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  • 1
    Publication Date: 2015-06-06
    Description: Indices of abundance are the bedrock for stock assessments or empirical management procedures used to manage fishery catches for fish populations worldwide, and are generally obtained by processing catch-rate data. Recent research suggests that geostatistical models can explain a substantial portion of variability in catch rates via the location of samples (i.e. whether located in high- or low-density habitats), and thus use available catch-rate data more efficiently than conventional "design-based" or stratified estimators. However, the generality of this conclusion is currently unknown because geostatistical models are computationally challenging to simulation-test and have not previously been evaluated using multiple species. We develop a new maximum likelihood estimator for geostatistical index standardization, which uses recent improvements in estimation for Gaussian random fields. We apply the model to data for 28 groundfish species off the U.S. West Coast and compare results to a previous "stratified" index standardization model, which accounts for spatial variation using post-stratification of available data. This demonstrates that the stratified model generates a relative index with 60% larger estimation intervals than the geostatistical model. We also apply both models to simulated data and demonstrate (i) that the geostatistical model has well-calibrated confidence intervals (they include the true value at approximately the nominal rate), (ii) that neither model on average under- or overestimates changes in abundance, and (iii) that the geostatistical model has on average 20% lower estimation errors than a stratified model. We therefore conclude that the geostatistical model uses survey data more efficiently than the stratified model, and therefore provides a more cost-efficient treatment for historical and ongoing fish sampling data.
    Print ISSN: 1054-3139
    Electronic ISSN: 1095-9289
    Topics: Biology , Geosciences , Physics
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  • 2
    Publication Date: 2016-02-26
    Description: Better understanding of variation in growth will always be an important problem in ecology, since variation in growth can have substantial consequences for ecological and evolutionary dynamics. Individual variation in growth can arise from a variety of processes; for example, individuals within a population vary in their intrinsic metabolic rates and behavioral traits, which may influence their foraging dynamics and access to resources. However, when adopting a growth model, we face trade-offs between model complexity, biological interpretability of parameters, and goodness of fit. We explore how different formulations of the von Bertalanffy Growth Function (vBGF) with individual random effects and environmental predictors affect these trade-offs. In the vBGF, the growth of an organism results from a dynamic balance between anabolic and catabolic processes. We start from a formulation of the vBGF that models the anabolic coefficient ( q ) as a function of the catabolic coefficient (κ), a coefficient related to the properties of the environment (γ) and a parameter that determines the relative importance of behavior and environment in determining growth (Ψ). We treat the vBGF parameters as a function of individual random effects and environmental variables. We use simulations to show how different functional forms and individual or group variability in the growth function's parameters provide a very flexible description of growth trajectories. We then consider a case study of two fish populations of Salmo marmoratus and Salmo trutta to test the goodness of fit and predictive power of the models, along with the biological interpretability of vBGF's parameters when using different model formulations. The best models, according to AIC, included individual variability in both κ and γand cohort as predictor of growth trajectories, and are consistent with the hypothesis that habitat selection is more important than behavioral and metabolic traits in determining lifetime growth trajectories of the two fish species. Model predictions of individual growth trajectories were largely more accurate than predictions based on mean size-at-age of fish. Our method shares information across individuals, and thus, for both the marble and brown trout populations investigated, allows using a single measurement early in the life of individual fish or cohort to obtain accurate predictions of lifetime individual or cohort size-at-age. This article is protected by copyright. All rights reserved.
    Print ISSN: 1051-0761
    Electronic ISSN: 1939-5582
    Topics: Biology
    Published by Wiley on behalf of The Ecological Society of America (ESA).
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  • 3
    Publication Date: 2014-09-18
    Description: Analytical Chemistry DOI: 10.1021/ac5026418
    Print ISSN: 0003-2700
    Electronic ISSN: 1520-6882
    Topics: Chemistry and Pharmacology
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  • 4
    Publication Date: 2003-04-12
    Description: DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. This approach enabled the discovery of candidate genes for developmental diseases including autism.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882961/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882961/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Scherer, Stephen W -- Cheung, Joseph -- MacDonald, Jeffrey R -- Osborne, Lucy R -- Nakabayashi, Kazuhiko -- Herbrick, Jo-Anne -- Carson, Andrew R -- Parker-Katiraee, Layla -- Skaug, Jennifer -- Khaja, Razi -- Zhang, Junjun -- Hudek, Alexander K -- Li, Martin -- Haddad, May -- Duggan, Gavin E -- Fernandez, Bridget A -- Kanematsu, Emiko -- Gentles, Simone -- Christopoulos, Constantine C -- Choufani, Sanaa -- Kwasnicka, Dorota -- Zheng, Xiangqun H -- Lai, Zhongwu -- Nusskern, Deborah -- Zhang, Qing -- Gu, Zhiping -- Lu, Fu -- Zeesman, Susan -- Nowaczyk, Malgorzata J -- Teshima, Ikuko -- Chitayat, David -- Shuman, Cheryl -- Weksberg, Rosanna -- Zackai, Elaine H -- Grebe, Theresa A -- Cox, Sarah R -- Kirkpatrick, Susan J -- Rahman, Nazneen -- Friedman, Jan M -- Heng, Henry H Q -- Pelicci, Pier Giuseppe -- Lo-Coco, Francesco -- Belloni, Elena -- Shaffer, Lisa G -- Pober, Barbara -- Morton, Cynthia C -- Gusella, James F -- Bruns, Gail A P -- Korf, Bruce R -- Quade, Bradley J -- Ligon, Azra H -- Ferguson, Heather -- Higgins, Anne W -- Leach, Natalia T -- Herrick, Steven R -- Lemyre, Emmanuelle -- Farra, Chantal G -- Kim, Hyung-Goo -- Summers, Anne M -- Gripp, Karen W -- Roberts, Wendy -- Szatmari, Peter -- Winsor, Elizabeth J T -- Grzeschik, Karl-Heinz -- Teebi, Ahmed -- Minassian, Berge A -- Kere, Juha -- Armengol, Lluis -- Pujana, Miguel Angel -- Estivill, Xavier -- Wilson, Michael D -- Koop, Ben F -- Tosi, Sabrina -- Moore, Gudrun E -- Boright, Andrew P -- Zlotorynski, Eitan -- Kerem, Batsheva -- Kroisel, Peter M -- Petek, Erwin -- Oscier, David G -- Mould, Sarah J -- Dohner, Hartmut -- Dohner, Konstanze -- Rommens, Johanna M -- Vincent, John B -- Venter, J Craig -- Li, Peter W -- Mural, Richard J -- Adams, Mark D -- Tsui, Lap-Chee -- 38103/Canadian Institutes of Health Research/Canada -- P01 GM061354/GM/NIGMS NIH HHS/ -- New York, N.Y. -- Science. 2003 May 2;300(5620):767-72. Epub 2003 Apr 10.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics and Genomic Biology, The Hospital for Sick Children, Toronto, Ontario, Canada, M5G 1X8. steve@genet.sickkids.on.ca〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/12690205" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Autistic Disorder/genetics ; Chromosome Aberrations ; Chromosome Fragile Sites ; Chromosome Fragility ; Chromosome Mapping ; Chromosomes, Human, Pair 7/*genetics ; Computational Biology ; Congenital Abnormalities/genetics ; CpG Islands ; DNA, Complementary ; Databases, Genetic ; Euchromatin/genetics ; Expressed Sequence Tags ; Gene Duplication ; Genes, Overlapping ; Genetic Diseases, Inborn/genetics ; Genomic Imprinting ; Humans ; In Situ Hybridization, Fluorescence ; Limb Deformities, Congenital/genetics ; Mice ; Molecular Sequence Data ; Mutation ; Neoplasms/genetics ; Pseudogenes ; RNA/genetics ; Retroelements ; *Sequence Analysis, DNA ; Williams Syndrome/genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 5
    Publication Date: 2013-11-24
    Description: Journal of the American Chemical Society DOI: 10.1021/ja407396v
    Print ISSN: 0002-7863
    Electronic ISSN: 1520-5126
    Topics: Chemistry and Pharmacology
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  • 6
    Publication Date: 2013-06-21
    Description: Author(s): Michael J. Skaug, Joshua Mabry, and Daniel K. Schwartz The mobility of molecules on a solid surface plays a key role in diverse phenomena such as friction and self-assembly and in surface-based technologies like heterogeneous catalysis and molecular targeting. To understand and control these surface processes, a universally applicable model of surface t... [Phys. Rev. Lett. 110, 256101] Published Thu Jun 20, 2013
    Keywords: Condensed Matter: Structure, etc.
    Print ISSN: 0031-9007
    Electronic ISSN: 1079-7114
    Topics: Physics
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  • 7
    Publication Date: 1999-07-06
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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