Search results for "Modeling"

showing 10 items of 4489 documents

Corrigendum to “Soil fungal community composition does not alter along a latitudinal gradient through the maritime and sub-Antarctic” Fungal Ecology …

2012

0106 biological sciencesEcologyFungal ecologyEcologyEcological ModelingEnvironmental ethicsPlant ScienceBiologySub antarctic010603 evolutionary biology01 natural sciencesCommunity compositionEcology Evolution Behavior and Systematics010606 plant biology & botanyFungal Ecology
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Combining molecular microbial ecology with ecophysiology and plant genetics for a better understanding of plant-microbial communities' interactions i…

2013

18 pages; International audience

0106 biological sciencesEcophysiologyquantitative geneticsecophysiologyPlant genetics[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil studyBiology[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study01 natural sciences03 medical and health sciencesplant–microbes interactionsMicrobial ecologyBotany[ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/SymbiosisComputingMilieux_MISCELLANEOUS030304 developmental biology2. Zero hunger0303 health sciencesRhizosphere[ SDE.BE ] Environmental Sciences/Biodiversity and EcologyEcologymodelingQuantitative geneticsMicrobial population biology[SDE.BE]Environmental Sciences/Biodiversity and Ecologymicrobial communityrhizosphere010606 plant biology & botany[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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Behavior of mixed Chlorophyceae cultures under prolonged dark exposure. Respiration rate modeling

2016

[EN] The behavior of three different microalgal cultures, when exposed for a long period (>48 h) to dark conditions, was studied with a methodology based on respirometry. The cultures were transferred to darkness and the oxygen evolution in the reactors was monitored after successive air injections. Several sequential oxygen uptake rates were thus calculated and a respiration constant, assuming a first order decay of a fraction of the biomass, was obtained by calibration. Initial specific oxygen uptake rates were in the range of 0.9 5.1 mg O2 g TSS−1 h−1 and dark respiration constants in the range of 0.005 0.018 h−1.

0106 biological sciencesEnvironmental EngineeringChlorophyceae010501 environmental sciencesManagement Monitoring Policy and Law01 natural sciencesRespirometry010608 biotechnologyLong periodBotanyRespirationMicroalgaeTECNOLOGIA DEL MEDIO AMBIENTE0105 earth and related environmental sciencesNature and Landscape ConservationbiologyRespirationModelingOxygen evolutionDecaybiology.organism_classificationOxygen uptakeEnvironmental chemistryDarknessRespiration rateEcological Engineering
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Fragmentation-related patterns of genetic differentiation in pedunculate oak (<i>Quercus robur</i>) at two hierarchical scales

2016

Populations at species’ range margins are expected to show lower genetic diversity than populations at the core of the range. Yet, long-lived, widespread tree species are expected to be resistant to genetic impoverishment, thus showing comparatively high genetic diversity within populations and low differentiation among populations. Here, we study the distribution of genetic variation in the pedunculate oak ( L.) at its range margin in Finland at two hierarchical scales using 15 microsatellite loci. At a regional scale, we compared variation within versus among three oak populations. At a landscape scale, we examined genetic structuring within one of these populations, growing on an islan…

0106 biological sciencesFragmentation (reproduction)education.field_of_studyGenetic diversityEcologyRange (biology)Ecological ModelingPopulationForestry15. Life on landBiologybiology.organism_classification010603 evolutionary biology01 natural sciencesQuercus roburHabitatGenetic variationMicrosatelliteeducation010606 plant biology & botanySilva Fennica
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Ecology, Phylogeny, and Potential Nutritional and Medicinal Value of a Rare White “Maitake” Collected in a Mediterranean Forest

2020

Albino Grifola frondosa (Dicks.) Gray &ldquo

0106 biological sciencesGrifola frondosabioprospectingBiology01 natural sciences03 medical and health sciencesDry weightStaphylococcus epidermidisBotanypolypore fungupolypore fungusMediterranean forestInternal transcribed spacer<i>Grifola frondosa</i>lcsh:QH301-705.5Ribosomal DNAGrifola frondosa030304 developmental biologyNature and Landscape Conservation0303 health sciencesMushroomEcologySettore BIO/02 - Botanica SistematicaEcological Modeling<i>Quercus pubescens</i>ITS rDNAbiology.organism_classificationGrifolaAgricultural and Biological Sciences (miscellaneous)medicinal mushroomfungal diversityphylogeneticslcsh:Biology (General)Quercus pubescensSettore BIO/03 - Botanica Ambientale E ApplicataBasidiocarpphylogenetic010606 plant biology & botanybasidiomyceteDiversity
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Coupling agent-based with equation-based models to study spatially explicit megapopulation dynamics

2018

International audience; The incorporation of the spatial heterogeneity of real landscapes into population dynamics remains extremely difficult. We propose combining equation-based modelling (EBM) and agent-based modelling (ABM) to overcome the difficulties classically encountered. ABM facilitates the description of entities that act according to specific rules evolving on various scales. However, a large number of entities may lead to computational difficulties (e.g., for populations of small mammals, such as voles, that can exceed millions of individuals). Here, EBM handles age-structured population growth, and ABM represents the spreading of voles on large scales. Simulations applied to t…

0106 biological sciencesHybrid modellingTheoretical computer scienceComputer sciencePopulation[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]010603 evolutionary biology01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]Travelling waveArvicolaPopulation growtheducation[SDV.EE]Life Sciences [q-bio]/Ecology environmenteducation.field_of_studySpatial contextual awareness010604 marine biology & hydrobiologyEcological ModelingDispersal15. Life on land[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationSpatial heterogeneityCoupling (computer programming)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Biological dispersalMontane ecology[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC][SDE.BE]Environmental Sciences/Biodiversity and EcologyHybrid modelHybrid modelEcological Modelling
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Inferring individual fate from aquatic acoustic telemetry data

2020

13 pages, 8 figures, 1 table.-- This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

0106 biological sciencesInformation retrievalSurvivalComputer science010604 marine biology & hydrobiologyEcological ModelingFateNatural mortalityPredationDispersalVDP::Matematikk og Naturvitenskap: 400Creative commonsFishing mortality010603 evolutionary biology01 natural sciencesTelemetryTable (database)Acoustic telemetry14. Life underwaterLicenseFish behaviourEcology Evolution Behavior and Systematics
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Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks

2019

Abstract The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of an…

0106 biological sciencesMarine conservationMaximum sustainable yieldFish stockFish school010603 evolutionary biology01 natural sciencesAcoustic surveyEnvironmental dataAnchovymedia_common.cataloged_instanceEuropean unionEcology Evolution Behavior and Systematicsmedia_commonEcologybiologySettore INF/01 - Informaticabusiness.industry010604 marine biology & hydrobiologyApplied MathematicsEcological ModelingEnvironmental resource managementPelagic zonebiology.organism_classificationClassificationComputer Science ApplicationsGeographyComputational Theory and MathematicsFishing industryModeling and SimulationbusinessNeural networks
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Predicting marine species distributions: complementarity of food-web and Bayesian hierarchical modelling approaches

2019

16 pages, 9 figures, 3 tables, 1 appendix

0106 biological sciencesMarine conservationSpecies distributionBayesian inference010603 evolutionary biology01 natural sciencesMediterranean SeaSpatial ecology14. Life underwaterCentro Oceanográfico de MurciaPesqueríasSpecies distribution modelsCommercial speciesSpatial planningEcospacebiologyEcology010604 marine biology & hydrobiologyEcological ModelingMerluccius merluccius15. Life on landbiology.organism_classificationEnvironmental niche modellingHabitatFood-web modelBayesian modelSpatial ecologyEnvironmental science
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Fungal Diversity in the Mediterranean Area

2020

The Special Issue entitled “Fungal Diversity in the Mediterranean Area” aimed at highlighting the role of various organisms in the Mediterranean habitat. The role of fungi at the root and phyllosphere level; the biodiversity in small island territories and the sea; rare forms of fungi never previously found; the commercial, food, and therapeutic value of some ascomycetes and basidiomycetes; the diversity related to fungi associated with galls on plants; and the important role of culture collection for the ex situ conservation of fungal biodiversity are the topics dealt with in this Special Issue.

0106 biological sciencesMediterranean climateBiodiversitybioprospectingmycorrhizaBiology010603 evolutionary biology01 natural sciencesMediterranean forestlcsh:QH301-705.5Marine fungiNature and Landscape ConservationBioprospectingGenetic diversityEcologyEcology010604 marine biology & hydrobiologyEcological Modelingmarine fungifungiEx situ conservationAgricultural and Biological Sciences (miscellaneous)medicinal mushroomfungal diversityHabitatlcsh:Biology (General)PhyllosphereDiversity
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