Search results for "bayesian"

showing 10 items of 604 documents

Value of information in multiple criteria decision making: an application to forest conservation

2019

Abstract Developing environmental conservation plans involves assessing trade-offs between the benefits and costs of conservation. The benefits of conservation can be established with ecological inventories or estimated based on previously collected information. Conducting ecological inventories can be costly, and the additional information may not justify these costs. To clarify the value of these inventories, we investigate the multiple criteria value of information associated with the acquisition of improved ecological data. This information can be useful when informing the decision maker to acquire better information. We extend the concept of the value of information to a multiple crite…

0106 biological sciencesForest planningEnvironmental EngineeringBayesian decision theory010504 meteorology & atmospheric sciencesOperations researchComputer sciencepäätöksentekoComputational intelligenceEcological data010603 evolutionary biology01 natural sciencesValue of informationoptimointiEnvironmental Chemistrysimulointiconservation planningSafety Risk Reliability and Quality0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and Technologydecision analysisbayesilainen menetelmäsimulationDecision makermonitavoiteoptimointiPreferencemetsiensuojelukriteerittrade-offsMultiple criteriainformation updatingluonnonsuojelukompromissitoptimizationValue (mathematics)Stochastic Environmental Research and Risk Assessment
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Potential of using data assimilation to support forest planning

2017

Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature…

0106 biological sciencesForest planningGlobal and Planetary Change010504 meteorology & atmospheric sciencesEcologyOperations researchProcess (engineering)Computer sciencemedia_common.quotation_subjectForestry01 natural sciencesBayesian statisticsData assimilationStochastic optimizationQuality (business)010606 plant biology & botany0105 earth and related environmental sciencesmedia_commonCanadian Journal of Forest Research
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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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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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Bayesian spatio-temporal approach to identifying fish nurseries by validating persistence areas

2015

Spatial and temporal closures of fish nursery areas to fishing have recently been recognized as useful tools for efficient fisheries management, as they preserve the reproductive potential of populations and increase the recruitment of target species. In order to identify and locate potential nursery areas for spatio-temporal closures, a solid understanding of species− environment relationships is needed, as well as spatial identification of fish nurseries through the application of robust analyses. One way to achieve knowledge of fish nurseries is to analyse the persistence of recruitment hotspots. In this study, we propose the comparison of different spatiotemporal model structures to ass…

0106 biological sciencesMediterranean climatehttp://aims.fao.org/aos/agrovoc/c_28840[SDV]Life Sciences [q-bio]01 natural sciencesMediterranean seaAbundance (ecology)Ecosystem approachEcologybiologyEcologyU10 - Informatique mathématiques et statistiquesinteraction élevage environnementmodèle de distributionMerluccius merlucciushttp://aims.fao.org/aos/agrovoc/c_41529zone de pêcheNursery areasSpatio temporal analysisanalyse bayésienneGeographyGestion des pêchesgestion spatialealevinageFisheries managementFishinganalyse spatiotemporellegestion des ressources naturellesAquatic Science010603 evolutionary biologyhttp://aims.fao.org/aos/agrovoc/c_24026étude comparativeHakeMerluccius merluccius14. Life underwaterhttp://aims.fao.org/aos/agrovoc/c_4699Ecology Evolution Behavior and Systematicshttp://aims.fao.org/aos/agrovoc/c_12399Distribution patternapproche ecosystémiqueÉcologie marinehttp://aims.fao.org/aos/agrovoc/c_4609010604 marine biology & hydrobiologybiology.organism_classificationBiologie marineFisheryThéorie bayésiennehttp://aims.fao.org/aos/agrovoc/c_9000115M40 - Écologie aquatiqueBayesian hierarchical modellingMarine protected areaSpatial fisheries managementNursery areas;Distribution pattern;Ecosystem approach;Spatial fisheries management;Spatio temporal analysis;Bayesian hierarchical modelling;Merluccius merluccius
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Ingestion of microplastics and occurrence of parasite association in Mediterranean anchovy and sardine

2020

10 pages, 6 figures, 1 table, supplementary data https://doi.org/10.1016/j.marpolbul.2020.111399

0106 biological sciencesMediterranean climatemarine litterMicroplastics[SDE.MCG]Environmental Sciences/Global ChangesMicroplasticsplastic debrishabitatZoologySmall pelagic fish010501 environmental sciencesAquatic Sciencecoastal areasOceanographyBayesian01 natural sciencesEngraulisMediterranean seaAbundance (ecology)AnchovyMediterranean SeaAnimalsHumansIngestionParasitesPesqueríasCentro Oceanográfico de Murcia14. Life underwaterPlastic ingestion0105 earth and related environmental sciencesFish parasitesbiology010604 marine biology & hydrobiologydigestive oral and skin physiologySardineFishesbiology.organism_classificationPollution3. Good healthengraulis-encrasicoluspilchardusBayesian. Gut contentssea-floor[SDE.BE]Environmental Sciences/Biodiversity and Ecologydietfeeding-behaviorGut contentsPlasticsWater Pollutants Chemical
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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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Empirical Bayes improves assessments of diversity and similarity when overdispersion prevails in taxonomic counts with no covariates

2019

Abstract The assessment of diversity and similarity is relevant in monitoring the status of ecosystems. The respective indicators are based on the taxonomic composition of biological communities of interest, currently estimated through the proportions computed from sampling multivariate counts. In this work we present a novel method to estimate the taxonomic composition able to work even with a single sample and no covariates, when data are affected by overdispersion. The presence of overdispersion in taxonomic counts may be the result of significant environmental factors which are often unobservable but influence communities. Following the empirical Bayes approach, we combine a Bayesian mo…

0106 biological sciencesMultivariate statisticsBiological dataEmpirical Bayesian estimationEcologyTaxonomic compositionGeneral Decision SciencesEnvironmental monitoring010501 environmental sciencesBayesian inference010603 evolutionary biology01 natural sciencesBiodiversity assessment; Dirichlet-Multinomial model; Empirical Bayesian estimation; Environmental monitoring; Taxonomic compositionMarginal likelihoodBayes' theoremOverdispersionStatisticsTaxonomic rankDirichlet-Multinomial modelBiodiversity assessmentEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEmpirical Bayes methodMathematics
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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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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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