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Ecological regime shift drives declining growth rates of sea turtles throughout the West Atlantic
Bjorndal, Karen A. ; Bolten, Alan B. (coaut.) ; Chaloupka, Milani (coaut.) ; Saba, Vincent S. (coaut.) ; Bellini, Cláudio (coaut.) ; Marcovaldi, Maria A. G. (coaut.) ; Santos, Armando J. B. (coaut.) ; Wurdig Bortolon, Luis Felipe (coaut.) ; Meylan, Anne B. (coaut.) ; Meylan, Peter A. (coaut.) ; Gray, Jennifer (coaut.) ; Hardy, Robert (coaut.) ; Brost, Beth (coaut.) ; Bresette, Michael (coaut.) ; Gorham, Jonathan C. (coaut.) ; Connett, Stephen (coaut.) ; Van Sciver Crouchley, Barbara (coaut.) ; Dawson, Mike (coaut.) ; Hayes, Deborah (coaut.) ; Diez, Carlos E. (coaut.) ; van Dam, Robert P. (coaut.) ; Willis, Sue (coaut.) ; Nava, Mabel (coaut.) ; Hart, Kristen M. (coaut.) ; Cherkiss, Michael S. (coaut.) ; Crowder, Andrew G. (coaut.) ; Pollock, Clayton (coaut.) ; Hillis-Starr, Zandy (coaut.) ; Muñoz Tenería, Fernando A. (coaut.) ; Herrera Pavón, Roberto Luis (coaut.) ; Labrada Martagón, Vanessa (coaut.) ; Lorences, Armando (coaut.) ; Negrete Philippe, Ana (coaut.) ; Lamont, Margaret M. (coaut.) ; Foley, Allen M. (coaut.) ; Bailey, Rhonda (coaut.) ; Carthy, Raymond R. (coaut.) ; Scarpino, Russell (coaut.) ; McMichael, Erin (coaut.) ; Provancha, Jane A. (coaut.) ; Brooks, Annabelle (coaut.) ; Jardim, Adriana (coaut.) ; López Mendilaharsu, Maria de los Milagros (coaut.) ; González Paredes, Daniel (coaut.) ; Estrades, Andrés (coaut.) ; Fallabrino, Alejandro (coaut.) ; Martínez-Souza, Gustavo (coaut.) ; Vélez Rubio, Gabriela M. (coaut.) ; Boulon Jr., Ralf H. (coaut.) ; Collazo, Jaime A. (coaut.) ; Wershoven, Robert (coaut.) ; Guzmán Hernández, Vicente (coaut.) ; Stringell, Thomas B. (coaut.) ; Sanghera, Amdeep (coaut.) ; Richardson, Peter B. (coaut.) ; Broderick, Annette C. (coaut.) ; Phillips, Quinton (coaut.) ; Calosso, Marta (coaut.) ; Claydon, John A. B. (coaut.) ; Metz, Tasha L. (coaut.) ; Gordon, Amanda L. (coaut.) ; Landry Jr., Andre M. (coaut.) ; Shaver, Donna J. (coaut.) ; Blumenthal, Janice (coaut.) ; Collyer, Lucy (coaut.) ; Godley, Brendan J. (coaut.) ; McGowan, Andrew (coaut.) ; Witt, Matthew J. (coaut.) ; Campbell, Cathi L. (coaut.) ; Lagueux, Cynthia J. (coaut.) ; Bethel, Thomas L. (coaut.) ; Kenyon, Lory (coaut.) ;
Contenido en: Global Change Biology Vol. 23, no. 11 (November 2017), p. 4556–4568 ISSN: 1365-2486
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Somatic growth is an integrated, individual-based response to environmental conditions, especially in ectotherms. Growth dynamics of large, mobile animals are particularly useful as bio-indicators of environmental change at regional scales. We assembled growth rate data from throughout the West Atlantic for green turtles, Chelonia mydas, which are long-lived, highly migratory, primarily herbivorous mega-consumers that may migrate over hundreds to thousands of kilometers. Our dataset, the largest ever compiled for sea turtles, has 9690 growth increments from 30 sites from Bermuda to Uruguay from 1973 to 2015. Using generalized additive mixed models, we evaluated covariates that could affect growth rates; body size, diet, and year have significant effects on growth. Growth increases in early years until 1999, then declines by 26% to 2015. The temporal (year) effect is of particular interest because two carnivorous species of sea turtles—hawksbills, Eretmochelys imbricata, and loggerheads, Caretta caretta—exhibited similar significant declines in growth rates starting in 1997 in the West Atlantic, based on previous studies. These synchronous declines in productivity among three sea turtle species across a trophic spectrum provide strong evidence that an ecological regime shift (ERS) in the Atlantic is driving growth dynamics. The ERS resulted from a synergy of the 1997/1998 El Niño Southern Oscillation (ENSO)—the strongest on record—combined with an unprecedented warming rate over the last two to three decades. Further support is provided by the strong correlations between annualized mean growth rates of green turtles and both sea surface temperatures (SST) in the West Atlantic for years of declining growth rates (r = −.94) and the Multivariate ENSO Index (MEI) for all years (r = .74). Granger-causality analysis also supports the latter finding.

We discuss multiple stressors that could reinforce and prolong the effect of the ERS. This study.

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Plant metabolomics: methods and protocols / edited by Nigel W. Hardy, Robert D. Hall
Hardy, Nigel W. (ed.) ; Hall, Robert D. (coed.) ;
New York : Humana Press , c2012
Clasificación: 572.42 / P5
Bibliotecas: Tapachula
SIBE Tapachula
ECO020013678 (Disponible)
Disponibles para prestamo: 1
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Resumen en inglés

This book is part of the ‘Methods in Molecular Biology’ series (no. 860), which is popular for including chapters with introductory notes on the topic, lists of necessary materials and reagents, step-by-step detailed protocols, and key notes on troubleshooting and avoiding common errors. This volume describes several techniques, methods and experimental considerations that are commonly used in the field of plant metabolomics. The field of metabolomics and plant metabolomics has developed significantly during the last 15 years and this book includes contributions by leading authors in the area who played key roles in the development of this field. An introductory chapter describes the field of metabolomics and its growth in the past few years, defines some common terms, and presents the workflow commonly used in metabolomics experiments, from the experimental design to data analysis.The book is divided into three parts that target important topics in any given metabolomics experiment: material preparation, chemical analysis approaches and data analysis. The first chapter of the first section of the book (Chapter 2) includes guidelines on designing metabolomics experiments, not only with regard to the statistical design but also including considerations regarding environmental control, sampling strategy and size of experiment, and potential pitfalls associated with each of these.

Chapter 3 presents an interesting protocol not only for the extraction of the metabolome of a plant but also microbial material, which could be applied in the field of plant–microbe interactions. The following chapter expands further on precautions necessary when sampling, transporting and storing biological material, which particularly apply in the field of plant metabolomics where it is common to sample material away from the laboratory. The first part of the book concludes with a chapter dedicated to a protocol for growing arabidopsis plants for metabolomics experiments, highlighting potential issues related to sample storage, sampling time-point strategies and considerations regarding the pooling of biological samples. The second part of the book is dedicated to chemical analysis approaches and contains a series of chapters that describe commonly used methods for the major analytical techniques in plant metabolomics, such as LC-MS and GC-MS. Protocols for GC-MS are presented in Chapters 6 and 7, which describe methods for analysing headspace volatiles and primary metabolites, respectively. This is followed by two chapters with protocols for liquid-chromatography-based mass-spectrometry, the first based on a HPLC system and the second describing a method based on UPLC. Chapters 10 and 11 describe the use of mass spectrometers (Orbitrap, FT-ICR-MS) able to generate an accurate mass fingerprint that can subsequently be used to identify plant metabolites. The following chapter describes a protocol for the extraction of Brassica green tissue and subsequent analysis using a combination of NMR and FI-ESI-MS.

Chapter 13 then describes a method for determining the concentrations of trace elements by using LC-ICP-MS in several components of cereal grains. This second part of the volume is concluded with a chapter that integrates the use of genomic and metabolomics approaches to quantify the presence of endophytes and alkaloids in perennial ryegrass. The third part of the book, dedicated to data analysis methods, consists of four chapters. Two of these deal with commonly used pre-processing software, such as MetAlign and TagFinder, and provide detailed instructions regarding their use. Chapter 17 addresses the subject of chemical identification, which is often one of the greatest bottlenecks of any metabolomics study. This particular chapter focuses on strategies used for chemical identification while using LC-MS and LC-SPE-NMR, and showcases how these can be used in combination to provide all the necessary information for structural identification of compounds. This part of the book concludes with a chapter dedicated to data mining techniques that can be used for the analysis of metabolomics datasets. This covers a wide range of data-mining tasks, such as regression, correlation analysis and hypothesis testing, while also providing useful information about matching these data-mining techniques to the goal of the experiment. The chapters presented in this volume stay true to the Methods and Protocols series, with a short piece of background information, a highly detailed step-by-step protocol, and additional practical information that will allow beginners in the field to set up repeatable, high-quality metabolomics experiments. The methods are well illustrated with diagrams, where appropriate, and often include summary tables.

This volume describes a wide range of protocols that use complex techniques routinely used in the field and often refers the reader to other publications for more detailed information about the concepts of the technology used (e.g. MS, NMR and even statistical methods). Describing the technological details is not the goal of this series of books; however, a new user would be advised that the correct interpretation of the results will often require some level of expert assistance and/or further reading about the technologies used. Nevertheless, the wide range of techniques covered will ensure that researchers planning to work or already working in the field will find several chapters of interest in this volume. In summary, this is an excellent addition to the series and can provide much-needed support, especially to scientists starting in the growing field of plant metabolomics.


Practical applications of metabolomics in plant biology
Part I Material preparation
Aspects of experimental design for plant metabolomics experiments and guidelines for growth of plant material
Separating the inseparable: the metabolomic analysis of plant-pathogen interactions
Precautions for harvest, sampling, storage, and transport of crop plant metabolomics samples
Tissue preparation using arabidopsis
Part II Chemical analysis approaches
Solid phase micro-extraction GC-MS analysis of natural volatile components in melon and rice
Profiling primary metabolites of tomato fruit with gas chromatography/mass spectrometry
High-performance liquid chromatography-mass spectrometry analysis of plant metabolites in brassicaceae
UPLC-MS-based metabolite analysis in tomato
High precision measurement and fragmentation analysis for metabolite identification
Fourier transform ion cyclotron resonance mass-spectrometry for plant metabolite profiling and metabolite identification
Combined NMR and flow injection ESI-MS for brassicaceae metabolomics
ICP-MS and LC-ICP-MS for analysis of trace elements content and speciation in cereal grains
The use of genomics and metabolomics methods to quantify fungal endosymbionts and alkaloids in grasses
Part III Data analysis
Data (pre- )processing of nominal and accurate mass LC-MS or GC-MS data using MetAlign
TagFinder: preprocessing software for the fingerprinting and the profiling of gas chromatography-mass spectrometry based metabolome analyses
Chemical identification strategies using liquid chromatography-photodiode array-solid phase extraction-nuclear magnetic resonance/mass spectrometry
A strategy for selecting data mining techniques in metabolomics