Search results for "611"

showing 10 items of 259 documents

The (de)politicisation of nuclear power: The Finnish discussion after Fukushima

2017

When the Fukushima accident occurred in March 2011, Finland was at the height of a nuclear renaissance, with the Government’s decision-in-principle in 2010 to allow construction of two new nuclear reactors. This article examines the nuclear power debate in Finland after Fukushima. We deploy the concepts of (de)politicisation and hyperpoliticisation in the analysis of articles in the country’s main newspaper. Our analysis indicates that Finnish nuclear exceptionalism manifested in the safety-related depoliticising and the nation’s prosperity-related hyperpoliticisation arguments of the pro-nuclear camp. The anti-nuclear camp used politicisation strategies, such as economic arguments, to sho…

010504 meteorology & atmospheric sciencesParliamentmedia_common.quotation_subject010501 environmental sciences01 natural sciencesnuclear power debateNewspaperArts and Humanities (miscellaneous)Political scienceDevelopmental and Educational Psychologyta517Fukushima Nuclear Accidentta518FukushimaNuclear energy policyta611Finland0105 earth and related environmental sciencesmedia_commonGovernmentbusiness.industryCommunicationPoliticsNuclear renaissanceNuclear power(de)politicisationNuclear power debateExceptionalismEconomyNuclear Power PlantsPublic Opinionta5141businessPublic Understanding of Science
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Accounting for preferential sampling in species distribution models

2019

D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…

0106 biological sciencesComputer scienceQH301 BiologySpecies distributionPoint processesStochastic partial differential equation01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_6774EspèceAbundance (ecology)StatisticsPesqueríasQAOriginal Researchhttp://aims.fao.org/aos/agrovoc/c_241990303 health sciencesEcologyU10 - Informatique mathématiques et statistiquesSampling (statistics)Integrated nested Laplace approximationstochastic partial differential equationVariable (computer science)symbolsÉchantillonnageSpecies Distribution Models (SDMs)Modèle mathématiqueBayesian probabilityNDASDistribution des populations010603 evolutionary biologyQH30103 medical and health sciencessymbols.namesakeCovariateQA MathematicsSDG 14 - Life Below WaterCentro Oceanográfico de Murciaspecies distribution modelsRelative species abundanceEcology Evolution Behavior and Systematicspoint processes030304 developmental biologyNature and Landscape Conservationhttp://aims.fao.org/aos/agrovoc/c_6113http://aims.fao.org/aos/agrovoc/c_7280Markov chain Monte Carlointegrated nested Laplace approximationU30 - Méthodes de rechercheBayesian modelling
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New national and regional Annex I Habitat records: from #21 to #25

2021

New Italian data on the distribution of the Annex I Habitats 3170*, 6110*, 91E0*, 9320, 9330 are reported in this contribution. Specifically, one new occurrence in Natura 2000 sites is presented and six new cells are added in the European Environment Agency 10 km × 10 km reference grid. The new data refer to the Italian administrative regions of Sardinia, Sicily and Umbria.

0106 biological sciencesEcologyconservationPlant cultureForestryPlant Science93309320010603 evolutionary biology01 natural sciences3170* 6110* 91E0* 9320 9330 92/43/EEC Directive conservation EEA vegetationSB1-1110vegetation92/43/EEC DirectiveSettore BIO/03 - Botanica Ambientale E Applicata91E0*3170*6110*QK900-989Plant ecologyEEAEcology Evolution Behavior and Systematics010606 plant biology & botanyPlant Sociology
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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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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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Transcriptome analysis revealed that a quorum sensing system regulates the transfer of the pAt megaplasmid in Agrobacterium tumefaciens.

2016

Background Agrobacterium tumefaciens strain P4 is atypical, as the strain is not pathogenic and produces a for this species unusual quorum sensing signal, identified as N-(3-hydroxy-octanoyl)-homoserine lactone (3OH,C8-HSL). Results By sequence analysis and cloning, a functional luxI-like gene, named cinI, has been identified on the At plasmid of A. tumefaciens strain P4. Insertion mutagenesis in the cinI gene and transcriptome analyses permitted the identification of 32 cinI-regulated genes in this strain, most of them encoding proteins responsible for the conjugative transfer of pAtP4. Among these genes were the avhB genes that encode a type 4 secretion system (T4SS) involved in the forma…

0301 basic medicineacylhomoserime lactoneIdentification[SDV]Life Sciences [q-bio]AgrobacteriumPlasmidePlant Rootsfluids and secretionsPlasmidSolanum lycopersicumhttp://aims.fao.org/aos/agrovoc/c_16014Expression des gènesDynamique des populationsCloning MolecularPhylogenyGeneticsbiology000 - Autres thèmeshttp://aims.fao.org/aos/agrovoc/c_27583food and beveragesAgrobacterium tumefaciensLactonehttp://aims.fao.org/aos/agrovoc/c_768[SDV] Life Sciences [q-bio]Quorum sensingT4SSConjugation GeneticPropriété biologiquehttp://aims.fao.org/aos/agrovoc/c_35128PlasmidsResearch Articlehttp://aims.fao.org/aos/agrovoc/c_4145BiotechnologyDtr systemSéquence nucléotidiqueAgrobacteriumSequence analysisMutagenesis (molecular biology technique)At plasmid03 medical and health scienceshttp://aims.fao.org/aos/agrovoc/c_4891Bacterial Proteinsstomatognathic systemhttp://aims.fao.org/aos/agrovoc/c_3081Geneticshttp://aims.fao.org/aos/agrovoc/c_1501Acylhomoserine lactoneTranscriptomicsGenehttp://aims.fao.org/aos/agrovoc/c_6111H20 - Maladies des plantesCloning[ SDV ] Life Sciences [q-bio]Bactériologiehttp://aims.fao.org/aos/agrovoc/c_27444Sequence Analysis RNATranscription géniqueConjugationGene Expression ProfilingBiologie moléculaireGene Expression Regulation Bacterialbiochemical phenomena metabolism and nutritionQuorum sensing;Agrobacterïum;At plasmid;transcriptomics;conjugation;T4SS;Dtr system;Acylhomoserine lactonebiology.organism_classificationhttp://aims.fao.org/aos/agrovoc/c_27527Quorum sensinghttp://aims.fao.org/aos/agrovoc/c_3791030104 developmental biologyAgrobacterium tumefaciensbacteriaGenetic Fitness
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Empiricism and Relationism Intertwined: Hume and Einstein’s Special Theory of Relativity

2016

Einstein acknowledged that his reading of Hume influenced the development of his special theory of relativity. In this article, I juxtapose Hume’s philosophy with Einstein’s philosophical analysis related to his special relativity. I argue that there are two common points to be found in their writings, namely an empiricist theory of ideas and concepts, and a relationist ontology regarding space and time. The main thesis of this article is that these two points are intertwined in Hume and Einstein.

060106 history of social sciencesTheory of FormsSpace and timeSpecial relativity0603 philosophy ethics and religionsymbols.namesakeTheory of relativityHistory and Philosophy of ScienceStatic interpretation of timeHistory of special relativity0601 history and archaeologyEinsteinta611SpacetimePhilosophy06 humanities and the artsEpistemologyDavidPhilosophyPhilosophical analysis060302 philosophysymbolsEinstein AlbertEinsteinHumeAlbertEmpiricismHume DavidTHEORIA. An International Journal for Theory, History and Foundations of Science
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New national and regional Annex I Habitat records: from #60 to #82

2023

New Italian data on the distribution of the Annex I Habitats are reported in this contribution. Specifically, 8 new occurrences in Natura 2000 sites are presented and 49 new cells are added in the EEA 10 km × 10 km reference grid. The new data refer to the Italian administrative regions of Campania, Calabria, Marche, Piedmont, Sardinia, Sicily, Tuscany and Umbria. Relevés and figures are provided as Supplementary material respectively 1 and 2.

2250*1240 1310 1420 2250* 3130 3220 3260 3270 3280 4090 6110* 6430 7210* 8210 91AA* 91B0 91E0* 92A0 92D0 933091AA*92D01310142091B03270328032607210*933031308210124032206430Settore BIO/03 - Botanica Ambientale E Applicata409091E0*6110*92A0
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