Publications
| Authors | Title | Year | Journal | Volume / Pages | ||
|---|---|---|---|---|---|---|
| Allard, D. Droesbeke, J.-J.; Lejeune, M. & Saporta, G. (Hrsg.) | Validation d'un modèle géostatistique pour l'interpolation : application à un événement pluvieux [BibTeX] |
2006 | Analyse statistique des données spatiales | |||
BibTeX:
@incollection{Allard2006,
author = {Allard, D.},
title = {Validation d'un modèle géostatistique pour l'interpolation : application à un événement pluvieux},
booktitle = {Analyse statistique des données spatiales},
publisher = {Editions Technip},
year = {2006}
}
|
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| Allard, D.; Froidevaux, R. & Biver, P. | Conditional Simulation of Multi-Type Non Stationary Markov Object Models Respecting Specified Proportions [BibTeX] |
2006 | Mathematical Geology | Vol. 38 , pp. 959-986 |
||
BibTeX:
@article{Allard2006a,
author = {Allard, D. and Froidevaux, R. and Biver, P.},
title = {Conditional Simulation of Multi-Type Non Stationary Markov Object Models Respecting Specified Proportions},
journal = {Mathematical Geology},
year = {2006},
volume = {38},
pages = {959-986},
note = {doi:10.1007/s11004-006-9057-5}
}
|
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| Allard, D. & Gabriel, E. Guérif, M. & King, D. (Hrsg.) | Détection de zones de changement abrupt pour des variables non permanentes du sol: vers la définition de zones homogènes ? [BibTeX] |
2007 | Agriculture de précision | , pp. 165-176 | ||
BibTeX:
@incollection{Allard2007,
author = {Allard, D. and Gabriel, E.},
title = {Détection de zones de changement abrupt pour des variables non permanentes du sol: vers la définition de zones homogènes ?},
booktitle = {Agriculture de précision},
publisher = {Editions Quae},
year = {2007},
pages = {165-176}
}
|
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| Allard, D. & Naveau, P. | A new spatial skew-normal random field model [BibTeX] |
2007 | Communications in Statistics-Theory and Methods | Vol. 36 (9-12) , pp. 1821-1834 |
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BibTeX:
@article{Allard2007a,
author = {Allard, D. and Naveau, P.},
title = {A new spatial skew-normal random field model},
journal = {Communications in Statistics-Theory and Methods},
year = {2007},
volume = {36},
number = {9-12},
pages = {1821-1834},
url = { |
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| Angevin, F.; Klein, E.K.; Choimet, C.; Gauffreteau, A.; Lavigne, C.; Messean, A. & Meynard, J.M. | Modelling impacts of cropping systems and climate on maize cross-pollination in agricultural landscapes: The MAPOD model |
2008 | European Journal of Agronomy | Vol. 28 (3) , pp. 471-484 |
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| Abstract: New concerns about crop coexistence in agricultural landscapes are being expressed in reaction to the prospect of introducing transgenic crops into European cropping systems: these include meeting current consumer demand for non-GM products, respecting threshold levels required for organic farming labels as well as keeping food cultures separated from those destined for the pharmaceutical and energy industries. To address these concerns in the case of maize crops, we have chosen a modelling approach. Our aim was to simulate cross-pollination in the case of existing agricultural landscapes, taking into account the effect of climate and cropping techniques in order to forecast gene escape from genetically modified maize to non-GM maize. The resulting spatially explicit model, MAPOD (Matricial Approach to Pollen Dispersal), is presented in this paper. A preliminary evaluation is also provided. Pollen exchanges between GM and non-GM maize crops are simulated and influencing factors such as field sizes and shapes, distribution of GM and non-GM fields in the agricultural landscape as well as flowering dates and dynamics are integrated. Model parameter values were either derived from existing models of pollen dispersal or estimated from experimental field studies. The preliminary evaluation of MAPOD was carried out by comparing simulation results with data from two French and one American gene flow field trials. MAPOD was found to provide good average predictive values. Examples of output data illustrate the capacity of the model to simulate a wide range of agricultural contexts. These simulation results provide a basis for designing coexistence rules and monitoring procedure set-up. (c) 2007 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Angevin2008,
author = {Angevin, F. and Klein, E. K. and Choimet, C. and Gauffreteau, A. and Lavigne, C. and Messean, A. and Meynard, J. M.},
title = {Modelling impacts of cropping systems and climate on maize cross-pollination in agricultural landscapes: The MAPOD model},
journal = {European Journal of Agronomy},
year = {2008},
volume = {28},
number = {3},
pages = {471-484},
note = {Cited References: *CPVO, 2001, PROTOCOL DISTINCT TP *EUR COMM DIR GEN, 2006, EUROBAROMETER *EUR COMM, 2003, OFFICIAL J EUROPEAN, V46, P36 *EUR COMM, 2005, EUR AGR STAT Q B AGR *GNIS, 2003, REGLEMENTS TECHNIQUE, V1, P83 ALLEN RG, 1994, ICID B, V43, P35 ANGEVIN F, 2002, SCENARIOS CO EXISTEN, P52 AYLOR DE, 2004, AGR FOREST METEOROL, V123, P125, DOI 10.1016/j.agrformet.2003.12.007 BANNERT M, 2007, EUR J AGRON, V27, P44, DOI 10.1016/j.eja.2007.01.002 BASSETTI P, 1993, CROP SCI, V33, P279 BASSETTI P, 1994, AGRON J, V86, P699 BATEMAN AJ, 1947, HEREDITY, V1, P235 BATEMAN AJ, 1947, J GENET, V48, P257 BOLANOS J, 1993, FIELD CROP RES, V31, P233 BOYAT A, 1984, PHYSL MAIS, P199 BOYAT A, 1990, PHYSL PRODUCTION MAI, P335 BRISSON N, 1998, AGRONOMIE, V18, P311 BYRNE PF, 2003, J FOOD AGR ENV, V1, P258 CAMPBELL GS, 1998, INTRO ENV BIOPHYSICS CARCOVA J, 2000, CROP SCI, V40, P1056 COLBACH N, 2001, AGR ECOSYST ENVIRON, V83, P235 COLBACH N, 2001, AGR ECOSYST ENVIRON, V83, P255 DERIEUX M, 1982, MAYDICA, V27, P59 DERIEUX M, 1990, HEAT UNITS REQUIREME, V35, P41 DIFAZIO SP, 2002, THESIS OREGON STATE DUPLESSIS DP, 1967, S AFR J AGR SCI, V10, P667 DUPONT S, 2006, AGR FOREST METEOROL, V141, P82, DOI 10.1016/j.agrformet.2006.09.004 DURAND R, 1969, B TECHNIQUE INFORMAT, V238, P185 EMBERLIN J, 1999, REP DISPERSAL MAIZE FONSECA AE, 2003, CROP MANAG, P1 FONSECA AE, 2005, FIELD CROP RES, V94, P114, DOI 10.1016/j.fcr.2004.12.001 FUNK T, 2006, EUR J AGRON, V24, P26, DOI 10.1016/j.eja.2005.04.002 GAY P, 1983, PHYSL MAIS, P1 GIRARDIN P, 1987, AGRONOMIE, V7, P289 GIRARDIN P, 1990, PHYSL PROD MAIS, P187 GLIDDON CJ, 1999, GENE FLOW AGR RELEVA, P49 GOGGI AS, 2007, INT J BIOMETEOROL, V51, P493, DOI 10.1007/s00484-007-0088-5 HALL AJ, 1981, MAYDICA, V26, P19 HALSEY ME, 2005, CROP SCI, V45, P2172, DOI 10.2135/cropsci2003.0664 HERRERO MP, 1980, CROP SCI, V20, P796 HERRERO MP, 1981, CROP SCI, V21, P105 HSU SU, 1991, J GENET BREED, V45, P215 JAROSZ N, 2003, AGR FOREST METEOROL, V119, P37, DOI 10.1016/S0168-1923(03)00118-7 JAROSZ N, 2004, ATMOS ENVIRON, V38, P5555, DOI 10.1016/j.atmosenv.2004.06.027 JEMISON JM, 2001, AGBIOFORUM, V4, P87 JONES CA, 1986, CERES MAIZE SIMULATI, P49 JONES MD, 1950, OKLA AGR EXP STN T T, V38, P1 KLEIN EK, 2002, EFFET DISCONTINUITE, P31 KLEIN EK, 2003, ECOL MONOGR, V73, P131 KLEIN EK, 2006, J APPL ECOL, V43, P141, DOI 10.1111/j.1365-2664.2005.01108.x LAVIGNE C, 1998, THEOR APPL GENET, V96, P886 LAVIGNE C, 2004, INTROGRESSION GENETI, P351 LIZASO JI, 2003, CROP SCI, V43, P892 LONNQUIST JH, 1943, J AM SOC AGRON, V35, P923 LOOS C, 2003, J THEOR BIOL, V225, P241, DOI 10.1016/S0022-5193(03)00243-1 LUNA VS, 2001, CROP SCI, V41, P1551 MCCARTNEY HA, 1985, MATH MODELLING CROP, P107 MESSEAN A, 2006, TECHNICAL REPORT SER MEYNARD JM, 2001, ISOLEMENT COLLECTES PURSEGLOVE JW, 1972, TROPICAL CROPS MONOC RAYNOR GS, 1972, AGRON J, V64, P420 RICHTER O, 2004, ECOL MODEL, V174, P55, DOI 10.1016/j.ecolmodel.2003.12.046 RIEGER MA, 2002, SCIENCE, V296, P2386 SCHOPER JB, 1986, CROP SCI, V26, P1029 SESTER M, 2003, P GMCC 03 DIAS SLAG, P108 STAPPER M, 1979, 794513 PAP AM SOC AG, P37 STRUIK PC, 1992, NETH J AGR SCI, V40, P409 TREU R, 2000, EVIDENCE PUBLICATION TUFTO J, 1997, THEOR POPUL BIOL, V52, P16 URIBELARREA M, 2002, CROP SCI, V42, P1910 WESTGATE ME, 2003, CROP SCI, V43, P934 YAMAMURA K, 2004, POPUL ECOL, V46, P87, DOI 10.1007/s10144-004-0174-z},
url = { |
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| Aries, F.; Briand, E. & Bruchoul, C. | Some covariants related to Steiner surfaces |
2008 | Geometric Modeling And Algebraic Geometry | , pp. 31-46 | ||
| Abstract: A Steiner surface is the generic case of a quadratically parameterizable quartic surface used in geometric modeling. This paper studies quadratic parameterizations of surfaces under the angle of Classical Invariant Theory. Precisely, it exhibits a collection of covariants associated to projective quadratic parameterizations of surfaces, under the actions of linear reparameterization and linear transformations of the target space. Each of these covariants comes with a simple geometric interpretation. As an application, some of these covariants are used to produce explicit equations and inequalities defining the orbits of projective quadratic parameterizations of quartic surfaces. | ||||||
BibTeX:
@article{Aries2008,
author = {Aries, F. and Briand, E. and Bruchoul, C.},
title = {Some covariants related to Steiner surfaces},
journal = {Geometric Modeling And Algebraic Geometry},
year = {2008},
pages = {31-46},
note = {Times Cited: 0},
url = { |
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| Aries, F.; Galligo, A. & Lê, T. Chenin, P.; Lyche, T. & Schumaker, L. (Hrsg.) | Using Bézier patches of bidegree (1,2) for corn leaf modeling [BibTeX] |
2007 | Curve and Surface Design. Avignon 2006 | |||
BibTeX:
@incollection{Aries2007,
author = {Aries, F. and Galligo, A. and Lê, T.H.},
title = {Using Bézier patches of bidegree (1,2) for corn leaf modeling},
booktitle = {Curve and Surface Design. Avignon 2006},
publisher = {Nashboro Press},
year = {2007}
}
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| Ayme, V.; Souche, S.; Caranta, C.; Jacquemond, M.; Chadoeuf, J.; Palloix, A. & Moury, B. | Different Mutations in the Genome-Linked Protein VPg of Potato virus Y Confer Virulence on the pvr23 Resistance in Pepper [BibTeX] |
2006 | Molecular Plant-Microbe Interactions | Vol. 19 (5) , pp. 557-563 |
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BibTeX:
@article{Ayme2006,
author = {Ayme, V. and Souche, S. and Caranta, C. and Jacquemond, M. and Chadoeuf, J. and Palloix, A. and Moury, B.},
title = {Different Mutations in the Genome-Linked Protein VPg of Potato virus Y Confer Virulence on the pvr23 Resistance in Pepper},
journal = {Molecular Plant-Microbe Interactions},
year = {2006},
volume = {19},
number = {5},
pages = {557-563}
}
|
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| Bailleul, F.; Charrassin, J.B.; Monestiez, P.; Roquet, F.; Biuw, M. & Guinet, C. | Successful foraging zones of southern elephant seals from the Kerguelen Islands in relation to oceanographic conditions [BibTeX] |
2007 | Philosophical Transactions of the Royal Society Series B | Vol. 362 (1487) , pp. 2169-2181 |
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BibTeX:
@article{Bailleul2007,
author = {Bailleul, F. and Charrassin, J. B. and Monestiez, P. and Roquet, F. and Biuw, M. and Guinet, C.},
title = {Successful foraging zones of southern elephant seals from the Kerguelen Islands in relation to oceanographic conditions},
journal = {Philosophical Transactions of the Royal Society Series B},
year = {2007},
volume = {362},
number = {1487},
pages = {2169-2181},
url = { |
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| Bailly, J.-S.; Monestiez, P. & Lagacherie, P. | Modelling Spatial Variability Along Drainage Networks with Geostatistics [BibTeX] |
2006 | Mathematical Geology | Vol. 38 , pp. 515-539 |
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BibTeX:
@article{Bailly2006,
author = {Bailly, J-S. and Monestiez, P. and Lagacherie, Ph.},
title = {Modelling Spatial Variability Along Drainage Networks with Geostatistics},
journal = {Mathematical Geology},
year = {2006},
volume = {38},
pages = {515-539}
}
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| Beaudouin, R.; Ginot, V. & Monod, G. | Growth characteristics of eastern mosquitofish Gambusia holbrooki in a northern habitat (Brittany, France) |
2008 | Journal Of Fish Biology | Vol. 73 (10) , pp. 2468-2484 |
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| Abstract: The two coefficients of the von Bertalanffy growth model [maximal standard length (L-S infinity) and initial growth rate (a)] were determined in eastern mosquitofish Gambusia holbrooki in the most northern area where it is established (Rennes, Brittany, France). The estimated mean L-S infinity was 57.7 and 25.0 mm in females and males, respectively. The value of a was identical for both males and females before the males diverged from the females by slowing down their growth, probably because of the onset of puberty. The sexual competition reported in males would be responsible for higher interindividual variability of L-S infinity in males than in females. a was positively correlated with water temperature and could be modulated by fish density and length at birth. Moreover, interindividual variability of a was influenced in a complex way by interactions between water temperature, length at birth and fish density. When compared to the data from studies in G. holbrooki inhabiting their native range or the southern introduced range, the present results suggest that the thermal tolerance domain for growth was altered and that males exhibited a shorter length at sexual maturity and a shorter L-S infinity in the population established in Rennes. | ||||||
BibTeX:
@article{Beaudouin2008a,
author = {Beaudouin, R. and Ginot, V. and Monod, G.},
title = {Growth characteristics of eastern mosquitofish Gambusia holbrooki in a northern habitat (Brittany, France)},
journal = {Journal Of Fish Biology},
year = {2008},
volume = {73},
number = {10},
pages = {2468-2484},
note = {Cited References: *NSW NAT PARKS WIL, 2003, NSW THREAT AB PLAN P *R DEV COR TEAM, 2005, R LANG ENV STAT COMP ARTHINGTON AH, 1989, ECOLOGY EVOLUTION LI, P333 BENCE JR, 1986, ECOLOGY, V67, P324 BISAZZA A, 1991, BEHAV ECOLOGY FISHES, P257 BISAZZA A, 1995, ETHOL ECOL EVOL, V7, P169 BOX GEP, 1964, J R STAT SOC B, V26, P211 BROWNPETERSON N, 1990, ENVIRON BIOL FISH, V27, P33 CABRAL JA, 1999, ACTA OECOL, V20, P607 CAMPTON DE, 1988, AQUACULTURE, V68, P221 CARTER CG, 1993, CAN J ZOOL, V71, P392 CONSTANZ GD, 1989, ECOLOGY EVOLUTION LI, P149 COURTENAY WR, 1989, ECOLOGY EVOLUTION LI, P319 CRIVELLI AJ, 1987, REV ECOL-TERRE VIE, V42, P421 DAFRANCA M, 1953, ARQUIVOS MUSEU BOCAG, V25, P39 FERNANDEZDELGADO C, 1989, FRESHWATER BIOL, V22, P395 FLODMARK LEW, 2004, J FISH BIOL, V65, P460, DOI 10.1111/j.1095-8649.2004.00463.x GADGIL M, 1970, AM NAT, V104, P1 GALL GAE, 1974, CALIF FISH GAME, V60, P26 GELINEAU A, 1998, AQUACULTURE, V167, P247 JOBLING M, 1996, J FISH BIOL, V49, P658 JOBLING M, 1997, GLOBAL WARMING IMPLI, P225 KEANE JP, 2004, NEW ZEAL J MAR FRESH, V38, P857 KRUMHOLZ LA, 1948, ECOL MONOGR, V18, P4 LLOYD LN, 1985, AUST J MAR FRESH RES, V36, P447 LOWE S, 2000, 100 WORLDS WORST INV MCPEEK MA, 1992, BEHAV ECOL, V3, P1 MEFFE GK, 1990, COPEIA, P10 MEFFE GK, 1991, CAN J FISH AQUAT SCI, V48, P60 MEFFE GK, 1992, COPEIA 0203, P94 OTTO RG, 1973, J FISH BIOL, V5, P575 PEN LJ, 1991, AQUAT CONSERV, V1, P159 PEREZBOTE JL, 2005, ITAL J ZOOL, V72, P241 PYKE GH, 2005, REV FISH BIOL FISHER, V15, P339, DOI 10.1007/s11160-006-6394-x RUPP HR, 1996, J AM MOSQUITO CONT 1, V12, P155 SNELSON FF, 1989, ECOLOGY EVOLUTION LI, P149 STEARNS SC, 1983, AM ZOOL, V23, P65 STEARNS SC, 2000, NATURWISSENSCHAFTEN, V87, P476 STOCKWELL CA, 1999, ANIM CONSERV, V2, P103 VARGAS MJ, 1996, HYDROBIOLOGIA, V341, P215 VONBERTALANFFY L, 1938, HUM BIOL, V10, P181 VONDRACEK B, 1988, ENVIRON BIOL FISH, V21, P45 WANG N, 2000, N AM J AQUACULT, V62, P161 WEEKS SC, 1996, EVOLUTION, V50, P1358 WOOTTON RJ, 1990, ECOLOGY TELEOST FISH WURTSBAUGH WA, 1983, T AM FISH SOC, V112, P653 ZHAO Y, 2001, J FISH BIOL, V59, P569 ZULIAN E, 1995, ETHOL ECOL EVOL, V7, P1},
url = { |
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| Beaudouin, R.; Monod, G. & Ginot, V. | Selecting parameters for calibration via sensitivity analysis: An indlividual-based model of mosquitofish population dynamics |
2008 | Ecological Modelling | Vol. 218 (1-2) , pp. 29-48 |
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| Abstract: A stochastic individual-based model (IBM) of mosquitofish population dynamics in experimental ponds was constructed in order to increase, virtually, the number of replicates of control populations in an ecotoxicology trial, and thus to increase the statistical power of the experiments. In this context, great importance had to be paid to model calibration as this conditions the use of the model as a reference for statistical comparisons. Accordingly, model calibration required that both mean behaviour and variability behaviour of the model were in accordance with real data. Currently, identifying parameter values from observed data is still an open issue for IBMs, especially when the parameter space is large. our model included 41 parameters: 30 driving the model expectancy and 11 driving the model variability. Under these conditions, the use of "Latin hypercube" sampling would most probably have "missed" some important combinations of parameter values. Therefore, complete factorial design was preferred. Unfortunately, due to the constraints of the computational capacity, cost-acceptable "complete designs" were limited to no more than nine parameters, the calibration question becoming a parameter selection question. In this study, successive "complete designs" were conducted with different sets of parameters and different parameter values, in order to progressively narrow the parameter space. For each "complete design", the selection of a maximum of nine parameters and their respective n values was carefully guided by sensitivity analysis. Sensitivity analysis was decisive in selecting parameters that were both influential and likely to have strong interactions. According to this strategy, the model of mosquitofish population dynamics was calibrated on real data from two different years of experiments, and validated on real data from another independent year. This model includes two categories of agents; fish and their living environment. Fish agents have four main processes: growth, survival, puberty and reproduction. The outputs of the model are the length frequency distribution of the population and the 16 scalar variables describing the fish populations. In this study, the length frequency distribution was parameterized by 10 scalars in order to be able to perform calibration. The recently suggested notion of "probabilistic distribution of the distributions" was also applied to our case study, and was shown to be very promising for comparing length frequency distributions (as such). (C) 2008 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Beaudouin2008,
author = {Beaudouin, R. and Monod, G. and Ginot, V.},
title = {Selecting parameters for calibration via sensitivity analysis: An indlividual-based model of mosquitofish population dynamics},
journal = {Ecological Modelling},
year = {2008},
volume = {218},
number = {1-2},
pages = {29-48},
note = {Cited References: ANGULO O, 2005, CR BIOL, V328, P387, DOI 10.1016/j.cvri.2004.11.007 BARD Y, 1974, NONLINEAR PARAMETER BEARD TD, 2000, T AM FISH SOC, V129, P561 BROWNPETERSON N, 1990, ENVIRON BIOL FISH, V27, P33 CABRAL JA, 2001, ECOL ENG, V16, P537 DEANGELIS DL, 1991, ECOL MODEL, V57, P91 DEGRAAF GJ, 2005, AQUAC RES, V36, P55 DEJONG FMW, 2005, HUM ECOL RISK ASSESS, V11, P157 DIDAY E, 2001, 112 CEREMADE, P1 DREZE V, 1998, B FR PECHE PISCIC, V350, P465 DREZE V, 2000, ECOTOXICOLOGY, V9, P93 GIDDINGS JM, 1984, ENVIRON TOXICOL CHEM, V3, P465 GINOT V, 2002, ECOL MODEL, V157, P23 GINOT V, 2006, ECOL MODEL, V193, P479, DOI 10.1016/j.ecolmodel.2005.08.025 GRIMM V, 1999, ECOL MODEL, V115, P129 GRIMM V, 2002, OECOLOGIA, V131, P196 GRIMM V, 2005, INDIVIDUAL BASED MOD GRIMM V, 2006, ECOL MODEL, V198, P115, DOI 10.1016/j.ecolmodel.2006.04.023 HEMELRIJK CK, 2005, BEHAV ECOL, V16, P178, DOI 10.1093/beheco/arh149 HERRMANN B, 2005, FISH RES, V71, P1, DOI 10.1016/j.fishres.2004.08.024 JAWORSKA JS, 1997, ECOL MODEL, V99, P113 KENNEDY JH, 1999, ENVIRON TOXICOL CHEM, V18, P113 KRISTIANSEN T, 2007, CAN J FISH AQUAT SCI, V64, P136, DOI 10.1139/F06-176 MADENJIAN CP, 1993, CAN J FISH AQUAT SCI, V50, P97 MAES J, 2005, FISH OCEANOGR, V14, P17 MOOIJ WM, 2003, ECOL APPL, V13, P794 MULLON C, 2003, FISH OCEANOGR, V12, P396 PERSSON L, 2004, P ROY SOC LOND B BIO, V271, P2489, DOI 10.1098/rspb.2004.2854 PYKE GH, 2005, REV FISH BIOL FISHER, V15, P339, DOI 10.1007/s11160-006-6394-x RAILSBACK SF, 2002, NATURAL RESOURCE MOD, V15, P83 RATTO M, 2001, COMPUT PHYS COMMUN, V136, P212 SALTELLI A, 2000, SENSITIVITY ANAL SANDERSON H, 2002, ENVIRON SCI POLLUT R, V9, P429, DOI 10.1065/espr2001.09.085 SHAW JL, 1994, AQUATIC MESOCOSM STU, P85 SHAW JL, 1996, ENVIRON TOXICOL CHEM, V15, P605 SOUBEYRAND S, 2007, MATH BIOSCI, V210, P508, DOI 10.1016/j.mbs.2007.06.005 TATARA CP, 2002, ENVIRON TOXICOL CHEM, V21, P2191 VANNES EH, 2002, ECOL MODEL, V152, P261 VANWINKLE W, 1998, ECOL MODEL, V110, P175 VONBERTALANFFY L, 1938, HUM BIOL, V10, P181 VRAC M, 2004, REV STAT APPL, V52, P67 WALTER E, 1997, IDENTIFICATION PARAM},
url = { |
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| Bel, L.; Allard, D.; Laurent, J.M.; Cheddadi, R. & Bar-Hen, A. | CART algorithm for spatial data: Application to environmental and ecological data |
2009 | Computational Statistics & Data Analysis | Vol. 53 (8) , pp. 3082-3093 |
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| Abstract: Most statistical learning techniques such as Classification And Regression Trees (CART) assume independent samples to compute classification rules. This assumption is very practical for estimating quantities involved in the algorithm and for assessing asymptotic properties of estimators. In many environmental or ecological applications, the data under study are a sample of some regionalized variables, which can be modeled as random fields with spatial dependence. When the sampling scheme is very irregular, a direct application of supervised classification algorithms leads to biased discriminant rules due, for example, to the possible oversampling of some areas. The CART algorithm is adapted to the case of spatially dependent samples, focusing on environmental and ecological applications. Two approaches are considered. The first one takes into account the irregularity of the sampling by weighting the data according to their spatial pattern using two existing methods based on Voronoi tessellation and regular grid, and one original method based on kriging. The second one uses spatial estimates of the quantities involved in the construction of the discriminant rule at each step of the algorithm. These methods are tested on simulations and on a classical dataset to highlight their advantages and drawbacks. They are then applied on an ecological data set to explore the relationship between pollen data and presence/absence of tree species, which is an important question for climate reconstruction based on paleoecological data. (c) 2008 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Bel2009,
author = {Bel, L. and Allard, D. and Laurent, J. M. and Cheddadi, R. and Bar-Hen, A.},
title = {CART algorithm for spatial data: Application to environmental and ecological data},
journal = {Computational Statistics & Data Analysis},
year = {2009},
volume = {53},
number = {8},
pages = {3082-3093},
note = {0167-9473}
}
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| Bellier, E.; Monestiez, P.; Durbec, J. & Candau, J. | Identifying spatial relationships at multiple scales: principal coordinates of neighbour matrices (PCNM) and geostatistical approaches [BibTeX] |
2007 | Ecography | Vol. 30 (3) , pp. 385-399 |
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BibTeX:
@article{Bellier2007,
author = {Bellier, E. and Monestiez, P. and Durbec, J.P. and Candau, J.N.},
title = {Identifying spatial relationships at multiple scales: principal coordinates of neighbour matrices (PCNM) and geostatistical approaches},
journal = {Ecography},
year = {2007},
volume = {30},
number = {3},
pages = {385-399}
}
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| Brehelin, L.; Gascuel, O. & Martin, O. | Using repeated measurements to validate hierarchical gene clusters |
2008 | Bioinformatics | Vol. 24 (5) , pp. 682-688 |
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| Abstract: Motivation: Hierarchical clustering is a common approach to study protein and gene expression data. This unsupervised technique is used to find clusters of genes or proteins which are expressed in a coordinated manner across a set of conditions. Because of both the biological and technical variability, experimental repetitions are generally performed. In this work, we propose an approach to evaluate the stability of clusters derived from hierarchical clustering by taking repeated measurements into account. Results: The method is based on the bootstrap technique that is used to obtain pseudo-hierarchies of genes from resampled datasets. Based on a fast dynamic programming algorithm, we compare the original hierarchy to the pseudo-hierarchies and assess the stability of the original gene clusters. Then a shuffling procedure can be used to assess the significance of the cluster stabilities. Our approach is illustrated on simulated data and on two microarray datasets. Compared to the standard hierarchical clustering methodology, it allows to point out the dubious and stable clusters, and thus avoids misleading interpretations. | ||||||
BibTeX:
@article{Brehelin2008,
author = {Brehelin, L. and Gascuel, O. and Martin, O.},
title = {Using repeated measurements to validate hierarchical gene clusters},
journal = {Bioinformatics},
year = {2008},
volume = {24},
number = {5},
pages = {682-688},
note = {Times Cited: 2 1367-4803},
url = { |
||||||
| Bénard-Capelle, J.; Soubeyrand, S. & Neema, C. | Reproductive consequences of Colletotrichum lindemuthianum (Ascomycota) infection on wild bean plants (Phaseolus vulgaris) [BibTeX] |
2006 | Canadian Journal of Botany | Vol. 84 (10) , pp. 1542-1547 |
||
BibTeX:
@article{Benard-Capelle2006,
author = {Bénard-Capelle, J. and Soubeyrand, S. and Neema, C.},
title = {Reproductive consequences of Colletotrichum lindemuthianum (Ascomycota) infection on wild bean plants (Phaseolus vulgaris)},
journal = {Canadian Journal of Botany},
year = {2006},
volume = {84},
number = {10},
pages = {1542-1547},
url = {doi : 10.1139/B06-114}
}
|
||||||
| Calonnec, A.; Cartolaro, P. & Chadoeuf, J. | Highlighting Features of Spatiotemporal Spread of Powdery Mildew Epidemics in the Vineyard Using Statistical Modeling on Field Experimental Data |
2009 | Phytopathology | Vol. 99 (4) , pp. 411-422 |
||
| Abstract: A greater understanding of the development of powdery mildew epidemics on vines would improve disease management by making assessments of the risk of invasion more accurate. We characterized the spatiotemporal spread of epidemics in the vineyard, quantified their variability, and identified the factors responsible for it. We described changes in the probability of infection of a leaf in a plot over time and as a function of distance from a source of disease. Logistic models were fitted to field data from artificially inoculated plots. The velocity of spread decreased along the row and increased in the direction of the prevailing winds. The rate of progression over time was plot dependent, and the velocity was dependent on the vigor of the vine (0.1 to 0.27 m day(-1) in areas of moderate vigor and 1.1 m day(-1) in areas of high vigor). When applied to a larger plot with natural primary foci, the spatiotemporal logistic model showed that the velocity and the slope of the gradient in space depended on the foci; however, the velocity remained in the same range. During the period of highest susceptibility for grape, the probability of a leaf becoming infected increased from 2.5 to 13%. Our logistic model was able to predict changes in disease over time of its extension within the plot; however, the crop heterogeneity prevented prediction of variability of disease at the vine scale. | ||||||
BibTeX:
@article{Calonnec2009,
author = {Calonnec, A. and Cartolaro, P. and Chadoeuf, J.},
title = {Highlighting Features of Spatiotemporal Spread of Powdery Mildew Epidemics in the Vineyard Using Statistical Modeling on Field Experimental Data},
journal = {Phytopathology},
year = {2009},
volume = {99},
number = {4},
pages = {411-422},
note = {0031-949X}
}
|
||||||
| Calonnec, A.; Cartolaro, P.; Deliere, L. & Chadoeuf, J. | Powdery mildew on grapevine: the date of primary contamination affects disease development on leaves and damage on grape |
2006 | Bulletin OILB/SROP | Vol. 29 (11) , pp. 67-73 |
||
| Abstract: The temporal evolution of the disease (powdery mildew caused by Uncinula necator) on leaves and damage on grape was monitored at different scales in an experiment in France using cv. Cabernet Sauvignon, in 1999 and 2001 in order to study the effect of early primary contamination on epidemic development and its relationship with damage on grape. At a vine scale, on vines artificially inoculated with 12 days delay, the disease evolution on leaves was delayed. At flowering, early contaminated vines were 60% more diseased than late contaminated vines. On bunches, the progression and final disease incidence were significantly different with (at veraison) an average severity of 99% for early contaminated vines versus 62% for late contaminated ones and 29% for uncontaminated ones. A significant difference for the Incidence-Severity relationship at the leaf scale was quantified indicating the difference in symptoms according to the date of contamination. At the plot scale (330 vines), we compared the maps of frequency of diseased leaves per vine at different scoring dates with the maps of frequency of bunches with a given level of damage. Epidemics initiated earlier were characterised by higher severity for a given level of frequency of diseased leaves (at the vine scale) and higher final diseased leaves frequency (at the plot scale). Early difference in the number of diseased leaves led to significant differences in the number of highly damaged clusters (>25%) and in the average clusters severity. The analysis of disease maps demonstrated the spatial relationship between the frequency of diseased leaves at flowering and the frequency of severely damaged bunches. | ||||||
BibTeX:
@article{Calonnec2006,
author = {Calonnec, A. and Cartolaro, P. and Deliere, L. and Chadoeuf, J.},
title = {Powdery mildew on grapevine: the date of primary contamination affects disease development on leaves and damage on grape},
journal = {Bulletin OILB/SROP},
year = {2006},
volume = {29},
number = {11},
pages = {67-73},
note = {Times Cited: 0},
url = { |
||||||
| Certain, G.; Bellier, E.; Planque, B. & Bretagnolle, V. | Characterising the temporal variability of the spatial distribution of animals: an application to seabirds at sea [BibTeX] |
2007 | Ecography | Vol. 30 (5) , pp. 695-708 |
||
BibTeX:
@article{Certain2007,
author = {Certain, G. and Bellier, E. and Planque, B. and Bretagnolle, V.},
title = {Characterising the temporal variability of the spatial distribution of animals: an application to seabirds at sea},
journal = {Ecography},
year = {2007},
volume = {30},
number = {5},
pages = {695-708},
url = { |
||||||
| Chadoeuf, J.; Bacro, J.N.; Thebaud, G. & Labonne, G. | Testing the boolean hypothesis in the non-convex case when a bounded grain can be assumed |
2008 | Environmetrics | Vol. 19 (2) , pp. 123-136 |
||
| Abstract: Spatial independence of objects is a strong hypothesis when using boolean models. Methods to test it have then been developed, but only when the objects are convex. We propose here to replace this assumption by a bound assumption of the objects which can be more easily assumed when modeling spatial patterns in ecology and agricultural science. A test is then proposed, based on the length of the voids of the intersection between transect lines and a dilation of the original process related to the bound value. Its application is shown to several examples, together with its extension to an epidemiological case on orchards, where this problem comes from. Copyright (c) 2007 John Wiley & Sons, Ltd. | ||||||
BibTeX:
@article{Chadoeuf2008,
author = {Chadoeuf, J. and Bacro, J. N. and Thebaud, G. and Labonne, G.},
title = {Testing the boolean hypothesis in the non-convex case when a bounded grain can be assumed},
journal = {Environmetrics},
year = {2008},
volume = {19},
number = {2},
pages = {123-136},
note = {Cited References: BERTUZZI P, 1995, EUR J SOIL SCI, V46, P215 CRESSIE N, 1991, STAT SPATIAL DATA DIGGLE PJ, 1981, BIOMETRICS, V37, P531 HALL P, 1988, INTRO THEORY COVERAG KAMPHORST EC, 2005, CATENA, V62, P189, DOI 10.1016/j.catena.2005.05.006 LASLETT GM, 1985, UNPUB INTENSITY ESTI MOLCHANOV S, 1997, STAT BOOLEAN MODELFO ROUSSET C, 2004, ORG SPATIALE ACTIVIT SCHMITT M, 1991, J APPL PROBAB, V28, P702 STOYAN D, 1995, STOCHASTIC GEOMETRY THEBAUD G, 2005, THESIS ECOLE NATL SU WIEGAND T, 2006, J ECOL, V94, P825, DOI 10.1111/j.1365-2745.2006.01113.x},
url = { |
||||||
| Chadoeuf, J.; Goulard, M.; Lefèvre, F.; Monestiez, P. & Pichot, C. Droesbeke, J.-J.; Lejeune, M. & Saporta, G. (Hrsg.) | Poisson non-stationnaire et échantillonnage semi-raréfié: comment les cèdres du Luberon envahissent-ils l'espace? [BibTeX] |
2006 | Analyse statistique des données spatiales | |||
BibTeX:
@incollection{Chadoeuf2006,
author = {Chadoeuf, J. and Goulard, M. and Lefèvre, F. and Monestiez, P. and Pichot, C.},
title = {Poisson non-stationnaire et échantillonnage semi-raréfié: comment les cèdres du Luberon envahissent-ils l'espace?},
booktitle = {Analyse statistique des données spatiales},
publisher = {Editions Technip},
year = {2006},
note = {* INRA Centre d'Avignon, Documentation, Domaine St Paul, Site .Agroparc, 84914 Avignon cedex 9}
}
|
||||||
| Chekroun, M.D. & Roques, L.J. | Models of population dynamics under the influence of external perturbations: mathematical results |
2006 | Comptes Rendus Mathematique | Vol. 343 (5) , pp. 307-310 |
||
| Abstract: In this note, we describe the stationary equilibria and the asymptotic behaviour of an heterogeneous logistic reaction-diffusion equation under the influence of autonomous or time-periodic forcing terms. We show that the study of the asymptotic behaviour in the time-periodic forcing case can be reduced to the autonomous one, the last one being described in function of the 'size' of the external perturbation. Our results can be interpreted in terms of maximal sustainable yields from populations. We briefly discuss this last aspect through a numerical computation. | ||||||
BibTeX:
@article{Chekroun2006,
author = {Chekroun, M. D. and Roques, L. J.},
title = {Models of population dynamics under the influence of external perturbations: mathematical results},
journal = {Comptes Rendus Mathematique},
year = {2006},
volume = {343},
number = {5},
pages = {307-310},
note = {Cited References: BERESTYCKI H, 2005, J MATH BIOL, V51, P75 CHEKROUN M, UNPUB INFLUENCE SEAS FISHER RA, 1937, ANN EUGEN, V7, P335 HALE JK, 1990, J INTEGRAL EQUAT, V2, P463 PAZY A, 1983, SEMIGROUP LINEAR OPE ROQUES L, 2006, HARVESTING MODELS HE SELL GR, 2002, DYNAMICS EVOLUTIONAR SHIGESADA N, 1986, THEOR POPUL BIOL, V30, P143},
url = { |
||||||
| Corbane, C.; Andrieux, P.; Voltz, M.; Chadoeuf, J.; Albergel, J.; Robbez-Masson, J. & Zante, P. | Assessing the variability of soil surface characteristics in row-cropped fields: The case of Mediterranean vineyards in Southern France [BibTeX] |
2008 | Catena | Vol. 72 (1) , pp. 79-90 |
||
BibTeX:
@article{Corbane2008,
author = {Corbane, C. and Andrieux, P. and Voltz, M. and Chadoeuf, J. and Albergel, J. and Robbez-Masson, J.M. and Zante, P.},
title = {Assessing the variability of soil surface characteristics in row-cropped fields: The case of Mediterranean vineyards in Southern France},
journal = {Catena},
year = {2008},
volume = {72},
number = {1},
pages = {79-90}
}
|
||||||
| Cristofol, M. & Roques, L. | Biological invasions: Deriving the regions at risk from partial measurements |
2008 | Mathematical Biosciences | Vol. 215 (2) , pp. 158-166 |
||
| Abstract: We consider the problem of forecasting the regions at higher risk for newly introduced invasive species. Favourable and unfavourable regions may indeed not be known a priori, especially for exotic species whose hosts in native range and newly-colonised areas can be different. Assuming that the species is modelled by a logistic-like reaction-diffusion equation, we prove that the spatial arrangement of the favourable and unfavourable regions can theoretically be determined using only partial measurements of the population density: (1) a local 'spatio-temporal' measurement, during a short time period and, (2) a 'spatial' measurement in the whole region susceptible to colonisation. We then present a stochastic algorithm which is proved analytically, and then on several numerical examples, to be effective in deriving these regions. (C) 2008 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Cristofol2008,
author = {Cristofol, M. and Roques, L.},
title = {Biological invasions: Deriving the regions at risk from partial measurements},
journal = {Mathematical Biosciences},
year = {2008},
volume = {215},
number = {2},
pages = {158-166},
note = {Cited References: *USDA NAT INV SPEC, 2006, EX ORD, P13112 ALBANO P, 2000, ELECT J DIFF EQNS, V22, P1 BAUDOUIN L, 2002, INVERSE PROBL, V18, P1537 BERESTYCKI H, 2005, J MATH BIOL, V51, P75, DOI 10.1007/s00285-004-0313-3 BERESTYCKI H, 2005, J MATH PURE APPL, V84, P1101, DOI 10.1016/j.matpur.2004.10.006 CANTRELL RS, 2003, SERIES MATH COMPUTAT CARDOULIS L, 2008, J INV 3 POSED PROB, V5, P127 CRISTOFOL M, 2006, INVERSE PROBL, V22, P1561, DOI 10.1088/0266-5611/22/5/003 EVANS LC, 1998, PARTIAL DIFFERENTIAL FISHER RA, 1937, ANN EUGENIC 4, V7, P355 FURSIKOV A, 2000, TRANSLATIONS MATH MO HAJEK B, 1988, MATH OPER RES, V13, P311 HENDERSON D, 2003, HDB METAHEURISTICS, P287 KINEZAKI N, 2006, POPUL ECOL, V48, P263, DOI 10.1007/s10144-006-0263-2 KIRKPATRICK S, 1983, SCIENCE, V220, P671 KOLMOGOROV A, 1937, B U ETAT MOSCOW, V6, P1 LIEBHOLD AM, 1995, FOREST SCI MONOGR, V30, P1 OKUBO A, 2002, DIFFUSION ECOLOGICAL ROQUES L, 2007, J MATH BIOL, V55, P189, DOI 10.1007/s00285-007-0076-8 ROQUES L, 2007, MATH BIOSCI, V210, P34, DOI 10.1016/j.mbs.2007.05.007 ROQUES L, 2007, SIAM J APPL MATH, V68, P133, DOI 10.1137/060676994 SHIGESADA N, 1986, THEOR POPUL BIOL, V30, P143 SHIGESADA N, 1997, BIOL INVASIONS THEOR SKELLAM JG, 1951, BIOMETRIKA, V38, P196 TURCHIN P, 1998, QUANTITATIVE ANAL MO},
url = { |
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| Darmency, H.; Klein, E.K.; De Garanbe, T.G.; Gouyon, P.H.; Richard-Molard, M. & Muchembled, C. | Pollen dispersal in sugar beet production fields |
2009 | Theoretical And Applied Genetics | Vol. 118 (6) , pp. 1083-1092 |
||
| Abstract: Pollen-mediated gene flow has important implications for biodiversity conservation and for breeders and farmers' activities. In sugar beet production fields, a few sugar beet bolters can produce pollen as well as be fertilized by wild and weed beet. Since the crop, the wild beets, and the weed beets are the same species and intercross freely, the question of pollen flow is an important issue to determine the potential dispersal of transgenes from field to field and to wild habitats. We report here an experiment to describe pollen dispersal from a small herbicide-resistant sugar beet source towards male sterile target plants located along radiating lines up to 1,200 m away. Individual dispersal functions were inferred from statistical analyses and compared. Pollen limitation, as expected in root-production fields, was confirmed at all the distances from the pollen source. The number of resistant seeds produced by bait plants best fitted a fat-tailed probability distribution curve of pollen grains (power-law) dependent on the distance from the pollen source. A literature survey confirmed that power-law function could fit in most cases. The b coefficient was lower than 2. The number of fertilized flowers by background (herbicide-susceptible) pollen grains was uniform across the whole field. Airborne pollen had a fertilization impact equivalent to that of one adjacent bolter. The individual dispersal function from different pollen sources can be integrated to provide the pollen cloud composition for a given target plant, thus allowing modeling of gene flow in a field, inter-fields in a small region, and also in seed-production area. Long-distance pollen flow is not negligible and could play an important role in rapid transgene dispersal from crop to wild and weed beets in the landscape. The removing of any bolting, herbicide-resistant sugar beet should be compulsory to prevent the occurrence of herbicide-resistant weed beet, thus preventing gene flow to wild populations and preserving the sustainable utility of the resistant varieties. Whether such a goal is attainable remains an open question and certainly would be worth a large scale experimental study. | ||||||
BibTeX:
@article{Darmency2009,
author = {Darmency, H. and Klein, E. K. and De Garanbe, T. G. and Gouyon, P. H. and Richard-Molard, M. and Muchembled, C.},
title = {Pollen dispersal in sugar beet production fields},
journal = {Theoretical And Applied Genetics},
year = {2009},
volume = {118},
number = {6},
pages = {1083-1092},
note = {0040-5752}
}
|
||||||
| Debain, S.; Chadaeuf, J.; Curt, T.; Kunstler, G. & Lepart, J. | Comparing effective dispersal in expanding population of Pinus sylvestris and Pinus nigra in calcareous grassland [BibTeX] |
2007 | Canadian Journal of Forest Research | Vol. 37 (4) , pp. 705-718 |
||
BibTeX:
@article{Debain2007,
author = {Debain, S. and Chadaeuf, J. and Curt, T. and Kunstler, G. and Lepart, J.},
title = {Comparing effective dispersal in expanding population of Pinus sylvestris and Pinus nigra in calcareous grassland},
journal = {Canadian Journal of Forest Research},
year = {2007},
volume = {37},
number = {4},
pages = {705-718},
url = { |
||||||
| Debras, J.F.; Senoussi, R.; Rieux, R.; Buisson, E. & Dutoit, T. | Spatial distribution of an arthropod community in a pear orchard (southern France) - Identification of a hedge effect |
2008 | Agriculture Ecosystems & Environment | Vol. 127 (3-4) , pp. 166-176 |
||
| Abstract: This study analysed specific features of the spatial distribution of a global population of arthropods in an experimental orchard of pear trees, Pyrus communis (L.), in southern France. Insect fauna was sampled by regular beating of the 210 trees in the experimental orchard from spring to autumn in three consecutive years (2004-2006). This orchard, where no chemical treatments had been applied since 2000, is bordered to the north by a mixed hedge, to the south by a cypress hedge of Cupressus sempervirens (L.), and to the east and west by other crops. Statistical analyses of climatic variables comparing the 3 years showed no differences with respect to rainfall, temperature or wind variables during psyllid proliferation periods. However, statistical spatial analyses demonstrated a hedge effect on local ecological variables, such as population abundance, species richness and the Shannon diversity index, in a zone close to the mixed hedge, by comparison with zones close to other margins of the orchard. This spatial distribution exhibited temporal stability and pointed to two distinct zones: one unprotected and one protected by the mixed hedge from the Mistral wind. The first zone contained a population of psyllids that was significantly larger than that in the protected zone, which harboured a great majority of beneficial insects. This spatial stability over 3 years suggested in particular that climatic factors were related to psyllids, while spatial factors, such as distance from the mixed hedge, were related to beneficial insects. In the light of these results, we concluded as to the strong potential role that hedges could play in reducing crop pest populations. (C) 2008 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Debras2008,
author = {Debras, J. F. and Senoussi, R. and Rieux, R. and Buisson, E. and Dutoit, T.},
title = {Spatial distribution of an arthropod community in a pear orchard (southern France) - Identification of a hedge effect},
journal = {Agriculture Ecosystems & Environment},
year = {2008},
volume = {127},
number = {3-4},
pages = {166-176},
note = {Cited References: ALTIERI MA, 1999, AGR ECOSYST ENVIRON, V74, P19 AVIRON S, 2003, INT ASS LANDSC EC WO BARBAR Z, 2006, EXP APPL ACAROL, V40, P175, DOI 10.1007/s10493-006-9044-z BOHAN DA, 2000, J ANIM ECOL, V69, P367 BUREL F, 1996, CRIT REV PLANT SCI, V15, P169 BUTTS EC, 1973, ECOL APPL, V14, P1615 DEBRAS JF, 2006, ANN APPL BIOL, V149, P347, DOI 10.1111/j.1744-7348.2006.00102.x DEBRAS JF, 2007, CR BIOL, V330, P664, DOI 10.1016/j.crvi.2007.07.003 DUELLI P, 1998, BIODIVERS CONSERV, V7, P297 ERLER F, 2004, PHYTOPARASITICA, V32, P295 FOURNIER E, 2002, AGR ECOSYST ENVIRON, V89, P253 FULLER RJ, 1995, CONSERV BIOL, V9, P1425 GAY E, 2006, J DAIRY SCI, V89, P2487 GIBBS AL, 2002, INT STAT REV, V70, P419 GREENLEAF SS, 2006, P NATL ACAD SCI USA, V103, P13890, DOI 10.1073/pnas.0600929103 GRUM L, 1971, EKOLOGIA POLSKA, V19, P47 HERZOG F, 2005, AGR ECOSYST ENVIRON, V108, P189, DOI 10.1016/j.agee.2005.02.003 HONEK A, 1988, PEDOBIOLOGIA, V32, P233 HUANG JK, 2002, NATURE, V418, P678 JEANNERET P, 2000, INTERCHANGES INSECTS JERVIS MA, 1996, INSECT NATURAL ENEMI KREITER S, 2002, ENVIRON ENTOMOL, V31, P648 LYOUSSOUFI A, 1994, THESIS AIX MARSEILLE MANLY BFJ, 1991, RANDOMIZATION M CARL MAUDSLEY MJ, 2000, J ENVIRON MANAGE, V60, P65 MICHEL N, 2006, ACTA OECOL, V30, P11, DOI 10.1016/j.actao.2005.12.006 NAEEM S, 1997, NATURE, V390, P507 ORTIZ R, 1998, J BIOTECHNOL, V1, P1 SAKATA H, 2000, POPUL ECOL, V42, P171 SCOTT DW, 1992, PRACTICE VISUALIZATI SISTERSON MS, 2007, ENVIRON ENTOMOL, V36, P121 SOLOMON MG, 2000, BIOCONTROL SCI TECHN, V10, P91 SOTHERTON NW, 1984, ANN APPL BIOL, V105, P423 SUCKLING DM, 2006, J APPL ENTOMOL, V130, P263, DOI 10.1111/j.1439-0418.2006.01064.x THOMAS CFG, 2001, J APPL ECOL, V38, P100 THOMAS MB, 1992, OECOLOGIA, V89, P78 TIXIER MS, 2006, EXP APPL ACAROL, V39, P227, DOI 10.1007/s10493-006-9010-9 WAY MJ, 1992, ANNU REV ENTOMOL, V37, P479},
url = { |
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| Devaux, C.; Klein, E.K.; Lavigne, C.; Sausse, C. & Messean, A. | Environmental and landscape effects on cross-pollination rates observed at long distance among French oilseed rape Brassica napus commercial fields |
2008 | Journal Of Applied Ecology | Vol. 45 (3) , pp. 803-812 |
||
| Abstract: 1. Evaluation of our ability to predict cross-pollination rates (CPR) at long distance using dispersal functions estimated in experimental set-ups differing by either their scale or their environmental conditions is crucial to establish appropriate management rules following the release of genetically modified (GM) crops. 2. From 1998 to 2004 we measured oilseed rape CPR in commercial fields for 44 donor-recipient couples separated by 220 up to 2000 m, from up to three different pollen donor cultivars in two French oilseed rape production areas. We followed the same sampling and screening designs and tested the effect of region, year, size, cultivar and distance on the observed CPR. 3. We then compared observed CPR to predictions from six empirical pollen dispersal models based on dispersal kernels that were fitted previously at the local and landscape scales. These predictions allowed us to test the possibility to extrapolate and up-scale dispersal kernels. 4. The observed CPR varied from 0% to 0.092%. They were higher in Champagne-Ardennes, where they depended negatively on distance, than in Bourgogne where they did not depend on distance. CPR also differed among years, being nil for the last 3 successive years, partly because of different environmental conditions and detection issues. CPR depended further on the source cultivars due to differences in pollen production. Dispersal kernels fitted at the local scale lead to systematic and huge underestimation of CPR, when observed. The power-law kernel fitted at the landscape scale under-estimated CPR by two orders of magnitude above 400 m but followed the rate of decrease of the observed pollination with distance. 5. Synthesis and applications. Caution should be taken when extrapolating and up-scaling dispersal kernels and models because predictions may differ greatly from observations. Models should rely at least upon dispersal kernels estimated from landscape-scale data obtained in different regions. Models should also integrate several phenomena at the agro-ecosystem scale including the dispersal by insects and become more mechanistic to account for variations observed among years, environments and distance to borders. | ||||||
BibTeX:
@article{Devaux2008,
author = {Devaux, C. and Klein, E. K. and Lavigne, C. and Sausse, C. and Messean, A.},
title = {Environmental and landscape effects on cross-pollination rates observed at long distance among French oilseed rape Brassica napus commercial fields},
journal = {Journal Of Applied Ecology},
year = {2008},
volume = {45},
number = {3},
pages = {803-812},
note = {Cited References: *SAS I INC, 1989, SAS STAT US GUID VER ABRAMOWITZ M, 1964, HDB MATH FUNCTIONS F ARIAS DM, 1994, THEOR APPL GENET, V89, P655 AUSTERLITZ F, 2004, MOL ECOL, V13, P937, DOI 10.1111/j.1365-294X.2004.02100.x BATEMAN AJ, 1947, HEREDITY, V1, P303 BECKIE HJ, 2003, ECOL APPL, V13, P1276 CHAMPOLIVIER J, 1999, BCPC SYMP SER, P233 COLBACH N, 2005, EUROPEAN J AGRONOMY, V21, P193 CRAWLEY MJ, 2004, P ROY SOC LOND B BIO, V271, P1909, DOI 10.1098/rspb.2004.2814 CRESSWELL JE, 2004, J APPL ECOL, V41, P539 CRESSWELL JE, 2006, FUNCT ECOL, V20, P245, DOI 10.1111/j.1365-2435.2006.01085 DEVAUX C, 2007, MOL ECOL, V16, P487, DOI 10.1111/j.1365-294X.2006.03155.x ELLSTRAND NC, 2003, PHILOS T R SOC B, V358, P1163, DOI 10.1098/rstb.2003.1299 FRECKLETON RP, 2004, J APPL ECOL, V41, P599 HALL L, 2000, WEED SCI, V48, P688 HOYLE M, 2006, FUNCTIONAL ECOLOGY, V20, P1 KLEIN EK, 2003, ECOL MONOGR, V73, P131 KLEIN EK, 2006, J APPL ECOL, V43, P141, DOI 10.1111/j.1365-2664.2005.01108.x LAVIGNE C, 2004, INTROGRESSION GENETI, P353 RAMSAY G, 2003, QUANTIFYING LANDSCAP RIEGER MA, 2002, SCIENCE, V296, P2386 SCHEFFLER JA, 1995, PLANT BREEDING, V114, P317 SHAW MW, 2006, P R SOC B, V273, P1705, DOI 10.1098/rspb.2006.3491 SIMARD MJ, 2002, WEED TECHNOL, V16, P433 SIMPSON E, 2006, PLANT GENET RESOUR-C, V4, P96, DOI 10.1079/PGR2005103 SIMPSON EC, 1999, BCPC SYMP SER, P75 SLAVOV GT, 2002, ECOLOGICAL AGRONOMIC, P106 SQUIRE GR, 2003, PHILOS T ROY SOC B, V358, P1779, DOI 10.1098/rstb.2003.1403 STANILAND BK, 2000, CAN J PLANT SCI, V80, P521 THOMPSON CE, 1999, BCPC SYMP SER, P95 WEEKES R, 2005, TRANSGENIC RES, V14, P749, DOI 10.1007/s11248-005-0943-2},
url = { |
||||||
| Devaux, C.; Lavigne, C.; Austerlitz, F. & Klein, E.K. | Modelling and estimating pollen movement in oilseed rape (Brassica napus) at the landscape scale using genetic markers [BibTeX] |
2007 | Molecular Ecology | Vol. 16 , pp. 487-499 |
||
BibTeX:
@article{Devaux2007,
author = {Devaux, C. and Lavigne, C. and Austerlitz, F. and Klein, E. K.},
title = {Modelling and estimating pollen movement in oilseed rape (Brassica napus) at the landscape scale using genetic markers},
journal = {Molecular Ecology},
year = {2007},
volume = {16},
pages = {487-499}
}
|
||||||
| Dur, G.; Souissi, S.; Devreker, D.; Ginot, V.; Schmitt, F.G. & Hwang, J.S. | An individual-based model to study the reproduction of egg bearing copepods: Application to Eurytemora affinis (Copepoda Calanoida) from the Seine estuary, France |
2009 | Ecological Modelling | Vol. 220 (8) , pp. 1073-1089 |
||
| Abstract: Limited empirical studies have elucidated the daily egg production and associated reproductive processes of egg bearing copepod. Herein, we present an individual-based model which constitutes a realistic representation of the reproduction in egg bearing copepods. The model has been parameterized using an extensive set of experimental data obtained from the literature and from the laboratory and field experiments on the estuarine copepod Eurytemora affinis. The proposed model takes into account the adult female longevity, the clutch size and interclutch duration, which is a function of egg maturation time and latency time required by the female after egg hatching to produce a new clutch. The embryonic development time and hatching success are also taken into account. The effect of temperature on the means and variances of above-mentioned reproductive parameters has been also incorporated. A multi agent system based generic platform "Mobidyc" has been used to generate and calibrate the model. The model demonstrates the reproductive parameters of females of E. affinis which is validated through individual based experiments. Temperature specific simulations provide a dynamical explanation of temperature effect on the cumulative egg production. The daily survival principally affects the number of clutches produced per female during its life span. The results obtained in the present study by combining temperature and survival effects reveal the relatively greater importance of the first factor on the daily egg production of egg-carrying copepods. The present model is generic and hence easily applicable to other animals with comparable reproductive strategy. (c) 2009 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Dur2009,
author = {Dur, G. and Souissi, S. and Devreker, D. and Ginot, V. and Schmitt, F. G. and Hwang, J. S.},
title = {An individual-based model to study the reproduction of egg bearing copepods: Application to Eurytemora affinis (Copepoda Calanoida) from the Seine estuary, France},
journal = {Ecological Modelling},
year = {2009},
volume = {220},
number = {8},
pages = {1073-1089},
note = {0304-3800}
}
|
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| El Smaily, M.; Hamel, F. & Roques, L. | Homogenization and influence of fragmentation in a biological invasion model |
2009 | Discrete and Continuous Dynamical Systems | Vol. 25 (1) , pp. 321-342 |
||
| Abstract: In this paper, some properties of the minimal speeds of pulsating Fisher-KPP fronts in periodic environments are established. The limit of the speeds at the homogenization limit is proved rigorously. Near this limit, generically, the fronts move faster when the spatial period is enlarged, but the speeds vary only at the second order. The dependence of the speeds on habitat fragmentation is also analyzed in the case of the patch model. | ||||||
BibTeX:
@article{ElSmaily2009,
author = {El Smaily, M. and Hamel, F. and Roques, L.},
title = {Homogenization and influence of fragmentation in a biological invasion model},
journal = {Discrete and Continuous Dynamical Systems},
year = {2009},
volume = {25},
number = {1},
pages = {321-342},
note = {Times Cited: 0},
url = { |
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| Fabre, F.; Bruchou, C.; Palloix, A. & Moury, B. | Key determinants of resistance durability to plant viruses: Insights from a model linking within- and between-host dynamics |
2009 | Virus Research | Vol. 141 (2) , pp. 140-149 |
||
| Abstract: The emergence of new genotypes of parasites involves several evolutionary, epidemiological and ecological processes whose individual effects and interactions are difficult to disentangle using experimental approaches. Here, a model is proposed to investigate how these processes lead to the emergence of plant viral genotypes breaking down qualitative resistance genes. At the individual plant scale, selection, drift and mutation processes shape the evolution of viral populations from a set of differential equations. The spatial segregation of virus genotypes in their hosts is also considered. At the host population scale, the epidemiological dynamics is given by an individual-based algorithm. Global sensitivity analyses allowed ranking the ten demo-genetic and epidemiological parameters of the model according to their impact on the mean and variance of the risk of breakdown of a plant resistance. Demo-genetic parameters (number and nature Of Mutations involved in breakdown, fitness of mutant genotypes) had the largest impact on the mean breakdown Fisk, whereas epidemiological parameters had more influence on its standard deviation. It is discussed how these results can be used to choose the potentially most durable resistance genes among a pool of candidates. Finally, Our analyses point out the parameters which should be estimated more precisely to improve durability predictions. (C) 2008 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Fabre2009,
author = {Fabre, F. and Bruchou, C. and Palloix, A. and Moury, B.},
title = {Key determinants of resistance durability to plant viruses: Insights from a model linking within- and between-host dynamics},
journal = {Virus Research},
year = {2009},
volume = {141},
number = {2},
pages = {140-149},
note = {0168-1702}
}
|
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| Fallour-Rubio, D.; Guibal, F.; Klein, E.K.; Bariteau, M. & Lefevre, F. | Rapid changes in plasticity across generations within an expanding cedar forest |
2009 | Journal Of Evolutionary Biology | Vol. 22 (3) , pp. 553-563 |
||
| Abstract: We investigated the inter-individual variation of phenotypic plasticity and its evolution across three generations within an expanding forest. Plasticity was assessed in situ from dendrochronological data as the response of radial growth to summer rainfall. A linear mixed model was used to account for spatial effects (environment and stand structure), temporal factors (stand dynamics) and the variation with age. Beyond these effects, our results reveal a significant inter-individual variance of growth and plasticity within each generation. We also show that the mean values and variances of growth and plasticity changed significantly across generations, with different patterns for both traits. The possible environmental and genetic drivers of these changes are discussed. Contrasting with the trade-off between stress tolerance and plasticity generally observed among populations, we detected a positive covariance at the individual level, which does not support the cost of plasticity hypothesis in this case. | ||||||
BibTeX:
@article{Fallour-Rubio2009,
author = {Fallour-Rubio, D. and Guibal, F. and Klein, E. K. and Bariteau, M. and Lefevre, F.},
title = {Rapid changes in plasticity across generations within an expanding cedar forest},
journal = {Journal Of Evolutionary Biology},
year = {2009},
volume = {22},
number = {3},
pages = {553-563},
note = {Cited References: BOUVET JM, 2005, ANN BOT-LONDON, V96, P811, DOI 10.1093/aob/mci231 BROMMER JE, 2005, EVOLUTION, V59, P1362 CHARMANTIER A, 2008, SCIENCE, V320, P800, DOI 10.1126/science.1157174 CHUINE I, 2000, J ECOL, V88, P561 COINTAT M, 1996, REV FR, V48, P503 CRISPO E, 2007, EVOLUTION, V61, P2469, DOI 10.1111/j.1558-5646.2007.00203.x DAUBREE JB, 1993, ANN SCI FOR S1, V50, S271 DAVIS MB, 2001, SCIENCE, V292, P673 DUCOUSSO A, 1996, ANN SCI FOREST, V53, P775 DUNCAN RP, 1989, NZ NATURAL SCI, V16, P31 ELLNER S, 1994, AM NAT, V143, P403 ERIKSSON G, 1980, STUD SUEC FALLOUR D, 1998, THESIS U AIX MARSEIL FALLOUR D, 2001, J HERED, V92, P260 GILLESPIE JH, 1989, GENETICS, V10, P253 GUIBAL F, 1985, ECOL MEDIT, V11, P87 GUIOT J, 1986, REV STAT APPL, V34, P15 HIGGINS SI, 2003, J ECOL, V91, P341 KAUFMAN SR, 2001, OECOLOGIA, V127, P487 LEFEVRE F, 2004, HEREDITY, V93, P542, DOI 10.1038/sj.hdy.6800549 LITTELL RC, 2006, SAS MIXED MODELS MATYAS C, 1992, SILVAE GENET, V41, P370 MCLACHLAN JS, 2005, ECOLOGY, V86, P2088 MIKOLA J, 1982, SILVA FENNICA, V16, P141 MINER BG, 2005, TRENDS ECOL EVOL, V20, P685, DOI 10.1016/j.tree.2005.08.002 MODRZYNSKI J, 2002, FOREST ECOL MANAG, V165, P105 NUSSEY DH, 2005, SCIENCE, V310, P304, DOI 10.1126/science.1117004 NUSSEY DH, 2007, J EVOLUTION BIOL, V20, P831, DOI 10.1111/j.1420-91001.2007.01300.x PIGLIUCCI M, 2003, EVOLUTION, V57, P1455 PIGLIUCCI M, 2005, TRENDS ECOL EVOL, V20, P481, DOI 10.1016/j.tree.2005.06.001 REHFELDT GE, 2001, CLIMATIC CHANGE, V50, P355 REHFELDT GE, 2002, GLOBAL CHANGE BIOL, V8, P912 RELYEA RA, 2002, AM NAT, V159, P272 SAVOLAINEN O, 2004, FOREST ECOL MANAG, V197, P79, DOI 10.1016/j.foreco.2004.05.006 SAVOLAINEN O, 2007, ANNU REV ECOL EVOL S, V38, P595, DOI 10.1146/annurev.ecolsys.38.091206.095646 SCHLICHTING CD, 1986, ANNU REV ECOL SYST, V17, P667 SCHWEINGRUBER FH, 1990, DENDROCHRONOLOGIA, V8, P9 SKROPPA T, 1997, GENET, V4, P171 STEINGER T, 2003, J EVOLUTION BIOL, V16, P313 STOKES MA, 1968, INTRO TREE RING DATI VIA S, 1995, TRENDS ECOL EVOL, V10, P212 WADDINGTON CH, 1953, EVOLUTION, V7, P386 ZHENG YQ, 1999, THEOR APPL GENET, V98, P765},
url = { |
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| Fayard, J.; Klein, E.K. & Lefevre, F. | Long distance dispersal and the fate of a gene from the colonization front |
2009 | Journal of Evolutionary Biology | Vol. 22 (11) , pp. 2171-2182 |
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| Abstract: There is an increasing recognition that long distance dispersal (LDD) plays a key role in establishing spatial genetic structure during colonization. Recent works, focused on short distance dispersal, demonstrated that a neutral mutation arising at the colonization front can either 'surf' with the wave front and reach high frequencies or stay near its place of origin at low frequencies. Here, we examine how LDD, and more generally the shape of the dispersal kernel, modifies this phenomenon and how the width of the colonization corridor affects the fate of the mutation. We demonstrate that when LDD events are more frequent, the 'surfing phenomenon' is less frequent, probably because any alleles can get far ahead from the colonization front and preclude the invasion by others alleles, thus leading to an attenuation of the diversity loss. We also demonstrate that the width of the colonization corridor influences the fate of the mutation, wide spaces decreasing the probability of invasion. Overall, the genetic structure of diversity resulted not only from LDD but also particularly from the shape of the dispersal kernel. | ||||||
BibTeX:
@article{Fayard2009,
author = {Fayard, J. and Klein, E. K. and Lefevre, F.},
title = {Long distance dispersal and the fate of a gene from the colonization front},
journal = {Journal of Evolutionary Biology},
year = {2009},
volume = {22},
number = {11},
pages = {2171-2182},
url = { |
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| Flecher, C.; Naveau, P. & Allard, D. | Estimating the closed skew-normal distribution parameters using weighted moments |
2009 | Statistics & Probability Letters | Vol. 79 (19) , pp. 1977-1984 |
||
| Abstract: Skewness is often present in a wide range of applied problems. One possible approach to model this skewness is based on the class of skew-normal distributions. Fitting such distributions remains an inference challenge in various cases. In this paper. we propose and study novel estimators using weighted moments for the closed multivariate skew-normal distribution. (C) 2009 Published by Elsevier B.V. | ||||||
BibTeX:
@article{Flecher2009,
author = {Flecher, C. and Naveau, P. and Allard, D.},
title = {Estimating the closed skew-normal distribution parameters using weighted moments},
journal = {Statistics & Probability Letters},
year = {2009},
volume = {79},
number = {19},
pages = {1977-1984},
url = { |
||||||
| Forbes, F.; Peyrard, N.; Fraley, C.; Georgian-Smith, D.; Goldhaber, D.M. & Raftery, A.E. | Model-based region-of-interest selection in dynamic breast MRI |
2006 | Journal of Computer Assisted Tomography | Vol. 30 (4) , pp. 675-687 |
||
| Abstract: Magnetic resonance imaging (MRI) is emerging as a, powerful tool for the diagnosis of breast abnormalities. Dynamic analysis of the temporal pattern of contrast uptake has been applied in differential diagnosis of benign and malignant lesions to improve. specificity. Selecting a region of interest (ROI) is an almost universal step in the process of examining the contrast uptake characteristics of a breast lesion. We propose an ROI selection method that combines model-based clustering of the pixels with Bayesian morphology, a new statistical image segmentation method. We then investigate tools for subsequent analysis of signal intensity time course data in the selected region. Results on a database of 19 patients indicate that the method provides informative segmentations and good detection rates. | ||||||
BibTeX:
@article{Forbes2006,
author = {Forbes, F. and Peyrard, N. and Fraley, C. and Georgian-Smith, D. and Goldhaber, D. M. and Raftery, A. E.},
title = {Model-based region-of-interest selection in dynamic breast MRI},
journal = {Journal of Computer Assisted Tomography},
year = {2006},
volume = {30},
number = {4},
pages = {675-687},
note = {Cited References: ARMITAGE P, 2005, MED IMAGE ANAL, V9, P315 BANFIELD JD, 1993, BIOMETRICS, V49, P803 BESAG J, 1986, J ROY STAT SOC B MET, V48, P259 BLUEMKE DA, 2004, JAMA-J AM MED ASSOC, V292, P2735 CHEN WJ, 2004, MED PHYS, V31, P1076 CHOI N, 2005, J COMPUT ASSIST TOMO, V29, P834 DEMPSTER AP, 1977, J ROY STAT SOC B MET, V39, P1 DEPASQUALE F, 2004, J ROY STAT SOC C-A 3, V53, P475 DEURLOO EE, 2005, RADIOLOGY, V234, P693 FISCHER H, 1999, INT J IMAG SYST TECH, V10, P199 FORBES F, 1999, J AM STAT ASSOC, V94, P555 FRALEY C, 2002, J AM STAT ASSOC, V97, P611 FRALEY C, 2003, J CLASSIF, V20, P263 HEIJMANS HJAM, 1995, SIAM REV, V37, P1 HELBICH TH, 2000, EUR J RADIOL, V34, P208 HELD K, 1997, IEEE T MED IMAGING, V16, P878 HYLTON N, 2005, J CLIN ONCOL, V23, P1678 JACOBS MA, 2004, J MAGNET RESONANCE I, V21, P23 KASS RE, 1995, J AM STAT ASSOC, V90, P733 KNEESHAW PJ, 2003, BRIT J CANCER, V88, P4 KUHL CK, 2000, EUR RADIOL, V10, P46 LI AJ, 1999, STREAMING DATA ANAL LIBERMAN L, 2002, RADIOL CLIN N AM, V40, P409 LIU PF, 1998, BRIT J RADIOL, V71, P501 LUCHT REA, 2005, INVEST RADIOL, V40, P442 MCLACHLAN GJ, 2000, FINITE MIXTURE MODEL MIYAKE K, 2005, J COMPUT ASSIST TOMO, V29, P772 NUNES LW, 2001, RADIOLOGY, V219, P484 PADHANI AR, 2002, J MAGN RESON IMAGING, V16, P407 PEDICONI F, 2005, INVEST RADIOL, V40, P448 PENN AI, 1999, ACAD RADIOL, V6, P156 PFLEIDERER SR, 2005, INVEST RADIOL, V40, P458 PREDA A, 2005, INVEST RADIOL, V40, P349 SAMPAT MP, 2005, HDB IMAGE VIDEO PROC, P1195 SARDANELLI F, 2004, EUR RADIOL, V14, P65 SCHWARZ G, 1978, ANN STAT, V6, P461 SINHA S, 1997, JMRI-J MAGN RESON IM, V7, P1016 SZABO BK, 2003, ACTA RADIOL, V44, P379 TOZAKI M, 2005, RAD MED, V23, P43 TZACHEVA AA, 2003, J MAGN RESON IMAGING, V17, P337 VOMWEG TW, 2003, MED PHYS, V30, P2350 VORNWEG TW, 2004, EUR RADIOL, V14, P1732 WELLS WM, 1996, IEEE T MED IMAGING, V15, P429 WIENER JI, 2005, AM J ROENTGENOL, V184, P878 WOODHAMS R, 2005, J COMPUT ASSIST TOMO, V29, P644 YOO SS, 2002, INVEST RADIOL, V37, P647 ZHANG YY, 2001, IEEE T MED IMAGING, V20, P45},
url = { |
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| Gaba, S.; Cabaret, J.; Ginot, V. & Silvestre, A. | The early drug selection of nematodes to anthelmintics: stochastic transmission and population in refuge |
2006 | Parasitology | Vol. 133 , pp. 345-356 |
||
| Abstract: We have developed an individual-based model to reflect the complexity of the early phase of drug resistance selection in a nematode/sheep model. The infection process consists of the stochastic ingestion of infective larvae spatially aggregated in clumps. Each clump corresponds to infective larvae, which are the offspring of the mature nematodes from a given sheep. We studied the dynamics of the parasitic population and the frequency of the recessive resistance alleles during selection by anthelmintic treatments. The interaction between genetic and demographic processes illustrated the trade-off between the control of the infection and the delay of resistance selection. We confirmed the importance of the number of treatments and their timing. The same treatment frequency may result in different outcomes on resistance selection in relation to the size of the refuge (infective larvae on pasture). Treatment applied during the summer (when the mortality of infective larvae on pasture was high), may lead to a rapid selection of drug resistance and a lack of control of sheep and pasture contamination. We showed that higher stocking rates were also a force in promoting the resistance allele selection. | ||||||
BibTeX:
@article{Gaba2006b,
author = {Gaba, S. and Cabaret, J. and Ginot, V. and Silvestre, A.},
title = {The early drug selection of nematodes to anthelmintics: stochastic transmission and population in refuge},
journal = {Parasitology},
year = {2006},
volume = {133},
pages = {345-356},
note = {Cited References: AUMONT G, 1992, PREV VET MED, V12, P245 BARGER IA, 1993, INT J PARASITOL, V23, P463 BARNES EH, 1995, PARASITOL TODAY, V11, P56 BISHOP SC, 2000, PARASITOLOGY 4, V121, P435 CABARET J, 1984, REV MED VET, V135, P627 CABARET J, 2002, VET PARASITOL, V105, P33 CHARTIER C, 1992, VET RES COMMUN, V16, P327 CORNELL SJ, 2003, P NATL ACAD SCI USA, V100, P7401 CORNELL SJ, 2004, P ROY SOC LOND B BIO, V271, P1243 CRISCIONE CD, 2005, TRENDS PARASITOL, V21, P212 DOBSON RJ, 1987, IMA J MATH APPL MED, V4, P279 DOBSON RJ, 1990, INT J PARASITOL, V20, P353 DOBSON RJ, 1990, INT J PARASITOL, V20, P359 DONALD AD, 1973, INT J PARASITOL, V3, P219 ELARD L, 1999, PARASITOL RES, V85, P452 EUZEBY J, 1964, REV MED VET, V10, P629 GABA S, 2005, PARASITOLOGY 3, V131, P393 GETTINBY G, 1989, VET PARASITOL, V32, P57 GRENFELL BT, 1987, PARASITOLOGY, V95, P389 GUESDON JC, 2003, C EUR UN PAR FRANC 7 HANSEN JW, 1980, EPIDEMIOLOGY CONTROL, V9, P471 HONG C, 1996, VET REC, V139, P83 KAPLAN RM, 2004, TRENDS PARASITOL, V20, P477 LEATHWICK DM, 1995, INT J PARASITOL, V25, P1479 LENORMAND T, 1998, P ROY SOC LOND B BIO, V265, P1985 MAGNEON N, 1986, THESIS NATL SUPERIEU MAY RM, 1977, MATH BIOSCI, V35, P301 MEHLHORN H, 2001, ENCY REFERENCE PARAS, P363 PATERSON S, 2000, PARASITOL TODAY, V16, P528 POULIN R, 1998, EVOLUTIONARY ECOLOGY SAUL A, 1995, PARASITOLOGY 4, V111, P531 SAULAI M, 2001, GENETICS SELECTION E, V33, P25 SHAW DJ, 1995, PARASITOLOGY S, V111, P111 SMITH G, 1985, PARASITOL TODAY, V1, P76 SMITH G, 1990, INT J PARASITOL, V20, P913 SMITH G, 1999, INT J PARASITOL, V29, P77 TALLIS GM, 1969, MATH BIOSCI, V4, P39 VACHER C, 2003, J EVOLUTION BIOL, V16, P378 Part 3},
url = { |
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| Gaba, S.; Chadoeuf, J.; Monestiez, P.; Sauve, C.; Cortet, J. & Cabaret, J. | Estimation of abomasum strongyle nematode infections in sheep at necropsy: Tentative proposals for a simplified technique |
2006 | Veterinary Parasitology | Vol. 140 (1-2) , pp. 105-113 |
||
| Abstract: Several necropsy techniques are available for estimating the abundance of gastro-intestinal nematodes in abomasum of ruminants. Standardization of techniques is needed to allow accurate comparisons between laboratories. Here we propose a standardized technique for estimating the abundance of worms. We intend to compare the worms' number estimations in lambs and ewes based on contents and washings, to determine the uniformity of worm counts in aliquots, and to estimate the total worm number from washings. The digesta (or "contents") and the washings of the abornasum are treated separately. The worms of each subsample are diluted with water and the total number of worms is estimated on a small volume (aliquots) of these subsamples. The use of aliquots assumes that the worms are uniformly distributed in the whole volume of each subsample. We first confirmed that the use of aliquots is appropriate in most cases. We then show that the use of the washings alone allows a faster and a suitable estimation of the total worm burden for all strongyle species of the abomasum in both ewes and lambs. The evaluation of our necropsy procedure is a first step to a standardized technique which should be improved by validation in other laboratories. (c) 2006 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Gaba2006a,
author = {Gaba, S. and Chadoeuf, J. and Monestiez, P. and Sauve, C. and Cortet, J. and Cabaret, J.},
title = {Estimation of abomasum strongyle nematode infections in sheep at necropsy: Tentative proposals for a simplified technique},
journal = {Veterinary Parasitology},
year = {2006},
volume = {140},
number = {1-2},
pages = {105-113},
note = {Cited References: *MAFF, 1986, MAN VET PAR LAB TECH, P1 *R DEV COR TEAM, 2004, R LANG ENV STAT COMP CLARK CJ, 1971, EXPT PARISITOLOGY, V30, P181 COLES GC, 2006, VET PARASITOL, V136, P167 DOWNEY NE, 1981, EPIDEMIOLOGY CONTROL, P69 EYSKER M, 1993, VET PARASITOL, V46, P205 HANSEN J, 1994, EPIDEMIOLOGY DIAGNOS, P171 KASSAI T, 1999, VET HELMINTHOLOGY, P260 MCCULLAGH P, 1989, GEN LINEAR MODELS REINECKE RK, 1967, ONDERSTEPOORT J VET, V34, P547 VIGNAU ML, 1999, PARASITOLOGIA PRACTI, P129},
url = { |
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| Gaba, S. & Goubiere, S. | To delay once or twice: the effect of hypobiosis and free-living stages on the stability of host-parasite interactions |
2008 | Journal Of The Royal Society Interface | Vol. 5 (25) , pp. 919-928 |
||
| Abstract: The life cycle of many endoparasites can be delayed by free-living infective stages and a developmental arrestment in the host referred to as hypobiosis. We investigated the effects of hypobiosis and its interaction with delay in the free-living stages on host parasite population dynamics by expanding a previous attempt by Dobson & Hudson. When the parasite life cycle does not include free-living stages, hypobiosis destabilizes the host parasite interactions, irrespective of the assumptions about the regulation of the host population dynamics. Interestingly, the destabilizing effect varies in a nonlinear way with the duration of hypobiosis, the maximal effect being expected for three to five months delay. When the parasite life cycle involves free-living stages, hypobiosis of short or intermediate duration increases the destabilizing effect of the first time delay. However, hypobiosis of a duration of five months or more can stabilize interactions, irrespective of the regulation of the host population dynamics. Overall, we con. rmed that hypobiosis is an unusual time delay as it can stabilize a two-way interaction. Contrary to the previous conclusions, such an atypical effect does not require self-regulation of the host population, but instead depends on the existence of free-living stages. | ||||||
BibTeX:
@article{Gaba2008,
author = {Gaba, S. and Goubiere, S.},
title = {To delay once or twice: the effect of hypobiosis and free-living stages on the stability of host-parasite interactions},
journal = {Journal Of The Royal Society Interface},
year = {2008},
volume = {5},
number = {25},
pages = {919-928},
note = {Cited References: *R DEV COR TEAM, 2005, R LANG ENV STAT COMP ALBON SD, 2002, P ROY SOC LOND B BIO, V269, P1625, DOI 10.1098/rspb.2002.2064 ANDERSON RM, 1978, J ANIM ECOL, V47, P219 ANDERSON RM, 1991, INFECT DIS HUMANS DY BUCKLING A, 2002, NATURE, V420, P496, DOI 10.1038/nature01164 CABARET J, 1977, REC MED VET, V153, P419 CABARET J, 1984, REV MED VET, V135, P627 CHIEJINA SN, 1988, VET PARASITOL, V28, P103 DIECKMANN U, 2002, ADAPTIVE DYNAMICS IN DOBSON AP, 1992, J ANIM ECOL, V61, P487 DOBSON AP, 1994, PARASITIC INFECT DIS, P301 EDELSTEINKESHET L, 1988, MATH MODELS BIOL FORDE SE, 2004, NATURE, V431, P841, DOI 10.1038/nature02906 GABA S, 2005, PARASITOLOGY 3, V131, P393, DOI 10.1017/S003118200500764X GIBBS HC, 1986, ADV PARASIT, V25, P129 GULLAND FMD, 1992, PARASITOLOGY, V105, P493 HAWKINS BA, 2000, THEORETICAL APPROACH HAYDON DT, 2002, P ROY SOC LOND B BIO, V269, P1609, DOI 10.1098/rspb.2002.2053 HUDSON PJ, 1985, ECOLOGY GENETICS HOS, P79 HUDSON PJ, 1998, SCIENCE, V282, P2256 IRVINE RJ, 2000, PARASITOLOGY, V120, P279, DOI 10.1017/S0031182099005430 KOELLA JC, 2003, AM NAT, V161, P698 KOT M, 2001, ELEMENTS MATH ECOLOG MAY RM, 1978, J ANIM ECOL, V47, P249 MAY RM, 1981, THEORETICAL ECOLOGY MCGLADE JM, 1999, ADV ECOLOGICAL THEOR MICHEL JF, 1974, ADV PARASIT, V12, P274 MOORE SL, 2002, SCIENCE, V297, P2015 NEWEY S, 2005, INT J PARASITOL, V35, P367, DOI 10.1016/j.ijpara.2004.12.003 NUNN CL, 2004, AM NAT S, V164, S90 POULIN R, 2000, EVOLUTIONARY BIOL HO RENSHAW E, 1991, MODELLING BIOL POPUL SCOTT ME, 1989, PARASITOL TODAY, V5, P176 STIEN A, 2002, INT J PARASITOL, V32, P991 TOMPKINS DM, 1999, PARASITOL TODAY, V15, P311 TOMPKINS DM, 2002, ECOLOGY WILDLIFE DIS, P45 WILSON K, 2004, SOAY SHEEP DYNAMICS, P113},
url = { |
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| Gaba, S.; Gruner, L. & Cabaret, J. | The establishment rate of a sheep nematode: Revisiting classics using a meta-analysis of 87 experiments |
2006 | Veterinary Parasitology | Vol. 140 (3-4) , pp. 302-311 |
||
| Abstract: Strongyle nematode establishment rate in their host is a highly variable life history trait, which makes it difficult to estimate. A meta-analysis was applied to the nematode Teladorsagia circumcincta of sheep in order to acquire a general framework of the factors modulating this life trait. A linear model was built with individual data on 540 infected lambs extracted from 13 articles. Lambs breed and age, time lag between last infection and the interaction between infection mode, infective dose and the number of repeated infective doses were significantly related with the establishment rate. The influence of infection mode on nematode establishment rate was also evaluated by comparing nematode establishment rate distributions within lamb populations infected under different conditions. Natural and repeated experimental infections lead to similar distribution of establishment rate. Conversely, these infection conditions resulted in different parasite establishment rates in average (12.7 and 23.4%, respectively). Three hypotheses are discussed to explain this result: immune protective response, host avoidance behaviour and parasite virulence. (c) 2006 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Gaba2006,
author = {Gaba, S. and Gruner, L. and Cabaret, J.},
title = {The establishment rate of a sheep nematode: Revisiting classics using a meta-analysis of 87 experiments},
journal = {Veterinary Parasitology},
year = {2006},
volume = {140},
number = {3-4},
pages = {302-311},
note = {Cited References: ATKINSON AC, 1985, PLOTS TRANSFORMATION BURNHAM KP, 2002, MODEL SELECTION MULT CABARET J, 1986, VET PARASITOL, V9, P315 CALLINAN APL, 1982, INT J PARASITOL, V12, P531 CHAMBERS JM, 1992, STAT MODELS CHEHRESA A, 1997, INT J PARASITOL, V27, P541 DINEEN JK, 1966, PARASITOLOGY, V56, P639 EYSKER M, 1981, RES VET SCI, V30, P62 EYSKER M, 1993, VET PARASITOL, V46, P205 GASNIER N, 1994, THESIS U TOURS GIBSON TE, 1973, J COMP PATHOL, V83, P583 GIBSON TE, 1975, VET PARASITOL, V1, P85 GIBSON TE, 1976, INT J BIOMETEOROL, V20, P49 GIBSON TE, 1976, J COMP PATHOL, V86, P269 GLASS GV, 1977, REV RES EDUC, V5, P351 GRUNER L, 1988, INCREASING SMALL RUM, P259 GRUNER L, 1994, INT J PARASITOL, V24, P347 GRUNER L, 2004, GENET SEL EVOL, V36, P217 HONG C, 1986, INT J PARASITOL, V16, P63 HONG C, 1987, INT J PARASITOL, V17, P951 HONG C, 1989, VET PARASITOL, V31, P125 HUTCHINGS MR, 2001, ECOLOGY, V82, P1138 IHAKA R, 1996, J COMPUTATIONAL GRAP, V5, P299 MALLET S, 1985, ANN RECH VET, V16, P99 MICHEL JF, 1963, PARASITOLOGY, V53, P63 REID JFS, 1975, J COMP PATHOL, V85, P269 ROSE JH, 1976, RES VET SCI, V21, P76 ROSSANIGO CE, 1996, PARASITOL RES, V82, P304 SANGSTER NC, 1980, RES VET SCI, V29, P26 SEATON DS, 1989, RES VET SCI, V46, P241 SMITH G, 1994, INT J PARASITOL, V24, P167 TORGERSON PR, 2003, PARASITOLOGY 5, V126, P417 VENABLE WN, 1999, MODERN APPL STAT SPL WILSON K, 1997, PARASITOL TODAY, V13, P33},
url = { |
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| Gabriel, E. & Allard, D. | Evaluating the sampling pattern when detecting Zones of Abrupt Change |
2008 | Environmental And Ecological Statistics | Vol. 15 (4) , pp. 469-489 |
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| Abstract: We present a method for detecting the zones where an irregularly sampled variable changes abruptly in the plane. Such zones are called Zones of Abrupt Change (ZACs). This method not only allows estimation of ZACs, but also testing of their statistical significance against the null hypothesis of a stationary correlated random field. The sampling pattern, in particular its local density, is crucial in the detection of potential ZACs. In this paper, we address the problem of evaluating the sampling pattern by assessing the power of the local test used for detecting ZACs. It is shown that mapping the power allows us to identify zones where ZACs may or may not be detected. The methodology is applied to a soil data set sampled at eight different dates in an agricultural field. Detecting ZACs for the soil water content allowed us to identify permanent structures in the agricultural field related to the boundaries between different soil types. Mapping the power for various sampling densities proved to be useful to determine the minimal sampling density necessary for detecting ZACs. | ||||||
BibTeX:
@article{Gabriel2008,
author = {Gabriel, E. and Allard, D.},
title = {Evaluating the sampling pattern when detecting Zones of Abrupt Change},
journal = {Environmental And Ecological Statistics},
year = {2008},
volume = {15},
number = {4},
pages = {469-489},
note = {Cited References: ADLER RJ, 2000, ANN APPL PROBAB, V10, P1 ALLARD D, 2005, 2 UN BIOST PROC SPAT ARONOWICH M, 1988, ADV APPL PROBAB, V18, P901 BANERJEE S, 2003, J AM STAT ASSOC, V98, P946, DOI 10.1198/C16214503000000909 BARBUJANI G, 1989, SYST ZOOL, V38, P376 BOCQUETAPPEL JP, 1994, SYST BIOL, V43, P442 CAOJ, 1999, ADV APPL PROBAB SGSA, V31, P579 CHAUDHURI P, 1999, J AM STAT ASSOC, V94, P807 CHILES JP, 1999, GEOSTATISTICS MODELI CRESSIE N, 1993, STAT SPATIAL DATA DUDOIT S, 2003, STAT SCI, V18, P71 FORTIN MJ, 1994, ECOLOGY, V75, P956 FORTIN MJ, 1995, OIKOS, V72, P323 GABRIEL E, 2004, P 4 INT C GEOST ENV, P437 GABRIEL E, 2004, THESIS U MONTPELLIER GABRIEL E, 2007, EUR J SOIL SCI, V58, P1273, DOI 10.1111/j.1365-2389.2007.00920.x GLEYZE JF, 2001, SPATIAL CLUSTERING M, P311 GUERIF M, 2001, P 3 EUR C PREC AGR, P677 HALL P, 2001, J ROY STAT SOC B 3, V63, P569 JACQUEZ GM, 1998, P 8 INT S SPAT DAT H, P496 JACQUEZ GM, 2000, J GEOGR SYST, V2, P221 LANTUEJOUL C, 1991, J MICROSC-OXFORD, V161, P387 MARY B, 2001, P 3 EUR C PREC AGR F, P431 ODEN NL, 1993, GEOGR ANAL, V25, P315 PAGEL M, 2004, NATURE, V428, P275, DOI 10.1038/428275a WOMBLE WH, 1951, SCIENCE, V114, P315 WORSLEY KJ, 1994, ADV APPL PROBAB, V26, P13 WORSLEY KJ, 2001, ADV APPL PROBAB, V33, P773},
url = { |
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| Gabriel, E.; Allard, D.; Mary, B. & Guerif, M. | Detecting zones of abrupt change in soil data, with an application to an agricultural field [BibTeX] |
2007 | European Journal of Soil Science | Vol. 58 (6) , pp. 1273-1284 |
||
BibTeX:
@article{Gabriel2007,
author = {Gabriel, E. and Allard, D. and Mary, B. and Guerif, M.},
title = {Detecting zones of abrupt change in soil data, with an application to an agricultural field},
journal = {European Journal of Soil Science},
year = {2007},
volume = {58},
number = {6},
pages = {1273-1284},
url = { |
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| Garrigues, S.; Allard, D. & Baret, F. | Modeling temporal changes in surface spatial heterogeneity over an agricultural site |
2008 | Remote Sensing of Environment | Vol. 112 (2) , pp. 588-602 |
||
| Abstract: High temporal frequency remote sensing observations are required to monitor vegetation functioning. These observations are currently provided by moderate resolution sensor (with pixel size ranging from 250 m to 10 km). However, the intra-pixel spatial heterogeneity which may be important at moderate resolution, induces a scaling bias on non-linear estimation processes of land surface variable. A possible strategy to correct this scaling bias consists in using variogram model of high spatial resolution data (e.g. SPOT/HRV 20 m) as a proxy for the spatial heterogeneity within moderate resolution pixel. However, ways have to be found to get prior knowledge of this intra-pixel spatial heterogeneity metric without systematic concurrent high spatial resolution images. This paper aims at proposing a spatio-temporal model of the variogram of high spatial resolution data, which enables us to retrieve the spatial heterogeneity within moderate spatial resolution pixel using a temporal sampling of few high spatial resolution scenes. It capitalizes on variogram modeling of a time series of high spatial resolution NDVI images to quantify and model the temporal changes in landscape spatial heterogeneity over a particular crop site (Fundulea, Romania). We first demonstrate that important temporal variations in surface spatial heterogeneity observed over an agricultural site mainly result from the shift in seasonal trajectories between crop classes (here winter versus summer crops). The mean length scale as measured by the variogram integral range is mainly influenced by the gathering of fields with similar NDVI values. The scene overall spatial variability and the spatial heterogeneity within moderate resolution pixels, as quantified by the variogram. sill and the dispersion variance, respectively, increase with the difference in NDVI between winter and summer crops. The influence of surface spatial heterogeneity on the description of land surface processes is thus critical when the phenological variability between crop classes is maximum, suggesting that the number of high spatial resolution scenes should increase at these periods of the seasonal cycle. Then, based on these observations, we build a model describing the temporal course of surface spatial heterogeneity, i.e. the temporal trajectory of the variogram of high spatial resolution NDVI image, as a function of crop seasonality. Once calibrated from a temporal sampling of few high spatial resolution scenes, this model proves to be powerful to predict the variogram at a date at which the high spatial resolution scene is not available and thus to retrieve the spatial heterogeneity within moderate resolution pixels through the seasonal cycle within a mean relative uncertainty of 20%. (C) 2007 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Garrigues2008a,
author = {Garrigues, S. and Allard, D. and Baret, F.},
title = {Modeling temporal changes in surface spatial heterogeneity over an agricultural site},
journal = {Remote Sensing of Environment},
year = {2008},
volume = {112},
number = {2},
pages = {588-602},
note = {Cited References: AHL DE, 2004, REMOTE SENS ENVIRON, V93, P168, DOI 10.1016/j.rse.2004.07.003 BARET F, 2001, ROMANIAN AGR RES, V16, P69 BROWN JF, 1993, PHOTOGRAMM ENG REM S, V59, P977 CARDOT H, 2003, J APPL STAT, V30, P1185, DOI 10.1080/0266476032000107187 CHILES JP, 1999, GEOSTATISTICS MODELI CRESSIE NAC, 1993, STAT SPATIAL DATA CSILLAG F, 2002, ECOSCIENCE, V9, P177 DEFRIES R, 1995, REMOTE SENS ENVIRON, V54, P209 FAIVRE R, 1997, J AGR BIOL ENVIR ST, V2, P87 FRIEDL MA, 1995, REMOTE SENS ENVIRON, V54, P233 GARRIGUES S, 2006, REMOTE SENS ENVIRON, V103, P81, DOI 10.1016/j.rse.2006.03.013 GARRIGUES S, 2006, REMOTE SENS ENVIRON, V106, P286 GARRIGUES S, 2007, IEEE T GEOSCI REMO 2, V45, P1823, DOI 10.1109/TGRS.2007.894572 HEUVELINK GBM, 1999, GEODERMA, V89, P47 HIPPS DO, 1996, SCALING HYDROLOGY US, P113 HOLBEN BN, 1998, REMOTE SENS ENVIRON, V66, P1 HU ZL, 1997, IEEE T GEOSCI REMOTE, V35, P747 LANTUEJOUL C, 2002, GEOSTATISTICAL SIMUL LOVEJOY S, 2001, INT J REMOTE SENS, V22, P1191 LYONS TJ, 2004, AGR FOREST METEOROL, V121, P153, DOI 10.1016/j.agrformet.2003.08.031 MERLIN O, 2005, IEEE T GEOSCI REMOTE, V43, P2036, DOI 10.1109/TGRS.2005.853192 MOULIN S, 1997, J CLIMATE, V10, P1154 PELLENQ J, 2003, J HYDROL, V276, P112, DOI 10.1016/S0022-1694(03)00066-0 PIELKE RA, 1990, LANDSCAPE ECOL, V4, P133 RAFFY M, 1994, INT J REMOTE SENS, V15, P2359 RAHMAN H, 1994, INT J REMOTE SENS, V15, P123 SCHIMEL DS, 1993, SCALING PHYSL PROCES, P21 SERRA J, 1982, IMAGE ANAL MATH MORP WACKERNAGEL H, 2003, MILTIVIBRATE GEOSTST WENDROTH O, 1999, J HYDROL, V215, P38},
url = { |
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| Garrigues, S.; Allard, D. & Baret, F. | Using first and second order variograms for characterizing landscape spatial structures from remote sensing imagery [BibTeX] |
2007 | IEEE Transactions on Geosciences and Remote Sensing | Vol. 45 , pp. 1823-1834 |
||
BibTeX:
@article{Garrigues2007,
author = {Garrigues, S. and Allard, D. and Baret, F.},
title = {Using first and second order variograms for characterizing landscape spatial structures from remote sensing imagery},
journal = {IEEE Transactions on Geosciences and Remote Sensing},
year = {2007},
volume = {45},
pages = {1823-1834},
url = {doi:10.1109/TGRS.2007.894572}
}
|
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| Garrigues, S.; Allard, D. & Baret, F. | Influence of the spatial heterogeneity on the non linear Estimation of Leaf Area Index from moderate resolution remote sensing data [BibTeX] |
2006 | Remote Sensing in Environment | Vol. 105 , pp. 286-298 |
||
BibTeX:
@article{Garrigues2006a,
author = {Garrigues, S. and Allard, D. and Baret, F.},
title = {Influence of the spatial heterogeneity on the non linear Estimation of Leaf Area Index from moderate resolution remote sensing data},
journal = {Remote Sensing in Environment},
year = {2006},
volume = {105},
pages = {286-298}
}
|
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| Garrigues, S.; Allard, D.; Baret, F. & Morisette, J. | Multivariate quantification of landscape spatial heterogeneity using variogram models |
2008 | Remote Sensing of Environment | Vol. 112 (1) , pp. 216-230 |
||
| Abstract: The monitoring of earth surface processes at a global scale requires high temporal frequency remote sensing observations provided up to now by moderate spatial resolution sensors (from 250 m to 7 kin). Non-linear estimation processes of land surface variables derived from remote sensing data can be biased by the surface spatial heterogeneity within the moderate spatial resolution pixel. Quantifying this surface spatial heterogeneity is thus required to correct non-linear estimation processes of land surface variables. The first step in this process is to properly characterize the scale of spatial variation of the processes structuring the landscape. Since the description of land surface processes generally involves various spectral bands, a multivariate approach to characterize the surface spatial heterogeneity from multi-spectral remote sensing observations has to be established. This work aims at quantifying the landscape spatial heterogeneity captured by red and near infrared high spatial resolution images using direct and cross-variograms modeled together with the geostatistical linear model of coregionalization. This model quantifies the overall spatial variability and correlation of red and near infrared reflectances over the scene. In addition, it provides an explicit understanding of the landscape spatial structures captured by red and near infrared reflectances and is thus appropriate to describe landscapes composed of areas with contrasted red and near infrared spectral properties. The application of the linear model of coregionalization to 18 contrasted landscapes provides a spatial signature of red and near infrared spectral properties characterizing each type of landscape. Low vegetation cover sites are characterized by positive spatial correlation between red and near infrared. The mosaic pattern of vegetation fields and bare soil fields over crop sites generates high and negative spatial correlation between red and near infrared and increases the spatial variability of red and near infrared. On forest sites, the important amount of vegetation limits the spatial variability of red and the shadow effects mainly captured by near infrared induce a low and positive spatial correlation between red and near infrared. Finally, the linear model of coregionalization applied to red and near infrared is shown to be more powerful than the univariate variogram modeling applied to NDVI because the second order stationarity hypothesis on which variogram modeling relies is more frequently verified for red and near infrared than for NDVI. (C) 2007 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Garrigues2008,
author = {Garrigues, S. and Allard, D. and Baret, F. and Morisette, J.},
title = {Multivariate quantification of landscape spatial heterogeneity using variogram models},
journal = {Remote Sensing of Environment},
year = {2008},
volume = {112},
number = {1},
pages = {216-230},
note = {Cited References: AHL DE, 2004, REMOTE SENS ENVIRON, V93, P168, DOI 10.1016/j.rse.2004.07.003 ATKINSON PM, 1999, INT J REMOTE SENS, V20, P2663 BARET F, UNPUB VALERI NETWORK BRUNIQUELPINEL V, 1998, REMOTE SENS ENVIRON, V65, P61 CHAVEZ PS, 1992, PHOTOGRAMM ENG REM S, V58, P957 CHEN JM, 1992, PLANT CELL ENVIRON, V15, P421 CHILES JP, 1999, GEOSTATISTICS MODELI CSILLAG F, 2002, ECOSCIENCE, V9, P177 CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 FAIVRE R, 1997, J AGR BIOL ENVIR ST, V2, P87 FRIEDL MA, 1995, REMOTE SENS ENVIRON, V54, P233 GARRIGUES S, 2006, REMOTE SENS ENVIRON, V103, P81, DOI 10.1016/j.rse.2006.03.013 GARRIGUES S, 2006, REMOTE SENS ENVIRON, V106, P286 GOULARD M, 1992, MATH GEOL, V24, P269 HEUVELINK GBM, 1999, GEODERMA, V89, P47 HIPPS DO, 1996, SCALING HYDROLOGY US, P113 HU ZL, 1997, IEEE T GEOSCI REMOTE, V35, P747 JACKSON RD, 1983, REMOTE SENS ENVIRON, V13, P409 JUPP DLB, 1988, IEEE T GEOSCI REMOTE, V26, P463 LACAZE B, 1994, INT J REMOTE SENS, V15, P2437 LANTUEJOUL C, 2002, GEOSTATISTICAL SIMUL LOVEJOY S, 2001, INT J REMOTE SENS, V22, P1191 LYONS TJ, 2004, AGR FOREST METEOROL, V121, P153, DOI 10.1016/j.agrformet.2003.08.031 MATHERON G, 1965, VARIABLES REGIONALIS MERLIN O, 2005, IEEE T GEOSCI REMOTE, V43, P2036, DOI 10.1109/TGRS.2005.853192 MORISETTE J, 1997, COMPUT GEOSCI, V23, P317 MYNENI RB, 1991, PHOTON VEGETATION IN MYNENI RB, 2002, REMOTE SENS ENVIRON, V83, P214 OLIVER MA, 2001, MODELLING SCALE GEOG, P193 PELLENQ J, 2003, J HYDROL, V276, P112, DOI 10.1016/S0022-1694(03)00066-0 PIELKE RA, 1990, LANDSCAPE ECOL, V4, P133 PRICE JC, 1996, INT J REMOTE SENS, V17, P3411 RAFFY M, 1994, INT J REMOTE SENS, V15, P2359 SCHIMEL DS, 1993, SCALING PHYSL PROCES, P21 SELLERS PJ, 1987, REMOTE SENS ENVIRON, V21, P143 SELLERS PJ, 1997, SCIENCE, V275, P602 SERRA J, 1982, IMAGE ANAL MATH MORP STONGE BA, 1995, INT J REMOTE SENS, V16, P1999 WACKERNAGEL H, 2003, MULTIVARIATE GEOSTAT WEISS M, 1999, REMOTE SENS ENVIRON, V70, P293 WENDROTH O, 1999, J HYDROL, V215, P38 WOODCOCK CE, 1988, REMOTE SENS ENVIRON, V25, P323 WOODCOCK CE, 1988, REMOTE SENS ENVIRON, V25, P349},
url = { |
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| Garrigues, S.; Allard, D.; Baret, F. & Weiss, M. | Quantifying spatial heterogeneity at the landscape scale using variograrn models |
2006 | Remote Sensing of Environment | Vol. 103 (1) , pp. 81-96 |
||
| Abstract: The monitoring of earth surface dynamic processes at a global scale requires high temporal frequency remote sensing observations which are provided up to now by moderate spatial resolution sensors. However, the spatial heterogeneity within the moderate spatial resolution pixel biases non-linear estimation processes of land surface variables from remote sensing data. To limit its influence on the description of land surface processes, corrections based on the quantification of the intra-pixel heterogeneity may be applied to non-linear estimation processes. A complementary strategy is to define the proper pixel size to capture the spatial variability of the data and minimize the intra-pixel variability. This work provides a methodology to characterize and quantify the spatial heterogeneity of landscape vegetation cover from the modeling of the variogram of high spatial resolution NDVI data. NDVI variograms for 18 landscapes extracted from the VALERI database show that the land use is the main factor of spatial variability as quantified by the variogram sill. Crop sites are more heterogeneous than natural vegetation and forest sites at the landscape level. The integral range summarizes all structural parameters of the variograin into a single characteristic area. Its square root quantifies the mean length scale (i.e. spatial scale) of the data, which varies between 216 and 1060 in over the 18 landscapes considered. The integral range is also used as a yardstick to judge if the size of an image is large enough to measure properly the length scales of the data with the variogram. We propose that it must be smaller than 5% of the image surface. The theoretical dispersion variance, computed from the variograin model, quantifies the spatial heterogeneity within a moderate resolution pixel. It increases rapidly with pixel size until this size is larger than the mean length scale of the data. Finally based on the analysis of 18 landscapes, the sufficient pixel size to capture the major part of the spatial variability of the vegetation cover at the landscape scale is estimated to be less than 100 m. Since for all the heterogeneous landscapes the loss of NDVI spatial variability was small at this spatial resolution, the bias generated by the intra-pixel spatial heterogeneity on non-linear estimation processes will be reduced. (c) 2006 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Garrigues2006,
author = {Garrigues, S. and Allard, D. and Baret, F. and Weiss, M.},
title = {Quantifying spatial heterogeneity at the landscape scale using variograrn models},
journal = {Remote Sensing of Environment},
year = {2006},
volume = {103},
number = {1},
pages = {81-96},
note = {Cited References: ATKINSON PM, 1995, IEEE T GEOSCI REMOTE, V33, P768 ATKINSON PM, 2001, MODELLING SCALE GEOG, P237 BARET F, IN PRESS REMOTE SENS BIAN L, 1997, SCALE REMOTE SENSING, P57 BIERKENS MFP, 2000, UPSCALING DOWNSCALIN BRUNIQUELPINEL V, 1998, REMOTE SENS ENVIRON, V65, P61 CAO C, 1997, SCALE REMOTE SENSING, P57 CARR JR, 1996, COMPUT GEOSCI, V22, P849 CHILES JP, 1999, GEOSTATISTICS MODELI COLLINS JB, 1999, PHOTOGRAMM ENG REM S, V65, P41 COSH MH, 2003, J HYDROL, V276, P128 CRESSIE N, 1985, MATH GEOL, V17, P563 CSILLAG F, 1996, MATH GEOL, V28, P385 CSILLAG F, 1997, SCALE REMOTE SENSING, P247 CSILLAG F, 2002, ECOSCIENCE, V9, P177 CURRAN PJ, 1988, REMOTE SENS ENVIRON, V24, P493 CURRAN PJ, 2002, SPATIAL STAT REMOTE, P115 DECOLA L, 1989, PHOTOGRAMM ENG REM S, V55, P601 DECOLA L, 1993, FRACTALS GEOGRAPHY, P282 FRIEDL MA, 1997, SCALE REMOTE SENSING, P113 GAGALOWICZ A, 1983, THESIS U P M CURIE P GARRIGUES S, IN PRESS REMOTE SENS GARRIGUES S, 2004, THESIS ECOLE NATL SU HARALICK RM, 1974, REMOTE SENS ENVIRON, V3, P3 HENEBRY GM, 1993, REMOTE SENS ENVIRON, V46, P233 HU ZL, 1997, IEEE T GEOSCI REMOTE, V35, P747 HU ZL, 1998, INT J REMOTE SENS, V19, P2451 JACKSON RD, 1983, REMOTE SENS ENVIRON, V13, P409 JOURNEL AG, 1993, MATH GEOL, V25, P329 JULESZ B, 1962, IEEE T INFORM THEORY, V8, P84 JUPP DLB, 1988, IEEE T GEOSCI REMOTE, V26, P463 JUPP DLB, 1989, IEEE T GEOSCI REMOTE, V27, P247 KOLASA J, 1991, ECOLOGICAL HETEROGEN, P1 LACAZE B, 1994, INT J REMOTE SENS, V15, P2437 LAM NSN, 1993, FRACTALS GEOGRAPHY LANTUEJOUL C, 2002, GEOSTATISTICAL SIMUL LOVEJOY S, 2001, INT J REMOTE SENS, V22, P1191 MALLAT S, 1999, WAVELET TOUR SIGNAL MANDELBROT BB, 1983, FRACTAL GEOMETRY NAT MARCEAU DJ, 1994, REMOTE SENS ENVIRON, V49, P105 MATHERON G, 1965, VARIABLES REGIONALIS MORISETTE JT, IN PRESS IEEE T GEOS MORISETTE JT, 2002, REMOTE SENS ENVIRON, V83, P77 MYERS DE, 1997, SCALE REMOTE SENSING, P273 OLIVER MA, 2001, MODELLING SCALE GEOG, P193 ONEILL RV, 1991, ECOLOGICAL HETEROGEN, P85 PUECH C, 1994, INT J REMOTE SENS, V15, P2421 QUATTROCHI DA, 1997, SCALE REMOTE SENSING RAFFY M, 1994, INT J REMOTE SENS, V15, P2353 RAHMAN AF, 2003, REMOTE SENS ENVIRON, V84, P192 RAMSTEIN G, 1989, INT J REMOTE SENS, V10, P1019 SERRA J, 1982, IMAGE ANAL MATH MORP SHANNON E, 1948, BELL SYST TECH J, V379, P623 STEIN A, 2003, AGR ECOSYST ENVIRON, V94, P31 STONGE BA, 1995, INT J REMOTE SENS, V16, P1999 TIAN YH, 2002, REMOTE SENS ENVIRON, V83, P414 WACKERNAGEL H, 2003, MULTIVARIATE GEOSTAT WALSH SJ, 1997, SCALE REMOTE SENSING, P27 WEISS M, 2000, AGRONOMIE, V20, P3 WOODCOCK C, 1992, INT J REMOTE SENS, V13, P3167 WOODCOCK CE, 1987, REMOTE SENS ENVIRON, V21, P311 WOODCOCK CE, 1988, REMOTE SENS ENVIRON, V25, P323 WOODCOCK CE, 1988, REMOTE SENS ENVIRON, V25, P349},
url = { |
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| Gay, E.; Barnouin, J. & Senoussi, R. | A spatial clustering analysis for continuous variables with application to milk somatic cell score in France [BibTeX] |
2007 | Veterinary Research | Vol. 38 (4) , pp. 596-596 |
||
BibTeX:
@article{Gay2007,
author = {Gay, E. and Barnouin, J. and Senoussi, R.},
title = {A spatial clustering analysis for continuous variables with application to milk somatic cell score in France},
journal = {Veterinary Research},
year = {2007},
volume = {38},
number = {4},
pages = {596-596}
}
|
||||||
| Gay, E.; Barnouin, J. & Senoussi, R. | A spatial hazard model for cluster detection on continuous disease indicators: Application to bovine mastitis in France [BibTeX] |
2007 | International Journal of Health Geography | Vol. 38 (4) , pp. 585-596 |
||
BibTeX:
@article{Gay2007a,
author = {Gay, E. and Barnouin, J. and Senoussi, R.},
title = {A spatial hazard model for cluster detection on continuous disease indicators: Application to bovine mastitis in France},
journal = {International Journal of Health Geography},
year = {2007},
volume = {38},
number = {4},
pages = {585-596}
}
|
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| Gay, E.; Barnouin, J. & Senoussi, R. | Spatial and temporal patterns of herd somatic cell score in France [BibTeX] |
2006 | Journal of Dairy Science | Vol. 89 (7) , pp. 2487-2498 |
||
BibTeX:
@article{Gay2006,
author = {Gay, E. and Barnouin, J. and Senoussi, R.},
title = {Spatial and temporal patterns of herd somatic cell score in France},
journal = {Journal of Dairy Science},
year = {2006},
volume = {89},
number = {7},
pages = {2487-2498},
url = { |
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| Gerard, P.R.; Klein, E.K.; Austerlitz, F.; Fernandez-Manjarres, J.F. & Frascaria-Lacoste, N. | Assortative mating and differential male mating success in an ash hybrid zone population |
2006 | Bmc Evolutionary Biology | Vol. 6 |
||
| Abstract: Background: The structure and evolution of hybrid zones depend mainly on the relative importance of dispersal and local adaptation, and on the strength of assortative mating. Here, we study the influence of dispersal, temporal isolation, variability in phenotypic traits and parasite attacks on the male mating success of two parental species and hybrids by real-time pollen flow analysis. We focus on a hybrid zone population between the two closely related ash species Fraxinus excelsior L. (common ash) and F. angustifolia Vahl (narrow-leaved ash), which is composed of individuals of the two species and several hybrid types. This population is structured by flowering time: the F. excelsior individuals flower later than the F. angustifolia individuals, and the hybrid types flower in-between. Hybrids are scattered throughout the population, suggesting favorable conditions for their local adaptation. We estimate jointly the best-fitting dispersal kernel, the differences in male fecundity due to variation in phenotypic traits and level of parasite attack, and the strength of assortative mating due to differences in flowering phenology. In addition, we assess the effect of accounting for genotyping error on these estimations. Results: We detected a very high pollen immigration rate and a fat-tailed dispersal kernel, counterbalanced by slight phenological assortative mating and short-distance pollen dispersal. Early intermediate flowering hybrids, which had the highest male mating success, showed optimal sex allocation and increased selfing rates. We detected asymmetry of gene flow, with early flowering trees participating more as pollen donors than late flowering trees. Conclusion: This study provides striking evidence that long-distance gene flow alone is not sufficient to counter-act the effects of assortative mating and selfing. Phenological assortative mating and short-distance dispersal can create temporal and spatial structuring that appears to maintain this hybrid population. The asymmetry of gene flow, with higher fertility and increased selfing, can potentially confer a selective advantage to early flowering hybrids in the zone. In the event of climate change, hybridization may provide a means for F. angustifolia to further extend its range at the expense of F. excelsior. | ||||||
BibTeX:
@article{Gerard2006,
author = {Gerard, P. R. and Klein, E. K. and Austerlitz, F. and Fernandez-Manjarres, J. F. and Frascaria-Lacoste, N.},
title = {Assortative mating and differential male mating success in an ash hybrid zone population},
journal = {Bmc Evolutionary Biology},
year = {2006},
volume = {6},
note = {Cited References: ABRAMOWITZ M, 1964, HDB MATH FUNCTIONS F ADAMS WT, 1991, BIOCH MARKERS POPULA, P157 ARAKI H, 2005, MOL ECOL, V14, P4097 ARNOLD ML, 1997, OXFORD SERIES ECOLOG AUSTERLITZ F, 2000, GENETICS, V154, P1309 AUSTERLITZ F, 2003, HEREDITY, V90, P282 AUSTERLITZ F, 2004, MOL ECOL, V13, P937 BACILIERI R, 1996, EVOLUTION, V50, P900 BACLES CFE, 2005, EVOLUTION, V59, P979 BARTON NH, 2001, MOL ECOL, V10, P551 BINGGELI P, GENDER VARIATION ASH BRACHET S, 1999, MOL ECOL, V8, P157 BROYLES SB, 1990, EVOLUTION, V44, P1454 BROYLES SB, 2002, EVOLUTION, V56, P1943 BURCZYK J, 2005, MOL ECOL, V14, P2525 BURCZYK JL, 1997, HEREDITY 6, V79, P638 CADET C, 2004, AM NAT, V164, P779 CAMPBELL DR, 2000, TRENDS ECOL EVOL, V15, P227 CHARNOV EL, 1982, THEORY SEX ALLOCATIO CHEPTOU PO, 2002, J EVOLUTION BIOL, V15, P753 CLARK JS, 1998, AM NAT, V152, P204 COLES S, 2001, INTRO STAT MODELING CONNER JK, 1996, EVOLUTION, V50, P1137 CORNMAN RS, 2004, EVOLUTION, V58, P2669 COYNE JA, 2004, SPECIATION CRUZAN MB, 1994, EVOLUTION, V48, P1946 DEVAUX C, 2005, MOL ECOL, V14, P2269 DEVLIN B, 1990, AM NAT, V136, P87 ELLE E, 2000, AM NAT, V156, P622 FERDY JB, 2002, AM NAT, V160, P74 FERNANDEZMANJARRES JF, 2006, MOL ECOL, V15, P3245 FOX GA, 2003, EVOL ECOL RES, V5, P1 GERARD PR, 2006, ANN FOREST SCI, V63, P733 GERARD PR, 2006, MOL ECOL, V15, P3655 GOODWILLIE C, 2005, ANNU REV ECOL EVOL S, V36, P47 HARDY OJ, 2004, J EVOLUTION BIOL, V17, P795 HENDRY AP, 2005, MOL ECOL, V14, P901 JARNE P, 1993, ANNU REV ECOL SYST, V24, P441 JATO V, 2004, GRANA, V43, P217 JEANDROZ S, 1997, MOL PHYLOGENET EVOL, V7, P241 JONES AG, 2003, MOL ECOL, V12, P2511 KLEIN EK, 2006, BIOMED CENTRAL ECOLO, V6, P3 KLINKHAMER PGL, 1997, TRENDS ECOL EVOL, V12, P260 KLINKHAMER PGL, 2005, EVOLUTIONARY ECOLOGY LAMONT BB, 2003, J EVOLUTION BIOL, V16, P551 LEFORT F, 1999, MOL ECOL, V8, P1075 MARIGO G, 2000, TREES-STRUCT FUNCT, V15, P1 MARSHALL TC, 1998, MOL ECOL, V7, P639 MCNEILLY T, 1968, HEREDITY, V23, P205 MEAGHER TR, 1986, AM NAT, V128, P199 MORAND ME, 2002, MOL ECOL, V11, P377 MORANDPRIEUR ME, 2003, AM J BOT, V90, P949 MORANDPRIEUR ME, 2003, EVOLUTION MAINTIEN S NURMINIEMI M, 1998, EVOL ECOL, V12, P487 NURNBERGER B, 2005, HEREDITY, V94, P247 ODDOUMURATORIO S, 2003, MOL ECOL, V12, P3427 ODDOUMURATORIO S, 2005, MOL ECOL, V14, P4441 PICARD JF, 1983, FORET ENTREPRISE, V83, P2 PORCHER E, 2005, J EVOLUTION BIOL, V18, P497 RAQUIN C, 2002, ANN FOR SCI, V59, P219 RAQUIN C, 2002, FOR GENET, V9, P103 RITLAND K, 2002, HEREDITY 4, V88, P221 ROBLEDOARNUNCIO JJ, 2005, HEREDITY, V94, P13 ROBLEDOARNUNCIO JJ, 2006, GENETICS, V173, P1033 RUNDLE HD, 2005, ECOL LETT, V8, P336 SILVERTOWN J, 2005, HEREDITY, V95, P198 SLAVOV GT, 2005, MOL ECOL, V14, P3109 SMOUSE PE, 1999, J EVOLUTION BIOL, V12, P1069 SORK VL, 1999, TRENDS ECOL EVOL, V14, P219 STREIFF R, 1999, MOL ECOL, V8, P831 VALBUENACARABANA M, 2005, HEREDITY, V95, P457 WARDLE P, 1961, J ECOL, V49, P739 WEIS AE, 2005, EVOL ECOL RES, V7, P161 WEIS AE, 2005, J EVOLUTION BIOL, V18, P536},
url = { |
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| Gibert, C.; Chadoeuf, J.; Nicot, P.; Vercambre, G.; Genard, M. & Lescourret, F. | Modelling the effect of cuticular crack surface area and inoculum density on the probability of nectarine fruit infection by Monilinia laxa |
2009 | Plant Pathology | Vol. 58 (6) , pp. 1021-1031 |
||
| Abstract: The effects of cuticular crack surface area and inoculum density on the infection of nectarine fruits by conidia of Monilinia laxa were studied using artificial inoculations with conidial suspensions and dry airborne conidia during the 2004 and 2005 seasons, respectively. Additionally, the effect of ambient humidity on fruit infection was evaluated in the 2005 experiment. An exploratory analysis indicated that (i) ambient humidity did not significantly explain the observed variability of data, but that (ii) the incidence of fruit infection increased both with increasing inoculum density and increasing surface area of cuticular cracks. The product of these two variables represented the inoculum dose in the cracks, and was used as a predictor of fruit infection in the model. Natural infection in the orchard was observed to increase throughout the season in both 2004 and 2005. The relationship between the probability of fruit infection by M. laxa and the artificially inoculated dose in the cuticular cracks was well described by a logistic regression model once natural inoculum density was taken into account (pseudo R2 = 65%). This function could be helpful for estimating the risk of fruit infection at harvest based on fruit size and natural inoculum density. | ||||||
BibTeX:
@article{Gibert2009,
author = {Gibert, C. and Chadoeuf, J. and Nicot, P. and Vercambre, G. and Genard, M. and Lescourret, F.},
title = {Modelling the effect of cuticular crack surface area and inoculum density on the probability of nectarine fruit infection by Monilinia laxa},
journal = {Plant Pathology},
year = {2009},
volume = {58},
number = {6},
pages = {1021-1031},
url = { |
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| Gilbert, C.; Chadoeuf, J.; Vercambre, G.; Genard, M. & Lescourret, F. | Cuticular cracking on nectarine fruit surface: Spatial distribution and development in relation to irrigation and thinning |
2007 | Journal Of The American Society For Horticultural Science | Vol. 132 (5) , pp. 583-591 |
||
| Abstract: Investigations on "natural" cuticular cracks were conducted on nectarine fruit [Prunus persica (L.) Batsch var. nucipersica (Suckow) C.K. Schneid.]. A method for quantifying the cuticular crack surface area on a whole fruit basis was proposed. By using a stratified sampling design, the spatial distribution of the cuticular cracks over three regions (stylar end, peduncle, and cheek), their morphology, and the estimation of the total proportion of cuticular cracks on the fruit were studied. These features were examined during fruit development and in response to several fruit growing conditions corresponding to various crop loads and irrigation regimes. Cuticular cracks on nectarine fruit occurred during the final rapid fruit growth stage. Larger fruit presented higher cuticular crack densities in the apical regions than in the cheek regions. Thin and larger cuticular cracks occurred continuously during fruit development. Cuticular cracks represented 10% to 12.5% of the fruit surface area for well irrigated or low crop load trees, whereas they covered less than 4.5% for the heavy crop load and water deficit treatments. Cheek regions largely contributed to the total cuticular crack surface area (> 60%), regardless of the fruit growing conditions. After irrigation was restricted, cuticular crack development was limited. A positive relationship was established between the cuticular crack surface area per fruit surface area and the fruit fresh weight. | ||||||
BibTeX:
@article{Gilbert2007,
author = {Gilbert, C. and Chadoeuf, J. and Vercambre, G. and Genard, M. and Lescourret, F.},
title = {Cuticular cracking on nectarine fruit surface: Spatial distribution and development in relation to irrigation and thinning},
journal = {Journal Of The American Society For Horticultural Science},
year = {2007},
volume = {132},
number = {5},
pages = {583-591},
note = {Times Cited: 0 0003-1062},
url = { |
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| Ginot, V.; Gaba, S.; Beaudouin, R.; Ariès, F. & Monod, H. | Combined use of local and ANOVA-based global sensitivity analyses for the investigation of a stochastic dynamic model: application to the case study of an individual-based model of a fish population [BibTeX] |
2006 | Ecological Modelling | Vol. 193 , pp. 479-491 |
||
BibTeX:
@article{Ginot2006,
author = {Ginot, V. and Gaba, S. and Beaudouin, R. and Ariès, F. and Monod, H.},
title = {Combined use of local and ANOVA-based global sensitivity analyses for the investigation of a stochastic dynamic model: application to the case study of an individual-based model of a fish population},
journal = {Ecological Modelling},
year = {2006},
volume = {193},
pages = {479-491}
}
|
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| Ginot, V. & Monod, H. Amblard, F. & Phan, D. (Hrsg.) | Explorer les modèles par simulation : application aux analyses de sensibilité [BibTeX] |
2007 | Modélisation et simulation multi-agents (...) | |||
BibTeX:
@incollection{Ginot2007inpress,
author = {Ginot, V. and Monod, H.},
title = {Explorer les modèles par simulation : application aux analyses de sensibilité},
booktitle = {Modélisation et simulation multi-agents (...)},
publisher = {Hermès},
year = {2007}
}
|
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| Gonod, L.V.; Chadoeuf, J. & Chenu, C. | Spatial distribution of microbial 2,4-dichlorophenoxy acetic acid mineralization from field to microhabitat scales |
2006 | Soil Science Society Of America Journal | Vol. 70 (1) , pp. 64-71 |
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| Abstract: Little is known about spatial variability of microbial activity, particularly at microscales. This is especially true for the fate and degradation of pesticides. The objective was to sample soil from micro to field scales and apply geostatistics on the potential mineralization of a widely used herbicide 2,4-dichlorophenoxy acetic acid (2,4-D; C8H6Cl2O3). Soil cores were sampled in the plow layer of a cultivated soil with a systematic sampling procedure. In a first experiment 2,4-D mineralization was measured on 39 crushed cores and we analyzed variability of mineralization at the field scale, from decameter to meter and from meter to decimeter scale. In a second experiment, 432 soil cubes (about 216 mm(3)) were used to study the variability of mineralization at the "microhabitat" scale from meter to millimeter. The spatial dependence of 2,4-D mineralization was first quantified by computing an empirical variogram function. Spatial independence was then tested by comparing the empirical variogram function to its individual confidence bounds at 95% level obtained under independence assumption by a Monte-Carlo Method. The potential for 2,4-D mineralization was spatially heterogeneous from field to microhabitat. Mineralization variability increased when the scale decreased from field to microhabitats. Specifically, the coefficient of variability (CV) of 2,4-D mineralization was of 18.5% at the field scale, 7-22% at the meter scale, 47.9% at the inter-cores scale, and 25-160% at the intra-core scale (microhabitat scale). 2,4-D mineralization was spatially structured only at the microhabitat scale (hot spots). This variability at fine scales should be considered when sampling soil processes involving microbial activities. | ||||||
BibTeX:
@article{Gonod2006,
author = {Gonod, L. V. and Chadoeuf, J. and Chenu, C.},
title = {Spatial distribution of microbial 2,4-dichlorophenoxy acetic acid mineralization from field to microhabitat scales},
journal = {Soil Science Society Of America Journal},
year = {2006},
volume = {70},
number = {1},
pages = {64-71},
note = {Times Cited: 3 0361-5995},
url = { |
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| Grechi, I.; Sauge, M.H.; Sauphanor, B.; Hilgert, N.; Senoussi, R. & Lescourret, F. | How does winter pruning affect peach tree - Myzus persicae interactions? |
2008 | Entomologia Experimentalis Et Applicata | Vol. 128 (3) , pp. 369-379 |
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| Abstract: Winter tree pruning is a cultural practice known to modify vegetative growth, which is likely to affect the development of pests. However, it has been poorly addressed as a cultural control method for diminishing the population levels of the green peach aphid, Myzus persicae (Sulzer) (Homoptera: Aphididae), in peach [Prunus persica (L.) Batsch (Rosaceae)] orchards. In this study, we conducted a 2-year, on-station experiment to evaluate how winter pruning affects peach-M. persicae interactions, by examining tree vegetative growth, aphid population dynamics, and crop yield and fruit quality. We collected data under an insect-proof shelter on adult peach trees submitted to various levels of pruning and artificially infested with aphids. Our results showed that pruning enhanced shoot growth due to the proportion of growing shoots, which increased exponentially (10-60%), whereas the growth rate of growing shoots was not affected. The degree of infestation of peach trees increased with increasing pruning intensity. This effect was mainly due to the increase of the proportion of growing shoots, on which aphids developed better than on rosettes. In turn, the higher the aphid infestation, the higher the aphid-induced shoot-tip damage, leaf curling, and leaf fall that disturbed the growth of growing shoots. However, aphids did not considerably reduce fruit quality at harvest. They did not affect fresh fruit weight, and the refractometric index (indicator of sugar content) was reduced by only 3-4%. The relevance of winter pruning as a cultural method for pest control in orchards conducted under integrated fruit production guidelines is discussed. | ||||||
BibTeX:
@article{Grechi2008,
author = {Grechi, I. and Sauge, M. H. and Sauphanor, B. and Hilgert, N. and Senoussi, R. and Lescourret, F.},
title = {How does winter pruning affect peach tree - Myzus persicae interactions?},
journal = {Entomologia Experimentalis Et Applicata},
year = {2008},
volume = {128},
number = {3},
pages = {369-379},
note = {Cited References: *ACTA, 1974, PECH, V3 *R DEV COR TEAM, 2006, R LANG ENV STAT COMP ANSTEAD JA, 2005, INSECT BIOCHEM MOLEC, V35, P249, DOI 10.1016/j.ibmb.2004.12.004 AWMACK CS, 2002, ANNU REV ENTOMOL, V47, P817 BROWN MW, 1992, ENVIRON ENTOMOL, V21, P485 CANDOLFI MP, 1993, J APPL ENTOMOL, V115, P233 CHEN X, 1997, THESIS U AVIGNON PAY CROSS JV, 1997, IOBC SROP B, V20 DAVIES FT, 2004, J AM SOC HORTIC SCI, V129, P344 DEBRUYN L, 2002, OECOLOGIA, V130, P594 DEJONG TM, 1987, PHYSIOL PLANTARUM, V71, P83 DIXON AFG, 1987, APHIDS THEIR BIOL A, V2, P269 FAUST M, 1989, PHYSL TEMPERATE ZONE FORSHEY CG, 1985, J AM SOC HORTIC SCI, V110, P128 GETZ WM, 1982, ANNU REV ENTOMOL, V27, P447 GIAUQUE P, 2003, CONDUITE VERGER PECH GIROUSSE C, 2003, NEW PHYTOL, V157, P83 GIROUSSE C, 2005, PLANT PHYSIOL, V137, P1474, DOI 10.1104/pp.104.057430 GORDON D, 2006, TREE PHYSIOL, V26, P537 GOTTWALD TR, 1995, PLANT DIS, V79, P266 GUILLEMAUD T, 2003, B ENTOMOL RES, V93, P289, DOI 10.1079/BER2003241 INBAR M, 2001, OIKOS, V94, P228 JANSSON RK, 1986, ENVIRON ENTOMOL, V15, P49 JOHNSON SN, 2003, ECOL ENTOMOL, V28, P533 KARAGOUNIS C, 2006, J APPL ENTOMOL, V130, P150, DOI 10.1111/j.1439-0418.2006.01048.x KARLEY AJ, 2004, ECOL ENTOMOL, V29, P383 KENNEDY JS, 1959, ANNU REV ENTOMOL, V4, P139 KORICHEVA J, 1998, ANNU REV ENTOMOL, V43, P195 LAKSO AN, 1984, J AM SOC HORTIC SCI, V109, P861 LECLANT F, 1970, ENTOMOPHAGA, V15, P53 LENFANT C, 1992, PHYTOMA, V445, P44 MARINI RP, 2002, VIRGINIA COOPERATIVE, V422 MAZZONI E, 1999, IOBC B, V22, P39 MERCIER V, 2008, CROP PROT, V27, P678, DOI 10.1016/j.cropro.2007.09.013 MUELLER TF, 1988, ENTOMOL EXP APPL, V47, P145 MULLER CB, 2001, ECOL ENTOMOL, V26, P330 NICHOLAS AH, 2005, BIOCONTROL, V50, P271, DOI 10.1007/s10526-004-0334-2 NYROP JP, 2006, ACTA HORTIC, V707, P187 PEGADARAJU V, 2005, PLANT PHYSIOL, V139, P1927, DOI 10.1104/pp.105.070433 PRICE PW, 1991, OIKOS, V62, P244 SANDSTROM J, 2000, CHEMOECOLOGY, V10, P17 SANSAVINI S, 1997, SCI HORTIC-AMSTERDAM, V68, P25 SCHNEIDER GW, 1957, P AM SOC HORTIC SCI, V69, P141 SINGH BU, 2004, CROP PROT, V23, P739, DOI 10.1016/j.cropro.2004.01.004 STRAW NA, 2005, FOREST ECOL MANAG, V213, P349, DOI 10.1016/j.foreco.2005.04.002 TAKEDA S, 1979, APPL ENTOMOL ZOOL, V14, P356 TEDER T, 2002, ECOL ENTOMOL, V27, P94 VANEMDEN HF, 1969, ANNU REV ENTOMOL, V14, P197 VEEN BW, 1985, ANN APPL BIOL, V107, P319 WHITAKER PM, 2006, ENVIRON ENTOMOL, V35, P488},
url = { |
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| Grimm, V.; Berger, U.; Bastiansen, F.; Eliassen, S.; Ginot, V.; Giske, J.; Goss-Custard, J.; Grand, T.; Heinz, S.K.; Huse, G.; Huth, A.; Jepsen, J.U.; Jorgensen, C.; Mooij, W.M.; Muller, B.; Pe'er, G.; Piou, C.; Railsback, S.F.; Robbins, A.M.; Robbins, M.M.; Rossmanith, E.; Ruger, N.; Strand, E.; Souissi, S.; Stillman, R.A.; Vabo, R.; Visser, U. & DeAngelis, D.L. | A standard protocol for describing individual-based and agent-based models |
2006 | Ecological Modelling | Vol. 198 (1-2) , pp. 115-126 |
||
| Abstract: Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers. (c) 2006 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Grimm2006,
author = {Grimm, V. and Berger, U. and Bastiansen, F. and Eliassen, S. and Ginot, V. and Giske, J. and Goss-Custard, J. and Grand, T. and Heinz, S. K. and Huse, G. and Huth, A. and Jepsen, J. U. and Jorgensen, C. and Mooij, W. M. and Muller, B. and Pe'er, G. and Piou, C. and Railsback, S. F. and Robbins, A. M. and Robbins, M. M. and Rossmanith, E. and Ruger, N. and Strand, E. and Souissi, S. and Stillman, R. A. and Vabo, R. and Visser, U. and DeAngelis, D. L.},
title = {A standard protocol for describing individual-based and agent-based models},
journal = {Ecological Modelling},
year = {2006},
volume = {198},
number = {1-2},
pages = {115-126},
note = {Cited References: ABER JD, 1997, B ECOL SOC AM, V78, P232 AXELROD R, 1997, COMPLEXITY COOPERATI BILLARI F, 2003, AGENT BASED COMPUTAT BOTKIN DB, 1972, J ECOL, V60, P849 DEANGELIS DL, 1980, ECOL MODEL, V8, P133 DEANGELIS DL, 1992, INDIVIDUAL BASED MOD DEANGELIS DL, 2005, ANNU REV ECOL EVOL S, V36, P147 DEUTSCHMAN DH, 1997, SCIENCE, V277, P1688 DORNDORF N, 1999, THESIS PHILLIPS U MA EDMONDS B, 2003, J ARTIF SOC SOC SIMU EPSTEIN J, 1996, GROWING ARTIFICIAL S FORD ED, 2000, SCI METHOD ECOLOGICA FOWLER M, 2003, UML DISTILLED BRIEF GILBERT N, 2005, SIMULATION SOCIAL SC GINOT V, 2002, ECOL MODEL, V157, P23 GOPEN GD, 1990, AM SCI, V78, P550 GRIMM V, 1999, ECOL MODEL, V115, P129 GRIMM V, 1999, ECOL MODEL, V115, P275 GRIMM V, 2002, NAT RESOUR MODEL, V15, P23 GRIMM V, 2003, OIKOS, V102, P124 GRIMM V, 2004, OIKOS, V105, P501 GRIMM V, 2005, INDIVIDUAL BASED MOD HACKLANDER K, 1999, BEHAV ECOL, V10, P592 HALES D, 2003, J ARTIF SOC SOC SIMU, V6 HUCKFELDT R, 2004, POLITICAL DISAGREEME HUSE G, 2002, HDB FISH FISHERIES, P228 HUTH A, 1992, J THEOR BIOL, V156, S36 HUTH A, 1994, ECOL MODEL, P75 INADA Y, 2002, J THEOR BIOL, V214, P371 KUNZ H, 2003, ARTIF LIFE, V9, P237 LIU JG, 1995, FOREST ECOL MANAG, V73, P157 LOREK H, 1999, ECOL MODEL, V115, P199 PARKER DC, 2003, ANN ASSOC AM GEOGR, V93, P314 PECK SL, 2004, TRENDS ECOL EVOL, V19, P530 PITT WC, 2003, ECOL MODEL, V166, P109 RAILSBACK SF, 2001, ECOL MODEL, V139, P47 REUTER H, 1994, ECOL MODEL, V75, P147 ROUCHIER J, 2003, J ARTIF SOC SOC SIMU SHUGART HH, 1984, THEORY FOREST DYNAMI SHUGART HH, 1992, ANNU REV ECOL SYST, V23, P15 STRAND E, 2002, AM NAT, V159, P624 TESFATSION L, 2002, ARTIF LIFE, V8, P55 TYLER JA, 1994, REV FISH BIOL FISHER, V4, P91 VANWINKLE W, 1993, T AM FISH SOC, V122, P397 ZEIGLER BP, 2000, THEORY MODELING SIMU},
url = { |
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| Klein, E.; Lavigne, C.; Picault, H.; Renard, M. & Gouyon, P. | Pollen dispersal of oilseed rape: estimation of the dispersal function and effects of field dimension [BibTeX] |
2006 | Journal of Applied Ecology | Vol. 43 (141-151) |
||
BibTeX:
@article{Klein2006,
author = {Klein, E.K. and Lavigne, C. and Picault, H. and Renard, M. and Gouyon, P.H.},
title = {Pollen dispersal of oilseed rape: estimation of the dispersal function and effects of field dimension},
journal = {Journal of Applied Ecology},
year = {2006},
volume = {43},
number = {141-151}
}
|
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| Klein, E.K.; Desassis, N. & Oddou-Muratorio, S. | Pollen flow in the wildservice tree, Sorbus torminalis (L.) Crantz. IV. Whole interindividual variance of male fecundity estimated jointly with the dispersal kernel |
2008 | Molecular Ecology | Vol. 17 (14) , pp. 3323-3336 |
||
| Abstract: Interindividual variance of male reproductive success (MRS) contributes to genetic drift, which in turn interacts with selection and migration to determine the short-term response of populations to rapid changes in their environment. Individual relative MRS can be estimated through paternity analysis and can be further dissected into fecundity and spatial components. Existing methods to achieve this decomposition either rely on the strong assumption of a random distribution of pollen donors (TwoGener) or estimate only the part of the variance of male fecundity that is explained by few covariates. We developed here a method to estimate jointly the whole variance of male fecundity and the pollen dispersal curve from the genotypic information of sampled seeds and their putative fathers and geographical information of all individuals in the study area. We modelled the relative individual fecundities as a log-normally distributed random effect. We used a Bayesian approach, well suited to the hierarchical nature of the model, to estimate these fecundities. When applied to Sorbus torminalis, the estimated variance of male fecundity corresponded to an effective density of trees 13 times lower than the observed density (d(obs)/d(ep) similar to 13). This value is between the value (similar to 2) estimated with a classical mating model including three covariates (neighbourhood density, diameter, flowering intensity) that affect fecundity and the value (similar to 30) estimated with TwoGener. The estimated dispersal kernel was close to previous results. This approach allows fine monitoring of ongoing genetic drift in natural populations, and quantitative dissection of the processes contributing to drift, including human actions. | ||||||
BibTeX:
@article{Klein2008,
author = {Klein, E. K. and Desassis, N. and Oddou-Muratorio, S.},
title = {Pollen flow in the wildservice tree, Sorbus torminalis (L.) Crantz. IV. Whole interindividual variance of male fecundity estimated jointly with the dispersal kernel},
journal = {Molecular Ecology},
year = {2008},
volume = {17},
number = {14},
pages = {3323-3336},
note = {Cited References: ADAMS WT, 1991, BIOCH MARKERS POPULA, P157 AUSTERLITZ F, 2001, GENETICS, V157, P851 AUSTERLITZ F, 2002, GENETICS, V161, P355 AUSTERLITZ F, 2004, MOL ECOL, V13, P937, DOI 10.1111/j.1365-294X.2004.02100.x BACLES CFE, 2005, EVOLUTION, V59, P979 BANERJEE S, 2003, HIERARCHICAL MODELIN BEAUMONT MA, 2004, NAT REV GENET, V5, P251, DOI 10.1038/nrg1318 BURCZYK J, 2002, MOL ECOL, V11, P2379 BURCZYK J, 2005, MOL ECOL, V14, P2525, DOI 10.1111/j.1365-294X.2005.02593.x CLARK JS, 1998, ECOL MONOGR, V68, P213 CLARK JS, 2006, TRENDS ECOL EVOL, V21, P375, DOI 10.1016/j.tree.2006.03.016 DEVAUX C, 2007, MOL ECOL, V16, P487, DOI 10.1111/j.1365-294X.2006.03155.x DEVLIN B, 1990, AM NAT, V136, P87 EMERY AM, 2001, MOL ECOL, V10, P1265 GERARD PR, 2006, BMC EVOL BIOL, V6, ARTN 96 GILKS WR, 1996, INTERDISCIPLINARY ST GOTO S, 2006, MOL ECOL, V15, P2985, DOI 10.1111/j.1365-294X.2006.02976.x HADFIELD JD, 2006, MOL ECOL, V15, P3715, DOI 10.1111/j.1365-294X.2006.03050.x HAMRICK JL, 2004, FOREST ECOL MANAG, V197, P323, DOI 10.1016/j.foreco.2004.05.023 HARDY OJ, 2004, J EVOLUTION BIOL, V17, P795, DOI 10.1111/j.1420-9101.2004.00713.x HUBER PJ, 1981, ROBUST STAT IRWIN AJ, 2003, HEREDITY, V90, P187, DOI 10.1038/sj.hdy.6800215 KLEIN EK, 2006, BMC ECOL, V6, ARTN 3 KLEIN EK, 2006, J APPL ECOL, V43, P141, DOI 10.1111/j.1365-2664.2005.01108.x LANDE R, 1983, EVOLUTION, V37, P1210 LANDE R, 1987, VIABLE POPULATIONS C, P87 LAVIGNE C, 1998, THEOR APPL GENET, V96, P886 MEAGHER TR, 1986, AM NAT, V128, P199 NIELSEN R, 2001, GENETICS, V157, P1673 ODDOUMURATORIO S, 2001, MOL ECOL NOTES, V1, P297 ODDOUMURATORIO S, 2003, MOL ECOL, V12, P3427, DOI 10.1046/j.1365-294X.2003.01989.x ODDOUMURATORIO S, 2004, MOL ECOL, V13, P3689, DOI 10.1111/j.1365-294X.2004.02373.x ODDOUMURATORIO S, 2005, MOL ECOL, V14, P4441, DOI 10.1111/j.1365-294X.2005.02720.x ODDOUMURATORIO S, 2006, AM J BOT, V93, P1650 PATEL JK, 1976, HDB STAT DISTRIBUTIO PETIT RJ, 2006, ANNU REV ECOL EVOL S, V37, P187, DOI 10.1146/annurev.ecolsys.37.091305.110215 ROBLEDOARNUNCIO JJ, 2005, HEREDITY, V94, P13, DOI 10.1038/sj.hdy.6800542 ROBLEDOARNUNCIO JJ, 2006, AM NAT, V168, P500 SCHNABEL A, 1998, MOL ECOL, V7, P819 SHIMATANI K, 2007, POPUL ECOL, V49, P317, DOI 10.1007/s10144-007-0050-8 SLAVOV GT, 2005, MOL ECOL, V14, P3109, DOI 10.1111/j.1365-294X.2005.02620.x SMOUSE PE, 1994, GENETICS, V136, P313 SMOUSE PE, 1999, J EVOLUTION BIOL, V12, P1069 SMOUSE PE, 2001, EVOLUTION, V55, P260 SMOUSE PE, 2004, FOREST ECOL MANAG, V197, P21, DOI 10.1016/j.foreco.2004.05.049 SORK VL, 1999, TRENDS ECOL EVOL, V14, P219},
url = { |
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| Klein, E.K.; Lavigne, C. & Gouyon, P.-H. | Mixing of propagules from discrete sources at long distance: comparing a dispersal tail to an exponential |
2006 | BMC Ecology | Vol. 6 , pp. 3 |
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| Abstract: BACKGROUND: Rare long distance dispersal events impact the demography and the genetic structure of populations. When dispersal is modelled via a dispersal kernel, one possible characterisation of long-distance dispersal is given by the shape of the tail of the kernel, i.e. its type of decay. This characteristic is known to directly act on the speed and pattern of colonization, and on the spatial structure of genetic diversity during colonization. In particular, colonization waves behave differently depending on whether the kernel decreases faster or slower than an exponential (i.e. is thin-tailed vs. fat-tailed). To interpret and extend published results on the impact of long-distance dispersal on the genetic structure of populations, we examine a classification of dispersal kernels based on the shape of their tails and formally demonstrate qualitative differences among them that can influence the predicted diversity of a propagule pool sampled far from two distinct sources. RESULTS: We show that a fat-tailed kernel leads asymptotically to a diverse propagule pool containing a balanced mixing of the propagules from the two sources, whereas a thin-tailed kernel results in all propagules originating from the closest source. We further show that these results hold for biologically relevant distances under certain circumstances, and in particular if the number of propagules is large enough, as would be the case for pollen or seeds. CONCLUSION: To understand the impact of long-distance dispersal on the structure and dynamics of a metapopulation, it might be less important to precisely estimate an average dispersal distance than to determine if the tail of the dispersal kernel is fatter or thinner than that of an exponential function. Depending solely on this characteristic, a metapopulation will behave similarly to an island model with a diverse immigrant pool or to a stepping-stone model with migrants from closest populations. Our results further help to understand why thin-tailed dispersal kernels lead to a colonization wave of constant speed, whereas fat-tailed dispersal kernels lead to a wave of increasing speed. Our results also suggest that the diversity of the pollen cloud of a mother plant should increase with increasing isolation for fat-tailed kernels, whereas it should decrease for thin-tailed kernels. | ||||||
BibTeX:
@article{Klein2006a,
author = {Klein, Etienne K. and Lavigne, Claire and Gouyon, Pierre-Henri},
title = {Mixing of propagules from discrete sources at long distance: comparing a dispersal tail to an exponential},
journal = {BMC Ecology},
year = {2006},
volume = {6},
pages = {3},
note = {Times Cited: 0},
url = { |
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| Kunstler, G.; Chadoeuf, J.; Klein, E.K.; Curt, T.; Bouchaud, M. & Lepart, J. | Tree colonization of sub-Mediterranean grasslands: Effects of effective dispersal and shrub facilitation [BibTeX] |
2007 | Canadian Journal of Forest Research | Vol. 37 , pp. 103-115 |
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BibTeX:
@article{Kunstler2007,
author = {Kunstler, G. and Chadoeuf, J. and Klein, E. K. and Curt, T. and Bouchaud, M. and Lepart, J.},
title = {Tree colonization of sub-Mediterranean grasslands: Effects of effective dispersal and shrub facilitation},
journal = {Canadian Journal of Forest Research},
year = {2007},
volume = {37},
pages = {103-115}
}
|
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| Lannou, C.; Soubeyrand, S.; Frezal, L. & Chadoeruf, J. | Autoinfection in wheat leaf rust epidemics |
2008 | New Phytologist | Vol. 177 (4) , pp. 1001-1011 |
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| Abstract: Autoinfection (within-host inoculum transmission) allows plant pathogens locally to increase their density on an infected host. Estimating autoinfection is of particular importance in understanding epidemic development in host mixtures. More generally, autoinfection influences the rate of host colonization by the pathogen, as well as pathogen evolution. Despite its importance in epidemiological models, autoinfection has not yet been directly quantified. It was measured here on wheat (Triticum aestivum) leaves infected by a pathogenic fungus (Puccinia triticina). Autoinfection was measured either on inoculated leaves or by assessing the local progeny of spontaneous infections, and was described by a model of the form y = mu x(alpha), where alpha accounts for host saturation and mu represents the pathogen multiplication rate resulting from autoinfection. It was shown that autoinfection resulted in typical patterns of disease aggregation at the leaf level and influenced lesion distribution in the crop during the first epidemic stages. The parameter mu was calculated by taking overdispersion of the data and density dependence into account. It was found that a single lesion produced between 50 and 200 offspring by autoinfection, within a pathogen generation. By taking into account environmental variability, it was possible to estimate autoinfection under optimal conditions for epidemic development. | ||||||
BibTeX:
@article{Lannou2008,
author = {Lannou, C. and Soubeyrand, S. and Frezal, L. and Chadoeruf, J.},
title = {Autoinfection in wheat leaf rust epidemics},
journal = {New Phytologist},
year = {2008},
volume = {177},
number = {4},
pages = {1001-1011},
note = {Cited References: AYLOR DE, 1987, PHYTOPATHOLOGY, V77, P1442 AYLOR DE, 1990, PHYTOPATHOLOGY, V80, P1469 BARRETT JA, 1980, Z PFLANZENKRANKHEITE, V87, P383 BURDON JJ, 1976, OECOLOGIA, V26, P61 CLEVELAND WS, 1979, J AM STAT ASSOC, V74, P829 DIGGLE PJ, 1983, STAT ANAL SPATICAL P EYAL Z, 1968, PHYTOPATHOLOGY, V58, P530 GANDON S, 2002, AM NAT, V159, P658 GOYEAU H, 2007, FUNGAL GENET BIOL, V44, P474, DOI 10.1016/j.fgb.2007.02.006 KEESING F, 2006, ECOL LETT, V9, P485, DOI 10.1111/j.1461-0248.2006.00885.x LANNOU C, 2001, PHYTOPATHOLOGY, V91, P500 MACLACHLAN GJ, 1987, J ROY STAT SOC, V36, P318 MANLY B, 1997, RANDOMIZATION BOOTST MCCULLAGH P, 1989, GEN LINEAR MODELS MUNDT CC, 1985, PHYTOPATHOLOGY, V75, P930 MUNDT CC, 1986, PHYTOPATHOLOGY, V76, P832 MUNDT CC, 2002, ANNU REV PHYTOPATHOL, V40, P381, DOI 10.1146/annurev.phyto.40.011402.113723 OHARA RB, 1997, PLANT PATHOL, V46, P969 OHARA RB, 1998, PLANT PATHOL, V47, P394 OSTERGAARD H, 1983, PHYTOPATHOLOGY, V73, P166 ROBERT C, 2004, J EXPT BOT, V55, P1 ROBERT C, 2004, PHYTOPATHOLOGY, V94, P712 ROBINSON RA, 1984, PLANT PATHOSYSTEMS, V74, P1262 ROELFS AP, 1984, PHYTOPATHOLOGY, V74, P1262 ROUSE DI, 1981, PHYTOPATHOLOGY, V71, P1015 SOUBEYRAND S, 2007, J DATA SCI, V5, P67 TELLIER A, 2007, P R SOC B, V274, P809, DOI 10.1098/rspb.2006.0281 THRALL PH, 2002, PLANT PATHOL, V51, P169 VANBAALEN M, 1995, AM NAT, V146, P881 WILLOCQUET L, 2004, PHYTOPATHOLOGY, V94, P883},
url = { |
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| Lavigne, C.; Klein, E.K.; Mari, J.F.; Le Ber, F.; Adamczyk, K.; Monod, H. & Angevin, F. | How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape? |
2008 | Journal Of Applied Ecology | Vol. 45 (4) , pp. 1104-1113 |
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| Abstract: 1. It is well established that pollen-mediated gene flow among natural plant populations depends on a complex interaction between the spatial distribution of pollen sources and the short- and long-distance components of pollen dispersal. Despite this knowledge, spatial isolation strategies proposed in Europe to ensure the harvest purity of conventional crops are based on distance from the nearest genetically modified (GM) crop and on empirical data from two-plot experiments. Here, we investigate the circumstances under which the multiplicity of pollen sources over the landscape should be considered in strategies to contain GM crops. 2. We simulated pollen dispersal over eighty 6 x 6 km simulated landscapes differing in field characteristics and in amount of GM and conventional maize. Pollen dispersal was modelled either via a Normal Inverse Gaussian (NIG, currently used for European coexistence studies) or a bivariate Student (2Dt) kernel. These kernels differ in their amount of short- and long-distance dispersal. We used linear models to analyse the impact of local and landscape variables on impurity rates (i.e. proportion of seeds sired by pollen from a transgenic crop) in conventional fields and quantified their increase due to dispersal from other than the closest GM crops. 3. The average impurity rate over a landscape increased linearly with the proportion of GM maize over that landscape. The increase was twice as fast using the NIG kernel and was governed by the short-distance dispersal component. 4. Variation in impurity rates largely depended on the distance to the closest GM crop and the size of the receptor field. However, impurity rates were generally underestimated when only dispersal from the closest GM field was considered. 5. Synthesis and applications. Distance to the closest GM crop had most impact on impurity rates in conventional fields. However, impurity rates also depended on intermediate- to long-distance dispersal from distant GM crops. Therefore, isolation distances as currently defined will probably not allow long-term coexistence of GM and conventional crops, especially as the proportion of GM crops grown increases. We suggest strategies to account for this impact of long-distance dispersal. | ||||||
BibTeX:
@article{Lavigne2008,
author = {Lavigne, C. and Klein, E. K. and Mari, J. F. and Le Ber, F. and Adamczyk, K. and Monod, H. and Angevin, F.},
title = {How do genetically modified (GM) crops contribute to background levels of GM pollen in an agricultural landscape?},
journal = {Journal Of Applied Ecology},
year = {2008},
volume = {45},
number = {4},
pages = {1104-1113},
note = {Cited References: *R DEV COR TEAM, 2006, R LANG ENV STAT COMP ADAMCZYK K, 2007, REV INT GEOMATIQUE, V17, P469 ADAMS WT, 1991, BIOCH MARKERS POPULA, P157 ANGEVIN F, 2002, TECHNICAL REPORT SER, P52 ANGEVIN F, 2008, EUR J AGRON, V28, P471, DOI 10.1016/j.eja.2007.11.010 AYLOR DE, 2003, AGR FOREST METEOROL, V119, P111, DOI 10.1016/S0168-1923(03)00159-X BANNERT M, 2007, EUR J AGRON, V27, P44, DOI 10.1016/j.eja.2007.01.002 CEDDIA MG, 2007, ECOL MODEL, V205, P169, DOI 10.1016/j.ecolmodel.2007.02.025 CLARK JS, 1998, AM NAT, V152, P204 COLBACH N, 2005, EUR J AGRON, V22, P417, DOI 10.1016/j.eja.2004.06.004 DEVAUX C, 2007, MOL ECOL, V16, P487, DOI 10.1111/j.1365-294X.2006.03155.x DEVAUX C, 2008, J APPL ECOL, V45, P803, DOI 10.1111/j.1365-2664.2007.01400.x DEVOS Y, 2005, ENV BIOSAFETY RES, V4, P71 DUPONT S, 2006, AGR FOREST METEOROL, V141, P82, DOI 10.1016/j.agrformet.2006.09.004 GUSTAFSON DI, 2005, CROP SCI, V45, P1286, DOI 10.2135/cropsci2004.0137 HALSEY ME, 2005, CROP SCI, V45, P2172, DOI 10.2135/cropsci2003.0664 HOYLE M, 2007, ECOL APPL, V17, P1234 INGRAM J, 2000, PLANT VAR SEEDS, V13, P181 KEITT TH, 1997, CONSERV ECOL, V1, P1 KLEIN EK, 2003, ECOL MONOGR, V73, P131 KLEIN EK, 2006, BMC ECOL, V6, ARTN 3 KLEIN EK, 2006, J APPL ECOL, V43, P141, DOI 10.1111/j.1365-2664.2005.01108.x KUPARINEN A, 2007, ECOL APPL, V17, P431 LAVIGNE C, 1998, THEOR APPL GENET, V96, P886 MESSEAN A, 2006, TECHNICAL REPORT SER MOLLISON D, 1977, J ROY STAT SOC B MET, V39, P283 NATHAN R, 2005, DIVERS DISTRIB, V11, P125, DOI 10.1111/j.1366-9516.2005.00159.x OKABE A, 1992, SPATIAL TESSELLATION RAMSAY G, 2003, RG0216 DEFRA RIEGER MA, 2002, SCIENCE, V296, P2386 ROBLEDOAMUNCIO JJ, 2004, FOREST ECOL MANAG, V197, P245, DOI 10.1016/j.foreco.2004.05.016 ROBLEDOARNUNCIO JJ, 2006, AM NAT, V168, P500 SHAW MW, 2006, P R SOC B, V273, P1705, DOI 10.1098/rspb.2006.3491 SMOUSE PE, 2004, FOREST ECOL MANAG, V197, P21, DOI 10.1016/j.foreco.2004.05.049 SMOUSE PE, 2007, TREE GENET GENOMES, V3, P141, DOI 10.1007/s11295-006-0075-8 SORK VL, 2006, LANDSCAPE ECOL, V21, P821, DOI 10.1007/s10980-005-5415-9 STONE R, 1994, SCIENCE, V266, P1472 WEEKES R, 2007, TRANSGENIC RES, V16, P203, DOI 10.1007/s11248-006-9036-0 WILLENBORG CJ, 2006, CROP SCI, V45, P1286},
url = { |
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| Leblond, A.; Pradier, S.; Pittel, P.; Fortier, G.; Boireau, P.; Chadoeuf, J. & Sabatier, P. | An epidemiological survey of equine anaplasmosis (Anaplasma phagocytophilum) in Southern France [BibTeX] |
2006 | Revue Scientifique & Technique - Office International des Epizooties | Vol. 24 (3) , pp. 899-908 |
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BibTeX:
@article{Leblond2006,
author = {Leblond, A. and Pradier, S. and Pittel, P.H. and Fortier, G. and Boireau, P. and Chadoeuf, J. and Sabatier, P.},
title = {An epidemiological survey of equine anaplasmosis (Anaplasma phagocytophilum) in Southern France},
journal = {Revue Scientifique & Technique - Office International des Epizooties},
year = {2006},
volume = {24},
number = {3},
pages = {899-908}
}
|
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| van Lieshout, M.N.M. & Stoica, R.S. | Perfect simulation for marked point processes |
2006 | Computational Statistics & Data Analysis | Vol. 51 (2) , pp. 679-698 |
||
| Abstract: Some recently proposed exact simulation methods are extended to the case of marked point processes. Four families of algorithms are considered: coupling from the past, the clan of ancestors technique, the Gibbs sampler, and a Metropolis-Hastings algorithm based on birth and death proposals. From a theoretical point of view, conditions are given under which the algorithms yield unbiased samples in finite time. For practical application, a C++ library for marked point processes is described. The various algorithms are tested on several models, including the Widom-Rowlinson mixture model, multi-type pairwise interaction processes, and the Candy line segment model. A simulation study is carried out in order to analyse the proposed methods in terms of speed of convergence in relation to the parameters of the model. For the range of models investigated, the clan of ancestors algorithm using the incompatibility index is the fastest method among the ones analysed, while coupling from the past is applicable to the widest range of parameter values, and usually faster than the Metropolis-Hastings sampler. The latter two methods tend to be cumbersome if the underlying model is neither attractive nor repulsive. If one is prepared to approximate by discretisation, a proper choice of Gibbs sampler makes it possible to obtain samples from models that lack monotonicity or have such a high local stability bound as to rule out coupling from the past or clan of ancestor approaches in practice. (c) 2006 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Lieshout2006,
author = {van Lieshout, M. N. M. and Stoica, R. S.},
title = {Perfect simulation for marked point processes},
journal = {Computational Statistics & Data Analysis},
year = {2006},
volume = {51},
number = {2},
pages = {679-698},
note = {Cited References: BADDELEY A, 1989, INT STAT REV, V57, P89 BARNDORFFNIELSE.OE, 2001, COMPLEX STOCHASTIC S BERTHELSEN KK, 2001, SPATIAL JUMP PROCESS BERTHELSEN KK, 2002, BULL BRAZ MATH SOC, V33, P351 BESAG J, 1982, J APPL PROBAB, V19, P210 DALEY DJ, 1988, INTRO THEORY POINT P FERRARI PA, 2002, STOCH PROC APPL, V102, P63 FILL JA, 1998, ANN APPL PROBAB, V8, P131 FILL JA, 2000, P 41 ANN IEEE S FDN, P503 FILL JA, 2000, RANDOM STRUCT ALGOR, V17, P290 GARCIA NL, 2000, RESENHAS IME USP, V4, P283 GEYER CJ, 1994, SCAND J STAT, V21, P359 GEYER CJ, 1999, STOCHASTIC GEOMETRY, P79 GOULARD M, 1996, SCAND J STAT, V23, P365 GREEN PJ, 1995, BIOMETRIKA, V82, P711 HAGGSTROM O, 1998, STAT NEERL, V52, P360 HAGGSTROM O, 1999, BERNOULLI, V5, P641 HAGGSTROM O, 1999, SCAND J STAT, V26, P395 KENDALL WS, 1998, PROBABILITY 2000, P218 KENDALL WS, 2000, ADV APPL PROBAB, V32, P844 KENDALL WS, 2002, STOCH PROC APPL, V99, P177 MEYN SP, 1993, MARKOV CHAINS STOCHA MIRA A, 2001, J ROY STAT SOC B 3, V63, P593 MOLLER J, 1989, ANN I STAT MATH, V41, P565 MOLLER J, 1999, J ROY STAT SOC B 1, V61, P251 MURDOCH DJ, 1998, SCAND J STAT, V25, P483 OGATA Y, 1984, J ROY STAT SOC B MET, V46, P496 PRESTON CJ, 1977, B INT STAT I, V46, P371 PROPP JG, 1996, RANDOM STRUCT ALGOR, V9, P223 RIPLEY BD, 1977, J LOND MATH SOC, V15, P188 RIPLEY BD, 1977, J ROY STAT SOC B MET, V39, P172 STEENBEEK AG, 2002, CONTRIBUTIONS P GREO STEINSLAND I, 2006, COMPUT STAT DATA ANA STOICA R, 2004, INT J COMPUT VISION, V57, P121 THONNES E, 1999, ADV APPL PROBAB, V31, P69 VANLIESHOUT MNM, 2000, MARKOV POINT PROCESS VANLIESHOUT MNM, 2002, SPATIAL CLUSTER MODE, P61 VANLIESHOUT MNM, 2003, STAT NEERL, V57, P177 WIDOM B, 1970, J CHEM PHYS, V52, P1670},
url = { |
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| Llaurens, V.; Billiard, S.; Leducq, J.B.; Castric, V.; Klein, E.K. & Vekemans, X. | Does Frequency-Dependent Selection With Complex Dominance Interactions Accurately Predict Allelic Frequencies At The Self-Incompatibility Locus In Arabidopsis Halleri? |
2008 | Evolution | Vol. 62 (10) , pp. 2545-2557 |
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| Abstract: Frequency-dependent selection is a major force determining the evolutionary dynamics of alleles at the self-incompatibility locus (S-locus) in flowering plants. We introduce a general method using numerical simulations to test several alternative models of frequency-dependent selection on S-locus data from sporophytic systems, taking into account both genetic drift and observed patterns of dominance interactions among S-locus haplotypes (S-haplotypes). Using a molecular typing method, we estimated S-haplotype frequencies in a sample of 322 adult plants and of 245 offspring obtained from seeds sampled on 22 maternal plants, collected in a single population of Arabidopsis halleri (Brassicaceae). We found eight different S-haplotypes and characterized their dominance interactions by controlled pollinations. We then compared the likelihood of different models of frequency-dependent selection: we found that the observed haplotype frequencies and observed frequency changes in one generation best fitted a model with (1) the observed dominance interactions and (2) no pollen limitation. Overall, our population genetic models of frequency-dependent selection, including patterns of dominance interactions among S-haplotypes and genetic drift, can reliably predict polymorphism at the S-locus. We discuss how these approaches allow detecting additional processes influencing the evolutionary dynamics of the S-locus, such as purifying selection on linked loci. | ||||||
BibTeX:
@article{Llaurens2008,
author = {Llaurens, V. and Billiard, S. and Leducq, J. B. and Castric, V. and Klein, E. K. and Vekemans, X.},
title = {Does Frequency-Dependent Selection With Complex Dominance Interactions Accurately Predict Allelic Frequencies At The Self-Incompatibility Locus In Arabidopsis Halleri?},
journal = {Evolution},
year = {2008},
volume = {62},
number = {10},
pages = {2545-2557},
note = {Cited References: ANDERSON DR, 2002, J WILDLIFE MANAGE, V66, P912 BATEMAN AJ, 1952, HEREDITY, V6, P285 BATEMAN AJ, 1954, HEREDITY, V8, P305 BECHSGAARD J, 2004, J EVOLUTION BIOL, V17, P554, DOI 10.1111/j.1420-9101.2004.00699.x BILLIARD S, 2007, GENETICS, V175, P1351, DOI 10.1534/genetics.105.055095 BILLIARD S, 2008, MOL ECOL RESOUR, V8, P295, DOI 10.1111/j.1471-8286.2007.01985.x BOUCHER W, 1993, J MATH BIOL, V31, P149 BRENNAN A, 2002, HEREDITY, V89, P430, DOI 10.1038/sj.hdy.6800159 CASTRIC V, 2004, MOL ECOL, V13, P2873, DOI 10.1111/j.1365-294X.2004.02267.x CASTRIC V, 2007, BMC EVOL BIOL, V7, ARTN 132 CASTRIC V, 2008, PLOS GENETI IN PRESS CHOOKAJORN T, 2004, P NATL ACAD SCI USA, V101, P911, DOI 10.1073/pnas.2637116100 CLAUSS MJ, 2006, TRENDS PLANT SCI, V11, P449, DOI 10.1016/j.tplants.2006.07.005 DENETTANCOURT D, 2001, INCOMPATIBILITY INCO GLEMIN S, 2005, GENETICS, V171, P279 HATAKEYAMA K, 1998, HEREDITY 2, V80, P241 KARRON JD, 1990, THEOR APPL GENET, V79, P457 KATO S, 2004, HEREDITY, V92, P249, DOI 10.1038/sj.hdy.6800403 KOWYAMA Y, 1994, HEREDITY, V73, P275 LANE MD, 1995, HEREDITY, V75, P92 LAWRENCE MJ, 2000, ANN BOT-LONDON A, V85, P221 LLAURENS V, 2008, MOL ECOL, V17, P1577, DOI 10.1111/j.1365-294X.2007.03683.x MABLE BK, 2003, HEREDITY, V90, P422, DOI 10.1038/sj.hdy.6800261 NAGYLAKI T, 1975, GENETICS, V79, P545 NASRALLAH ME, 1991, DEV REGULATION PLANT, P130 NOU IS, 1993, SEX PLANT REPROD, V6, P79 OCKENDON DJ, 1975, EUPHYTICA, V24, P165 PRIGODA NL, 2005, MOL BIOL EVOL, V22, P1609, DOI 10.1093/molbev/msi153 RICHMAN AD, 1999, P NATL ACAD SCI USA, V96, P168 SAMPSON DR, 1967, GENETICS, V56, P241 SCHIERUP MH, 1997, GENETICS, V147, P835 SCHIERUP MH, 2000, GENET RES, V76, P51 SCHIERUP MH, 2006, GENETICS, V172, P477, DOI 10.1534/genetics.105.045682 STEVENS JP, 1989, HEREDITY, V62, P199 STOECKEL S, 2008, J EVOLUTION BIOL, V21, P889, DOI 10.1111/j.1420-9101.2008.01504.x STONE JL, 2004, HEREDITY, V92, P335, DOI 10.1038/sj.hdy.6800425 TAKAYAMA S, 2003, J EXP BOT, V54, P149, DOI 10.1093/jxb/erg007 TAKAYAMA S, 2005, ANNU REV PLANT BIOL, V56, P467, DOI 10.1146/annurev.arplant.56.032604.144249 UYENOYAMA MK, 1997, GENETICS, V147, P1389 UYENOYAMA MK, 2000, GENETICS, V156, P351 UYENOYAMA MK, 2003, THEOR POPUL BIOL, V63, P281, DOI 10.1016/S0040-5809(03)00020-0 UYENOYAMA MK, 2005, NEW PHYTOL, V165, P63, DOI 10.1111/j.1469-8137.2004.01246.x VEKEMANS X, 1998, EVOLUTION, V52, P19 WRIGHT S, 1939, GENETICS, V24, P538 YOKOYAMA S, 1982, HEREDITY, V48, P299},
url = { |
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| Magnussen, S.; Allard, D. & Wulder, M.A. | Poisson Voronoi tiling for finding clusters in spatial point patterns [BibTeX] |
2006 | Scandinavian Journal of Forest Research | Vol. 21 (3) , pp. 239-248 |
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BibTeX:
@article{Magnussen2006,
author = {Magnussen, S. and Allard, D. and Wulder, M. A.},
title = {Poisson Voronoi tiling for finding clusters in spatial point patterns},
journal = {Scandinavian Journal of Forest Research},
year = {2006},
volume = {21},
number = {3},
pages = {239-248},
url = { |
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| Monestiez, P.; Dubroca, L.; Bonnin, E.; Durbec, J. & Guinet, C. | Geostatistical modelling of spatial distribution of balenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts [BibTeX] |
2006 | Ecological Modelling | Vol. 193 , pp. 615-628 |
||
BibTeX:
@article{Monestiez2006,
author = {Monestiez, P. and Dubroca, L. and Bonnin, E. and Durbec, J.P. and Guinet, C.},
title = {Geostatistical modelling of spatial distribution of balenoptera physalus in the Northwestern Mediterranean Sea from sparse count data and heterogeneous observation efforts},
journal = {Ecological Modelling},
year = {2006},
volume = {193},
pages = {615-628}
}
|
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| Monestiez, P. & Nerini, D. | A cokriging method for spatial functional data with applications in oceanology |
2008 | Functional And Operatorial Statistics | , pp. 237-242 | ||
| Abstract: We propose a method based on a functional linear model which takes into account the spatial dependencies between sampled functions. The problem of estimating a function when spatial samples are available is turned to a standard cokriging problem for suitable choices of the regression function. This work is illustrated with environmental data in Antarctic where marine mammals operate as samplers. In the framework of second order stationarity, the application points out some difficulties when estimating the structure of spatial covariance between observations. | ||||||
BibTeX:
@article{Monestiez2008,
author = {Monestiez, P. and Nerini, D.},
title = {A cokriging method for spatial functional data with applications in oceanology},
journal = {Functional And Operatorial Statistics},
year = {2008},
pages = {237-242},
note = {Cited References: BAILLEUL F, 2007, DEEP-SEA RES PT II, V54, P343, DOI 10.1016/j.dsr2.2006.11.005 CARDOT H, 1999, STAT PROBABIL LETT, V45, P11 DABONIANG S, 2007, MATH METHODS STAT, V16, P298 GOULARD M, 1992, MATH GEOL, V24, P269 MEIRING W, 2007, J AM STAT ASSOC, V102, P788 RAMSAY LO, 2005, FUNCTIONAL DATA ANAL WACKERNAGEL H, 2003, MULTIVARIATE GEOSTAT CONTRIBUTIONS TO STATISTICS},
url = { |
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| Moury, B.; Fabre, F. & Senoussi, R. | Estimation of the number of virus particles transmitted by an insect vector [BibTeX] |
2007 | Proceedings of the National Academy of Sciences USA | Vol. 104 (45) , pp. 17891-17896 |
||
BibTeX:
@article{Moury2007,
author = {Moury, B. and Fabre, F. and Senoussi, R.},
title = {Estimation of the number of virus particles transmitted by an insect vector},
journal = {Proceedings of the National Academy of Sciences USA},
year = {2007},
volume = {104},
number = {45},
pages = {17891-17896},
url = { |
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| Nerini, D.; Monestiez, P. & Mante, C. | Cokriging for spatial functional data |
2010 | Journal of Multivariate Analysis | Vol. 101 (2) , pp. 409-418 |
||
| Abstract: This work proposes to generalize the method of kriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies between curves. Under some regularity conditions of the curves, an ordinary kriging system is established in the infinite dimensional case. From a practical point-of-view, the decomposition of the curves into a functional basis boils down the problem of kriging in infinite dimension to a standard cokriging on basis coefficients. The methodological developments are illustrated with temperature profiles sampled with dives of elephant seals in the Antarctic Ocean. The projection of sampled profiles into a Legendre polynomial basis is performed with a regularization procedure based on spline smoothing which uses the variance of the sampling devices in order to estimate coefficients by quadrature. (C) 2009 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Nerini2010,
author = {Nerini, D. and Monestiez, P. and Mante, C.},
title = {Cokriging for spatial functional data},
journal = {Journal of Multivariate Analysis},
year = {2010},
volume = {101},
number = {2},
pages = {409-418},
url = { |
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| Oddou-Muratorio, S. & Klein, E.K. | Comparing direct vs. indirect estimates of gene flow within a population of a scattered tree species |
2008 | Molecular Ecology | Vol. 17 (11) , pp. 2743-2754 |
||
| Abstract: The comparison between historical estimates of gene flow, using variance in allelic frequencies, and contemporary estimates of gene flow, using parentage assignment, is expected to provide insights into ecological and evolutionary processes at work within and among populations. Genetic variation at six microsatellite loci was used to quantify genetic structure in the insect-pollinated, animal-dispersed, low-density tree Sorbus torminalis L. Crantz, and to derive historical estimates of gene flow. The neighbourhood size and root-mean-squared dispersal distance inferred from seedling genotypes (N-b = 70 individuals, sigma(e) = 417 m) were similar to those inferred from adult genotypes (N-b = 114 individuals, sigma(e) = 472 m). We also used parentage analyses and a neighbourhood model approach after an evaluation of the statistical properties of this method on simulated data. From our data, we estimated even contributions of seed- and pollen-mediated dispersal to the genetic composition of established seedlings, with both fat-tailed pollen and seed dispersal kernels, and slightly higher mean distance of pollen dispersal (248 m) as compared to seed dispersal (135 m). The resulting contemporary estimate of gene dispersal distance (sigma(c) = 211 m) was similar to twofold smaller than the historical estimates. Besides different assumptions and statistical nuances of both approaches, this discrepancy is likely to reflect a recent restriction in the scale of gene flow which requires manager's attention in a context of increasing forest fragmentation. | ||||||
BibTeX:
@article{Oddou-Muratorio2008,
author = {Oddou-Muratorio, S. and Klein, E. K.},
title = {Comparing direct vs. indirect estimates of gene flow within a population of a scattered tree species},
journal = {Molecular Ecology},
year = {2008},
volume = {17},
number = {11},
pages = {2743-2754},
note = {Cited References: ABRAMOWITZ M, 1964, HDB MATH FUNCTIONS F ANGELONE S, 2007, MOL ECOL, V16, P1291, DOI 10.1111/j.1365-294X.2006.03202.x AUSTERLITZ F, 2004, MOL ECOL, V13, P937, DOI 10.1111/j.1365-294X.2004.02100.x BACLES CFE, 2005, EVOLUTION, V59, P979 BURCZYK J, 2004, EVOLUTION, V58, P956 BURCZYK J, 2006, GENETICS, V173, P363, DOI 10.1534/genetics.105.046805 BUSH RM, 1992, NEW FOREST, V6, P179 CLARK JS, 1998, AM NAT, V152, P204 CRAWFORD TJ, 1984, HEREDITY, V52, P273 DUNPHY BK, 2005, HEREDITY, V94, P418, DOI 10.1038/sj.hdy.6800622 DUTECH C, 2005, AM J BOT, V92, P252 FRANKHAM R, 1995, GENET RES, V66, P95 GONZALEZMARTINEZ SC, 2006, MOL ECOL, V15, P4577, DOI 10.1111/j.1365-294X.2006.03118.x HARDESTY BD, 2006, ECOL LETT, V9, P516, DOI 10.1111/j.1461-0248.2006.00897.x HARDY OJ, 2002, MOL ECOL NOTES, V2, P618 HARDY OJ, 2006, MOL ECOL, V15, P559, DOI 10.1111/j.1365-294X.2005.02785.x JONES FA, 2005, AM NAT, V166, P543 JORDANO P, 2007, P NATL ACAD SCI USA, V104, P3278 KALISZ S, 2001, EVOLUTION, V55, P1560 LEBLOIS R, 2003, MOL BIOL EVOL, V20, P491, DOI 10.1093/molbev/msg034 LEBLOIS R, 2004, GENETICS, V166, P1081 LOISELLE BA, 1995, AM J BOT, V82, P1420 MANEL S, 2005, TRENDS ECOL EVOL, V20, P136, DOI 10.1016/j.tree.2004.12.004 MEAGHER TR, 1986, AM NAT, V128, P199 MORGAN MT, 2001, EVOLUTION, V55, P272 ODDOUMURATORIO S, 2001, EVOLUTION, V55, P1123 ODDOUMURATORIO S, 2004, MOL ECOL, V13, P3689, DOI 10.1111/j.1365-294X.2004.02373.x ODDOUMURATORIO S, 2005, MOL ECOL, V14, P4441, DOI 10.1111/j.1365-294X.2005.02720.x ODDOUMURATORIO S, 2006, AM J BOT, V93, P1650 OTEROARNAIZ A, 2005, MOL ECOL, V14, P4313, DOI 10.1111/j.1365-294X.2005.02762.x ROBLEDOARNUNCIO JJ, 2007, MOL ECOL, V16, P5098, DOI 10.1111/j.1365-294X.2007.03427.x ROUSSET F, 1997, GENETICS, V145, P1219 ROUSSET F, 2000, J EVOLUTION BIOL, V13, P58 ROUSSET F, 2004, GENETIC STRUCTURE SE SCHWEIZER M, 2007, MOL ECOL, V16, P2463, DOI 10.1111/j.1365-294X.2007.03284.x SMOUSE PE, 2005, HEREDITY, V94, P640, DOI 10.1038/sj.hdy.6800674 VEKEMANS X, 2004, MOL ECOL, V13, P921, DOI 10.1046/j.1365-294X.2004.02076.x WHITLOCK MC, 1999, HEREDITY 2, V82, P117 WOHLGEMUTH T, 2002, FOREST ECOL MANAG, V166, P1 WRIGHT S, 1943, GENETICS, V28, P114 WRIGHT S, 1951, ANN EUGEN, V15, P323},
url = { |
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| Oddou-Muratorio, S.; Klein, E.K.; Demesure-Musch, B. & Austerlitz, F. | Real-time patterns of pollen flow in the wild-service tree, Sorbus torminalis (Rosaceae). III. Mating patterns and the ecological maternal neighborhood |
2006 | American Journal of Botany | Vol. 93 (11) , pp. 1650-1659 |
||
| Abstract: Understanding the role of mother plants as pollen recipients in shaping mating patterns is essential for understanding the evolution of populations and in particular to predict the consequence of habitat fragmentation. Here, we investigated variation in mating patterns due to maternal phenotypic traits, phenological variance, and landscape features in Sorbus torminalis, a hermaphroditic, insect-pollinated and low-density, European temperate forest tree. The diversity and composition of pollen clouds received by maternal trees in S. torminalis were mainly determined by their conspecific neighborhood: isolated individuals sample more diversity through more even paternal contributions, low relatedness among paternal genes, and high rates of long-distance pollen dispersal within their progenies. Maternal phenotypic traits related to pollinator attractiveness also had an effect, but only when competition was strong: in this case, larger mother trees with more flowers sampled more diversity. The floral architecture of S. torminalis, with multiple-seeded fruit, strongly shaped mating patterns, with higher levels of correlated paternity among seeds belonging to the same fruit (30% full sibs) than among seeds belonging to different fruits (14% full sibs). Finally, flowering phenology affected the distribution of diversity among maternal pollen clouds, but the earliest and latest mother trees did not receive less diversity of pollen than the others. | ||||||
BibTeX:
@article{Oddou-Muratorio2006,
author = {Oddou-Muratorio, S. and Klein, E. K. and Demesure-Musch, B. and Austerlitz, F.},
title = {Real-time patterns of pollen flow in the wild-service tree, Sorbus torminalis (Rosaceae). III. Mating patterns and the ecological maternal neighborhood},
journal = {American Journal of Botany},
year = {2006},
volume = {93},
number = {11},
pages = {1650-1659},
note = {Cited References: *SAS I, 1998, SAS STAT US GUID REL AUGSPURGER CK, 1983, BIOTROPICA, V15, P257 BARRETT SCH, 2002, NAT REV GENET, V3, P274 BONNET E, 2002, J STAT SOFTW, V7, P1 CHARNOV EL, 1976, THEORETICAL POPULATI, V9, P129 CRESSWELL JE, 2004, J APPL ECOL, V41, P539 DICK CW, 2001, P ROY SOC LOND B BIO, V268, P2391 DICK CW, 2003, MOL ECOL, V12, P753 ELLSTRAND NC, 1993, ANNU REV ECOL SYST, V24, P217 FUCHS EJ, 2003, CONSERV BIOL, V17, P149 GARCIA C, 2005, MOL ECOL, V14, P1821 GOMORY D, 2003, FOREST ECOL MANAG, V174, P117 GOODELL K, 1997, AM J BOT, V84, P1362 GRIFFIN AR, 1989, SEXUAL REPROD TREE C HARDY OJ, 2002, MOL ECOL NOTES, V2, P618 HARDY OJ, 2004, GENETICS, V168, P1601 HODGINS KA, 2006, HEREDITY, V96, P262 KEATLEY MR, 2004, AUST J BOT, V52, P47 KLEIN EK, 2006, BIOMED CENTRAL ECOLO, V6, P3 LEDIG FT, 1986, CONSERVATION BIOL SC, P77 LOISELLE BA, 1995, AM J BOT, V82, P1420 MARSHALL TC, 1998, MOL ECOL, V7, P639 MOTTEN AF, 1992, AM J BOT, V79, P419 NIELSEN R, 2003, MOL ECOL, V12, P3157 OCONNELL LM, 2004, HEREDITY, V93, P443 ODDOUMURATORIO S, 2003, MOL ECOL, V12, P3427 ODDOUMURATORIO S, 2004, MOL ECOL, V13, P3689 ODDOUMURATORIO S, 2005, MOL ECOL, V14, P4441 OHASHI K, 2002, FUNCT ECOL, V16, P492 PYKE GH, 1984, ANNU REV ECOL SYST, V15, P523 QUESADA M, 2001, AM J BOT, V88, P2113 ROBLEDOAMUNCIO JJ, 2004, FOREST ECOL MANAG, V197, P245 ROBLEDOARNUNCIO JJ, 2004, MOL ECOL, V13, P2567 ROCHA OJ, 2001, AM J BOT, V88, P1600 SANMARTINGAJARDO I, 2003, REV BIOL TROP, V51, P691 SMOUSE PE, 2005, HEREDITY, V94, P640 WARD M, 2005, HEREDITY, V95, P246 WEIS AE, 2004, AM J BOT, V91, P825 WHITE GM, 2002, P NATL ACAD SCI USA, V99, P2038},
url = { |
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| Peyrard, N.; Pellegrin, F.; Chadoeuf, J. & Nandris, D. | Statistical analysis of the spatio-temporal dynamics of rubber tree (Hevea brasiliensis) trunk phloem necrosis: no evidence of pathogen transmission |
2006 | Forest Pathology | Vol. 36 (5) , pp. 360-371 |
||
| Abstract: Trunk phloem necrosis (TPN) of Hevea brasiliensis is an irreversible syndrome of the phloem that spreads from the collar towards the tapping cut. It is responsible for the cessation of latex production, the main constraint in rubber plantations worldwide. Numerous investigations have been undertaken to understand the mechanisms of this disease. The apparent linear spread of TPN supported the initial hypothesis of a biotic causal agent for TPN. However, previous and recent aetiological analyses remained inconclusive and the pathogen hypothesis is tending to be abandoned. In this paper we present a complementary statistical analysis of spatio-temporal epidemiological data collected in a rubber plantation in Cote d'Ivoire. There, four study plots were surveyed each year from 2000 to 2003, with tree-by-tree disease assessment. In two plots, the tapping knife was systematically disinfected with sodium hypochlorite to stop any virus or viroid transmission. Based on permutation tests, our analysis confirmed the aetiological results: there was no evidence for spread by pathogen transmission. However, the spatial structure of the disease was clear. These results strengthen the current alternative scenario of a multi-factor physiological disease caused by an accumulation of exogenous and endogenous stresses. Spatial heterogeneity of the risk factors probably results in the presence of areas of stress that can explain the spatial patterns observed among the TPN cases. The final contribution of this study was confirmation of the curative effect of sodium hypochlorite in the earliest stages of the disease, thus opening the way for control of this disease. | ||||||
BibTeX:
@article{Peyrard2006,
author = {Peyrard, N. and Pellegrin, F. and Chadoeuf, J. and Nandris, D.},
title = {Statistical analysis of the spatio-temporal dynamics of rubber tree (Hevea brasiliensis) trunk phloem necrosis: no evidence of pathogen transmission},
journal = {Forest Pathology},
year = {2006},
volume = {36},
number = {5},
pages = {360-371},
note = {Cited References: BOBILIOFF W, 1919, ARCH VOOR RUBBERCULT, V3, P172 CHRESTIN H, 2004, PLANT DIS, V88, P1047 CLIFF AD, 1981, SPATIAL PROCESS MODE DERRICK KS, 2000, ANNU REV PHYTOPATHOL, V38, P181 KEUCHENIUS PE, 1924, ARCH RUBBER CULT, V8, P803 KOZLOWSKI TT, 1999, SCAND J FOREST RES, V14, P596 LARANJEIRA FF, 1998, FITOPATOL BRAS, V23, P397 MANLY BFJ, 1997, RANDOMIZATION BOOTST MIELKE P, 2001, PERMUTATION METHODS NANDRIS D, 1984, P 75 ANN C RUBB RES, P59 NANDRIS D, 1991, EUR J FOREST PATHOL, V21, P325 NANDRIS D, 1991, EUR J FOREST PATHOL, V21, P340 NANDRIS D, 2004, P INT RUBB RES DEV B, P32 NANDRIS D, 2004, P INT RUBB RES DEV B, P55 NANDRIS D, 2004, PLANT DIS, V88, P1047 PARANJOTHY K, 1977, P RRIM PLANT C, P74 PELLEGRIN F, 2004, PLANT DIS, V88, P1046 PETHYBRIDGE SJ, 2000, PLANT DIS, V84, P513 PEYRARD N, 2005, REV STAT APPL, V53, P59 SOOKMARK U, 2004, P INT RUBB RES DEV B, P66 THEBAUD G, 2004, ACTA HORTIC, V657, P471 THEBAUD G, 2005, PHYTOPATHOLOGY, V95, P1453 VANDELANDE HL, 1993, NETH J PLANT PATHOL, V99, P129 VANDELANDE HL, 1999, PLANT PATHOL, V48, P189 WARE GW, 1989, REV ENV CONTAM TOXIC, V107},
url = { |
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| Picard, N.; Bar-Hen, A.; Mortier, F. & Chadoeuf, J. | Understanding the dynamics of an undisturbed tropical rain forest from the spatial pattern of trees |
2009 | Journal Of Ecology | Vol. 97 (1) , pp. 97-108 |
||
| Abstract: 1. Considering that the spatial pattern of trees is a footprint of the biological processes that drive their dynamics, increasing work has been undertaken to analyse spatial patterns and fit spatial point processes to them. When diameter is taken into account, the underlying point process is a marked point process. The question then is how to correctly model the dependence between the mark and location, and the different patterns at the different scales, to gain understanding of the underlying biological processes. 2. The data used comes from the Paracou rain forest in French Guiana (5 degrees 15' N, 52 degrees 55' W). The spatial pattern of trees in this forest exhibits regularity at small distances (c. 6 m) and clustering at larger distances (c. 30 m). The pattern is linked to diameter, with a shift from clustering to regularity as trees grow. 3. Two models of spatial pattern are used. The first one is pattern-driven in the sense that it breaks down the observed pattern into a mixture of regular, clustered and random contributions. The second one is process-based and uses a simple individual-based space-dependent model of forest dynamics as a simulation algorithm. It is obtained as the limit of this spatio-temporal model when time tends to infinity. 4. Both models are consistent with the observed pattern, with a better fit provided by the second model. Moreover this second model provides a biological interpretation of the observed pattern in terms of forest dynamics. However the first model's implementation is simpler (both for simulation and for parameter estimation). 5. Synthesis. Modelling the spatial pattern of plants using spatial point processes gives insights into the biological processes that drive their dynamics. It allows the reconstruction of their dynamics given only a snapshot of plant locations. Very few solutions exist to model complex marked spatial patterns when point location and mark are dependent. We defined and compared two point processes that successfully modelled the spatial pattern of trees in a rain forest with interaction between tree location and tree size. Both models highlight competition (either symmetric or asymmetric) as a driving process towards regularity. The second model further reveals a self-organizing dynamic with a feedback effect of competition. | ||||||
BibTeX:
@article{Picard2009,
author = {Picard, N. and Bar-Hen, A. and Mortier, F. and Chadoeuf, J.},
title = {Understanding the dynamics of an undisturbed tropical rain forest from the spatial pattern of trees},
journal = {Journal Of Ecology},
year = {2009},
volume = {97},
number = {1},
pages = {97-108},
note = {Cited References: BATISTA JLF, 1998, FOREST ECOL MANAG, V110, P293 BELYEA LR, 2002, J ECOL, V90, P223 BIENG MAN, 2007, THESIS ENGREF PARIS BIGING GS, 1992, FOREST SCI, V38, P695 BUSING RT, 2004, J VEG SCI, V15, P831 CALE WG, 1989, BIOSCIENCE, V39, P600 CAPLAT P, 2008, ECOL MODEL, V211, P491, DOI 10.1016/j.ecolmodel.2007.10.002 CLARK DA, 1984, AM NAT, V124, P769 COLE RG, 1999, J ECOL, V87, P963 COMAS C, 2007, BIOMETRICAL J, V49, P176, DOI 10.1002/bimj.200510268 CRESSIE N, 1993, STAT SPATIAL DATA CUTLER NA, 2008, J ECOL, V96, P231, DOI 10.1111/j.1365-2745.2007.01344.x DESSARD H, 2004, ECOLOGY MANAGEMENT N, P177 DIGGLE PJ, 1983, INT STAT REV, V51, P11 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DRUCKENBROD DL, 2005, J VEG SCI, V16, P37 FIKSEL T, 1984, ELEKTRON INFORMATION, V20, P270 FORD ED, 1981, ANN BOT-LONDON, V48, P481 FORGET PM, 1999, J TROP ECOL 3, V15, P301 FORMAN RTT, 1980, ECOLOGY, V61, P1267 GOREAUD F, 2003, J VEG SCI, V14, P681 GOREAUD F, 2004, P INT SPAT STAT WORK GOULARD M, 1996, SCAND J STAT, V23, P365 GOURLETFLEURY S, 2004, ECOLOGY MANAGEMENT N GREIGSMITH P, 1964, QUANTITATIVE PLANT E GUAN YT, 2006, BIOMETRICS, V62, P126, DOI 10.1111/j.1541-0420.2005.00395.x HANUS ML, 1998, FOREST SCI, V44, P125 HE FL, 2000, J ECOL, V88, P676 HILLERISLAMBERS J, 2002, NATURE, V417, P732 HOGMANDER H, 1999, BIOMETRICS, V55, P1051 ILLIAN J, 2003, STOCHASTIC GEOMETRY, P71 ILLIAN JB, 2006, R200605 AALB U DEP M KOKKILA T, 2002, SILVA FENN, V36, P265 LIU JG, 1995, FOREST ECOL MANAG, V73, P157 LOUSSIER B, 2003, THESIS ECOLE POLYTEC MATEU J, 1998, ECOL MODEL, V108, P163 MOEUR M, 1997, FOREST ECOL MANAG, V94, P175 MOLLER J, 2004, STAT INFERENCE SIMUL NEEFF T, 2005, REV BRASILEIRA CARTO, V57, P1 NELDER JA, 1965, COMPUT J, V7, P308 PARROTT L, 2004, FOREST ECOL MANAG, V194, P29, DOI 10.1016/j.foreco.2004.01.051 PELISSIER R, 1998, J TROP ECOL 1, V14, P1 PENTTINEN A, 1992, FOREST SCI, V38, P806 PENTTINEN A, 2004, SPATIAL POINT PROCES, P193 PICARD N, 2001, ECOL MODEL, V145, P69 PICARD N, 2001, NAT RESOUR MODEL, V14, P147 PICARD N, 2002, ANN FOR SCI, V59, P41 PICARD N, 2008, SCANDINAVIAN J STAT, DOI 10.1111/J.1467-9469.2008.00612.X PIELOU EC, 1960, J ECOL, V48, P575 PIELOU EC, 1969, INTRO MATH ECOLOGY RATHBUN SL, 1994, J AM STAT ASSOC, V89, P1164 RENSHAW E, 2001, COMPUT STAT DATA AN, V36, P85 RENSHAW E, 2007, COMPUT STAT DATA AN, V51, P3123, DOI 10.1016/j.csda.2006.07.035 SCHLATHER M, 2001, BERNOULLI, V7, P99 SCHLATHER M, 2002, MATH NACHR, V239, P204 SCHLATHER M, 2004, J ROY STAT SOC B 1, V66, P79 STERNER RW, 1986, J ECOL, V74, P621 STOLL P, 2005, J ECOL, V93, P395, DOI 10.1111/j.1365-2745.2005.00989.x STOYAN D, 1994, FRACTALS RANDOM SHAP STOYAN D, 2000, STAT SCI, V15, P61 TSCHESCHEL A, 2006, COMPUT STAT DATA AN, V51, P859, DOI 10.1016/j.csda.2005.09.007 TURNBULL LA, 2007, J ECOL, V95, P79, DOI 10.1111/j.1365-2745.2006.01184.x VERZELEN N, 2006, ECOL COMPLEX, V3, P209, DOI 10.1016/j.ecocom.2006.03.001 WEINER J, 2001, AM NAT, V158, P438 WIEGAND T, 2006, J ECOL, V94, P825, DOI 10.1111/j.1365-2745.2006.01113.x},
url = { |
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| Roques, L.; Auger-Rozenberg, M.A. & Roques, A. | Modelling the impact of an invasive insect via reaction-diffusion |
2008 | Mathematical Biosciences | Vol. 216 (1) , pp. 47-55 |
||
| Abstract: An exotic, specialist seed chalcid, Megastigmus schimitscheki, has been introduced along with its cedar host seeds from Turkey to southeastern France during the early 1990s. It is now expanding in plantations of Atlas Cedar (Cedrus atlantica). We propose a model to predict the expansion and impact of this insect. This model couples a time-discrete equation for the ovo-larval stage with a two-dimensional reaction-diffusion equation for the adult stage, through a formula linking the solution of the reaction-diffusion equation to a seed attack rate. Two main diffusion operators, of Fokker-Planck and Fickian types, are tested. We show that taking account of the dependence of the insect mobility with respect to spatial heterogeneity, and choosing the appropriate diffusion operator, are critical factors for obtaining good predictions. (c) 2008 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Roques2008a,
author = {Roques, L. and Auger-Rozenberg, M. A. and Roques, A.},
title = {Modelling the impact of an invasive insect via reaction-diffusion},
journal = {Mathematical Biosciences},
year = {2008},
volume = {216},
number = {1},
pages = {47-55},
note = {Cited References: BERESTYCKI H, 2005, J MATH BIOL, V51, P75, DOI 10.1007/s00285-004-0313-3 BERESTYCKI H, 2005, J MATH PURE APPL, V84, P1101, DOI 10.1016/j.matpur.2004.10.006 BOIVIN S, 2006, THESIS U PARIS 11 CANTRELL RS, 2003, SERIES MATH COMPUTAT FABRE JP, 2004, BIOL INVASIONS, V6, P11 GROSS LJ, 1992, SUMM WORKSH IND BAS, P511 HANNUNEN S, 2001, ENVIRON ENTOMOL, V30, P517 HEDLIN AF, 1980, CONE SEED INSECTS N JARRY M, 1997, CAN ENTOMOL, V129, P7 KAMIJO K, 1962, INSECTA MATSUMURANA, V25, P18 KAREIVA P, 1987, AM NAT, V130, P233 KAREIVA PM, 1983, OECOLOGIA, V56, P234 KINEZAKI N, 2003, THEOR POPUL BIOL, V64, P291, DOI 10.1016/S0040-5809(03)00091-1 KLEIN EK, 2006, BMC ECOL, V6, ARTN 3 LIEBHOLD AM, 1995, FOREST SCI MONOGR, V30, P1 LUIK A, 1999, J APPL ENTOMOL, V123, P561 MARSH LM, 1988, J THEOR BIOL, V133, P113 MOLLISON D, 1977, J ROY STAT SOC B MET, V39, P283 MURRAY JD, 2002, INTERDISCIPLINARY AP, V17 NATHAN R, 2002, SEED DISPERSAL FRUGI, P69 OKUBO A, 2002, DIFFUSION ECOLOGICAL ROQUES A, 1983, INSECTES RAVAGEURS C ROQUES A, 1998, P 5 INT C CON SEED W, P101 ROQUES A, 2003, J NAT HIST, V37, P127, DOI 10.1080/00222930110096069 ROQUES L, 2007, MATH BIOSCI, V210, P34, DOI 10.1016/j.mbs.2007.05.007 SHIGESADA N, 1997, BIOL INVASIONS THEOR SKELLAM JG, 1951, BIOMETRIKA, V38, P196 TURCHIN P, 1998, QUANTITATIVE ANAL MO TURGEON JJ, 1994, ANNU REV ENTOMOL, V39, P179},
url = { |
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| Roques, L. & Chekroun, M.D. | On population resilience to external perturbations [BibTeX] |
2007 | Siam Journal on Applied Mathematics | Vol. 68 (1) , pp. 133-153 |
||
BibTeX:
@article{Roques2007b,
author = {Roques, L. and Chekroun, M. D.},
title = {On population resilience to external perturbations},
journal = {Siam Journal on Applied Mathematics},
year = {2007},
volume = {68},
number = {1},
pages = {133-153},
url = { |
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| Roques, L. & Hamel, F. | Mathematical analysis of the optimal habitat configurations for species persistence [BibTeX] |
2007 | Mathematical Biosciences | Vol. 210 (1) , pp. 34-59 |
||
BibTeX:
@article{Roques2007a,
author = {Roques, L. and Hamel, F.},
title = {Mathematical analysis of the optimal habitat configurations for species persistence},
journal = {Mathematical Biosciences},
year = {2007},
volume = {210},
number = {1},
pages = {34-59},
url = { |
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| Roques, L.; Roques, A.; Berestycki, H. & Kretzschmar, A. | A population facing climate change: joint influences of Allee effects and environmental boundary geometry |
2008 | Population Ecology | Vol. 50 (2) , pp. 215-225 |
||
| Abstract: As a result of climate change, many populations have to modify their range to follow the suitable areas-their "climate envelope"-often risking extinction. During this migration process, they may face absolute boundaries to dispersal because of external environmental factors. Consequently, not only the position, but also the shape of the climate envelope can be modified. We use a reaction-diffusion model to analyse the effects on population persistence of simultaneous changes in the position and shape of the climate envelope. When the growth term is of logistic type, we show that extinction and persistence are principally conditioned by the species mobility and the speed of climate change, but not by the shape of the climate envelope. However, with a growth term taking an Allee effect into account, we find a high sensitivity to variations in the shape of the climate envelope. In this case, the species which have a high mobility, although they could more easily follow the migration of the climate envelope, would be at risk of extinction when encountering a local narrowing of the boundary geometry. This effect can be attenuated by a progressive opening at the exit of the narrowing into the available space, even though this leads temporarily to a diminished area of the climate envelope. | ||||||
BibTeX:
@article{Roques2008,
author = {Roques, L. and Roques, A. and Berestycki, H. and Kretzschmar, A.},
title = {A population facing climate change: joint influences of Allee effects and environmental boundary geometry},
journal = {Population Ecology},
year = {2008},
volume = {50},
number = {2},
pages = {215-225},
note = {Cited References: ALLEE WC, 1938, SOCIAL LIFE ANIMALS AMANN H, 1976, J DIFFER EQUATIONS, V21, P367 ARONSON DG, 1978, ADV MATH, V30, P33 BEREC L, 2007, TRENDS ECOL EVOL, V22, P185, DOI 10.1016/j.tree.2006.12.002 BERESTYCKI H, 1980, J ANAL MATH, V38, P144 BERESTYCKI H, 2005, J MATH BIOL, V51, P75, DOI 10.1007/s00285-004-0313-3 BERESTYCKI H, 2006, CR MATH, V343, P711, DOI 10.1016/j.crma.2006.09.036 BERESTYCKI H, 2008, IN PRESS DISCRET CON CANTRELL RS, 2003, SERIES MATH COMPUTAT CHAPUISAT G, 2005, COMMUN PART DIFF EQ, V30, P1805, DOI 10.1080/03605300500300006 DEASI MN, 2005, THEOR POPUL BIOL, V67, P33 DENNIS B, 1989, NAT RES MODEL, V3, P481 FIFE PC, 1979, ARCH RATIONAL MECH A, V70, P31 FISHER RA, 1937, ANN EUGENIC 4, V7, P355 GROOM MJ, 1998, AM NAT, V151, P487 HILKER FM, 2005, BIOL INVASIONS, V7, P817, DOI 10.1007/s10530-005-5215-9 HURFORD A, 2006, THEOR POPUL BIOL, V70, P244, DOI 10.1016/j.tpb.2006.06.009 JAEGER JAG, 2004, CONSERV BIOL, V18, P1651 KEITT TH, 2001, AM NAT, V157, P203 KING JR, 2003, P ROY SOC LOND A MAT, V459, P2529, DOI 10.1098/rspa.2003.1134 KOLMOGOROV AN, 1937, B MGU A, V1, P1 LEWIS MA, 1993, THEOR POPUL BIOL, V43, P141 LUTSCHER F, 2006, B MATH BIOL, V68, P2129, DOI 10.1007/s11538-006-9100-1 MATANO H, 2006, NETW HETEROG MEDIA, V1, P537 MCCARTHY MA, 1997, ECOL MODEL, V103, P99 OKUBO A, 2002, DIFFUSION ECOLOGICAL OWEN MR, 2001, B MATH BIOL, V63, P655 PACHEPSKY E, 2005, THEOR POPUL BIOL, V67, P61, DOI 10.1016/j.tpb.2004.09.001 PARMESAN C, 2003, NATURE, V421, P37, DOI 10.1038/nature01286 PARMESAN C, 2006, ANNU REV ECOL EVOL S, V37, P637 POTAPOV AB, 2004, B MATH BIOL, V66, P975, DOI 10.1016/j.bulm.2003.10.010 ROBINET C, 2007, GLOBAL ECOL BIOGEOGR, V16, P460 ROBINET C, 2007, OIKOS, V116, P1227, DOI 10.1111/j.2007.0030-1299.15891.x SHI JP, 2006, J MATH BIOL, V52, P807, DOI 10.1007/s00285-006-0373-7 SHIGESADA N, 1997, BIOL INVASIONS THEOR SOLOMON S, 2007, CLIMATE CHANGE 2007 STEPHENS PA, 1999, TRENDS ECOL EVOL, V14, P401 THOMAS CD, 2004, NATURE, V427, P145, DOI 10.1038/nature02121 TOBIN PC, 2007, ECOL LETT, V10, P36, DOI 10.1111/j.1461-0248.2006.00991.x TURCHIN P, 1998, QUANTITATIVE ANAL MO VEIT RR, 1996, AM NAT, V148, P255 WALTHER GR, 2002, NATURE, V416, P389},
url = { |
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| Roques, L. & Stoica, R.S. | Species persistence decreases with habitat fragmentation: an analysis in periodic stochastic environments [BibTeX] |
2007 | Journal of Mathematical Biology | Vol. 55 , pp. 189-205 |
||
BibTeX:
@article{Roques2007,
author = {Roques, L. and Stoica, R. S.},
title = {Species persistence decreases with habitat fragmentation: an analysis in periodic stochastic environments},
journal = {Journal of Mathematical Biology},
year = {2007},
volume = {55},
pages = {189-205}
}
|
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| Ruy, S.; Findeling, A. & Chadoeuf, J. | Effect of mulching techniques on plot scale runoff: FDTF modeling and sensitivity analysis |
2006 | Journal of Hydrology | Vol. 326 (1-4) , pp. 277-294 |
||
| Abstract: Water balance of agricultural field are strongly modified by mulching techniques with crop residues as they act upon the production function (formation of the excess rainfall) and the transfer function (transport of the excess rainfall to the plot outlet). The aim of this paper is to investigate the effect of crop residues on the production and the transfer functions at the plot scale. Previous experiments conducted on runoff plots (20 m(2)) were analyzed using the first differenced transfer function (FDTF) model which is based on the unit hydrograph theory. Four treatments were analyzed: bare soil (T0), no till and no plant with 1.5 t ha(-1) of residue mulch (T1), direct drilling of corn with 1.5 and 4.5 t ha(-1) of residue mulch (T2 and T3, respectively). Hyetographs and runoff hydrographs were collected at a 20 s time step. Transfer functions and implicit production functions were estimated on each plot using an iterative algorithm for the calibration. Then, model precision was tested (i) by stochastic simulations to estimate the local uncertainty due to experimental errors, and (ii) by performing a bootstrap analysis to assess the global uncertainty due to the effect of rainfall event sampling. The calibrated functions were consistent with experimental data: for T0, the large amount of runoff and the small time to peak of the experimental hydrographs was represented by a sharp and narrow transfer function, whereas for T3 the small and delayed amount of runoff was represented by a broader and more spread transfer function. Also, model precision was slightly affected by measurement errors on experimental data, whereas rainfall event sampling generated substantial uncertainties on the transfer functions. The FDTF model proved powerful in analyzing the effect of mulch covers when runoff data is available. The model was able to separate the effect of predicting rainfall excess and the transport of the excess rainfall over the plot. Also, the bootstrap methodology appeared useful to assess uncertainties on model parameters due to rainfall event sampling. (c) 2005 Elsevier B.V. All rights reserved. | ||||||
BibTeX:
@article{Ruy2006,
author = {Ruy, S. and Findeling, A. and Chadoeuf, J.},
title = {Effect of mulching techniques on plot scale runoff: FDTF modeling and sensitivity analysis},
journal = {Journal of Hydrology},
year = {2006},
volume = {326},
number = {1-4},
pages = {277-294},
note = {Cited References: *CAMPB SCI I, 1998, CR10X MEAS CONTR SYS ABRAHAMS AD, 1994, J HYDROL, V156, P431 BRISTOW KL, 1986, AGR FOREST METEOROL, V36, P193 BUSSIERE F, 1994, AGR FOREST METEOROL, V68, P1 DUBAND D, 1993, J HYDROL, V150, P115 EFRON B, 1993, MONOGRAPHS STAT APPL, V57 FIEDLER FR, 1997, THESIS COLORADO STAT FINDELING A, 2000, 25 C EUR GEOPH SOC N FINDELING A, 2001, THESIS ENGREF FINDELING A, 2003, J HYDROL, V275, P49 FINDELING A, 2003, WATER RESOUR RES, V39 GILLEY JE, 1991, J IRRIG DRAIN E-ASCE, V117, P503 GILLEY JE, 1994, J IRRIGATION DRAINAG, V120, P440 GONZALEZSOSA E, 1999, AGR FOR METEOROL, V97, P151 HAAN CT, 1977, STAT METHODS HYDROLO MANLY BFJ, 1997, RANDOMIZATION BOOTST MIELKE PW, 2001, PERMUTATION METHODS NALBANTIS I, 1995, J HYDROL, V168, P127 NASH JE, 1970, J HYDROL, V10, P282 PHILIP JR, 1957, SOIL SCI, V83, P345 POESEN JWA, 1991, SOIL TILL RES, V21, P209 RABINOVICH SG, 2000, MEASUREMENT ERRORS U RAO KPC, 1998, SOIL TILL RES, V48, P51 RODRIGUEZ F, 2005, HYDROL PROCESS, V19, P1021 RUTTER AJ, 1971, AGRICULTURAL METEORO, V9, P367 SAVABI MR, 1994, T ASAE, V37, P1093 SCOPEL E, 1998, WORLD C SOIL SCI MON SEMPERETORRES D, 1992, NAT HAZARDS, V5, P17 SHERMAN LK, 1932, ENG NEWS-REC, V108, P501 TOSTADO JMA, 1996, ETUDE MODELISATION E VALENTIN C, 1992, GEODERMA, V55, P225 VAUCLIN M, 1994, REV SCI EAU, V7, P81 YU B, 2000, HYDROLOG SCI J, V45, P709 ZACHMANN JE, 1989, SOIL SCI SOC AM J, V53, P1846 ZIN I, 2003, EGS AGU EUG JOINT AS, V5},
url = { |
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| Senoussi, R. & Gay, E. Lechverova, R.; Saxl, I. & Benes, V. (Hrsg.) | Assessing spatial clustering via Hellinger distance statistics [BibTeX] |
2006 | Internat. Conf. Stereology, Spatial Statistics, Stochastic Geometry | , pp. 119-130 | ||
BibTeX:
@inproceedings{Senoussi2006,
author = {Senoussi, R. and Gay, E.},
title = {Assessing spatial clustering via Hellinger distance statistics},
booktitle = {Internat. Conf. Stereology, Spatial Statistics, Stochastic Geometry},
publisher = {Union of Czeck Mathematicians and Physicists},
year = {2006},
pages = {119-130}
}
|
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| Soubeyrand, S.; Beaudouin, R.; Desassis, N. & Monod, G. | Model-based estimation of the link between the daily survival probability and a time-varying covariate, application to mosquitofish survival data |
2007 | Mathematical Biosciences | Vol. 210 (2) , pp. 508-522 |
||
| Abstract: The survival probability in a group of individuals may evolve in time due to the influence of a time-varying covariate. In this paper we present a model-based approach allowing the estimation of the functional link between the survival probability and a time-varying covariate when data are grouped and time-period censored. The approach is based on an underlying model consisting in non-stationary Markov processes and describing the survival of individuals. The underlying model is aggregated in time and at the group level to handle the group structure of data and the censoring. The aggregation yields a generalized non-linear mixed model. Then, a Bayesian procedure allows the estimation of the model parameters and the description of the link between the survival probability and the time-varying covariate This approach is applied in order to explore the relationship between the daily survival probability of mosquitofish (Gambusia holbrooki) and their time-varying lengths (small mosquitofish die with a higher rate than large ones because they are more affected by predation, cannibalism and environmental stress). (C) 2007 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Soubeyrand2007d,
author = {Soubeyrand, S. and Beaudouin, R. and Desassis, N. and Monod, G.},
title = {Model-based estimation of the link between the daily survival probability and a time-varying covariate, application to mosquitofish survival data},
journal = {Mathematical Biosciences},
year = {2007},
volume = {210},
number = {2},
pages = {508-522},
note = {Cited References: BOTSFORD LW, 1987, ENVIRON BIOL FISH, V20, P143 BOXSTEFFENSMEIE.JM, 2004, EVENT HIST MODELING BROOKS SP, 2002, J ROY STAT SOC B 4, V64, P616 BROWN CR, 2004, BEHAV ECOL SOCIOBIOL, V56, P498, DOI 10.1007/s00265-004-0813-6 CABRAL JA, 2001, ECOL ENG, V16, P537 CHALITA LVAS, 2006, COMMUN STAT-SIMUL C, V35, P975, DOI 10.1080/03610910600880450 DAVIDIAN M, 1995, NONLINEAR MODELS REP DINSMORE SJ, 2002, ECOLOGY, V83, P3476 DOYLE CJ, 2005, ECOTOX ENVIRON SAFE, V61, P392, DOI 10.1016/j.ecoenv.2004.10.012 DREZE V, 2000, ECOTOXICOLOGY, V9, P93 EFRON B, 1993, INTRO BOOTSTRAP GINOT V, 2006, ECOL MODEL, V193, P479, DOI 10.1016/j.ecolmodel.2005.08.025 KOOPERBERG C, 1997, BIOMETRICS, V53, P1485 MCCULLOCH CE, 2001, GEN LINEAR MIXED MOD MULVEY M, 1995, ENVIRON TOXICOL CHEM, V14, P1411 ROBERT CP, 1999, MONTE CARLO STAT MET ROTELLA JJ, 2004, ANIMAL BIODIVERSITY, V27, P187 RUPPERT D, 2003, SEMIPARAMETRIC REGRE SCHWARTZ CC, 2006, WILDLIFE MONOGR, V161, P25 SHAFFER TL, 2004, AUK, V121, P526 SPARLING YH, 2006, BIOSTATISTICS, V7, P599, DOI 10.1093/biostatistics/kxj028 SPIEGELHALTER DJ, 2002, J ROY STAT SOC B 4, V64, P583 STEPHENS SE, 2003, THESIS MONTANA STATE TOFT G, 2003, ENVIRON HEALTH PERSP, V111, P695, DOI 10.1289/eph.6022 VONESH EF, 1997, LINEAR NONLINEAR MOD WAINRIGHT TW, 1984, P CALIF MOSQUIT VEC, V52, P110 WEI GCG, 1990, J AM STAT ASSOC, V85, P699 YIP PSF, 2005, AM J EPIDEMIOL, V161, P700, DOI 10.1093/aje/kwi088 YIP PSF, 2005, J ROY STAT SOC A S 1, V168, P233},
url = { |
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| Soubeyrand, S. & Chadoeuf, J. | Residual-based specification of a hidden random field included in a hierarchical spatial model [BibTeX] |
2007 | Computational Statistics & Data Analysis | Vol. 51 , pp. 6402-6422 |
||
BibTeX:
@article{Soubeyrand2007c,
author = {Soubeyrand, S. and Chadoeuf, J.},
title = {Residual-based specification of a hidden random field included in a hierarchical spatial model},
journal = {Computational Statistics & Data Analysis},
year = {2007},
volume = {51},
pages = {6402-6422}
}
|
||||||
| Soubeyrand, S.; Chadoeuf, J.; Sache, I. & Lannou, C. | Residual-based specification of the random-effects distribution for cluster data [BibTeX] |
2006 | Statistical Methodology | Vol. 3 (4) , pp. 464-482 |
||
BibTeX:
@article{Soubeyrand2006,
author = {Soubeyrand, S. and Chadoeuf, J. and Sache, I. and Lannou, C.},
title = {Residual-based specification of the random-effects distribution for cluster data},
journal = {Statistical Methodology},
year = {2006},
volume = {3},
number = {4},
pages = {464-482},
url = {doi: 10.1016/j.stamet.2005.12.005}
}
|
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| Soubeyrand, S.; Enjalbert, J.; Kretzschmar, A. & Sache, I. | Building anisotropic sampling schemes for the estimation of anisotropic dispersal |
2009 | Annals of Applied Biology | Vol. 154 (3) , pp. 399-411 |
||
| Abstract: Anisotropy, a structural property of dispersal, is observed in dispersal patterns occurring for a wide range of biological systems. While dispersal models more and more often incorporate anisotropy, the sampling schemes required to collect data for validation usually do not account for the anisotropy of dispersal data. Using a parametric model already published to describe the spatial spread of a plant disease, the wheat yellow rust, we carry out a study aimed at recommending an appropriate sampling scheme for anisotropic data. In a first step, we show with a simulation study that prior knowledge of dispersal anisotropy can be used to improve the sampling scheme. One of the main guidelines to be proposed is the orientation of the sampling grid around the main dispersal directions. In a second step, we propose a sequential sampling procedure (SSP) used to automatically build anisotropic sampling schemes adapted to the actual anisotropy of dispersal. The SSP is applied to simulated and real data. The proposed methodology is expected to be adapted easily to any kind of organisms with wind-borne propagule dispersal because it does not require the inclusion of biological features specific of the considered organism. | ||||||
BibTeX:
@article{Soubeyrand2009b,
author = {Soubeyrand, S. and Enjalbert, J. and Kretzschmar, A. and Sache, I.},
title = {Building anisotropic sampling schemes for the estimation of anisotropic dispersal},
journal = {Annals of Applied Biology},
year = {2009},
volume = {154},
number = {3},
pages = {399-411},
note = {Times Cited: 0},
url = { |
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| Soubeyrand, S.; Enjalbert, J. & Sache, I. | Accounting for roughness of circular processes: Using Gaussian random processes to model the anisotropic spread of airborne plant disease |
2008 | Theoretical Population Biology | Vol. 73 (1) , pp. 92-103 |
||
| Abstract: Variables with values in the circle or indexed by the circle have been studied in order to investigate questions in ecology, epidemiology, climatology and oceanography for example. To model circular variables with rough behaviors, the use of Gaussian random processes (GRPs) can be particularly convenient as will be seen in this paper. The roughness of a GRP being mainly determined by its correlation function, a circular correlation function convenient for rough processes is proposed. These mathematical tools are applied to describe the anisotropic spread of an airborne plant disease from a point source: a hierarchical model including two circular GRPs is built and used to analyze data coming from a field experiment. This random-effect model is fitted to data using a Monte-Carlo expectation-maximization (MCEM) algorithm. (C) 2007 Elsevier Inc. All rights reserved. | ||||||
BibTeX:
@article{Soubeyrand2008a,
author = {Soubeyrand, S. and Enjalbert, J. and Sache, I.},
title = {Accounting for roughness of circular processes: Using Gaussian random processes to model the anisotropic spread of airborne plant disease},
journal = {Theoretical Population Biology},
year = {2008},
volume = {73},
number = {1},
pages = {92-103},
note = {Cited References: AGRIOS GN, 2005, PLANT PATHOLOGY ARNOLD BC, 2006, ENVIRON ECOL STAT, V13, P253, DOI 10.1007/s10651-006-0009-5 AYLOR DE, 1990, ANNU REV PHYTOPATHOL, V28, P73 AYLOR DE, 1999, AGR FOREST METEOROL, V97, P275 AYLOR DE, 2001, J APPL METEOROL, V40, P1196 BICOUT DJ, 2003, PHYS REV E, V67, DOI 10.1103/PHYSREVE.67.031913 BURNHAM KP, 2002, MODEL SELECTION MULT CHADOEUF J, 2004, TEST NONPARAMETRIQUE CHRISTENSEN OF, 2004, J COMPUT GRAPH STAT, V13, P702, DOI 10.1198/106186004X2525 COCHRAN WO, 1998, P GRAPH INT 98, P65 DESASSIS N, 2005, GEOSTATISTICS ENV AP, P125 KLEIN EK, 2003, ECOL MONOGR, V73, P131 PESQUETPOPESCU B, 2002, IEEE SIGNAL PROC MAG, V19, P48 ROHANI P, 2002, AM NAT, V159, P469 STEIN ML, 2005, J ROY STAT SOC B 5, V67, P667 STOCKMARR A, 2002, J MATH BIOL, V45, P461, DOI 10.1007/s002850200157 TUFTO J, 1997, THEOR POPUL BIOL, V52, P16 WEI GCG, 1990, J AM STAT ASSOC, V85, P699 WILSON JD, 2000, J APPL METEOROL, V39, P1894 ZHANG H, 2002, BIOMETRICS, V58, P129},
url = { |
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| Soubeyrand, S.; Enjalbert, J.; Sanchez, A. & Sache, I. | Anisotropy, in density and in distance, of the dispersal of yellow rust of wheat: Experiments in large field plots and estimation [BibTeX] |
2007 | Phytopathology | Vol. 97 , pp. 1315-1324 |
||
BibTeX:
@article{Soubeyrand2007b,
author = {Soubeyrand, S. and Enjalbert, J. and Sanchez, A. and Sache, I.},
title = {Anisotropy, in density and in distance, of the dispersal of yellow rust of wheat: Experiments in large field plots and estimation},
journal = {Phytopathology},
year = {2007},
volume = {97},
pages = {1315-1324}
}
|
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| Soubeyrand, S.; Held, L.; Hohle, M. & Sache, I. | Modelling the spread in space and time of an airborne plant disease |
2008 | Journal of the Royal Statistical Society Series C | Vol. 57 , pp. 253-272 |
||
| Abstract: A spatiotemporal model is developed to analyse epidemics of airborne plant diseases which are spread by spores. The observations consist of measurements of the severity of disease at different times, different locations in the horizontal plane and different heights in the vegetal cover. The model describes the joint distribution of the occurrence and the severity of the disease. The three-dimensional dispersal of spores is modelled by combining a horizontal and a vertical dispersal function. Maximum likelihood combined with a parametric bootstrap is suggested to estimate the model parameters and the uncertainty that is attached to them. The spatiotemporal model is used to analyse a yellow rust epidemic in a wheatfield. In the analysis we pay particular attention to the selection and the estimation of the dispersal functions. | ||||||
BibTeX:
@article{Soubeyrand2008,
author = {Soubeyrand, S. and Held, L. and Hohle, M. and Sache, I.},
title = {Modelling the spread in space and time of an airborne plant disease},
journal = {Journal of the Royal Statistical Society Series C},
year = {2008},
volume = {57},
pages = {253-272},
note = {Cited References: AYLOR DE, 1990, ANNU REV PHYTOPATHOL, V28, P73 BERGER RD, 1997, PHYTOPATHOLOGY, V87, P1005 BROERS LHM, 1997, EUPHYTICA, V96, P215 BROWN JKM, 2002, SCIENCE, V297, P537 CAMPBELL CL, 1990, INTRO PLANT DIS EPID CHADOEUF J, 1992, BIOMETRICS, V48, P1165 CHANDLER RE, 2006, STAT METHODS SPATIOT, P177 DEVALLAVIEILLEP.C, 2000, PHYTOMA DEFENSE VEGE, V527, P22 DIGGLE AJ, 2002, PHYTOPATHOLOGY, V92, P1110 DJURLE A, 1991, AGR SYST, V37, P193 EFRON B, 1993, INTRO BOOTSTRAP EMGE RG, 1975, PHYTOPATHOLOGY, V65, P679 FERRANDINO FJ, 1993, PHYTOPATHOLOGY, V83, P795 FILIPE JAN, 2004, J THEOR BIOL, V226, P125, DOI 10.1016/S0022-5193(03)00278-9 FITT BDL, 1987, J PHYTOPATHOL, V118, P227 FRANTZEN J, 2000, BASIC APPL ECOL, V1, P83 GIBSON GJ, 1997, APPL STAT-J ROY ST C, V46, P215 GIBSON GJ, 1997, PHYTOPATHOLOGY, V87, P139 KIRKPATRICK S, 1983, SCIENCE, V220, P671 KLEIN EK, 2003, ECOL MONOGR, V73, P131 KOIZUMI S, 1991, RICE BLAST MODELLING, P75 LETT C, 2000, ACTA PHYTPATH ENTOMO, V35, P287 LOVELL DJ, 1997, PLANT PATHOL, V46, P126 MCCARTNEY HA, 1998, EPIDEMIOLOGY PLANT D, P138 MCCULLAGH P, 1989, SPATIAL COMPONENTS P, P127 MINOGUE KP, 1983, PHYTOPATHOLOGY, V73, P1168 MINOGUE KP, 1989, SPATIAL COMPONENTS P, P127 MOLLISON D, 1977, J ROY STAT SOC B MET, V39, P283 NELDER JA, 1965, COMPUT J, V7, P308 OTTEN W, 2003, ECOLOGY, V84, P3232 RAPILLY F, 1991, EPIDEMIOLOGIE PATHOL RIGBY RA, 2005, J ROY STAT SOC C-A 3, V54, P507 SACHE I, 1993, J PHYTOPATHOL, V138, P55 SACKETT KE, 2005, PHYTOPATHOLOGY, V95, P983, DOI 10.1094/PHYTO-95-0983 SACKETT KE, 2005, PHYTOPATHOLOGY, V95, P992, DOI 10.1094/PHYTO-95.0992 SCHERMESSER N, 1996, THESIS ECOLE NATL SU SHAW MW, 1994, ANNU REV PHYTOPATHOL, V32, P523 SHAW MW, 1995, P ROY SOC LOND B BIO, V259, P243 SHRUM, 1975, 347 PENNS STAT U COL STASINOPOULOS DM, 2006, INSTRUCTIONS HOW USE STOCKMARR A, 2002, J MATH BIOL, V45, P461, DOI 10.1007/s002850200157 TOMERLIN JR, 1988, PLANT DIS, V72, P455 TUFTO J, 1997, THEOR POPUL BIOL, V52, P16 VANDENBOSCH F, 1988, PHYTOPATHOLOGY, V78, P54 XU XM, 1998, PHYTOPATHOLOGY, V88, P1000 ZADOKS JC, 1977, ANN NY ACAD SCI, V287, P164 ZAWOLEK MW, 1992, PHYTOPATHOLOGY, V82, P1288 Part 3},
url = { |
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| Soubeyrand, S.; Laine, A.L.; Hanski, I. & Penttinen, A. | Spatiotemporal Structure of Host-Pathogen Interactions in a Metapopulation |
2009 | American Naturalist | Vol. 174 (3) , pp. 308-320 |
||
| Abstract: The ecological and evolutionary dynamics of species are influenced by spatiotemporal variation in population size. Unfortunately, we are usually limited in our ability to investigate the numerical dynamics of natural populations across large spatial scales and over long periods of time. Here we combine mechanistic and statistical approaches to reconstruct continuous-time infection dynamics of an obligate fungal pathogen on the basis of discrete-time occurrence data. The pathogen, Podosphaera plantaginis, infects its host plant, Plantago lanceolata, in a metapopulation setting where the presence of the pathogen has been recorded annually for 6 years in similar to 4,000 host populations across an area of 50 km x 70 km in Finland. The dynamics are driven by strong seasonality, with a high extinction rate during winter and epidemic expansion in summer for local pathogen populations. We are able to identify with our model the regions in the study area where overwintering has been most successful. These overwintering sites represent foci that initiate local epidemics during the growing season. There is striking heterogeneity at the regional scale in both the overwintering success of the pathogen and the encounter intensity between the host and the pathogen. Such heterogeneity has profound implications for the coevolutionary dynamics of the interaction. | ||||||
BibTeX:
@article{Soubeyrand2009a,
author = {Soubeyrand, S. and Laine, A. L. and Hanski, I. and Penttinen, A.},
title = {Spatiotemporal Structure of Host-Pathogen Interactions in a Metapopulation},
journal = {American Naturalist},
year = {2009},
volume = {174},
number = {3},
pages = {308-320},
note = {Times Cited: 0},
url = { |
||||||
| Soubeyrand, S.; Neuvonen, S. & Penttinen, A. | Mechanical-Statistical Modeling in Ecology: From Outbreak Detections to Pest Dynamics |
2009 | Bulletin Of Mathematical Biology | Vol. 71 (2) , pp. 318-338 |
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| Abstract: Knowledge about large-scale and long-term dynamics of (natural) populations is required to assess the efficiency of control strategies, the potential for long-term persistence, and the adaptability to global changes such as habitat fragmentation and global warming. For most natural populations, such as pest populations, large-scale and long-term surveys cannot be carried out at a high resolution. For instance, for population dynamics characterized by irregular abundance explosions, i.e., outbreaks, it is common to report detected outbreaks rather than measuring the population density at every location and time event. Here, we propose a mechanical-statistical model for analyzing such outbreak occurrence data and making inference about population dynamics. This spatio-temporal model contains the main mechanisms of the dynamics and describes the observation process. This construction enables us to account for the discrepancy between the phenomenon scale and the sampling scale. We propose the Bayesian method to estimate model parameters, pest densities and hidden factors, i.e., variables involved in the dynamics but not observed. The model was specified and used to learn about the dynamics of the European pine sawfly (Neodiprion sertifer Geoffr., an insect causing major defoliation of pines in northern Europe) based on Finnish sawfly data covering the years 1961-1990. In this application, a dynamical Beverton-Holt model including a hidden regime variable was incorporated into the model to deal with large variations in the population densities. Our results gave support to the idea that pine sawfly dynamics should be studied as metapopulations with alternative equilibria. The results confirmed the importance of extreme minimum winter temperatures for the occurrence of European pine sawfly outbreaks. The strong positive connection between the ratio of lake area over total area and outbreaks was quantified for the first time. | ||||||
BibTeX:
@article{Soubeyrand2009,
author = {Soubeyrand, S. and Neuvonen, S. and Penttinen, A.},
title = {Mechanical-Statistical Modeling in Ecology: From Outbreak Detections to Pest Dynamics},
journal = {Bulletin Of Mathematical Biology},
year = {2009},
volume = {71},
number = {2},
pages = {318-338},
note = {Cited References: AUSTARA O, 1971, NORSK ENT TIDSSKR, V18, P45 BERLINER LM, 2003, J GEOPHYS RES-ATMOS, V108 BUCKLAND ST, 2004, ECOL MODEL, V171, P157, DOI 10.1016/j.ecolmodel.2003.08.002 CAMPBELL EP, 2004, 49 CSIRO MATH INF SC CHILES JP, 1999, GEOSTATISTICS MODELI DUNGAN JL, 2002, ECOGRAPHY, V25, P626 DWYER G, 2004, NATURE, V430, P341, DOI 10.1038/nature02569 GERITZ SAH, 2004, J THEOR BIOL, V228, P261, DOI 10.1016/j.jtbi.2004.01.003 GRIMM V, 2005, SCIENCE, V310, P987, DOI 10.1126/science.1116681 HANSKI I, 1987, OIKOS, V50, P327 HANSKI I, 1990, POPULATION DYNAMICS, P253 IGLESIAS O, 2002, J APPL PHYS, V91, P4409 JUUTINEN P, 1967, COMMUN I FOREST FENN, V63, P1 JUUTINEN P, 1986, FOLIA FOR, V662, P1 LARSSON S, 1979, OECOLOGIA, V43, P157 LARSSON S, 1984, HOLARCTIC ECOL, V7, P81 LARSSON S, 2000, OIKOS, V89, P440 NEUVONEN S, 1990, OECOLOGIA, V83, P209 RIVOT E, 2004, ECOL MODEL, V179, P463, DOI 10.1016/j.ecolmodel.2004.05.011 ROBERT CP, 1999, MONTE CARLO STAT MET SAIKKONEN K, 1993, SAWFLY LIFE HIST ADA, P431 SAIKKONEN K, 1995, OIKOS, V74, P173 SOUBEYRAND S, 2007, J R SOC INTERFACE, V4, P985, DOI 10.1098/rsif.2007.1154 VANDIJK D, 1999, MACROECON DYN, V3, P311 VIRTANEN T, 1996, SILVA FENNICA, V30, P169 VIRTANEN T, 1998, J APPL ECOL, V35, P311 WEI GCG, 1990, J AM STAT ASSOC, V85, P699 WIEGAND T, 2003, OIKOS, V100, P209 WIKLE CK, 2003, ECOLOGY, V84, P1382 WIKLE CK, 2003, INT STAT REV, V71, P181 WIKLE CK, 2005, TECHNOMETRICS, V47, P80, DOI 10.1198/004017004000000572 WU W, 2005, CHEM PHYS LETT, V402, P519, DOI 10.1016/j.cplett.2004.12.080},
url = { |
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| Soubeyrand, S.; Sache, I.; Lannou, C. & Chadoeuf, J. | A frailty model to assess plant disease spread from individual count data [BibTeX] |
2007 | Journal of Data Science | Vol. 5 (1) , pp. 67-83 |
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BibTeX:
@article{Soubeyrand2007a,
author = {Soubeyrand, S. and Sache, I. and Lannou, C. and Chadoeuf, J.},
title = {A frailty model to assess plant disease spread from individual count data},
journal = {Journal of Data Science},
year = {2007},
volume = {5},
number = {1},
pages = {67-83}
}
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| Soubeyrand, S.; Thebaud, G. & Chadoeuf, J. | Accounting for biological variability and sampling scale: a multi-scale approach to building epidemic models [BibTeX] |
2007 | Journal of the Royal Society Interface | Vol. 4 , pp. 985-997 |
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BibTeX:
@article{Soubeyrand2007,
author = {Soubeyrand, S. and Thebaud, G. and Chadoeuf, J.},
title = {Accounting for biological variability and sampling scale: a multi-scale approach to building epidemic models},
journal = {Journal of the Royal Society Interface},
year = {2007},
volume = {4},
pages = {985-997}
}
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| Stoica, R.S.; Gay, E. & Kretzschmar, A. | Cluster pattern detection in spatial data based on Monte-Carlo inference [BibTeX] |
2007 | Biometrical Journal | Vol. 49 (4) , pp. 505-519 |
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BibTeX:
@article{Stoica2007,
author = {Stoica, R. S. and Gay, E. and Kretzschmar, A.},
title = {Cluster pattern detection in spatial data based on Monte-Carlo inference},
journal = {Biometrical Journal},
year = {2007},
volume = {49},
number = {4},
pages = {505-519}
}
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| Thebaud, G.; Dallot, S.; Labonne, G.; Peyrard, N.; Chadoeuf, J. & Calonnec, A. | Testing the spatial association of disease patterns between two dates in orchards |
2008 | XXth Internat. Symp. Virus Diseases Of Temperate Fruit Crops | (781) , pp. 255-260 | ||
| Abstract: The analysis of spatiotemporal patterns can provide clues about disease spread by assessing if the spatial pattern of diseased plants at one date is associated with the pattern of previously diseased plants. No generic statistical test was available to answer this question for spatiotemporal maps of binary data (healthy or diseased plants) in regular plantings (e.g., orchards). Here we describe a Monte Carlo test of the hypothesis that the location of newly diseased plants is independent of the location of previously diseased plants, even when the disease is spatially aggregated within each assessment period. This spatiotemporal test is designed to cope with the censorship arising on a lattice when plants are missing or cannot recover between the two dates. Expected patterns are simulated by shifting on a torus the whole pattern at the second date relatively to the pattern at the first date. For each simulation, we discard the censored points from observed and simulated data. In case of a positive association between disease patterns at two dates, the distances between newly and previously diseased trees should be smaller in the observed than in the simulated patterns. As an illustration, we analysed the dependence between patterns of trees showing Plum pox virus symptoms at two dates. | ||||||
BibTeX:
@article{Thebaud2008,
author = {Thebaud, G. and Dallot, S. and Labonne, G. and Peyrard, N. and Chadoeuf, J. and Calonnec, A.},
title = {Testing the spatial association of disease patterns between two dates in orchards},
journal = {XXth Internat. Symp. Virus Diseases Of Temperate Fruit Crops},
year = {2008},
number = {781},
pages = {255-260},
note = {Times Cited: 0 0567-7572},
url = { |
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| Thebaud, G.; Sauvion, N.; Chadoeuf, J.; Dufils, A. & Labonne, G. | Identifying risk factors for European stone fruit yellows from a survey |
2006 | Phytopathology | Vol. 96 (8) , pp. 890-899 |
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| Abstract: European stone fruit yellows (ESFY) is becoming a major economic problem for Prunus growers in Europe. The causal agent ("Candidatus Phytoplasma prunorum") and its vector (Cacopsylla pruni) have been identified, but the present knowledge of the risk factors for this disease relies, at best, on specific experiments. To assess the relative significance of several factors correlated with ESFY incidence in the field, an exhaustive survey was performed on apricot and Japanese plum orchards in the Crau plain (France). After a preliminary multivariate exploration of the data, we used a logistic regression model to analyze and predict the cumulative number of diseased trees on the basis of a set of quantitative (age, planting density, and area of the orchard) and categorical variables (species, cultivar, and rootstock). Because of the nature of the data, we used an overdispersed binomial model and we developed a parametric bootstrap procedure based on the beta-binomial distribution to obtain confidence intervals. Our results indicated that the age, species, and cultivar of the scion were the major factors explaining the observed number of diseased trees. The planting density and the rootstocks used in the zone under study were less significant, and the area of the orchard had no effect. The residuals of the model showed that some explanatory variables had not been taken into account, because part of the remaining variability could be explained by a grower effect. The spatial distribution of the residuals suggested that one of the reasons for this grower effect was the correlation between orchards closer than 100 m, possibly caused by the flight behavior of infectious vectors. | ||||||
BibTeX:
@article{Thebaud2006,
author = {Thebaud, G. and Sauvion, N. and Chadoeuf, J. and Dufils, A. and Labonne, G.},
title = {Identifying risk factors for European stone fruit yellows from a survey},
journal = {Phytopathology},
year = {2006},
volume = {96},
number = {8},
pages = {890-899},
note = {Cited References: *R DEV COR TEAM, 2004, R LANG ENV STAT COMP AEGERTER BJ, 2003, PLANT DIS, V87, P732 BURT C, 1950, BRIT J PSYCHOL, V3, P166 CARRARO L, 1992, ACTA HORTIC, V309, P285 CARRARO L, 2001, EUR J PLANT PATHOL, V107, P695 CARRARO L, 2002, PLANT PATHOL, V51, P513 CARRARO L, 2004, ACTA HORTIC, V657, P449 CHABROLIN C, 1924, ANN EPIPHYT, V10, P263 COLLETT D, 1991, MODELLING BINARY DAT COOK RD, 1982, RESIDUALS INFLUENCE CROWDER MJ, 1978, APPLIED STATISTICS, V27, P34 DALLOT S, 2003, PHYTOPATHOLOGY, V93, P1543 DALLOT S, 2004, PHYTOPATHOLOGY, V94, P1390 DEWOLF ED, 2003, PHYTOPATHOLOGY, V93, P428 DIGGLE PJ, 1983, STAT ANAL SPATIAL PO DUVAL H, 1999, ARBO FRUIT, V524, P35 DUVAL H, 1999, PHYTOMA, V516, P38 EFRON B, 1993, INTRO BOOTSTRAP GARRETT KA, 2004, PHYTOPATHOLOGY, V94, P999 GOIDANICH G, 1933, B R STAZ PAT VEG ROM, V13, P160 GOTTWALD TR, 2002, PHYTOPATHOLOGY, V92, P361 HAMEL C, 2005, PHYTOPATHOLOGY, V95, P867 HILL MO, 1976, TAXON, V25, P249 HOTELLING H, 1933, J EDUC PSYCHOL, V24, P417 HUGHES G, 1993, PHYTOPATHOLOGY, V83, P759 HUGHES G, 1995, PLANT PATHOL, V44, P927 JARAUSCH W, 1999, ADV HORTICULTURAL SC, V13, P108 JARAUSCH W, 2000, J PHYTOPATHOL, V148, P489 KISON H, 2001, J PHYTOPATHOL, V149, P533 LABONNE G, 2004, ACTA HORTIC, V657, P465 LEMAIRE JM, 1998, ARBORICULTURE FRUITI, V520, P21 LINDSEY JK, 1999, J ROY STAT SOC C-A 4, V48, P553 LORENZ KH, 1994, Z PFLANZENK PFLANZEN, V101, P567 MANLY BFJ, 1991, RANDOMIZATION MONTE MATHERON G, 1965, VARIABLES REGIONALIS MCCULLAGH P, 1989, GEN LINEAR MODELS MILA AL, 2004, PHYTOPATHOLOGY, V94, P102 MORVAN G, 1977, EPPO B, V7, P37 NICOT PC, 1987, PHYTOPATHOLOGY, V77, P1346 RIBEIRO PJJ, 2003, 3 INT WORKSH DISTR S ROSSO PH, 2003, PHYTOPATHOLOGY, V93, P790 SEEMULLER E, 2004, INT J SYST EVOL MI 4, V54, P1217 SHTIENBERG D, 1996, PHYTOPATHOLOGY, V86, P123 THEBAUD G, 2004, ACTA HORTIC, V657, P471 THEBAUD G, 2005, PHYTOPATHOLOGY, V95, P1453 THIOULOUSE J, 1997, STAT COMPUT, V7, P75 WELHAM SJ, 2004, PLANT PATHOL, V53, P713 WILLIAMS DA, 1982, APPL STAT, V31, P144},
url = { |
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| Vieublé Gonod, L.; Chadoeuf, J. & Chenu, C. | Spatial distribution of microbial 2,4-dichlorophenoxy-acetic acid (2,4-D) mineralization from fields to microhabitat scales [BibTeX] |
2006 | Soil Science Society of America Journal | Vol. 70 (64-71) |
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BibTeX:
@article{VieubleGonod2006,
author = {Vieublé Gonod, L. and Chadoeuf, J. and Chenu, C.},
title = {Spatial distribution of microbial 2,4-dichlorophenoxy-acetic acid (2,4-D) mineralization from fields to microhabitat scales},
journal = {Soil Science Society of America Journal},
year = {2006},
volume = {70},
number = {64-71}
}
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