Search results for "Statistics"

showing 10 items of 7671 documents

Can Deliberately Incomplete Gene Sample Augmentation Improve a Phylogeny Estimate for the Advanced Moths and Butterflies (Hexapoda: Lepidoptera)?

2011

Abstract This paper addresses the question of whether one can economically improve the robustness of a molecular phylogeny estimate by increasing gene sampling in only a subset of taxa, without having the analysis invalidated by artifacts arising from large blocks of missing data. Our case study stems from an ongoing effort to resolve poorly understood deeper relationships in the large clade Ditrysia ( > 150,000 species) of the insect order Lepidoptera (butterflies and moths). Seeking to remedy the overall weak support for deeper divergences in an initial study based on five nuclear genes (6.6 kb) in 123 exemplars, we nearly tripled the total gene sample (to 26 genes, 18.4 kb) but only in a…

0106 biological sciencesNonsynonymous substitutionNuclear genetaxon samplingStatistics as TopicGenes Insect010603 evolutionary biology01 natural sciencesmolecular phylogeneticsGenetic Heterogeneitymissing data03 medical and health sciencesDitrysiaGeneticsAnimalsGelechioideaPhylogenyEcology Evolution Behavior and Systematics030304 developmental biologyGenetics0303 health sciencesbiologyNucleotidesHexapodaClassificationnuclear genesbiology.organism_classificationMissing dataLepidopteragene samplingTaxonMacrolepidopteraEvolutionary biologyMolecular phylogeneticsDitrysiaRegular ArticlesSystematic Biology
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Spatial dynamics of an invasive bird species assessed using robust design occupancy analysis: the case of the Eurasian collared dove ( Streptopelia d…

2007

Aim  The study of the spatial dynamics of invasive species is a key issue in invasion ecology. While mathematical models are useful for predicting the extent of population expansions, they are not suitable for measuring and characterizing spatial patterns of invasion unless the probability of detection is homogeneous across the distribution range. Here, we apply recently developed statistical approaches incorporating detection uncertainty to characterize the spatial dynamics of an invasive bird species, the Eurasian collared dove (Streptopelia decaocto). Location  France. Methods  Data on presence/absence of doves were recorded from 1996 to 2004 over 1045 grid cells (28 × 20 km) covering th…

0106 biological sciencesOccupancyRange (biology)PopulationMetapopulationSpatial distribution010603 evolutionary biology01 natural sciences[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsStatisticseducationComputingMilieux_MISCELLANEOUSEcology Evolution Behavior and Systematics[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologyeducation.field_of_studyEcologybiologyEcology010604 marine biology & hydrobiologyStreptopeliaConditional probability15. Life on landbiology.organism_classification[ SDV.EE.ECO ] Life Sciences [q-bio]/Ecology environment/EcosystemsGeographySpatial ecology[SDE.BE]Environmental Sciences/Biodiversity and EcologyJournal of Biogeography
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Dental wear proxy correlation in a long-term feeding experiment on sheep ( Ovis aries )

2021

Dietary reconstruction in vertebrates often relies on dental wear-based proxies. Although these proxies are widely applied, the contributions of physical and mechanical processes leading to meso- and microwear are still unclear. We tested their correlation using sheep ( Ovis aries , n = 39) fed diets of varying abrasiveness for 17 months as a model. Volumetric crown tissue loss, mesowear change and dental microwear texture analysis (DMTA) were all applied to the same teeth. We hereby correlate: (i) 46 DMTA parameters with each other, for the maxillary molars (M1, M2, M3), and the second mandibular molar (m2); (ii) 10 mesowear variables to each other and to DMTA for M1, M2, M3 and m2; and (…

0106 biological sciencesOrthodonticsMolar0303 health sciencesFuture studiesbiologyChemistryDental WearBiomedical EngineeringBiophysicsBioengineeringbiology.organism_classification010603 evolutionary biology01 natural sciencesBiochemistryMesowearBiomaterialsCorrelation03 medical and health sciencesstomatognathic systemProxy (statistics)Mandibular molarOvis030304 developmental biologyBiotechnologyJournal of The Royal Society Interface
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Reference growth charts for Posidonia oceanica seagrass: An effective tool for assessing growth performance by age and depth

2016

Abstract Growth performance of rhizomes has become among the most used descriptors for monitoring Posidonia oceanica seagrass dynamics and population status. However, ability to detect any change of growth in space or in time is often confounded by natural age-induced decline. To overcome this problem, we have produced reference growth charts, which in other areas are universally recognized as a very powerful tool for comparing growth of living beings during their ontogeny. Reference growth charts involving different P. oceanica growth performance measures (speed of growth and primary production of rhizomes) have been built using proper statistical frameworks (GLMM, Segmented and Quantile R…

0106 biological sciencesPercentileAgingDating methodGeneral Decision Sciences010603 evolutionary biology01 natural sciencesMediterranean seaAquatic plant ecologyStatisticsRange (statistics)ConfoundingSegmented regressionSeagrasseEcology Evolution Behavior and SystematicsbiologyEcologyEcologyLepidochronology010604 marine biology & hydrobiologybiology.organism_classificationSeagrassSegmented regressionDecision Sciences (all)Posidonia oceanicaShootBreakpointGLMMQuantile
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Estimation of fitness from energetics and life-history data: An example using mussels.

2017

Changing environments have the potential to alter the fitness of organisms through effects on components of fitness such as energy acquisition, metabolic cost, growth rate, survivorship, and reproductive output. Organisms, on the other hand, can alter aspects of their physiology and life histories through phenotypic plasticity as well as through genetic change in populations (selection). Researchers examining the effects of environmental variables frequently concentrate on individual components of fitness, although methods exist to combine these into a population level estimate of average fitness, as the per capita rate of population growth for a set of identical individuals with a particul…

0106 biological sciencesPhenotypic plasticityEcology010604 marine biology & hydrobiologyBiology010603 evolutionary biology01 natural sciencesSurvivorship curveStatisticsPer capitaPopulation growthProduction (economics)Set (psychology)Ecology Evolution Behavior and SystematicsSelection (genetic algorithm)OrganismNature and Landscape ConservationEcology and evolution
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Measuring phenotypes in fluctuating environments

2020

Despite considerable theoretical interest in how the evolution of phenotypic plasticity should be shaped by environmental variability and stochasticity, how individuals actually respond to these aspects of the environment within their own lifetimes remains unclear. We propose that this understanding has been hampered by experimental approaches that expose organisms to fluctuating environments (typically treatments where fluctuations in the environment are cyclical vs. erratic) for a pre‐determined duration while ensuring that the mean environment over that the entire exposure period is invariable. This approach implicitly assumes that responses to the mean and variance/predictability in the…

0106 biological sciencesPhenotypic plasticitybiologyfungiConfoundingDaphnia magnabiology.organism_classification010603 evolutionary biology01 natural sciencesDaphniaHeat toleranceEnvironment variableStatisticsPredictabilityMean radiant temperatureEcology Evolution Behavior and Systematics010606 plant biology & botanyFunctional Ecology
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Spontaneous quantity discrimination of artificial flowers by foraging honeybees

2020

ABSTRACTMany animals need to process numerical and quantity information in order to survive. Spontaneous quantity discrimination allows differentiation between two or more quantities without reinforcement or prior training on any numerical task. It is useful for assessing food resources, aggressive interactions, predator avoidance and prey choice. Honeybees have previously demonstrated landmark counting, quantity matching, use of numerical rules, quantity discrimination and arithmetic, but have not been tested for spontaneous quantity discrimination. In bees, spontaneous quantity discrimination could be useful when assessing the quantity of flowers available in a patch and thus maximizing f…

0106 biological sciencesPhysiology[SDV]Life Sciences [q-bio]ForagingSubitizingFlowersNumericAquatic Science010603 evolutionary biology01 natural sciencesPredation03 medical and health sciences0302 clinical medicineStatisticsApproximate number systemApproximate number systemAnimalsPredator avoidanceMolecular BiologyRatioEcology Evolution Behavior and SystematicsMathematicsArtificial flowerBees[SDV] Life Sciences [q-bio]Food resourcesInsect ScienceObject file systemAnimal Science and ZoologyApis mellifera030217 neurology & neurosurgery
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Risk of predation makes foragers less choosy about their food.

2017

18 pages; International audience; Animals foraging in the wild have to balance speed of decision making and accuracy of assessment of a food item's quality. If resource quality is important for maximizing fitness, then the duration of decision making may be in conflict with other crucial and time consuming tasks, such as anti-predator behaviours or competition monitoring. Individuals facing the risk of predation and/or competition should adjust the duration of decision making and, as a consequence, their level of choosiness for resources. When exposed to predation, the forager could either maintain its level of choosiness for food items but accept a reduction in the amount of food items con…

0106 biological sciencesPhysiologylcsh:MedicinePredationSocial SciencesKaplan-Meier EstimateChoice Behavior01 natural sciencesPredationCognitionMathematical and Statistical TechniquesBeetlesMedicine and Health Sciences[ SDV.EE.IEO ] Life Sciences [q-bio]/Ecology environment/SymbiosisPsychologyForagingDecision-makinglcsh:Sciencemedia_common2. Zero hungerMultidisciplinaryEcologyAnimal BehaviorEcology05 social sciencesEukaryotaPlantsTrophic InteractionsInsectsCommunity EcologyPhysical SciencesSeedsStatistics (Mathematics)Research ArticleRiskOpportunity costArthropodaMovementmedia_common.quotation_subjectDecision MakingForagingBiologyResearch and Analysis Methods010603 evolutionary biologyIntraspecific competitionCompetition (biology)Food PreferencesAnimals0501 psychology and cognitive sciencesQuality (business)050102 behavioral science & comparative psychologyStatistical MethodsBehavior[ SDE.BE ] Environmental Sciences/Biodiversity and Ecologylcsh:REcology and Environmental SciencesCognitive PsychologyFood ConsumptionOrganismsBiology and Life SciencesInterspecific competitionInvertebratesFoodPredatory BehaviorCognitive Sciencelcsh:QWeeds[SDE.BE]Environmental Sciences/Biodiversity and EcologyPhysiological ProcessesZoologyMathematicsNeuroscienceGeneralized Linear ModelDemography[SDV.EE.IEO]Life Sciences [q-bio]/Ecology environment/Symbiosis
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An Empirical Evaluation of the Utility of Convex Hull and Standard Ellipse Areas for Assessing Population Niche Widths from Stable Isotope Data

2013

Stable isotope analyses are increasingly employed to characterise population niche widths. The convex hull area (TA) in a δ¹³C–δ¹⁵N biplot has been used as a measure of isotopic niche width, but concerns exist over its dependence on sample size and associated difficulties in among-population comparisons. Recently a more robust method was proposed for estimating and comparing isotopic niche widths using standard ellipse areas (SEA), but this approach has yet to be tested with empirical stable isotope data. The two methods measure different kind of isotopic niche areas, but both are now widely used to characterise isotopic niche widths of populations. We used simulated data and an extensive e…

0106 biological sciencesPopulation Dynamicslcsh:MedicinePopulation Modeling01 natural sciencesTheoretical EcologyFood Web StructureStatisticsRange (statistics)lcsh:ScienceFreshwater EcologyCarbon Isotopeseducation.field_of_studyMultidisciplinaryEcologyδ13CEcologyStable isotope ratioStatisticsFishesBiogeochemistryisotopic nicheTrophic Interactionstrophic nicheCommunity Ecologyconvex hullResearch ArticlePopulationNichestable isotopesBiostatistics010603 evolutionary biologyNiche ConstructionNormal distributionBayesian ellipse areavakaat isotoopitAnimals14. Life underwaterStatistical MethodseducationBiologyEcological nicheNitrogen Isotopes010604 marine biology & hydrobiologylcsh:RComputational BiologySpecies InteractionsSample size determinationSample SizeravintolokeroEnvironmental scienceta1181lcsh:QPopulation EcologyEcosystem ModelingMathematicsPLOS ONE
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Testing hypotheses in evolutionary ecology with imperfect detection: capture-recapture structural equation modeling.

2012

8 pages; International audience; Studying evolutionary mechanisms in natural populations often requires testing multifactorial scenarios of causality involving direct and indirect relationships among individual and environmental variables. It is also essential to account for the imperfect detection of individuals to provide unbiased demographic parameter estimates. To cope with these issues, we developed a new approach combining structural equation models with capture-recapture models (CR-SEM) that allows the investigation of competing hypotheses about individual and environmental variability observed in demographic parameters. We employ Markov chain Monte Carlo sampling in a Bayesian frame…

0106 biological sciencesPopulation Dynamicsselection gradient analysesBiologystate-space models010603 evolutionary biology01 natural sciencesModels BiologicalStructural equation modelingMark and recapture010104 statistics & probabilitystructural equation modelslife history tradeoffsAnimalsPasseriformes0101 mathematicsSet (psychology)Ecology Evolution Behavior and SystematicsSelection (genetic algorithm)Ecosystemcapture-recapture models[ SDE.BE ] Environmental Sciences/Biodiversity and EcologyEcologyModel selectionCyanistesindividual heterogeneitybiology.organism_classificationCausalityBiological Evolutionevolutionary ecologyEvolutionary ecology[SDE.BE]Environmental Sciences/Biodiversity and EcologyEcology
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