Search results for "AOS"

showing 10 items of 330 documents

Paysandisia archon: Taxonomy, distribution, biology and life cycle

2017

The taxonomic position of the family Castniidae within the order Lepidoptera has changed over time. Initially, it was classified in the superfamily Sesioidea, and then it was grouped in a large assemblage including the Cossoidea, Sesioidea, and Zygaenoidea. Recent studies have included it in the superfamily Cossoidea. In Europe, the palm borer moth (PBM) Paysandisia archon is the only species of the Castniidae. This moth, native to South America (Argentina and Uruguay), was first reported in Europe (France and Spain) in 2001, but it is believed to have been introduced before 1995 on palm trees imported from Argentina. Since then, the moth has been reported in Belgium, Bulgaria, Cyprus Islan…

0106 biological sciencesIdentificationPlante hôteDistribution géographiquePaysandisia archonCossoideahttp://aims.fao.org/aos/agrovoc/c_25231http://aims.fao.org/aos/agrovoc/c_15807SesioideaIntroduced speciesArecaceaeArecaceaeCastniidae010603 evolutionary biology01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_8812Biologie animalehttp://aims.fao.org/aos/agrovoc/c_5083http://aims.fao.org/aos/agrovoc/c_4317http://aims.fao.org/aos/agrovoc/c_4698Palm borer Phoenix morphologyhttp://aims.fao.org/aos/agrovoc/c_11621Physiologie du développementbiologyEcologyTaxonomiebiology.organism_classificationH10 - Ravageurs des plantesPupaLepidoptera010602 entomologyhttp://aims.fao.org/aos/agrovoc/c_3791Settore AGR/11 - Entomologia Generale E ApplicataCycle de développementhttp://aims.fao.org/aos/agrovoc/c_29176http://aims.fao.org/aos/agrovoc/c_4268Zygaenoideahttp://aims.fao.org/aos/agrovoc/c_7631
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Bayesian spatio-temporal approach to identifying fish nurseries by validating persistence areas

2015

Spatial and temporal closures of fish nursery areas to fishing have recently been recognized as useful tools for efficient fisheries management, as they preserve the reproductive potential of populations and increase the recruitment of target species. In order to identify and locate potential nursery areas for spatio-temporal closures, a solid understanding of species− environment relationships is needed, as well as spatial identification of fish nurseries through the application of robust analyses. One way to achieve knowledge of fish nurseries is to analyse the persistence of recruitment hotspots. In this study, we propose the comparison of different spatiotemporal model structures to ass…

0106 biological sciencesMediterranean climatehttp://aims.fao.org/aos/agrovoc/c_28840[SDV]Life Sciences [q-bio]01 natural sciencesMediterranean seaAbundance (ecology)Ecosystem approachEcologybiologyEcologyU10 - Informatique mathématiques et statistiquesinteraction élevage environnementmodèle de distributionMerluccius merlucciushttp://aims.fao.org/aos/agrovoc/c_41529zone de pêcheNursery areasSpatio temporal analysisanalyse bayésienneGeographyGestion des pêchesgestion spatialealevinageFisheries managementFishinganalyse spatiotemporellegestion des ressources naturellesAquatic Science010603 evolutionary biologyhttp://aims.fao.org/aos/agrovoc/c_24026étude comparativeHakeMerluccius merluccius14. Life underwaterhttp://aims.fao.org/aos/agrovoc/c_4699Ecology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_12399Distribution patternapproche ecosystémiqueÉcologie marinehttp://aims.fao.org/aos/agrovoc/c_4609010604 marine biology & hydrobiologybiology.organism_classificationBiologie marineFisheryThéorie bayésiennehttp://aims.fao.org/aos/agrovoc/c_9000115M40 - Écologie aquatiqueBayesian hierarchical modellingMarine protected areaSpatial fisheries managementNursery areas;Distribution pattern;Ecosystem approach;Spatial fisheries management;Spatio temporal analysis;Bayesian hierarchical modelling;Merluccius merluccius
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New polymorphic microsatellite loci in the house sparrow, Passer domesticus.

2009

3 pages; International audience; We developed 13 new polymorphic microsatellite loci in the house sparrow (Passer domesticus), which exhibited from 2 to 15 alleles. Observed and expected heterozygosities ranged from 0.17 to 0.77 and from 0.35 to 0.85, respectively. We detected no linkage disequilibrium between loci. Allele frequencies supported Hardy–Weinberg equilibrium for 8 loci out of 13 after Bonferroni correction. Combined with loci previously isolated in the house sparrow, these new microsatellite markers provide valuable tools to study population genetics of this species.

0106 biological sciencesPasserLinkage disequilibriummicrosatellite010603 evolutionary biology01 natural sciences03 medical and health sciencesbiology.animalhttp://aims.fao.org/aos/agrovoc/c_3081GeneticsAlleleAllele frequencypasserineMoineauEcology Evolution Behavior and Systematics030304 developmental biologyGenetics0303 health sciencesSparrowbiologyhouse sparrowpasserine.[ SDV.GEN.GA ] Life Sciences [q-bio]/Genetics/Animal geneticsL10 - Génétique et amélioration des animauxbiology.organism_classificationPasserine[SDV.GEN.GA]Life Sciences [q-bio]/Genetics/Animal geneticsEvolutionary biologyMicrosatellitePopulation studyL20 - Écologie animalehttp://aims.fao.org/aos/agrovoc/c_7275Passerhttp://aims.fao.org/aos/agrovoc/c_1153Biotechnology
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Bayesian spatio-temporal discard model in a demersal trawl fishery

2014

Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel eff…

0106 biological sciencesPerteSpatial correlationhttp://aims.fao.org/aos/agrovoc/c_28840Computer scienceProcess (engineering)Bayesian probabilitySede Central IEOAquatic ScienceOceanography01 natural sciencesRessource halieutiquehttp://aims.fao.org/aos/agrovoc/c_2173Abundance (ecology)Component (UML)http://aims.fao.org/aos/agrovoc/c_4438Pesquerías14. Life underwaterM11 - Production de la pêchehttp://aims.fao.org/aos/agrovoc/c_7881Ecology Evolution Behavior and SystematicsChalutageU10 - Informatique mathématiques et statistiques010604 marine biology & hydrobiologyhttp://aims.fao.org/aos/agrovoc/c_2801204 agricultural and veterinary sciencesDiscardsFisheryRessource marineVariable (computer science)Théorie bayésienneM40 - Écologie aquatique040102 fisheries0401 agriculture forestry and fisherieshttp://aims.fao.org/aos/agrovoc/c_2942Fisheries managementPêche démersale
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Long-term mineral fertiliser use and maize residue incorporation do not compensate for carbon and nutrient losses from a Ferralsol under continuous m…

2015

9 pages; International audience; It has been repeatedly argued that mineral fertiliser application combined with in situ retention of crop residue biomass can sustain long-term productivity of West African soils. Using 20-year experimental data from southern Togo, a biannual rainfall area, we analysed the effect of two rates of mineral NPK fertiliser application to maize–cotton rotation on the long-term dynamics of soil C and nutrient contents, as compared with two control treatments. Mineral fertiliser treatments consisted of application to both maize (first season) and cotton (second season) the research-recommended NPK rates (Fertiliser-RR) and 1.5 times these rates (Fertiliser-1.5 RR). …

0106 biological sciencesRésidu de récolteCrop residueRotation culturalehttp://aims.fao.org/aos/agrovoc/c_27870[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomySoil fertility management01 natural sciencesSoil managementCrop rotationF01 - Culture des plantesSoil pHhttp://aims.fao.org/aos/agrovoc/c_10795http://aims.fao.org/aos/agrovoc/c_356572. Zero hungerSub-Saharan Africahttp://aims.fao.org/aos/agrovoc/c_166http://aims.fao.org/aos/agrovoc/c_718204 agricultural and veterinary sciencesPE&RCTillageRendement des cultureshttp://aims.fao.org/aos/agrovoc/c_8504http://aims.fao.org/aos/agrovoc/c_3335P33 - Chimie et physique du solCarbonehttp://aims.fao.org/aos/agrovoc/c_7170[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil studySoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyZea maysFertilisationMatière organique du solhttp://aims.fao.org/aos/agrovoc/c_10176[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/AgronomyFertilité du solhttp://aims.fao.org/aos/agrovoc/c_7801Propriété physicochimique du solhttp://aims.fao.org/aos/agrovoc/c_1301http://aims.fao.org/aos/agrovoc/c_16118GossypiumP35 - Fertilité du solSowingFarm Systems Ecology Group15. Life on landCrop rotationAgronomySoil water040103 agronomy & agricultureEngrais minéral0401 agriculture forestry and fisheriesEnvironmental scienceSoil fertilityAgronomy and Crop Sciencehttp://aims.fao.org/aos/agrovoc/c_6662F04 - Fertilisation010606 plant biology & botanyField Crops Research
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The plasma membrane oxidase NtrbohD is responsible for AOS production in elicited tobacco cells

2002

Summary A cDNA encoding a protein, NtrbohD, located on the plasma membrane and homologue to the flavocytochrome of the neutrophil NADPH oxidase, was cloned in tobacco. The corresponding mRNA was accumulated when tobacco leaves and cells were treated with the fungal elicitor cryptogein. After elicitation with cryptogein, tobacco cells transformed with antisense constructs of NtrbohD showed the same extracellular alkalinization as the control, but no longer produced active oxygen species (AOS). This work represents the first demonstration of the function of a homologue of gp91–phox in AOS production in elicited tobacco cells.

0106 biological sciencesTime FactorsNicotiana tabacumMolecular Sequence DataPlant ScienceBiologyGenes Plant01 natural sciencesFungal Proteins[SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics03 medical and health sciences[SDV.GEN.GPL] Life Sciences [q-bio]/Genetics/Plants geneticsComplementary DNATobaccoGene expressionGeneticsExtracellularAOSAmino Acid SequenceRNA MessengerCells CulturedComputingMilieux_MISCELLANEOUS030304 developmental biology0303 health sciencesOxidase testNADPH oxidaseGene Expression ProfilingAlgal ProteinsCell MembraneHydrogen PeroxideCell BiologyHydrogen-Ion ConcentrationPlants Genetically Modifiedbiology.organism_classification3. Good healthElicitorCell biologyPlant LeavesProtein TransportBiochemistryCell culturebiology.proteinOxidoreductasesReactive Oxygen Species010606 plant biology & botany
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Pseudomonas salomonii sp. nov., pathogenic on garlic, and Pseudomonas palleroniara sp. nov., isolated from rice

2002

International audience; A total of 26 strains, including 15 strains isolated from garlic plants with the typical symptoms of 'Café au lait' disease and 11 strains isolated from diseased or healthy rice seeds and sheaths infested by Pseudomonas fuscovaginae, were compared with 70 type or reference strains of oxidase-positive pathogenic or non-pathogenic fluorescent pseudomonads. The strains were characterized by using a polyphasic taxonomic approach. Numerical taxonomy of phenotypic characteristics showed that the garlic and rice strains were related to each other. However, they clustered into separate phenons, distinct from those of the other strains tested, and were different in several nu…

0106 biological sciences[SDV.SA]Life Sciences [q-bio]/Agricultural sciencesIdentificationADNPhénotype01 natural sciencesphenotypic characteristicsPseudomonas fuscovaginaeRNA Ribosomal 16SPhylogeny2. Zero hungerBase Composition0303 health sciencesbiologyPhylogenetic treeDNA–DNA hybridizationfood and beveragesGeneral MedicinePseudomonas palleronianaRNA BacterialPhenotypehttp://aims.fao.org/aos/agrovoc/c_5435Pseudomonas palleronianaPseudomonas salomoniiAllium sativumhttp://aims.fao.org/aos/agrovoc/c_290DNA Bacterialhttp://aims.fao.org/aos/agrovoc/c_27578Pseudomonas salomoniiPhenotypic characteristicMolecular Sequence DataDNA Ribosomal010603 evolutionary biologyMicrobiologyMicrobiologyNumerical taxonomy03 medical and health sciencesTerminology as TopicPseudomonaspolyphasic taxonomyGarlicGeneEcology Evolution Behavior and SystematicsH20 - Maladies des plantes030304 developmental biologyDNA-DNA hybridizationHybridation moléculaireSettore AGR/12 - Patologia VegetaleOryzaTaxonomie16S ribosomal RNAbiology.organism_classificationhttp://aims.fao.org/aos/agrovoc/c_3791http://aims.fao.org/aos/agrovoc/c_6304http://aims.fao.org/aos/agrovoc/c_5776Genes Bacterialhttp://aims.fao.org/aos/agrovoc/c_2347http://aims.fao.org/aos/agrovoc/c_7631
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Vegetation structure and greenness in Central Africa from Modis multi-temporal data.

2013

African forests within the Congo Basin are generally mapped at regional scale as broad-leaved evergreen forests, with a main distinction between terra-firme and swamp forests types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organisation and theirs relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28568Time Factors010504 meteorology & atmospheric sciencesDatabases FactualRainEcological Parameter Monitoringhttp://aims.fao.org/aos/agrovoc/c_900018001 natural sciencesTrees[ SDE ] Environmental Sciencesremote sensinghttp://aims.fao.org/aos/agrovoc/c_3062K01 - Foresterie - Considérations généralesDynamique des populationsForêt tropicale humidehttp://aims.fao.org/aos/agrovoc/c_6498http://aims.fao.org/aos/agrovoc/c_29008geography.geographical_feature_categoryCentral AfricaEcologyInventaire forestierVegetationArticlesClassificationSpatial heterogeneity[ SDE.MCG ] Environmental Sciences/Global ChangesDeciduoushttp://aims.fao.org/aos/agrovoc/c_7976CongoP31 - Levés et cartographie des solsForêt[SDE]Environmental SciencesSeasonshttp://aims.fao.org/aos/agrovoc/c_1432General Agricultural and Biological Scienceshttp://aims.fao.org/aos/agrovoc/c_34911Research ArticleF40 - Écologie végétaleTélédétectionClimate Change[SDE.MCG]Environmental Sciences/Global ChangesSpectroscopie infrarougeContext (language use)69Typologie010603 evolutionary biologySwampGeneral Biochemistry Genetics and Molecular BiologyCarbon Cycle[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentHumansAfrica Centralhttp://aims.fao.org/aos/agrovoc/c_1666http://aims.fao.org/aos/agrovoc/c_1344http://aims.fao.org/aos/agrovoc/c_8176[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmenthttp://aims.fao.org/aos/agrovoc/c_6111Ecosystem0105 earth and related environmental sciencesChangement climatiquegeographyCartographiehttp://aims.fao.org/aos/agrovoc/c_24174Enhanced vegetation index15. Life on landEvergreenVégétationStructure du peuplement13. Climate actionCouvert forestierPhysical geographyU30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_1653tropical rainforestTropical rainforest
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Fishery-dependent and -independent data lead to consistent estimations of essential habitats

2016

AbstractSpecies mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Es…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28840Biodiversité et Ecologiehabitatmodélisation spatialehttp://aims.fao.org/aos/agrovoc/c_38371OceanographyGaleus melastomus01 natural sciencesRessource halieutiquehttp://aims.fao.org/aos/agrovoc/c_38127Scyliorhinus caniculamodèle hiérarchiqueSpatial statisticsEcologymodèle de distributionSampling (statistics)Contrast (statistics)Cross-validationModélisation et simulationGeographyHabitatGestion des pêchesModeling and Simulationhttp://aims.fao.org/aos/agrovoc/c_10566http://aims.fao.org/aos/agrovoc/c_3456http://aims.fao.org/aos/agrovoc/c_38117survey designMarine conservationSpecies Distribution ModelsEcology (disciplines)Bayesian probabilityEtmopterus spinaxenquête statistiqueDonnée sur les pêchesmodèle spatiotemporelSede Central IEOContext (language use)Aquatic ScienceDistribution des populationsBayesian hierarchical models010603 evolutionary biologyhttp://aims.fao.org/aos/agrovoc/c_24026elasmobranchsBiodiversity and Ecologyélasmobrancheétude comparativeBayesian hierarchical models;Cross-validation;Species Distribution Models;Spatial statistics;INLA;elasmobranchs ; survey designINLA14. Life underwaterspecies distribution modelsEcology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_6113collecte des donnéesÉcologie marinehttp://aims.fao.org/aos/agrovoc/c_29788http://aims.fao.org/aos/agrovoc/c_4609010604 marine biology & hydrobiologyGestion et conservation des pêchescross validation[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulationmodèle bayésienFisheryM01 - Pêche et aquaculture - Considérations généraleshttp://aims.fao.org/aos/agrovoc/c_2a75d27eThéorie bayésienneM40 - Écologie aquatiqueSpatial ecologyhttp://aims.fao.org/aos/agrovoc/c_2942[SDE.BE]Environmental Sciences/Biodiversity and Ecologyvalidation croiséeElasmobranchii
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Modelling sensitive elasmobranchs habitat

2013

Basic information on the distribution and habitat preferences of ecologically important species is essential for their management and protection. In the Mediterranean Sea there is increasing concern over elasmobranch species because their biological (ecological) characteristics make them highly vulnerable to fishing pressure. Their removal could affect the structure and function of marine ecosystems, inducing changes in trophic interactions at the community level due to the selective elimination of predators or prey species, competitors and species replacement. In this study Bayesian hierarchical spatial models are used to map the sensitive habitats of the three most caught elasmobranch spe…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28840Etmopterus spinaxhabitatAquatic ScienceDistribution des populationshttp://aims.fao.org/aos/agrovoc/c_38371OceanographyGaleus melastomus010603 evolutionary biology01 natural sciencesElasmobranch habitatPredationMediterranean seahttp://aims.fao.org/aos/agrovoc/c_38127http://aims.fao.org/aos/agrovoc/c_3041Scyliorhinus caniculaMediterranean SeaVulnerable speciesMarine ecosystem14. Life underwaterhttp://aims.fao.org/aos/agrovoc/c_4699Ecology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_12399Trophic levelhttp://aims.fao.org/aos/agrovoc/c_6113biologyEcologyU10 - Informatique mathématiques et statistiques010604 marine biology & hydrobiologyScyliorhinus caniculabiology.organism_classificationBiologie marinetechnique de prévisionBayesian hierarchical spatial modelSpecies distribution modelingFisheryHabitatThéorie bayésienneGaleus melastomusM40 - Écologie aquatiquehttp://aims.fao.org/aos/agrovoc/c_10566http://aims.fao.org/aos/agrovoc/c_3456http://aims.fao.org/aos/agrovoc/c_38117Elasmobranchii
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