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,{"id":70046363,"text":"70046363 - 2012 - Upper Klamath Basin Landsat Image for October 16, 2004: Path 44 Row 31","interactions":[],"lastModifiedDate":"2013-06-10T13:25:12","indexId":"70046363","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for October 16, 2004: Path 44 Row 31","docAbstract":"This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046363","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for October 16, 2004: Path 44 Row 31, Dataset, https://doi.org/10.3133/70046363.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273540,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/erosl1t_10162004_p44r31_l5_usgs_NAD83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6f570e4b0097a7158e62f","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479556,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70042454,"text":"70042454 - 2012 - Design of future surveys","interactions":[],"lastModifiedDate":"2022-12-21T17:12:40.458852","indexId":"70042454","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"13","title":"Design of future surveys","docAbstract":"<p>This brief chapter addresses two related issues: how effort should be allocated to different parts of the sampling plan and, given optimal allocation, how large a sample will be required to achieve the PRISM accuracy target. Simulations based on data collected to date showed that 2 plots per cluster on rapid surveys, 2 intensive camps per field crew-year, 2-4 intensive plots per intensive camp, and 2-3 rapid surveys per intensive plot is the most efficient allocation of resources. Using this design, we investigated how crew-years should be allocated to each region in order to meet the PRISM accuracy target most efficiently. The analysis indicated that 40-50 crew-years would achieve the accuracy target for 18-24 of the 26 species breeding widely in the Arctic. This analysis was based on assuming that two rounds of surveys were conducted and that a 50% decline occurred between them. We discuss the complexity of making these estimates and why they should be viewed as first approximations.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Arctic shorebirds in North America: A decade of monitoring","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","usgsCitation":"Bart, J., and Smith, P., 2012, Design of future surveys, chap. 13 <i>of</i> Arctic shorebirds in North America: A decade of monitoring, v. 44, p. 201-210.","productDescription":"9 p.","startPage":"201","endPage":"210","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025859","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268317,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297351,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273108"}],"volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5455e4b0b290850f5ab8","contributors":{"editors":[{"text":"Bart, Jonathan R.","contributorId":74273,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":509162,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Johnston, Victoria H.","contributorId":70667,"corporation":false,"usgs":true,"family":"Johnston","given":"Victoria","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":509161,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":471579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Paul A.","contributorId":73477,"corporation":false,"usgs":true,"family":"Smith","given":"Paul A.","affiliations":[],"preferred":false,"id":471580,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042461,"text":"70042461 - 2012 - Appendix A: other methods for estimating trends of Arctic birds","interactions":[],"lastModifiedDate":"2015-01-16T11:18:45","indexId":"70042461","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Appendix A: other methods for estimating trends of Arctic birds","docAbstract":"<p>The Arctic PRISM was designed to determine shorebird population size and trend. During an extensive peer review of PRISM, some reviewers suggested that measuring demographic rates or monitoring shorebirds on migration would be more appropriate than estimating population size on the breeding grounds. However, each method has its own limitations. For demographic monitoring, an unbiased estimate based on a large sample of first-year survivorship would be extremely difficult for shorebirds in the arctic because the needed sample size would be unobtainable (in Canada at least) and the level of effort that would need to be expended (both financial and human resource-wise) would far exceed that of the current Arctic PRISM methodology. For migration monitoring, issues such as changes in use of monitored to non-monitored sites, residency times, and detection rates introduce bias that has not yet been resolved. While we believe demographic and migration monitoring are very valuable and are already components of the PRISM approach (e.g., Tier 2 sites focus on the collection of demographic data), we do not believe that either is likely to achieve the PRISM accuracy target of an 80% power to detect a 50% decline.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Arctic shorebirds in North America: a decade of monitoring","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","usgsCitation":"Bart, J., Brown, S., Morrison, R., and Smith, P., 2012, Appendix A: other methods for estimating trends of Arctic birds, chap. <i>of</i> Arctic shorebirds in North America: a decade of monitoring, v. 44, p. 245-251.","productDescription":"7 p.","startPage":"245","endPage":"251","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025683","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":268355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297339,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273108"}],"volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4d8ee4b0b290850f18e4","contributors":{"editors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":509163,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Johnston, Victoria","contributorId":90185,"corporation":false,"usgs":true,"family":"Johnston","given":"Victoria","affiliations":[],"preferred":false,"id":509164,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":471591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Stephen","contributorId":40096,"corporation":false,"usgs":true,"family":"Brown","given":"Stephen","affiliations":[],"preferred":false,"id":471589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, R.I. Guy","contributorId":52003,"corporation":false,"usgs":true,"family":"Morrison","given":"R.I. Guy","affiliations":[],"preferred":false,"id":471590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Paul A.","contributorId":73477,"corporation":false,"usgs":true,"family":"Smith","given":"Paul A.","affiliations":[],"preferred":false,"id":471592,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70156874,"text":"70156874 - 2012 - Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs","interactions":[],"lastModifiedDate":"2015-08-31T16:53:52","indexId":"70156874","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs","docAbstract":"<p><span>Variance components may play multiple roles (cf. Cox and Solomon 2003). First, magnitudes and relative magnitudes of the variances of random factors may have important scientific and management value in their own right. For example, variation in levels of invasive vegetation among and within lakes may suggest causal agents that operate at both spatial scales &ndash; a finding that may be important for scientific and management reasons. Second, variance components may also be of interest when they affect precision of means and covariate coefficients. For example, variation in the effect of water depth on the probability of aquatic plant presence in a study of multiple lakes may vary by lake. This variation will affect the precision of the average depth-presence association. Third, variance component estimates may be used when designing studies, including monitoring programs. For example, to estimate the numbers of years and of samples per year required to meet long-term monitoring goals, investigators need estimates of within and among-year variances. Other chapters in this volume (Chapters 7, 8, and 10) as well as extensive external literature outline a framework for applying estimates of variance components to the design of monitoring efforts. For example, a series of papers with an ecological monitoring theme examined the relative importance of multiple sources of variation, including variation in means among sites, years, and site-years, for the purposes of temporal trend detection and estimation (Larsen et al. 2004, and references therein).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Design and analysis of long-term ecological monitoring studies","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge; New York","doi":"10.1017/CBO9781139022422.013","usgsCitation":"Gray, B.R., 2012, Variance components estimation for continuous and discrete data, with emphasis on cross-classified sampling designs, chap. <i>of</i> Design and analysis of long-term ecological monitoring studies, p. 200-227, https://doi.org/10.1017/CBO9781139022422.013.","productDescription":"28 p.","startPage":"200","endPage":"227","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":307764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb71ae4b058f706e53f84","contributors":{"editors":[{"text":"Gitzen, Robert A.","contributorId":75498,"corporation":false,"usgs":true,"family":"Gitzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":570915,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":570916,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Cooper, Andrew B.","contributorId":112048,"corporation":false,"usgs":true,"family":"Cooper","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":570917,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Licht, Daniel S.","contributorId":113213,"corporation":false,"usgs":true,"family":"Licht","given":"Daniel S.","affiliations":[],"preferred":false,"id":570918,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":570914,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70154812,"text":"70154812 - 2012 - Exploring similarities among many species distributions","interactions":[],"lastModifiedDate":"2015-08-20T11:25:31","indexId":"70154812","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring similarities among many species distributions","docAbstract":"<p><span>Collecting species presence data and then building models to predict species distribution has been long practiced in the field of ecology for the purpose of improving our understanding of species relationships with each other and with the environment. Due to limitations of computing power as well as limited means of using modeling software on HPC facilities, past species distribution studies have been unable to fully explore diverse data sets. We build a system that can, for the first time to our knowledge, leverage HPC to support effective exploration of species similarities in distribution as well as their dependencies on common environmental conditions. Our system can also compute and reveal uncertainties in the modeling results enabling domain experts to make informed judgments about the data. Our work was motivated by and centered around data collection efforts within the Great Smoky Mountains National Park that date back to the 1940s. Our findings present new research opportunities in ecology and produce actionable field-work items for biodiversity management personnel to include in their planning of daily management activities.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond","conferenceDate":"July 16-20, 2012","conferenceLocation":"Chicago, IL","language":"English","publisher":"ACM","doi":"10.1145/2335755.2335835","usgsCitation":"Simmerman, S., Wang, J., Osborne, J., Shook, K., Huang, J., Godsoe, W., and Simons, T.R., 2012, Exploring similarities among many species distributions, <i>in</i> Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond, Chicago, IL, July 16-20, 2012, art38, https://doi.org/10.1145/2335755.2335835.","productDescription":"art38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038608","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":307001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2012-07-16","publicationStatus":"PW","scienceBaseUri":"55d6fa32e4b0518e3546bc3a","contributors":{"authors":[{"text":"Simmerman, Scott","contributorId":146748,"corporation":false,"usgs":false,"family":"Simmerman","given":"Scott","email":"","affiliations":[],"preferred":false,"id":568863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Jingyuan","contributorId":10771,"corporation":false,"usgs":false,"family":"Wang","given":"Jingyuan","email":"","affiliations":[],"preferred":false,"id":568864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osborne, James","contributorId":92188,"corporation":false,"usgs":true,"family":"Osborne","given":"James","email":"","affiliations":[],"preferred":false,"id":568865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shook, Kimberly","contributorId":146749,"corporation":false,"usgs":false,"family":"Shook","given":"Kimberly","email":"","affiliations":[],"preferred":false,"id":568866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hu, Jia","contributorId":146750,"corporation":false,"usgs":false,"family":"Hu","given":"Jia","affiliations":[],"preferred":false,"id":568867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Godsoe, William","contributorId":131175,"corporation":false,"usgs":false,"family":"Godsoe","given":"William","email":"","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":568868,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564226,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70159358,"text":"70159358 - 2012 - Maximizing the utility of monitoring to the adaptive management of natural resources","interactions":[],"lastModifiedDate":"2021-10-21T15:36:09.17483","indexId":"70159358","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Maximizing the utility of monitoring to the adaptive management of natural resources","docAbstract":"<p><span>Data collection is an important step in any investigation about the structure or processes related to a natural system. In a purely scientific investigation (experiments, quasi-experiments, observational studies), data collection is part of the scientific method, preceded by the identification of hypotheses and the design of any manipulations of the system to test those hypotheses. Data collection and the manipulations that precede it are ideally designed to maximize the information that is derived from the study. That is, such investigations should be designed for maximum power to evaluate the relative validity of the hypotheses posed. When data collection is intended to inform the management of ecological systems, we call it monitoring. Note that our definition of monitoring encompasses a broader range of data-collection efforts than some alternative definitions &ndash; e.g. Chapter 3. The purpose of monitoring as we use the term can vary, from surveillance or &ldquo;thumb on the pulse&rdquo; monitoring (see Nichols and Williams 2006), intended to detect changes in a system due to any non-specified source (e.g. the North American Breeding Bird Survey), to very specific and targeted monitoring of the results of specific management actions (e.g. banding and aerial survey efforts related to North American waterfowl harvest management). Although a role of surveillance monitoring is to detect unanticipated changes in a system, the same result is possible from a collection of targeted monitoring programs distributed across the same spatial range (Box 4.1). In the face of limited budgets and many specific management questions, tying monitoring as closely as possible to management needs is warranted (Nichols and Williams 2006). Adaptive resource management (ARM; Walters 1986, Williams 1997, Kendall 2001, Moore and Conroy 2006, McCarthy and Possingham 2007, Conroy et al. 2008a) provides a context and specific purpose for monitoring: to evaluate decisions with respect to achievement of specific management objectives; and to evaluate the relative validity of predictive system models. This latter purpose is analogous to the role of data collection within the scientific method, in a research context.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Design and analysis of long-term ecological monitoring studies","language":"English","publisher":"Cambridge University Press","publisherLocation":"Cambridge; New York","doi":"10.1017/CBO9781139022422.007","usgsCitation":"Kendall, W.L., and Moore, C., 2012, Maximizing the utility of monitoring to the adaptive management of natural resources, chap. <i>of</i> Design and analysis of long-term ecological monitoring studies, p. 74-98, https://doi.org/10.1017/CBO9781139022422.007.","productDescription":"24 p.","startPage":"74","endPage":"98","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028880","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":310570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562a08d8e4b011227bf1fd8a","contributors":{"editors":[{"text":"Gitzen, Robert A.","contributorId":75498,"corporation":false,"usgs":true,"family":"Gitzen","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":578197,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cooper, Andrew B.","contributorId":112048,"corporation":false,"usgs":true,"family":"Cooper","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":578198,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Millspaugh, Joshua J.","contributorId":11141,"corporation":false,"usgs":false,"family":"Millspaugh","given":"Joshua J.","affiliations":[],"preferred":false,"id":578199,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Licht, Daniel S.","contributorId":113213,"corporation":false,"usgs":true,"family":"Licht","given":"Daniel S.","affiliations":[],"preferred":false,"id":578200,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":578195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T.","contributorId":9767,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton T.","affiliations":[],"preferred":false,"id":578196,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70035463,"text":"70035463 - 2012 - GONe: Software for estimating effective population size in species with generational overlap","interactions":[],"lastModifiedDate":"2020-11-23T17:10:47.117736","indexId":"70035463","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"GONe: Software for estimating effective population size in species with generational overlap","docAbstract":"<p>GONe is a user‐friendly, Windows‐based program for estimating effective size (N<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><i></i></span><sub>e</sub>) in populations with overlapping generations. It uses the Jorde–Ryman modification to the temporal method to account for age structure in populations. This method requires estimates of age‐specific survival and birth rate and allele frequencies measured in two or more consecutive cohorts. Allele frequencies are acquired by reading in genotypic data from files formatted for either GENEPOP or TEMPOFS. For each interval between consecutive cohorts, Ne is estimated at each locus and over all loci. Furthermore, Ne estimates are output for three different genetic drift estimators (<i>F</i><sub><i>s</i></sub><span>,&nbsp;</span><i>F</i><sub><i>c</i></sub><span>&nbsp;and&nbsp;</span><i>F</i><sub><i>k</i></sub>). Confidence intervals are derived from a chi‐square distribution with degrees of freedom equal to the number of independent alleles. GONe has been validated over a wide range of Ne values, and for scenarios where survival and birth rates differ between sexes, sex ratios are unequal and reproductive variances differ.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1755-0998.2011.03057.x","issn":"1755098X","usgsCitation":"Coombs, J., Letcher, B., and Nislow, K., 2012, GONe: Software for estimating effective population size in species with generational overlap: Molecular Ecology Resources, v. 12, no. 1, p. 160-163, https://doi.org/10.1111/j.1755-0998.2011.03057.x.","productDescription":"4 p.","startPage":"160","endPage":"163","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":242880,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215106,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1755-0998.2011.03057.x"}],"volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-08-09","publicationStatus":"PW","scienceBaseUri":"505a1478e4b0c8380cd54a4d","contributors":{"authors":[{"text":"Coombs, J.A.","contributorId":91295,"corporation":false,"usgs":true,"family":"Coombs","given":"J.A.","affiliations":[],"preferred":false,"id":450790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, B. H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":48132,"corporation":false,"usgs":true,"family":"Letcher","given":"B.","middleInitial":"H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":450788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nislow, K.H.","contributorId":66477,"corporation":false,"usgs":true,"family":"Nislow","given":"K.H.","affiliations":[],"preferred":false,"id":450789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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