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Eva, H.D.; de Miranda, E.E.; Di Bella, C.M.; Gond, V.; Jones, S.; Achard, F.; Belward, A.S. |

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A vegetation map of South America |
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2002 |
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41 |
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Office for Official Publications of the European Communties |
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European Commission |
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Luxembourg |
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Environment series |
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92-894-4449-5 |
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EcoFoG @ webmaster @ 22 |
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26 |
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Author  |
Faustin, M.; Maciuk, A.; Lebrini, M.; Robert, F.; Roos, C.; Figadere, B. |

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Title |
Isolation of Geissospermum laeve alkaloids by pH-zone refining centrifugal partition chromatography for metal corrosion studies |
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Conference Article |
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2012 |
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Planta Medica |
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78 |
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11 |
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1270 |
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Control of metal corrosion is of technical, economical, environmental, and aesthetical importance. The use of corrosion inhibitors is one of the best options to protect metals and alloys from corrosion. The environmental toxicity of synthetic inhibitors has prompted the search for green compounds. Plant extracts have become important as an environmentally acceptable, readily available and renewable source for a wide range of biodegradable, heavy metals-free inhibitors. Among natural compounds, alkaloids have very high corrosion inhibition efficiency. An alkaloidic extract of Geissospermum laeve (Apocynaceae) has been fractionated by centrifugal partition chromatography using the pH-zone refining mode in order to investigate the effect of isolated alkaloids on C38 steel corrosion in HCl 1M. Indole alkaloids were identified by LC-MS, 1H and 13C NMR. |
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2012 International Congress on Natural Products Research, New York City, July 28- August 1, 2012 |
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EcoFoG @ webmaster @ |
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174 |
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Feuilly, Hélène |
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Title |
Désenclavement de villages du Maroni : impacts sur le foncier agricole et forestier |
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2008 |
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Diploma thesis |
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AgroParisTech |
Place of Publication |
Kourou - Guyane française |
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EcoFoG @ carole.legrand @ |
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218 |
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Fisher, Gregory L. ; Fu, Tinting ; Touboul, David ; Della-Negra, Serge ; Houël, Emeline ; Amusant, Nadine ; Duplais, Christophe ; Brunelle, Alain |
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Elucidation of natural product biosynthesis in Amazonian Sextonia rubra via 100 nm-scale TOF-SIMS tandem MS imaging |
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2017 |
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21st International Conference on Secondary Ion Mass Spectroscopy (SIMS21), Krakow (Poland), 10-15/09/2017 |
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1 |
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EcoFoG @ carole.legrand @ |
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303 |
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Author  |
Floch, J.-M.; Marcon, E.; Puech, F. |

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Title |
Les configurations de points |
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2018 |
Publication |
Manuel d'analyse spatiale |
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73-114 |
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Les statisticiens peuvent être amenés à étudier précisément des données spatialisées, par exemple la distribution des revenus des ménages, l’implantation sectorielle d’établissements industriels ou commerciaux, la localisation des établissements scolaires au sein des villes, etc. Des réponses peuvent être apportées grâce à des analyses menées à une ou plusieurs échelles géographiques prédéfinies comme au niveau des quartiers, des arrondissements ou des îlots. Toutefois, il est tentant de vouloir préserver la richesse des données individuelles et travailler en conservant la position exacte des entités étudiées. Si tel est le cas, cela revient pour un statisticien à élaborer des analyses à partir de données géolocalisées sans procéder à une quelconque agrégation géographique. Les observations sont appréhendées comme des points dans l’espace et l’objectif est de caractériser ces distributions de points. Comprendre et maîtriser des méthodes statistiques qui traitent ces informations individuelles et
spatialisées permet de travailler sur des données qui sont aujourd’hui de plus en plus accessibles et recherchées car elles fournissent des analyses très précises sur les comportements des acteurs économiques (ELLISON et al. 2010 ; BARLET et al. 2013). Dans ce cadre d’analyse, plusieurs questions méthodologiques importantes se posent alors au statisticien qui dispose de jeux de points à analyser : comment représenter et caractériser spatialement de telles données en utilisant des milliers voire des millions d’observations ? Quels outils statistiques existent et peuvent être mobilisés pour étudier ces observations relatives aux ménages, salariés, firmes, magasins, équipements ou déplacements par exemple? Comment prendre en compte les caractéristiques qualitatives ou quantitatives des observations étudiées? Comment mettre en évidence des éventuelles attractions ou répulsions entre les points ou entre différents types de points? Comment peut-on évaluer la significativité des résultats obtenus? etc. Ce chapitre a pour but d’aider le statisticien à apporter des résultats statistiquement robustes à
partir de l’étude de données spatialisées qui ne reposent pas sur un zonage prédéfini. Pour ce faire, nous nous appuierons sur une revue de la littérature des méthodes statistiques qui permettent de caractériser des distributions de points et nous expliciterons les enjeux associés. Nous expliquerons à partir d’exemples simples les avantages et les inconvénients des approches les plus souvent retenues. Le code sous R fourni permettra de reproduire les exemples traités. |
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Insee-Eurostat |
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Loonis, V.; Bellefon, M.-P. de |
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EcoFoG @ webmaster @ |
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317 |
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Author  |
Floch, J.-M.; Marcon, E.; Puech, F. |

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Title |
Spatial distribution of points |
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Book Chapter |
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2018 |
Publication |
Handbook of Spatial Analysis |
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71-111 |
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Statisticians carry out close examination of spatialized data, such as the distribution of household income, the location of industrial or commercial establishments, the distribution of schools in cities, etc. Answers can be found through analyses of one or more predefined geographical scales such as neighbourhoods, districts or statistical blocks. However, it is tempting to preserve the individual data and to work with the exact position of the entities that are being studied. If that is the case, statisticians have to conduct analyses based on geolocation data without carrying out any geographical aggregation. Observations are taken as points in space and the objective is to characterise these point distributions. Understanding and mastering statistical methods that process this individual and spatialized information enables us to work on data that are now increasingly accessible and sought after because they provide very precise analyses of distributions studied (Ellison et al. 2010; Barlet et al. 2013). In this framework of analysis, statisticians who have sets of points to analyse are faced with several important methodological questions: how can such data with thousands or even millions of observations be represented and characterised spatially? What statistical tools exist that can be used to study these observations relating to households, employees, firms, stores, equipment or travel, for example? How can the qualitative or quantitative characteristics of the observations being studied be taken into account? How can any attractions or repulsions between points or between different types of points be highlighted? How can we assess the significance of the results obtained, etc? The purpose of this chapter is to help statisticians to provide statistically robust results from the study of spatialized data that is not based on predefined zoning. To do this, we will review the literature on the subject of statistical methods used to characterise point distributions and we will explain the associated issues. We will use simple examples to explain the advantages and disadvantages of the most frequently adopted approaches. The code provided in R will be used to reproduce the examples covered. |
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Insee-Eurostat |
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Loonis, V.; Bellefon, M.-P. de |
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EcoFoG @ webmaster @ |
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318 |
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Author  |
Fonty, Emile |

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Title |
Etude de l'écologie du Spirotropis longifolia DC Baill. (Leguminosae Papilionoideae) – Espèce monodominante dans les forêts de Guyane française. |
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2011 |
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209 |
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Ph.D. thesis |
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Université Montpellier II |
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Montpellier - France |
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Couteron, Pierre |
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EcoFoG @ carole.legrand @ |
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197 |
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Author  |
Fournier, M.; Alméras, T.; Clair, B.; Gril, J. |

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Title |
Biomechanical Action and Biological Functions |
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Book Chapter |
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Year |
2014 |
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The Biology of Reaction Wood |
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139-169 |
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Springer Berlin Heidelberg |
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Berlin, Heidelberg |
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Gardiner, B.; Barnett, J.; Saranpää, P.; Gril, J. |
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978-3-642-10814-3 |
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EcoFoG @ webmaster @ Fournier2014 |
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254 |
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Author  |
Fournier, M.; Jaouen, G.; Duchateau, E.; Clair, B.; Coutand, C.; Alméras, T. |

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Title |
Gravitropism plays a key role in the diversity of tree ecological strategies at the advance regeneration stage |
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Book Chapter |
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2009 |
Publication |
Proceedings of the Sixth Plant Biomechanics Conference |
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361 |
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UMR EcoFoG |
Place of Publication |
Kourou - Guyane française |
Editor |
Thibaut, B. |
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November 16 - 21, 2009 |
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EcoFoG @ webmaster @ 23 |
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131 |
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Fournier, M.; Stockes, A.; Coutand, C.; Fourcaud, T.; Moulia, B. |
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Title |
Tree biomechanics and growth strategies in the context of forest functional ecology (Chap.1) |
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Book Chapter |
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2006 |
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Ecology and biomechanics : a mechanical approach to the ecology of animals and plants |
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1-33 |
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Introduction , 2 Sorne Biornechanical Characteristics of Trees , 3 1-.2.1 Wood as a Lightweight, Cellular- and Fiher- Reinforced Materia!..... 3 1.2.2 Wood Variability 5 1.2.3 Mechanics of Secondary Growth , , , 6 Biomechanical and Ecological Significance of Height. , , 6 1.3.1 Biomechanical Environmental Constraints on Tree Height and Their Ecological Significance, “. . 7 l.3.1.1 Safety Factor . 7 1.3.1.2 Analysis of Successive Shapes Occurring during Growth Due to the Continuous Increase of Supported Loads ....” ..“ 8 1.3.2 Biomechanical Functional Traits Defined from Risk Assessment.. 9 1.3.2.1 Buckling or Breakage·of Stems 9 1.3.2.2 Root Anchorage 9 1.3.3 Biomechanical Functional Traits and Processes lnvolved in Height Gro\vth Strategy .” “ .., , 13 The Growth Processes That Control the Mechanical Stability of Siender Tree StelTIS,., , ,......... . , , ,.. , ,.. ' , 14 1.4, l The Mechanical Control of Growth , , , ,.. , , , 14 1.4.2 The Control of Stem Orientation ta Maintain or Restore the Tree Form, and Allow Vertical Growth ” “ ” “ ..”'“.”,,, ..,.16 1.4,3 The Control of Root Growth to Secure Anchorage .... 21 A Practical Application of Tree Biomechanics in Ecology 21 Conclusion , 24 Références 25 |
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Taylor & Francis |
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Boca Raton (USA) |
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Herrel, A.; Speck, T.; Rowe, N.P. |
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EcoFoG @ webmaster @ 25 |
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66 |
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