Search results for "bay"

showing 10 items of 1187 documents

Seasonal Variations in Biochemical Composition of the ClamDosinia corrugatein Relation to the Reproductive Cycle and Environmental Conditions

2016

ABSTRACT Seasonal variations in biochemical composition of the clam Dosinia corrugate were investigated from August 2013 until July 2014 in Zhuanghe Bay in relation to environmental conditions and reproductive cycle. Separate biochemical analyses of the mantle, adductor muscle, foot, and gonad-visceral mass in each sex were undertaken. Spawning took place once a year from July to August and the massive spawning occurred in August with the highest water temperature and chlorophyll a levels. Utilization of glycogen took place during the spawning period, whereas protein was biosynthesized as the mature gametes formed. The glycogen value increased during the resting stage (autumn—winter). The r…

0106 biological sciencesChlorophyll aGonadGlycogenurogenital systemEcology010604 marine biology & hydrobiology04 agricultural and veterinary sciencesAquatic ScienceBiologyReproductive cyclebiology.organism_classification01 natural sciencesDosiniachemistry.chemical_compoundmedicine.anatomical_structurechemistry040102 fisheriesmedicineBiochemical composition0401 agriculture forestry and fisheriesMantle (mollusc)BayJournal of Shellfish Research
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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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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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Bryophyte Species Richness on Retention Aspens Recovers in Time but Community Structure Does Not

2014

Green-tree retention is a forest management method in which some living trees are left on a logged area. The aim is to offer ‘lifeboats’ to support species immediately after logging and to provide microhabitats during and after forest re-establishment. Several studies have shown immediate decline in bryophyte diversity after retention logging and thus questioned the effectiveness of this method, but longer term studies are lacking. Here we studied the epiphytic bryophytes on European aspen (Populus tremula L.) retention trees along a 30-year chronosequence. We compared the bryophyte flora of 102 ‘retention aspens’ on 14 differently aged retention sites with 102 ‘conservation aspens’ on 14 d…

0106 biological sciencesEcological Political Economy010504 meteorology & atmospheric sciencesDIVERSITYBiodiversitylcsh:MedicinePlant ScienceBryology01 natural scienceslehtisammaletMICROCLIMATIC GRADIENTSTreesbryophyte diversitysammaletAbundance (ecology)TREE RETENTIONlcsh:Science1183 Plant biology microbiology virologyConservation Scienceforest reestablishmentMultidisciplinaryEcologyEcologyLoggingmetsänkäsittelyForestryAgricultureBiodiversityFINLANDta4112metsätHabitatCommunity EcologyGROWTHResearch ArticleConservation of Natural ResourcesEPIPHYTIC BRYOPHYTESChronosequenceeducationCONSERVATIONForest managementBryophytaBiology010603 evolutionary biologyBOREAL FORESTelvytysPlant-Environment InteractionsEDGES0105 earth and related environmental sciencesPlant Ecologylcsh:REcology and Environmental SciencesBiology and Life SciencesBayes Theorem15. Life on landhakkuualueetREPRODUCTIONta1181lcsh:QBryophyteSpecies richnessmetsänhoitogreen tree retentionAgroecologyPLOS ONE
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Integrating spatial management measures into fisheries: The Lepidorhombus spp. case study

2020

Most fisheries management systems rely on a set of regulatory measures to achieve desired objectives. Controls on catch and effort are usually supplemented with gear restrictions, minimum landing sizes, and in the framework of the new common fisheries policy, limitation of discards and by-catch. However, the increasing use of spatial management measures such as conservation areas or spatial and temporal area closures faces new challenges for fishery managers. Here we present an integrated spatial framework to identify areas in which undersized commercial species are more abundant. Once these areas are identified they could be avoided by fishers, minimizing the fishing impact over the immatu…

0106 biological sciencesEconomics and EconometricsCentro Oceanográfico de SantanderFishingManagement Monitoring Policy and LawAquatic Science01 natural sciencesEnvironmental dataIntegrated fishery managementMedio MarinoUndersized fishBayesian modelsGeneral Environmental Sciencefishbiology010604 marine biology & hydrobiologySensitive areas04 agricultural and veterinary sciencesbiology.organism_classificationDiscardsFisheryLepidorhombusGeographyDiscardsocean policySpatial managementLanding obligation040102 fisheriesSpatial ecology0401 agriculture forestry and fisheriesFisheries managementMegrimecologyLaw
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Discard ban: A simulation-based approach combining hierarchical Bayesian and food web spatial models

2020

12 pages, 6 figures, 6 tables, 2 appendixes, supplementary data https://doi.org/10.1016/j.marpol.2019.103703

0106 biological sciencesEconomics and EconometricsComputer scienceFishingSede Central IEOContext (language use)Management Monitoring Policy and LawAquatic ScienceBayesian inference01 natural sciencesEnvironmental datamedia_common.cataloged_instanceEcoSimSpatial ecologyPesquerías14. Life underwaterEuropean unionGeneral Environmental Sciencemedia_commonEcospacebusiness.industry010604 marine biology & hydrobiologyEnvironmental resource management04 agricultural and veterinary sciencesFood web modelDiscardsDiscards13. Climate actionBayesian modelLanding obligationMediterranean sea040102 fisheries0401 agriculture forestry and fisheriesFisheries managementbusinessLaw
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Small-scale shrimp fisheries bycatch: a multi-criteria approach for data-poor situations

2020

Abstract Bycatch and discards from small-scale fisheries (SSF) are usually ignored when compared with industrial fisheries, not only by policy-makers, but also by scientists. Therefore, SSF social, economic and ecological impacts are poorly known and especially in the context of incidental catches, regardless of whether they become bycatch or discards. Such neglect is worrisome due to the role that SSF play in food security and poverty alleviation, particularly in coastal and rural communities in developing countries. In this study, a combination of sampling data and the fishers' behavior (specifically the basis of their decision on where to fish) were used. Bayesian models were applied to …

0106 biological sciencesEconomics and EconometricsFishingFishers' behaviorContext (language use)Management Monitoring Policy and LawAquatic Science01 natural sciencesCentro Oceanográfico de MurciaPesqueríasBayesian modelsGeneral Environmental ScienceFood security010604 marine biology & hydrobiologyShrimp fisherySubsistence agriculture04 agricultural and veterinary sciencesLivelihoodDiscardsBycatchFisheryGeographyEconomic incentives040102 fisheries0401 agriculture forestry and fisheriesLaw
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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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Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): an initial molecular study

2009

AbstractBackgroundIn the mega-diverse insect order Lepidoptera (butterflies and moths; 165,000 described species), deeper relationships are little understood within the clade Ditrysia, to which 98% of the species belong. To begin addressing this problem, we tested the ability of five protein-coding nuclear genes (6.7 kb total), and character subsets therein, to resolve relationships among 123 species representing 27 (of 33) superfamilies and 55 (of 100) families of Ditrysia under maximum likelihood analysis.ResultsOur trees show broad concordance with previous morphological hypotheses of ditrysian phylogeny, although most relationships among superfamilies are weakly supported. There are als…

0106 biological sciencesEntomologyNuclear geneUNESCO::CIENCIAS DE LA VIDA::Biología animal (Zoología) ::InvertebradosEvolutionmedia_common.quotation_subjectInitial molecular studyZoologyInsect010603 evolutionary biology01 natural sciencesProtein-coding nuclear genesLepidoptera genitaliaLepidoptera; Protein-coding nuclear genes; Initial molecular study03 medical and health sciencesDitrysiaPhylogenetics:CIENCIAS DE LA VIDA::Biología animal (Zoología) ::Invertebrados [UNESCO]Research articleQH359-425AnimalsCladeEcology Evolution Behavior and SystematicsPhylogeny030304 developmental biologymedia_common0303 health sciencesbiologyBayes TheoremSequence Analysis DNAbiology.organism_classificationBiological EvolutionLepidopteraEvolutionary biologyBombycoideaBMC Evolutionary Biology
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Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation

2019

The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…

0106 biological sciencesEstimation0303 health sciencesSequenceActive learning (machine learning)business.industryComputer scienceProbabilistic logicInferenceFunction (mathematics)Bayesian inferenceMachine learningcomputer.software_genre010603 evolutionary biology01 natural sciences03 medical and health sciencesArtificial intelligencebusinesscomputerThompson sampling030304 developmental biology
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