Search results for "Probability."

showing 10 items of 3396 documents

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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Calibrating Expert Assessments Using Hierarchical Gaussian Process Models

2020

Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…

0106 biological sciencesComputer sciencepäätöksentekoRECONCILIATIONInferencecomputer.software_genre01 natural sciencesSTOCK ASSESSMENTenvironmental management010104 statistics & probabilityJUDGMENTSELICITATIONkalakantojen hoito111 Mathematicstilastolliset mallitReliability (statistics)Applied Mathematicsgaussiset prosessitfisheries sciencebias correctionexpert elicitationPROBABILITY62P1260G15symbols62F15Statistics and ProbabilityarviointimenetelmätBayesian probabilityenvironmental management.Bayesian inferenceMachine learningHEURISTICSsymbols.namesakeasiantuntijatMANAGEMENT0101 mathematicsGaussian processGaussian processCATCH LIMITSbusiness.industrybayesilainen menetelmä010604 marine biology & hydrobiologyUnivariateExpert elicitationOPINIONSupra BayesArtificial intelligenceHeuristicsbusinessFISHERIEScomputerBayesian Analysis
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Examining nonstationarity in the recruitment dynamics of fishes using Bayesian change point analysis

2017

Marine ecosystems can undergo regime shifts, which result in nonstationarity in the dynamics of the fish populations inhabiting them. The assumption of time-invariant parameters in stock–recruitment models can lead to severe errors when forecasting renewal ability of stocks that experience shifts in their recruitment dynamics. We present a novel method for fitting stock–recruitment models using the Bayesian online change point detection algorithm, which is able to cope with sudden changes in the model parameters. We validate our method using simulations and apply it to empirical data of four demersal fishes in the southern Gulf of St. Lawrence. We show that all of the stocks have experience…

0106 biological sciencesEmpirical dataEcology010604 marine biology & hydrobiologyBayesian probabilityModel parametersAquatic Science010603 evolutionary biology01 natural sciencesChange-Point AnalysisEconometricsEnvironmental scienceFish <Actinopterygii>Marine ecosystem14. Life underwaterEcology Evolution Behavior and SystematicsChange detectionCanadian Journal of Fisheries and Aquatic Sciences
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Comparison of Bayesian and numerical optimization-based diet estimation on herbivorous zooplankton

2020

Consumer diet estimation with biotracer-based mixing models provides valuable information about trophic interactions and the dynamics of complex ecosystems. Here, we assessed the performance of four Bayesian and three numerical optimization-based diet estimation methods for estimating the diet composition of herbivorous zooplankton using consumer fatty acid (FA) profiles and resource library consisting of the results of homogeneous diet feeding experiments. The method performance was evaluated in terms of absolute errors, central probability interval checks, the success in identifying the primary resource in the diet, and the ability to detect the absence of resources in the diet. Despite …

0106 biological sciencesFood ChainBayesian probability010603 evolutionary biology01 natural sciencesZooplanktonGeneral Biochemistry Genetics and Molecular BiologyDistance measuresZooplanktonFASTARStatisticsAnimalsravintoaineetMixSIARHerbivoryMathematicsTrophic levelestimointi2. Zero hungerEstimationHerbivorefood web010604 marine biology & hydrobiologybayesilainen menetelmäplanktonFatty AcidsBayes TheorembiotracersArticlesFood webDietDaphniaQFASAvesikirputGeneral Agricultural and Biological SciencesEstimation methodsravintoverkotFood Analysis
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Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach

2021

In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator spe…

0106 biological sciencesGeneral MathematicsSpecies distributionBayesian probabilityspeciescoregionalized modelsBayesian hierarchical models010603 evolutionary biology01 natural sciences010104 statistics & probabilitymodelsEngraulisHakeAnchovyStatisticsComputer Science (miscellaneous)INLAdistributionEuropean anchovyPesqueríasCentro Oceanográfico de Murcia0101 mathematicsEngineering (miscellaneous)SPDEfishspecies interactionbiologymathematicslcsh:MathematicsUnivariateMerluccius merlucciusbiology.organism_classificationlcsh:QA1-939fisheriesEnvironmental sciencepredation
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SHAPE MATTERS: EFFECT OF POINT MUTATIONS ON RNA SECONDARY STRUCTURE

2013

A suitable model to dive into the properties of genotype-phenotype landscapes is the relationship between RNA sequences and their corresponding minimum free energy secondary structures. Relevant issues related to molecular evolvability and robustness to mutations have been studied in this framework. Here, we analyze the one-mutant neighborhood of the predicted secondary structure of 46 different RNAs, including tRNAs, viroids, larger molecules such as Hepatitis-δ virus, and several random sequences. The probability distribution of the effect of point mutations in linear structural motifs of the secondary structure is well fit by Pareto or Lognormal probability distributions functions, indep…

0106 biological sciencesGenetics0303 health sciencesPoint mutationRNARobustness (evolution)Computational biologyBiology010603 evolutionary biology01 natural sciencesNucleic acid secondary structureEvolvability03 medical and health sciencesControl and Systems EngineeringProbability distributionStructural motifRNA secondary structure sequence-structure map mutational effects linear motifsProtein secondary structure030304 developmental biologyAdvances in Complex Systems
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Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea)

2021

This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200 kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. Th…

0106 biological sciencesKrillbiologybusiness.industry010604 marine biology & hydrobiologyEuphausiaSettore MAT/01 - Logica MatematicaEuphausia crystallorophiasbiology.organism_classificationSpatial distributionMachine learning for pelagic species classification01 natural sciencesKrill identification010104 statistics & probabilityRoss SeaAcoustic dataArtificial intelligence0101 mathematicsCluster analysisbusinessRelative species abundanceGeologyEnergy (signal processing)Global biodiversityRemote sensing
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The analysis of convergence in ecological indicators: An application to the Mediterranean fisheries

2017

9 pages, 4 figures, 3 tables

0106 biological sciencesMediterranean climateIndex (economics)[SDE.MCG]Environmental Sciences/Global ChangesFishingGeneral Decision SciencesTransition probability matrix;Sede Central IEOtMediterranean sea010603 evolutionary biology01 natural sciencesEcological indicatorsMediterranean sea[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsEcosystem approach to fisheries managemenConvergence analysisMediterranean SeaEcosystemEcosystem approach to fisheries management14. Life underwaterEcology Evolution Behavior and SystematicsTrophic levelEstimationEcologybusiness.industry010604 marine biology & hydrobiologyEnvironmental resource managementTransition probability matrixFisheryEcological indicatorGeographyNon-parametric density estimation[SDV.SA.STP]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of fishery[SDE.BE]Environmental Sciences/Biodiversity and Ecologybusiness
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Assessing the spatiotemporal persistence of fish distributions: a case study on two red mullet species (Mullus surmuletus and M. barbatus) in the wes…

2020

Understanding the spatiotemporal persistence of fish distributions is key to defining fish hotspots and effective fisheries-restricted areas (FRAs). Hierarchical Bayesian spatiotemporal models provide an excellent framework to understand these distributions, as they can accommodate different spatiotemporal behaviour in the data, primarily due to their flexibility. The aim of this research was to characterize the fundamental behavioural patterns of fish as persistent, opportunistic or progressive by comparing different spatiotemporal model structures in order to provide better information for marine spatial planning. To illustrate this method, the spatiotemporal distributions of 2 sympatric …

0106 biological sciencesMediterranean climateRed mulletMullus surmuletusSpatiotemporalAquatic Science01 natural sciencesPersistence (computer science)010104 statistics & probabilityFisheries managementSpecies distribution modellingFisheries-restricted areasCentro Oceanográfico de MurciaPesquerías0101 mathematicsEcology Evolution Behavior and SystematicsEcologybiology010604 marine biology & hydrobiologyMarine spatial planningbiology.organism_classificationMarine spatial planningEnvironmental niche modellingFisheryGeographyFish <Actinopterygii>Fisheries management
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Bayesian analysis improves experimental studies about temporal patterning of aggression in fish.

2017

Made available in DSpace on 2018-12-11T17:15:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) This study aims to describe a Bayesian Hierarchical Linear Model (HLM) approach for longitudinal designs in fish's experimental aggressive behavior studies as an alternative to classical methods In particular, we discuss the advantages of Bayesian analysis in dealing with combined variables, non-statistically significant results and required sample size using an experiment of angelfish (Pterophyllum scalare) species as case study. Groups of 3 individuals were subjected to daily observations recorded for 10 min durin…

0106 biological sciencesMonte Carlo methodBayesian probabilityBayesian analysisAquaculture010603 evolutionary biology01 natural sciencesStability (probability)Behavioral NeuroscienceStatisticsAnimals0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyPterophyllum scalareProbabilitybiologyMarkov chain05 social sciencesMultilevel modelAggressive behaviorBayes TheoremGeneral MedicineCichlidsbiology.organism_classificationLongitudinal designMarkov ChainsAggressionVariable (computer science)Sample size determinationResearch DesignAnimal Science and ZoologyPsychologyMonte Carlo MethodBehavioural processes
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