Search results for "VOC"

showing 10 items of 1905 documents

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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Response to: The metabolic cost of whistling is low but measurable in dolphins

2020

Costs of sound production have been investigated only sparsely in cetaceans, despite recent efforts to understand how increasing anthropogenic noise affects these animals that rely extensively on sound for communication and foraging. Theoretical estimates suggest that metabolic costs of whistling

0106 biological sciencesSound SpectrographyPhysiology030310 physiologyAcousticsForagingSingingAquatic ScienceSound production010603 evolutionary biology01 natural sciences03 medical and health sciencesAnimalsMolecular BiologyEcology Evolution Behavior and SystematicsSound (geography)0303 health sciencesgeographygeography.geographical_feature_categoryMetabolic costBottle-Nosed DolphinNoiseInsect ScienceEnvironmental scienceAnimal Science and ZoologyVocalization AnimalJournal of Experimental Biology
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Impact of the invasive painted bug, Bagrada hilaris on physiological traits of its host Brassica oleracea var botrytis

2017

Bagrada hilaris is a herbivorous insect native of Asia and Africa, which has invaded southern Europe and North America where it causes major damage to cole crops. Laboratory experiments were conducted to assess how the infestation of this invasive species damages the host Brassica oleracea var botrytis, and to evaluate the interaction between plant emission of volatile organic compounds (VOC) and B. hilaris adults. Plant responses to insect feeding were evaluated through changes in photosynthesis, stomatal conductance, VOC emission, and visual damage on leaves. The impact of B. hilaris was compared with that of Nezara viridula, a polyphagous species distributed worldwide. Plant VOC role in …

0106 biological sciencesStomatal conductanceNonanalVisual damageStomatal conductancemedicine.disease_cause01 natural sciencesElectroantennographyBagrada hilaris; Electroantennography (EAG); Nezara viridula; Photosynthesis; Stomatal conductance; Visual damage; Volatile organic compounds (VOC); Ecology Evolution Behavior and Systematics; Ecology; Agronomy and Crop Science; Insect Sciencechemistry.chemical_compoundPhotosynthesiBagrada hilariVolatile organic compounds (VOC)InfestationBotanymedicinePhotosynthesisEcology Evolution Behavior and SystematicsHerbivoreBagrada hilarisElectroantennography (EAG)EcologybiologyHost (biology)fungiNezara viridulabiology.organism_classificationEcology Evolution Behavior and SystematicBagrada hilaris010602 entomologySettore AGR/11 - Entomologia Generale E ApplicatachemistryNezara viridulaInsect ScienceAgronomy and Crop Science010606 plant biology & botany
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Humusica 1, article 1: Essential bases – Vocabulary

2018

International audience; The Special Issue Humusica 1 corresponds to a field guide for the classification of terrestrial humus systems and forms. The present first article of the issue defines vocabulary, objects and concepts necessary for: (a) field investigation, (b) understanding the process of classification, (c) assigning ecological significance to the defined morpho-functional units, (d) discussing and exchanging scientific data about humus systems. The article starts with general considerations, as the necessity humans have to classify natural objects for sharing ideas and information on them. Then the article focuses on soil as functional element of every ecosystem. Historical and re…

0106 biological sciencesVocabularyComputer scienceProcess (engineering)media_common.quotation_subjectSoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study010603 evolutionary biology01 natural sciencesHumusHumus Humusica Humus form classification Humus system Humus vocabulary Soil classification Soil conceptSoil concept ABSTRACT[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsSoil classificationSoil conceptNatural (music)Humus vocabularymedia_common2. Zero hungerHumus form classificationTopsoilEcologyEcology04 agricultural and veterinary sciences15. Life on landAgricultural and Biological Sciences (miscellaneous)HumusField (geography)EpistemologyVariety (cybernetics)040103 agronomy & agricultureHumusica0401 agriculture forestry and fisheriesSoil horizon[SDE.BE]Environmental Sciences/Biodiversity and EcologyHumus system
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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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