204473,"corporation":false,"usgs":true,"family":"Meier","given":"Jacob","email":"","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boyd, Alec 0000-0003-2661-4126","orcid":"https://orcid.org/0000-0003-2661-4126","contributorId":204472,"corporation":false,"usgs":false,"family":"Boyd","given":"Alec","email":"","affiliations":[{"id":36944,"text":"Former employee at Northern Prairie Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":734078,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192672,"text":"70192672 - 2017 - A guide to multi-objective optimization for ecological problems with an application to cackling goose management","interactions":[],"lastModifiedDate":"2017-11-08T15:04:05","indexId":"70192672","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A guide to multi-objective optimization for ecological problems with an application to cackling goose management","docAbstract":"<p id=\"spar0010\">Choices in ecological research and management are the result of balancing multiple, often competing, objectives.<span>&nbsp;</span><i>Multi-objective optimization</i><span>&nbsp;</span>(MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem.</p><p id=\"spar0015\">A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the<span>&nbsp;</span><i>a priori</i><span>&nbsp;</span>strategy), or modelling preferences post-optimization (the<span>&nbsp;</span><i>a posteriori</i><span>&nbsp;</span>strategy). The<span>&nbsp;</span><i>a priori</i><span>&nbsp;</span>strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the<span>&nbsp;</span><i>a posteriori</i><span>&nbsp;</span>strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose (<i>Branta hutchinsii minima</i>) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the<span>&nbsp;</span><i>a priori</i><span>&nbsp;</span>strategy, and then by examining trade-offs in the Pareto set using the<span>&nbsp;</span><i>a posteriori</i><span>&nbsp;</span>strategy. We used four approaches for selecting a final solution within the<span>&nbsp;</span><i>a posteriori</i><span>&nbsp;</span>strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2016.10.010","usgsCitation":"Williams, P.J., and Kendall, W., 2017, A guide to multi-objective optimization for ecological problems with an application to cackling goose management: Ecological Modelling, v. 343, p. 54-67, https://doi.org/10.1016/j.ecolmodel.2016.10.010.","productDescription":"14 p.","startPage":"54","endPage":"67","ipdsId":"IP-074514","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470233,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2016.10.010","text":"Publisher Index Page"},{"id":348487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"343","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425bde4b0dc0b45b453c5","contributors":{"authors":[{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716696,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70192519,"text":"70192519 - 2017 - Mapping tree canopy cover in support of proactive prairie grouse conservation in western North America","interactions":[],"lastModifiedDate":"2017-10-26T13:39:12","indexId":"70192519","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Mapping tree canopy cover in support of proactive prairie grouse conservation in western North America","docAbstract":"<p><span>Invasive woody plant expansion is a primary threat driving fragmentation&nbsp;and loss of sagebrush (<i>Artemisia</i></span><span><span>&nbsp;</span>spp.) and prairie habitats across the central and western United States. Expansion of native woody plants, including conifer (primarily<i><span> Juniperus</span></i></span><span><span>&nbsp;</span>spp.) and<span> mesquite (<i>Prosopis</i></span></span><span><span>&nbsp;</span>spp.), over the past century is primarily attributable to wildfire suppression, historic periods of intensive livestock grazing, and changes in climate. To guide successful conservation programs aimed at reducing top-down stressors, we mapped invasive woody plants at regional scales to evaluate landscape level impacts, target restoration actions, and monitor restoration outcomes. Our overarching goal was to produce seamless regional products across sociopolitical boundaries with resolution fine enough to depict the spatial extent and degree of woody plant invasion relevant to greater sage-grouse<span>&nbsp;</span></span><i>(Centrocercus urophasianus)</i><span><span>&nbsp;</span>and lesser prairie-chicken<span>&nbsp;</span></span><i>(Tympanuchus pallidicinctus)</i><span>conservation efforts. We mapped<span> tree canopy</span><span>&nbsp;</span>cover at 1-m spatial resolution across an 11-state region (508 265 km</span><sup>2</sup><span>). Greater than 90% of occupied lesser prairie-chicken habitat was largely treeless for conifers (&lt;</span><span>&nbsp;</span><span>1% canopy cover), whereas &gt; 67% was treeless for mesquite. Conifers in the higher canopy cover classes (16</span><span>&nbsp;</span><span>−</span><span>&nbsp;</span><span>50% and &gt;</span><span>&nbsp;</span><span>50% canopy cover) were scarce (&lt;</span><span>&nbsp;</span><span>2% and 1% canopy cover), as was mesquite (&lt;</span><span>&nbsp;</span><span>5% and 1% canopy cover). Occupied habitat by sage-grouse was more variable but also had a relatively large proportion of treeless areas (</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math class=&quot;math&quot; xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mover accent=&quot;true&quot; is=&quot;true&quot;><mi is=&quot;true&quot;>x</mi><mo stretchy=&quot;true&quot; is=&quot;true&quot;>&amp;#x2212;</mo></mover></math>\"><span class=\"MJX_Assistive_MathML\">x−</span></span><span><span>&nbsp;</span>= 71, SE = 5%). Low to moderate levels of conifer cover (1</span><span>&nbsp;</span><span>−</span><span>&nbsp;</span><span>20%) were fewer (</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math class=&quot;math&quot; xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mover accent=&quot;true&quot; is=&quot;true&quot;><mi is=&quot;true&quot;>x</mi><mo stretchy=&quot;true&quot; is=&quot;true&quot;>&amp;#x2212;</mo></mover></math>\"><span class=\"MJX_Assistive_MathML\">x−</span></span><span><span>&nbsp;</span>= 23, SE = 5%) as were areas in the highest cover class (&gt;</span><span>&nbsp;</span><span>50%;<span>&nbsp;</span></span><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math class=&quot;math&quot; xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mover accent=&quot;true&quot; is=&quot;true&quot;><mi is=&quot;true&quot;>x</mi><mo stretchy=&quot;true&quot; is=&quot;true&quot;>&amp;#x2212;</mo></mover></math>\"><span class=\"MJX_Assistive_MathML\">x−</span></span><span>= 6, SE = 2%). Mapping indicated that a high proportion of invading woody plants are at a low to intermediate level. Canopy cover maps for conifer and mesquite resulting from this study provide the first and most geographically complete, high-resolution assessment of woody<span> plant cover</span><span>&nbsp;</span>as a top-down threat to western sage-steppe and prairie ecosystems.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2016.08.002","usgsCitation":"Falkowski, M.J., Evans, J.S., Naugle, D.E., Hagen, C.A., Carleton, S.A., Maestas, J.D., Henareh Khalyani, A., Poznanovic, A.J., and Lawrence, A.J., 2017, Mapping tree canopy cover in support of proactive prairie grouse conservation in western North America: Rangeland Ecology and Management, v. 70, no. 1, p. 15-24, https://doi.org/10.1016/j.rama.2016.08.002.","productDescription":"10 p.","startPage":"15","endPage":"24","ipdsId":"IP-073817","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482068,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.08.002","text":"Publisher Index Page"},{"id":347477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e953e4b09af898c8cc11","contributors":{"authors":[{"text":"Falkowski, Michael J.","contributorId":198547,"corporation":false,"usgs":false,"family":"Falkowski","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Jeffrey S.","contributorId":171756,"corporation":false,"usgs":false,"family":"Evans","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":716382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naugle, David E.","contributorId":82837,"corporation":false,"usgs":true,"family":"Naugle","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carleton, Scott A. 0000-0001-9609-650X scarleton@usgs.gov","orcid":"https://orcid.org/0000-0001-9609-650X","contributorId":4060,"corporation":false,"usgs":true,"family":"Carleton","given":"Scott","email":"scarleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maestas, Jeremy D.","contributorId":117298,"corporation":false,"usgs":true,"family":"Maestas","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":716385,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Henareh Khalyani, Azad","contributorId":194189,"corporation":false,"usgs":false,"family":"Henareh Khalyani","given":"Azad","email":"","affiliations":[],"preferred":false,"id":716386,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poznanovic, Aaron J.","contributorId":198548,"corporation":false,"usgs":false,"family":"Poznanovic","given":"Aaron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716387,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lawrence, Andrew J.","contributorId":198549,"corporation":false,"usgs":false,"family":"Lawrence","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716388,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70192642,"text":"70192642 - 2017 - Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression","interactions":[],"lastModifiedDate":"2017-11-07T14:44:39","indexId":"70192642","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5542,"text":"Advances in Statistical Climatology, Meteorology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression","docAbstract":"<p><span>Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ascmo-3-1-2017","usgsCitation":"Tipton, J., Hooten, M., and Goring, S., 2017, Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression: Advances in Statistical Climatology, Meteorology and Oceanography, v. 3, p. 1-16, https://doi.org/10.5194/ascmo-3-1-2017.","productDescription":"16 p.","startPage":"1","endPage":"16","ipdsId":"IP-076974","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ascmo-3-1-2017","text":"Publisher Index Page"},{"id":348403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"5a07e953e4b09af898c8cc0f","contributors":{"authors":[{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":716635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":716634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goring, Simon","contributorId":167180,"corporation":false,"usgs":false,"family":"Goring","given":"Simon","affiliations":[],"preferred":false,"id":716636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193167,"text":"70193167 - 2017 - Validation of daily increments periodicity in otoliths of spotted gar","interactions":[],"lastModifiedDate":"2017-11-20T15:37:49","indexId":"70193167","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3909,"text":"Journal of the Southeastern Association of Fish and Wildlife Agencies","active":true,"publicationSubtype":{"id":10}},"title":"Validation of daily increments periodicity in otoliths of spotted gar","docAbstract":"<p><span>Accurate age and growth information is essential in successful management of fish populations and for understanding early life history. We validated daily increment deposition, including the timing of first ring formation, for spotted gar (Lepisosteus oculatus) through 127 days post hatch. Fry were produced from hatchery-spawned specimens, and up to 10 individuals per week were sacrificed and their otoliths (sagitta, lapillus, and asteriscus) removed for daily age estimation. Daily age estimates for all three otolith pairs were significantly related to known age. The strongest relationships existed for measurements from the sagitta (r2 = 0.98) and the lapillus (r2 = 0.99) with asteriscus (r2 = 0.95) the lowest. All age prediction models resulted in a slope near unity, indicating that ring deposition occurred approximately daily. Initiation of ring formation varied among otolith types, with deposition beginning 3, 7, and 9 days for the sagitta, lapillus, and asteriscus, respectively. Results of this study suggested that otoliths are useful to estimate daily age of spotted gar juveniles; these data may be used to back calculate hatch dates, estimate early growth rates, and correlate with environmental factor that influence spawning in wild populations. is early life history information will be valuable in better understanding the ecology of this species.&nbsp;</span></p>","language":"English","publisher":"Southeastern Association of Fish and Wildlife Agencies","usgsCitation":"Snow, R.A., Long, J.M., and Frenette, B.D., 2017, Validation of daily increments periodicity in otoliths of spotted gar: Journal of the Southeastern Association of Fish and Wildlife Agencies, v. 4, p. 60-65.","productDescription":"6 p.","startPage":"60","endPage":"65","ipdsId":"IP-077724","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":349157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.seafwa.org/publications/journal/?id=402080"}],"volume":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bf9","contributors":{"authors":[{"text":"Snow, Richard A.","contributorId":176213,"corporation":false,"usgs":false,"family":"Snow","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":27443,"text":"Oklahoma Department of Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":722924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frenette, Bryan D.","contributorId":200628,"corporation":false,"usgs":false,"family":"Frenette","given":"Bryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722925,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193237,"text":"70193237 - 2017 - Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes","interactions":[],"lastModifiedDate":"2017-11-22T17:05:17","indexId":"70193237","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes","docAbstract":"<p>Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land use and anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (<i>Aquila chrysaetos</i>). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, U.S.A. We developed a spatially explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire prey resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative effects. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative effects of proposed management options to Golden Eagles and their habitats.</p>","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-77.1","usgsCitation":"Wiens, J.D., Schumaker, N.H., Inman, R.D., Esque, T., Longshore, K.M., and Nussear, K.E., 2017, Spatial demographic models to inform conservation planning of golden eagles in renewable energy landscapes: Journal of Raptor Research, v. 51, no. 3, p. 234-257, https://doi.org/10.3356/JRR-16-77.1.","productDescription":"24 p.","startPage":"234","endPage":"257","ipdsId":"IP-079327","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-77.1","text":"Publisher Index Page"},{"id":347904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"51","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bbae4b0531197afa004","contributors":{"authors":[{"text":"Wiens, J. David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":468,"corporation":false,"usgs":true,"family":"Wiens","given":"J.","email":"jwiens@usgs.gov","middleInitial":"David","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":718668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schumaker, Nathan H.","contributorId":199151,"corporation":false,"usgs":false,"family":"Schumaker","given":"Nathan","email":"","middleInitial":"H.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":718669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Inman, Richard D. rdinman@usgs.gov","contributorId":3316,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":718670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd C. tesque@usgs.gov","contributorId":127766,"corporation":false,"usgs":true,"family":"Esque","given":"Todd C.","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":718671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":718672,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nussear, Kenneth E.","contributorId":117361,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":718673,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70186169,"text":"70186169 - 2017 - Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2017-03-30T15:13:22","indexId":"70186169","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska","docAbstract":"<p><span>Sexual segregation occurs frequently in sexually dimorphic species, and it may be influenced by differential habitat requirements between sexes or by social or evolutionary mechanisms that maintain separation of sexes regardless of habitat selection. Understanding the degree of sex-specific habitat specialization is important for management of wildlife populations and the design of monitoring and research programs. Using mid-summer aerial survey data for Dall’s sheep (</span><i>Ovis dalli dalli</i><span>) in southern Alaska during 1983–2011, we assessed differences in summer habitat selection by sex and reproductive status at the landscape scale in Wrangell-St. Elias National Park and Preserve (WRST). Males and females were highly segregated socially, as were females with and without young. Resource selection function (RSF) models containing rugged terrain, intermediate values of the normalized difference vegetation index (NDVI), and open landcover types best explained resource selection by each sex, female reproductive classes, and all sheep combined. For male and all female models, most coefficients were similar, suggesting little difference in summer habitat selection between sexes at the landscape scale. A combined RSF model therefore may be used to predict the relative probability of resource selection by Dall’s sheep in WRST regardless of sex or reproductive status.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmammal/gyw135","usgsCitation":"Roffler, G.H., Adams, L., and Hebblewhite, M., 2017, Summer habitat selection by Dall’s sheep in Wrangell-St. Elias National Park and Preserve, Alaska: Journal of Mammalogy, v. 98, no. 1, p. 94-105, https://doi.org/10.1093/jmammal/gyw135.","productDescription":"12 p.","startPage":"94","endPage":"105","ipdsId":"IP-060082","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyw135","text":"Publisher Index Page"},{"id":338838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"98","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-17","publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca1","chorus":{"doi":"10.1093/jmammal/gyw135","url":"http://dx.doi.org/10.1093/jmammal/gyw135","publisher":"Oxford University Press (OUP)","authors":"Roffler Gretchen H., Adams Layne G., Hebblewhite Mark","journalName":"Journal of Mammalogy","publicationDate":"9/17/2016"},"contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":687741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hebblewhite, Mark","contributorId":190188,"corporation":false,"usgs":false,"family":"Hebblewhite","given":"Mark","email":"","affiliations":[],"preferred":false,"id":687743,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70187262,"text":"70187262 - 2017 - An integrated moral obligation model for landowner conservation norms","interactions":[],"lastModifiedDate":"2017-04-27T11:10:16","indexId":"70187262","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3404,"text":"Society & Natural Resources: An International Journal","active":true,"publicationSubtype":{"id":10}},"title":"An integrated moral obligation model for landowner conservation norms","docAbstract":"<p><span>This study applies an integrated moral obligation model to examine the role of environmental and cultural values, and beliefs in the activation of landowner conservation norms. Data for this study were collected through a self-administered survey of riparian landowners in two Minnesota watersheds: Sand Creek and Vermillion River watersheds. Study findings suggest that collectivistic and biospheric–altruistic values form the bases for the activation of personal norms. Further, beliefs about local responsibility and ability to act influence personal norms to protect water resources. Findings suggest that landowners’ personal norms of water conservation are more likely to be activated by conservation strategies that appeal to biospheric–altruistic and collectivistic values, emphasize adverse consequences of water pollution, highlight water resource protection as a local responsibility, and provide the resources needed to protect water resources.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/08941920.2016.1239289","usgsCitation":"Pradhananga, A.K., Davenport, M.A., Fulton, D.C., Maruyama, G.M., and Current, D., 2017, An integrated moral obligation model for landowner conservation norms: Society & Natural Resources: An International Journal, v. 30, no. 2, p. 212-227, https://doi.org/10.1080/08941920.2016.1239289.","productDescription":"16 p.","startPage":"212","endPage":"227","ipdsId":"IP-056505","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-31","publicationStatus":"PW","scienceBaseUri":"59030324e4b0e862d230f71d","contributors":{"authors":[{"text":"Pradhananga, Amit K.","contributorId":191478,"corporation":false,"usgs":false,"family":"Pradhananga","given":"Amit","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":693179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davenport, Mae A.","contributorId":191479,"corporation":false,"usgs":false,"family":"Davenport","given":"Mae","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maruyama, Geoffrey M.","contributorId":191480,"corporation":false,"usgs":false,"family":"Maruyama","given":"Geoffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":693181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Current, Dean","contributorId":191481,"corporation":false,"usgs":false,"family":"Current","given":"Dean","email":"","affiliations":[],"preferred":false,"id":693182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70186332,"text":"70186332 - 2017 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2016","interactions":[],"lastModifiedDate":"2023-04-07T16:33:01.002928","indexId":"70186332","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2016","docAbstract":"<p><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;We conducted a biomass-based assessment of the Lake Erie Western Basin fish community using data collected from 2013-2016 Western Basin (spring and autumn) bottom trawl surveys. Biomass of total catch per hectare has decreased 75 percent since 2013. Declines were observed across all functional groups, but most notable was the decline of Emerald Shiner, which decreased from 25.3 kg/ha in spring 2013 to <0.01 kg/ha by autumn  2013. The four primary predator species – Walleye, Yellow Perch, White Perch, and White Bass – all decreased from 2013 to 2015. In 2016, White Bass and Yellow Perch (all lifestages combined) continued to decline, while Walleye and White Perch (all ages combined) increased slightly from 5.6 kg/ha and 3.4 kg/ha to 9.0 kg/ha and 5.0 kg/ha, respectively (autumn catches). Despite decreasing trends in biomass, there was little change in biodiversity. Declines in forage biomass, i.e. Emerald Shiner and age-0 White Perch, resulted in an increased mean trophic level of catches. Forage fish to piscivore ratios reflected marked shifts in species composition toward greater forage in 2014 and 2016.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:8403202,&quot;4&quot;:[null,2,16777215],&quot;11&quot;:4,&quot;14&quot;:[null,2,0],&quot;15&quot;:&quot;Inconsolata, monospace, arial, sans, sans-serif&quot;,&quot;16&quot;:11,&quot;26&quot;:400}\" data-sheets-formula=\"=VLOOKUP(R[0]C[-5],Fixed!R2C[-6]:C[-4],3,false)\">We conducted a biomass-based assessment of the Lake Erie Western Basin fish community using data collected from 2013-2016 Western Basin (spring and autumn) bottom trawl surveys. Biomass of total catch per hectare has decreased 75 percent since 2013. Declines were observed across all functional groups, but most notable was the decline of Emerald Shiner, which decreased from 25.3 kg/ha in spring 2013 to &lt;0.01 kg/ha by autumn 2013. The four primary predator species – Walleye, Yellow Perch, White Perch, and White Bass – all decreased from 2013 to 2015. In 2016, White Bass and Yellow Perch (all lifestages combined) continued to decline, while Walleye and White Perch (all ages combined) increased slightly from 5.6 kg/ha and 3.4 kg/ha to 9.0 kg/ha and 5.0 kg/ha, respectively (autumn catches). Despite decreasing trends in biomass, there was little change in biodiversity. Declines in forage biomass, i.e. Emerald Shiner and age-0 White Perch, resulted in an increased mean trophic level of catches. Forage fish to piscivore ratios reflected marked shifts in species composition toward greater forage in 2014 and 2016.</span></p>","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bodamer Scarbro, B.L., Kraus, R.T., Kocovsky, P., and Vandergoot, C., 2017, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2016.","ipdsId":"IP-084961","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.83042561866203,\n              42.83947998725651\n            ],\n            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Center","active":true,"usgs":true}],"preferred":true,"id":688356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":150837,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":688359,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70186020,"text":"70186020 - 2017 - Quantifying the relative contribution of an ecological reserve to conservation objectives","interactions":[],"lastModifiedDate":"2017-03-30T15:18:26","indexId":"70186020","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the relative contribution of an ecological reserve to conservation objectives","docAbstract":"<p><span>Evaluating the role public lands play in meeting conservation goals is an essential step in good governance. We present a tool for comparing the regional contribution of each of a suite of wildlife management units to conservation goals. We use weighted summation (</span><i>simple additive weighting</i><span>) to compute a Unit Contribution Index (</span><i>UCI</i><span>) based on species richness, population abundance, and a conservation score based on IUCN Red List classified threat levels. We evaluate </span><i>UCI</i><span> for a subset of the 729 participating wetlands of the Integrated Waterbird Management and Monitoring (IWMM) Program across U.S. Fish and Wildlife Service Regions 3 (Midwest USA), 4 (Southeast USA), and 5 (Northeast USA). We found that the median across-Region </span><i>UCI</i><span> for Region 5 was greater than Regions 3 and 4, while Region 4 had the greatest within-Region </span><i>UCI</i><span> median. This index is a powerful tool for wildlife managers to evaluate the performance of units within the conservation estate.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2017.01.002","usgsCitation":"Aagaard, K., Lyons, J.E., and Thogmartin, W.E., 2017, Quantifying the relative contribution of an ecological reserve to conservation objectives: Global Ecology and Conservation, v. 9, p. 142-147, https://doi.org/10.1016/j.gecco.2017.01.002.","productDescription":"6 p.","startPage":"142","endPage":"147","ipdsId":"IP-079772","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470174,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2017.01.002","text":"Publisher Index Page"},{"id":338844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca3","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":687364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189110,"text":"70189110 - 2017 - Geologic influence on induced seismicity: Constraints from potential field data in Oklahoma","interactions":[],"lastModifiedDate":"2017-06-29T15:25:26","indexId":"70189110","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Geologic influence on induced seismicity: Constraints from potential field data in Oklahoma","docAbstract":"<p><span>Recent Oklahoma seismicity shows a regional correlation with increased wastewater injection activity, but local variations suggest that some areas are more likely to exhibit induced seismicity than others. We combine geophysical and drill hole data to map subsurface geologic features in the crystalline basement, where most earthquakes are occurring, and examine probable contributing factors. We find that most earthquakes are located where the crystalline basement is likely composed of fractured intrusive or metamorphic rock. Areas with extrusive rock or thick (&gt;4 km) sedimentary cover exhibit little seismicity, even in high injection rate areas, similar to deep sedimentary basins in Michigan and western North Dakota. These differences in seismicity may be due to variations in permeability structure: within intrusive rocks, fluids can become narrowly focused in fractures and faults, causing an increase in local pore fluid pressure, whereas more distributed pore space in sedimentary and extrusive rocks may relax pore fluid pressure.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL071808","usgsCitation":"Shah, A.K., and Keller, G.R., 2017, Geologic influence on induced seismicity: Constraints from potential field data in Oklahoma: Geophysical Research Letters, v. 44, no. 1, p. 152-161, https://doi.org/10.1002/2016GL071808.","productDescription":"10 p.","startPage":"152","endPage":"161","ipdsId":"IP-075927","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":470176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071808","text":"Publisher Index Page"},{"id":343173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100,\n              34\n            ],\n            [\n              -95,\n              34\n            ],\n            [\n              -95,\n              37\n            ],\n            [\n              -100,\n              37\n            ],\n            [\n              -100,\n              34\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"44","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-12","publicationStatus":"PW","scienceBaseUri":"595611b4e4b0d1f9f0506755","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":702919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keller, G. Randy","contributorId":40602,"corporation":false,"usgs":true,"family":"Keller","given":"G.","email":"","middleInitial":"Randy","affiliations":[],"preferred":false,"id":702920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70189600,"text":"70189600 - 2017 - The waterfall paradox: How knickpoints disconnect hillslope and channel processes, isolating salmonid populations in ideal habitats","interactions":[],"lastModifiedDate":"2017-07-18T12:36:02","indexId":"70189600","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The waterfall paradox: How knickpoints disconnect hillslope and channel processes, isolating salmonid populations in ideal habitats","docAbstract":"<p><span>Waterfalls create barriers to fish migration, yet hundreds of isolated salmonid populations exist above barriers and have persisted for thousands of years in steep mountainous terrain. Ecological theory indicates that small isolated populations in disturbance-prone landscapes are at greatest risk of extirpation because immigration and recolonization are not possible. On the contrary, many above-barrier populations are currently thriving while their downstream counterparts are dwindling. This quandary led us to explore geomorphic knickpoints as a mechanism for disconnecting hillslope and channel processes by limiting channel incision and decreasing the pace of base-level lowering. Using LiDAR from the Oregon Coast Range, we found gentler channel gradients, wider valleys, lower gradient hillslopes, and less shallow landslide potential in an above-barrier catchment compared to a neighboring catchment devoid of persistent knickpoints. Based on this unique geomorphic template, above-barrier channel networks are less prone to debris flows and other episodic sediment fluxes. These above-barrier catchments also have greater resiliency to flooding, owing to wider valleys with greater floodplain connectivity. Habitat preference models further indicate that salmonid habitat is present in greater quantity and quality in these above-barrier networks. Therefore the paradox of the persistence of small isolated fish populations may be facilitated by a geomorphic mechanism that both limits their connectivity to larger fish populations yet dampens the effect of disturbance by decreasing connections between hillslope and channel processes above geomorphic knickpoints.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2016.03.029","usgsCitation":"May, C., Roering, J., Snow, K., Griswold, K., and Gresswell, R.E., 2017, The waterfall paradox: How knickpoints disconnect hillslope and channel processes, isolating salmonid populations in ideal habitats: Geomorphology, v. 277, p. 228-236, https://doi.org/10.1016/j.geomorph.2016.03.029.","productDescription":"9 p.","startPage":"228","endPage":"236","ipdsId":"IP-066828","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":343992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"277","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596f1e26e4b0d1f9f0640763","contributors":{"authors":[{"text":"May, Christine","contributorId":99619,"corporation":false,"usgs":true,"family":"May","given":"Christine","affiliations":[],"preferred":false,"id":705363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roering, Joshua J.","contributorId":194297,"corporation":false,"usgs":false,"family":"Roering","given":"Joshua J.","affiliations":[],"preferred":false,"id":705364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snow, Kyle","contributorId":194786,"corporation":false,"usgs":false,"family":"Snow","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":705365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griswold, Kitty","contributorId":194787,"corporation":false,"usgs":false,"family":"Griswold","given":"Kitty","email":"","affiliations":[],"preferred":false,"id":705366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":147914,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":705367,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70193172,"text":"70193172 - 2017 - Otoliths","interactions":[],"lastModifiedDate":"2018-01-25T14:40:59","indexId":"70193172","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Otoliths","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Age and growth of fishes: Principles and techniques","language":"English","publisher":"American Fisheries Society","isbn":"978-1-934874-48-6","usgsCitation":"Long, J.M., and Grabowski, T.B., 2017, Otoliths, chap. <i>of</i> Age and growth of fishes: Principles and techniques.","ipdsId":"IP-078312","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":350626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350625,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/professional-and-trade/55078c/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6afac3e4b06e28e9c9a8e7","contributors":{"editors":[{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":725829,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":725830,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","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":718121,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70191191,"text":"70191191 - 2017 - Investigating impacts of oil and gas development on greater sage-grouse","interactions":[],"lastModifiedDate":"2017-10-02T13:54:33","indexId":"70191191","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","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":"Investigating impacts of oil and gas development on greater sage-grouse","docAbstract":"<p><span>The sagebrush (</span><i>Artemisia</i><span><span>&nbsp;</span>spp.) ecosystem is one of the largest ecosystems in western North America providing habitat for species found nowhere else. Sagebrush habitats have experienced dramatic declines since the 1950s, mostly due to anthropogenic disturbances. The greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>) is a sagebrush-obligate species that has experienced population declines over the last several decades, which are attributed to a variety of disturbances including the more recent threat of oil and gas development. We developed a hierarchical, Bayesian state-space model to investigate the impacts of 2 measures of oil and gas development, and environmental and habitat conditions, on sage-grouse populations in Wyoming, USA using male lek counts from 1984 to 2008. Lek attendance of male sage-grouse declined by approximately 2.5%/year and was negatively related to oil and gas well density. We found little support for the influence of sagebrush cover and precipitation on changes in lek counts. Our results support those of other studies reporting negative impacts of oil and gas development on sage-grouse populations and our modeling approach allowed us to make inference to a longer time scale and larger spatial extent than in previous studies. In addition to sage-grouse, development may also negatively affect other sagebrush-obligate species, and active management of sagebrush habitats may be necessary to maintain some species.<span>&nbsp;</span></span></p>","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21179","usgsCitation":"Green, A., Aldridge, C.L., and O’Donnell, M.S., 2017, Investigating impacts of oil and gas development on greater sage-grouse: Journal of Wildlife Management, v. 81, no. 1, p. 46-57, https://doi.org/10.1002/jwmg.21179.","productDescription":"12 p.","startPage":"46","endPage":"57","ipdsId":"IP-071286","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70193100,"text":"70193100 - 2017 - Geology and biostratigraphy of the Potomac River cliffs at Stratford Hall, Westmoreland County, Virginia","interactions":[],"lastModifiedDate":"2018-02-02T13:33:31","indexId":"70193100","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology and biostratigraphy of the Potomac River cliffs at Stratford Hall, Westmoreland County, Virginia","docAbstract":"<p><span>The cliffs along the Potomac River at Stratford Hall display extensive exposures of Miocene marine strata that belong successively to the Calvert, Choptank, St. Marys, and Eastover Formations. Within the lower part of this sequence, in the Calvert and Choptank Formations, there is well-developed cyclic stratigraphy. Above the Miocene units lies the marginal marine to deltaic Pleistocene Bacons Castle Formation, which is the highest and youngest formation exposed in the cliffs. The goals of this field trip guide are to (1) show the Miocene formations exposed in the cliffs and discuss the paleoenvironments within which they formed, (2) demonstrate the cyclicity in the Miocene marine formations and discuss its origin, (3) compare and contrast the section exposed at the Stratford and Nomini Cliffs with the classic Miocene Calvert Cliffs sequence exposed to the northeast in Calvert County, Maryland, and the Miocene sequence recovered in the Haynesville cores to the southeast in Richmond County, Virginia, (4) discuss and explain why a detailed correlation among these three places has been so difficult to attain, and (5) show typical lithologies of the Bacons Castle Formation and discuss the paleoenvironments in which they formed.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Blue Ridge to the Beach: Geological Field Excursions across Virginia","language":"English","publisher":"Geological Society of 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7586d9e4b00f54eb1d81f5","contributors":{"authors":[{"text":"Weems, Robert E. 0000-0002-1907-7804 rweems@usgs.gov","orcid":"https://orcid.org/0000-0002-1907-7804","contributorId":2663,"corporation":false,"usgs":true,"family":"Weems","given":"Robert","email":"rweems@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717986,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landacre, Bryan D. 0000-0002-0523-360X blandacre@usgs.gov","orcid":"https://orcid.org/0000-0002-0523-360X","contributorId":2722,"corporation":false,"usgs":true,"family":"Landacre","given":"Bryan","email":"blandacre@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717987,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189468,"text":"70189468 - 2017 - Replication and shedding kinetics of infectious hematopoietic necrosis virus in juvenile rainbow trout","interactions":[],"lastModifiedDate":"2018-03-26T12:20:32","indexId":"70189468","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3699,"text":"Virus Research","active":true,"publicationSubtype":{"id":10}},"title":"Replication and shedding kinetics of infectious hematopoietic necrosis virus in juvenile rainbow trout","docAbstract":"<p><span>Viral replication and shedding are key components of transmission and fitness, the kinetics of which are heavily dependent on virus, host, and environmental factors. To date, no studies have quantified the shedding kinetics of infectious hematopoietic necrosis virus (IHNV) in rainbow trout (</span><i>Oncorhynchus mykiss</i><span>), or how they are associated with replication, making it difficult to ascertain the transmission dynamics of this pathogen of high agricultural and conservation importance. Here, the replication and shedding kinetics of two M genogroup IHNV genotypes were examined in their naturally co-evolved rainbow trout host. Within host virus replication began rapidly, approaching maximum values by day 3 post-infection, after which viral load was maintained or gradually dropped through day 7. Host innate immune response measured as stimulation of Mx-1 gene expression generally followed within host viral loads. Shedding also began very quickly and peaked within 2</span><span>&nbsp;</span><span>days, defining a generally uniform early peak period of shedding from 1 to 4</span><span>&nbsp;</span><span>days after exposure to virus. This was followed by a post-peak period where shedding declined, such that the majority of fish were no longer shedding by day 12 post-infection. Despite similar kinetics, the average shedding rate over the course of infection was significantly lower in mixed compared to single genotype infections, suggesting a competition effect, however, this did not significantly impact the total amount of virus shed. The data also indicated that the duration of shedding, rather than peak amount of virus shed, was correlated with fish mortality. Generally, the majority of virus produced during infection appeared to be shed into the environment rather than maintained in the host, although there was more retention of within host virus during the post-peak period. Viral virulence was correlated with shedding, such that the more virulent of the two genotypes shed more total virus. This fundamental understanding of IHNV shedding kinetics and variation at the individual fish level could assist with management decisions about how to respond to disease outbreaks when they occur.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.virusres.2016.10.011","usgsCitation":"Wargo, A.R., Scott, R., Kerr, B., and Kurath, G., 2017, Replication and shedding kinetics of infectious hematopoietic necrosis virus in juvenile rainbow trout: Virus Research, v. 227, p. 200-211, https://doi.org/10.1016/j.virusres.2016.10.011.","productDescription":"12 p.","startPage":"200","endPage":"211","ipdsId":"IP-077881","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://scholarworks.wm.edu/vimsarticles/775","text":"Publisher Index Page"},{"id":343803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"227","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596886a0e4b0d1f9f05f59a1","contributors":{"authors":[{"text":"Wargo, Andrew R.","contributorId":47260,"corporation":false,"usgs":true,"family":"Wargo","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":704796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Robert J.","contributorId":45600,"corporation":false,"usgs":true,"family":"Scott","given":"Robert J.","affiliations":[],"preferred":false,"id":704797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kerr, Benjamin","contributorId":194626,"corporation":false,"usgs":false,"family":"Kerr","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":704798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":704799,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192402,"text":"70192402 - 2017 - Water quality and natural resources in the Green River Basin","interactions":[],"lastModifiedDate":"2018-02-02T13:29:57","indexId":"70192402","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Water quality and natural resources in the Green River Basin","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Water in Kentucky: Natural history, communities, and conservation","language":"English","publisher":"University Press of Kentucky","usgsCitation":"Lee, B.D., Williamson, T.N., and Crain, A.S., 2017, Water quality and natural resources in the Green River Basin, chap. <i>of</i> Water in Kentucky: Natural history, communities, and conservation, p. 133-150.","productDescription":"18 p.","startPage":"133","endPage":"150","ipdsId":"IP-046141","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":350972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":350971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.kentuckypress.com/live/title_detail.php?titleid=2917#.WnS7r7enFhE"}],"country":"United States","state":"Kentucky","otherGeospatial":"Green River Basin","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7586d9e4b00f54eb1d81f8","contributors":{"authors":[{"text":"Lee, Brad D.","contributorId":138937,"corporation":false,"usgs":false,"family":"Lee","given":"Brad","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":715703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crain, Angela S. 0000-0003-0969-6238 ascrain@usgs.gov","orcid":"https://orcid.org/0000-0003-0969-6238","contributorId":3090,"corporation":false,"usgs":true,"family":"Crain","given":"Angela","email":"ascrain@usgs.gov","middleInitial":"S.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70195834,"text":"70195834 - 2017 - A global analysis of traits predicting species sensitivity to habitat fragmentation","interactions":[],"lastModifiedDate":"2018-03-06T11:55:14","indexId":"70195834","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"A global analysis of traits predicting species sensitivity to habitat fragmentation","docAbstract":"<p><strong>Aim</strong></p><p>Elucidating patterns in species responses to habitat fragmentation is an important focus of ecology and conservation, but studies are often geographically restricted, taxonomically narrow or use indirect measures of species vulnerability. We investigated predictors of species presence after fragmentation using data from studies around the world that included all four terrestrial vertebrate classes, thus allowing direct inter-taxonomic comparison.</p><p><strong>Location</strong></p><p>World-wide.</p><p><strong>Methods</strong></p><p>We used generalized linear mixed-effect models in an information theoretic framework to assess the factors that explained species presence in remnant habitat patches (3342 patches; 1559 species, mostly birds; and 65,695 records of patch-specific presence–absence). We developed a novel metric of fragmentation sensitivity, defined as the maximum rate of change in probability of presence with changing patch size (‘Peak Change’), to distinguish between general rarity on the landscape and sensitivity to fragmentation per se.</p><p><strong>Results</strong></p><p>Size of remnant habitat patches was the most important driver of species presence. Across all classes, habitat specialists, carnivores and larger species had a lower probability of presence, and those effects were substantially modified by interactions. Sensitivity to fragmentation (measured by Peak Change) was influenced primarily by habitat type and specialization, but also by fecundity, life span and body mass. Reptiles were more sensitive than other classes. Grassland species had a lower probability of presence, though sample size was relatively small, but forest and shrubland species were more sensitive.</p><p><strong>Main conclusions</strong></p><p>Habitat relationships were more important than life-history characteristics in predicting the effects of fragmentation. Habitat specialization increased sensitivity to fragmentation and interacted with class and habitat type; forest specialists and habitat-specific reptiles were particularly sensitive to fragmentation. Our results suggest that when conservationists are faced with disturbances that could fragment habitat they should pay particular attention to specialists, particularly reptiles. Further, our results highlight that the probability of presence in fragmented landscapes and true sensitivity to fragmentation are predicted by different factors.</p>","language":"English","publisher":"Wiley","doi":"10.1111/geb.12509","usgsCitation":"Keinath, D., Doak, D.F., Hodges, K.E., Prugh, L.R., Fagan, W., Sekercioglu, C., Buchart, S.H., and Kauffman, M., 2017, A global analysis of traits predicting species sensitivity to habitat fragmentation: Global Ecology and Biogeography, v. 26, no. 1, p. 115-127, https://doi.org/10.1111/geb.12509.","productDescription":"13 p.","startPage":"115","endPage":"127","ipdsId":"IP-065257","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.12509","text":"Publisher Index Page"},{"id":352265,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-23","publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4d6","contributors":{"authors":[{"text":"Keinath, Douglas","contributorId":12747,"corporation":false,"usgs":true,"family":"Keinath","given":"Douglas","affiliations":[],"preferred":false,"id":730340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doak, Daniel F.","contributorId":46811,"corporation":false,"usgs":true,"family":"Doak","given":"Daniel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":730341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, Karen E.","contributorId":202978,"corporation":false,"usgs":false,"family":"Hodges","given":"Karen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":730342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prugh, Laura R. 0000-0001-9045-3107","orcid":"https://orcid.org/0000-0001-9045-3107","contributorId":196572,"corporation":false,"usgs":false,"family":"Prugh","given":"Laura","email":"","middleInitial":"R.","affiliations":[{"id":13194,"text":"School of Environmental and Forest Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":730343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":730344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sekercioglu, Cagan H.","contributorId":202979,"corporation":false,"usgs":false,"family":"Sekercioglu","given":"Cagan H.","affiliations":[],"preferred":false,"id":730345,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Buchart, Stuart H. M.","contributorId":202980,"corporation":false,"usgs":false,"family":"Buchart","given":"Stuart","email":"","middleInitial":"H. M.","affiliations":[],"preferred":false,"id":730346,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":189179,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":730218,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70192594,"text":"70192594 - 2017 - Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas","interactions":[],"lastModifiedDate":"2017-11-17T11:39:08","indexId":"70192594","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas","docAbstract":"<p><span>Since the beginning of the 20th century, the overall occupied range of the lesser prairie-chicken (</span><i>Tympanuchus pallidicinctus</i><span>) has declined by 84% commensurate with population trends. Much of this decline has been attributed to the loss and<span>&nbsp;</span><a title=\"Learn more about Fragmentation (cell biology)\" href=\"http://www.sciencedirect.com/topics/agricultural-and-biological-sciences/fragmentation-cell-biology\" data-mce-href=\"http://www.sciencedirect.com/topics/agricultural-and-biological-sciences/fragmentation-cell-biology\">fragmentation</a><span>&nbsp;</span>of native grasslands throughout the lesser prairie-chicken range. However, quantification of changes in land cover in the distribution of the lesser prairie-chicken is lacking. Our objectives were to (1) document changes in the areal extent and connectivity of grasslands in the identified lesser prairie-chicken range in Kansas, USA, (&gt;60% of extant lesser prairie-chicken population) from the 1950s to 2013 using remotely sensed data and (2) assess the potential of the Conservation Reserve Program (U.S. Department of Agriculture Program converting cropland to permanent cover; CRP) to mitigate grassland loss. Digital land cover maps were generated on a decadal time step through spectral classification of LANDSAT images and visual analysis of aerial photographs (1950s and 1960s). Landscape composition and configuration were assessed using FRAGSTATS to compute a variety of landscape metrics measuring changes in the amount of grassland present as well as changes in the size and configuration of grassland patches. With the exception of a single regional portion of the range, nearly all of the grassland converted to cropland in the lesser prairie-chicken range of Kansas occurred prior to the 1950s. Prior to the implementation of CRP, the amount of grassland decreased 3.6% between the 1950s and 1985 from 18,455 km</span><sup>2</sup><span><span>&nbsp;</span>to 17,788 km</span><sup>2</sup><span>. Since 1985, the overall amount of grassland in the lesser prairie-chicken range has increased 11.9% to 19,898 km</span><sup>2</sup><span><span>&nbsp;</span>due to implementation of CRP, although the area of grassland decreased between 1994 and 2013 as CRP contracts were not renewed by landowners. Since 1986 grassland in Kansas became more connected and less fragmented in response to the CRP. While the CRP has been successful in increasing grassland quantity and connectivity throughout the lesser prairie-chicken range in Kansas, offsetting loss of grassland since the 1950s, abundance and occupied range of lesser prairie-chickens has declined since the 1980s, suggesting that habitat quality is the principal factor influencing population demography of the species. Although the CRP is contributing to conservation actions for lesser prairie-chickens, efforts to improve habitat quality throughout the range of the lesser prairie-chicken are likely necessary to meet management goals. Continuation of the CRP faces an uncertain future in the face of rising commodity prices, energy development, and reduction in program scope, leaving open the possibility that these areas that have created habitat for lesser prairie-chickens could be lost.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2016.11.004","usgsCitation":"Haukos, D.A., Spencer, D., Hagen, C.A., Daniels, M.D., and Goodin, D., 2017, Conservation Reserve Program mitigates grassland loss in the lesser prairie-chicken range of Kansas: Global Ecology and Conservation, v. 9, p. 21-38, https://doi.org/10.1016/j.gecco.2016.11.004.","productDescription":"18 p.","startPage":"21","endPage":"38","ipdsId":"IP-078839","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470169,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2016.11.004","text":"Publisher Index Page"},{"id":349063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -102.01904296874999,\n              36.96744946416934\n            ],\n            [\n              -97.8662109375,\n              36.96744946416934\n            ],\n            [\n              -97.8662109375,\n              40.027614437486655\n            ],\n            [\n              -102.01904296874999,\n              40.027614437486655\n            ],\n            [\n              -102.01904296874999,\n              36.96744946416934\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23c02","contributors":{"authors":[{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spencer, David","contributorId":200553,"corporation":false,"usgs":false,"family":"Spencer","given":"David","affiliations":[],"preferred":false,"id":722646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":722647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Melinda D.","contributorId":166701,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":722648,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goodin, Doug","contributorId":200554,"corporation":false,"usgs":false,"family":"Goodin","given":"Doug","email":"","affiliations":[],"preferred":false,"id":722649,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196074,"text":"70196074 - 2017 - Geologic map of the Bateman Spring Quadrangle, Lander County, Nevada","interactions":[],"lastModifiedDate":"2018-03-16T10:47:54","indexId":"70196074","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5655,"text":"Nevada Bureau of Mines and Geology Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"185","title":"Geologic map of the Bateman Spring Quadrangle, Lander County, Nevada","docAbstract":"<p><span>This 1:24,000-scale geologic map of the Bateman Spring 7.5-minute quadrangle in Lander County, Nevada contains descriptions of 24 geologic units and one cross section. Accompanying text includes full unit descriptions and references. This quadrangle includes lower Paleozoic siliciclastic sedimentary rocks of the Roberts Mountain allochthon, Miocene intrusive dikes, alluvial deposits of the northern Shoshone Range piedmont, and riverine deposits of the Reese and Humboldt rivers.</span><br><br><span>Significant findings include: refined age estimates for the Ordovician-Cambrian Valmy Formation and Devonian Slaven Chert, based on new fossil information; and detailed mapping of late Quaternary fault traces along the Shoshone Range fault system.</span></p>","language":"English","publisher":"Nevada Bureau of Mines and Geology","usgsCitation":"Ramelli, A.R., Wrucke, C.T., and House, K., 2017, Geologic map of the Bateman Spring Quadrangle, Lander County, Nevada: Nevada Bureau of Mines and Geology Map 185.","ipdsId":"IP-093650","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352586,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.nbmg.unr.edu/CDP-Geol-Bateman-Spring-quad-p/m185z.htm"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8ebe4b0da30c1bfc4d0","contributors":{"authors":[{"text":"Ramelli, Alan R.","contributorId":203345,"corporation":false,"usgs":false,"family":"Ramelli","given":"Alan","email":"","middleInitial":"R.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":731215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wrucke, Chester T.","contributorId":203346,"corporation":false,"usgs":false,"family":"Wrucke","given":"Chester","email":"","middleInitial":"T.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":731216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":731214,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193645,"text":"70193645 - 2017 - Model-based estimators of density and connectivity to inform conservation of spatially structured populations","interactions":[],"lastModifiedDate":"2017-11-13T14:46:24","indexId":"70193645","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Model-based estimators of density and connectivity to inform conservation of spatially structured populations","docAbstract":"<p><span>Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1623","usgsCitation":"Morin, D.J., Fuller, A.K., Royle, J., and Sutherland, C., 2017, Model-based estimators of density and connectivity to inform conservation of spatially structured populations: Ecosphere, v. 8, no. 1, p. 1-16, https://doi.org/10.1002/ecs2.1623.","productDescription":"e01623; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-075226","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470168,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1623","text":"Publisher Index Page"},{"id":348721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-19","publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bee","contributors":{"authors":[{"text":"Morin, Dana J.","contributorId":200306,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721855,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139623,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sutherland, Chris","contributorId":150670,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[],"preferred":false,"id":721856,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192567,"text":"70192567 - 2017 - Fish assemblages","interactions":[],"lastModifiedDate":"2018-01-26T14:20:55","indexId":"70192567","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Fish assemblages","docAbstract":"<p><span>Methods to sample fishes in stream ecosystems and to analyze the raw data, focusing primarily on assemblage-level (all fish species combined) analyses, are presented in this chapter. We begin with guidance on sample site selection, permitting for fish collection, and information-gathering steps to be completed prior to conducting fieldwork. Basic sampling methods (visual surveying, electrofishing, and seining) are presented with specific instructions for estimating population sizes via visual, capture-recapture, and depletion surveys, in addition to new guidance on environmental DNA (eDNA) methods. Steps to process fish specimens in the field including the use of anesthesia and preservation of whole specimens or tissue samples (for genetic or stable isotope analysis) are also presented. Data analysis methods include characterization of size-structure within populations, estimation of species richness and diversity, and application of fish functional traits. We conclude with three advanced topics in assemblage-level analysis: multidimensional scaling (MDS), ecological networks, and loop analysis.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods in stream ecology, 3rd Edition","language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-12-416558-8.00016-0","isbn":"9780124165588","usgsCitation":"McGarvey, D.J., Falke, J.A., Li, H.W., and Li, J., 2017, Fish assemblages, chap. <i>of</i> Methods in stream ecology, 3rd Edition, p. 321-353, https://doi.org/10.1016/B978-0-12-416558-8.00016-0.","productDescription":"33 p.","startPage":"321","endPage":"353","ipdsId":"IP-070364","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":350703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6c4c95e4b06e28e9cabb04","contributors":{"editors":[{"text":"Hauer, F. Richard","contributorId":189116,"corporation":false,"usgs":false,"family":"Hauer","given":"F.","email":"","middleInitial":"Richard","affiliations":[],"preferred":false,"id":725976,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lamberti, G. A.","contributorId":44229,"corporation":false,"usgs":false,"family":"Lamberti","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":725977,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"McGarvey, Daniel J.","contributorId":201505,"corporation":false,"usgs":false,"family":"McGarvey","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":725973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Hiram W.","contributorId":18724,"corporation":false,"usgs":true,"family":"Li","given":"Hiram","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":725974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Judith","contributorId":74622,"corporation":false,"usgs":true,"family":"Li","given":"Judith","email":"","affiliations":[],"preferred":false,"id":725975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70192670,"text":"70192670 - 2017 - Post-rift magmatic evolution of the eastern North American “passive-aggressive” margin","interactions":[],"lastModifiedDate":"2017-11-29T13:55:13","indexId":"70192670","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Post-rift magmatic evolution of the eastern North American “passive-aggressive” margin","docAbstract":"<p><span>Understanding the evolution of passive margins requires knowledge of temporal and chemical constraints on magmatism following the transition from supercontinent to rifting, to post-rifting evolution. The Eastern North American Margin (ENAM) is an ideal study location as several magmatic pulses occurred in the 200 My following rifting. In particular, the Virginia-West Virginia region of the ENAM has experienced two postrift magmatic pulses at ∼152 Ma and 47 Ma, and thus provides a unique opportunity to study the long-term magmatic evolution of passive margins. Here we present a comprehensive set of geochemical data that includes new&nbsp;</span><sup>40</sup><span>Ar/</span><sup>39</sup><span>Ar ages, major and trace-element compositions, and analysis of radiogenic isotopes to further constrain their magmatic history. The Late Jurassic volcanics are bimodal, from basanites to phonolites, while the Eocene volcanics range from picrobasalt to rhyolite. Modeling suggests that the felsic volcanics from both the Late Jurassic and Eocene events are consistent with fractional crystallization. Sr-Nd-Pb systematics for the Late Jurassic event suggests HIMU and EMII components in the magma source that we interpret as upper mantle components rather than crustal interaction. Lithospheric delamination is the best hypothesis for magmatism in Virginia/West Virginia, due to tectonic instabilities that are remnant from the long-term evolution of this margin, resulting in a “passive-aggressive” margin that records multiple magmatic events long after rifting ended.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GC006646","usgsCitation":"Mazza, S.E., Gazel, E., Johnson, E.A., Bizmis, M., McAleer, R., and Biryol, C.B., 2017, Post-rift magmatic evolution of the eastern North American “passive-aggressive” margin: Geochemistry, Geophysics, Geosystems, v. 18, no. 1, p. 3-22, https://doi.org/10.1002/2016GC006646.","productDescription":"20 p.","startPage":"3","endPage":"22","ipdsId":"IP-079810","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":349550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.6667,\n              38.1667\n            ],\n            [\n              -78.6667,\n              38.1667\n            ],\n            [\n              -78.6667,\n              38.6667\n            ],\n            [\n              -79.6667,\n              38.6667\n            ],\n            [\n              -79.6667,\n              38.1667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-09","publicationStatus":"PW","scienceBaseUri":"5a60fc3de4b06e28e9c23bff","contributors":{"authors":[{"text":"Mazza, Sarah E. 0000-0001-8091-1186","orcid":"https://orcid.org/0000-0001-8091-1186","contributorId":198664,"corporation":false,"usgs":false,"family":"Mazza","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gazel, Esteban","contributorId":192876,"corporation":false,"usgs":false,"family":"Gazel","given":"Esteban","email":"","affiliations":[],"preferred":false,"id":716691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Elizabeth A. 0000-0001-7244-6122","orcid":"https://orcid.org/0000-0001-7244-6122","contributorId":198665,"corporation":false,"usgs":false,"family":"Johnson","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bizmis, Michael 0000-0002-4611-6928","orcid":"https://orcid.org/0000-0002-4611-6928","contributorId":198666,"corporation":false,"usgs":false,"family":"Bizmis","given":"Michael","email":"","affiliations":[],"preferred":false,"id":716693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":5301,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan J.","email":"rmcaleer@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":716689,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biryol, C. Berk","contributorId":198667,"corporation":false,"usgs":false,"family":"Biryol","given":"C.","email":"","middleInitial":"Berk","affiliations":[],"preferred":false,"id":716694,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70192516,"text":"70192516 - 2017 - Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","interactions":[],"lastModifiedDate":"2017-10-26T13:45:42","indexId":"70192516","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens","docAbstract":"<p><span>Loss of native grasslands by anthropogenic disturbances has reduced availability and connectivity of habitat for many grassland species. A primary threat to contiguous grasslands is the encroachment of woody vegetation, which is spurred by disturbances that take on many forms from energy development, fire suppression, and grazing. These disturbances are exacerbated by natural- and human-driven cycles of changes in climate punctuated by drought and desertification&nbsp;conditions. Encroachment of honey mesquite&nbsp;</span><i>(Prosopis glandulosa)</i><span><span>&nbsp;</span>into the prairies of southeastern New Mexico has potentially limited habitat for numerous grassland species, including lesser prairie-chickens<span>&nbsp;</span></span><i>(Tympanuchus pallidicinctus)</i><span>. To determine the magnitude of impacts of distribution of mesquite and how lesser prairie-chickens respond to mesquite presence on the landscape in southeastern New Mexico, we evaluated seasonal space use of lesser prairie-chickens in the breeding and nonbreeding seasons. We derived several remotely sensed spatial metrics to characterize the distribution of mesquite. We then used these data to create population-level resource utilization functions and predict intensity of use of lesser prairie-chickens across our study area. Home ranges were smaller in the breeding season compared with the nonbreeding season; however, habitat use was similar across seasons. During both seasons, lesser prairie-chickens used areas closer to leks and largely avoided areas with mesquite. Relative to the breeding season, during the nonbreeding season habitat use suggested a marginal increase in mesquite within areas of low intensity of use, yet aversion to mesquite was strong in areas of medium to high intensity of use. To our knowledge, our study is the first to demonstrate a negative behavioral response by lesser prairie-chickens to woody encroachment in native grasslands. To mitigate one of the possible limiting factors for lesser prairie-chickens, we suggest future conservation strategies be employed by<span> land managersto</span>&nbsp;reduce mesquite abundance in the southern portion of their current range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2016.09.006","usgsCitation":"Boggie, M.A., Strong, C.R., Lusk, D., Carleton, S.A., Gould, W., Howard, R.L., Nichols, C.T., Falkowski, M.J., and Hagen, C.A., 2017, Impacts of mesquite distribution on seasonal space use of lesser prairie-chickens: Rangeland Ecology and Management, v. 70, no. 1, p. 68-77, https://doi.org/10.1016/j.rama.2016.09.006.","productDescription":"10 p.","startPage":"68","endPage":"77","ipdsId":"IP-073814","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.09.006","text":"Publisher Index 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T.","contributorId":193024,"corporation":false,"usgs":false,"family":"Nichols","given":"Clay","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":716415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Falkowski, Michael J.","contributorId":198547,"corporation":false,"usgs":false,"family":"Falkowski","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716416,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716417,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
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