Search results for "Statistics"

showing 10 items of 7671 documents

The Bias of combining variables on fish's aggressive behavior studies.

2019

Made available in DSpace on 2019-10-06T16:27:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-01 Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive …

0106 biological sciencesBayesian probabilityPosterior probabilityBayesian analysisPoisson distribution010603 evolutionary biology01 natural sciencesBehavioral Neurosciencesymbols.namesakeBiasPrior probabilityStatisticsAnimals0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyPterophyllum scalareMathematicsProbabilitybiologyBehavior Animal05 social sciencesMultilevel modelBayes TheoremGeneral MedicineCichlidsbiology.organism_classificationAggressive behaviourMarkov ChainsAggressionVariable (computer science)Sample size determinationData Interpretation StatisticalsymbolsAnimal Science and ZoologyPooled dataMonte Carlo MethodBehavioural processes
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Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

2018

International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…

0106 biological sciencesCanopyEarth observationPhoton010504 meteorology & atmospheric sciencesF40 - Écologie végétalehttp://aims.fao.org/aos/agrovoc/c_1920Soil Science01 natural sciencesMeasure (mathematics)http://aims.fao.org/aos/agrovoc/c_7701Multi-angle remote sensingProbability theoryhttp://aims.fao.org/aos/agrovoc/c_718Foliage clumping indexRange (statistics)http://aims.fao.org/aos/agrovoc/c_3081[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyComputers in Earth SciencesLeaf area indexhttp://aims.fao.org/aos/agrovoc/c_4039http://aims.fao.org/aos/agrovoc/c_4116Photon recollision probabilityhttp://aims.fao.org/aos/agrovoc/c_10672http://aims.fao.org/aos/agrovoc/c_32450105 earth and related environmental sciencesMathematicsRemote sensinghttp://aims.fao.org/aos/agrovoc/c_8114GeologyVegetationhttp://aims.fao.org/aos/agrovoc/c_5234http://aims.fao.org/aos/agrovoc/c_7558Leaf area indexhttp://aims.fao.org/aos/agrovoc/c_7273http://aims.fao.org/aos/agrovoc/c_1236http://aims.fao.org/aos/agrovoc/c_1556U30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_4026010606 plant biology & botanyhttp://aims.fao.org/aos/agrovoc/c_6124
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Airborne-laser-scanning-derived auxiliary information discriminating between broadleaf and conifer trees improves the accuracy of models for predicti…

2020

Managing forests for ecosystem services and biodiversity requires accurate and spatially explicit forest inventory data. A major objective of forest management inventories is to estimate the standing timber volume for certain forest areas. In order to improve the efficiency of an inventory, field based sample-plots can be statistically combined with remote sensing data. Such models usually incorporate auxiliary variables derived from canopy height models. The inclusion of forest type variables, which quantify broadleaf and conifer volume proportions, has been shown to further improve model performance. Currently, the most common way of quantifying broadleaf and conifer forest types is by ca…

0106 biological sciencesCanopysekametsätMean squared errorForest managementBiodiversityClimate changeairborne laser scanningManagement Monitoring Policy and Law010603 evolutionary biology01 natural sciencesforest type mapStatisticscanopy height modelimage-based point cloudsNature and Landscape ConservationForest inventorymetsäsuunnitteluForestryPercentage pointmetsänarviointipuutavaranmittausOrdinary least squaresordinary least squares regression modelsEnvironmental sciencemixed and heterogeneously structured forestkaukokartoitushigh-precision forest inventorymetsänhoitobest fit modelsmerchantable timber volumelaserkeilaus010606 plant biology & botanyForest Ecology and Management
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Assessing sampling coverage of species distribution in biodiversity databases

2019

Abstract Aim Biodiversity databases are valuable resources for understanding plant species distributions and dynamics, but they may insufficiently represent the actual geographic distribution and climatic niches of species. Here we propose and test a method to assess sampling coverage of species distribution in biodiversity databases in geographic and climatic space. Location Europe. Methods Using a test selection of 808,794 vegetation plots from the European Vegetation Archive (EVA), we assessed the sampling coverage of 564 European vascular plant species across both their geographic ranges and realized climatic niches. Range maps from the Chorological Database Halle (CDH) were used as bac…

0106 biological sciencesChorological Database Halle (CDH)Range (biology)multi-scale[SDE.MCG]Environmental Sciences/Global Changesvegetation-plot databasesSpecies distributionPlant Science[SDV.BID]Life Sciences [q-bio]/Biodiversitycomputer.software_genre010603 evolutionary biology01 natural sciencesmacro-ecology333: Bodenwirtschaft und Ressourcen577: ÖkologieRealized niche widthMacroecologyEcological niche[SDV.EE]Life Sciences [q-bio]/Ecology environmentspatial scaleEcologyDatabaseNull modelvegetation plot databasesclimatic nichevascular plantSampling (statistics)species rangeVegetation15. Life on landDynamic Match Coefficient (DMC)sampling biasGeographyrealized niche1181 Ecology evolutionary biologymacroecology[SDE.BE]Environmental Sciences/Biodiversity and Ecologycomputer010606 plant biology & botanyEuropean Vegetation Archive (EVA)
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Establishing the occurrence and profile of polycyclic aromatic hydrocarbons in marine sediments: The eastern Mediterranean coast of Spain as a case s…

2019

Sampling, cost-effective analysis, diagnosis of sources of pollution and assessment of potential toxicological effects were included in the case study. Marine sediments collected from 24 points along the eastern Mediterranean coast of Spain (Comunitat Valenciana region) in 2010, 2011, 2012 and 2015 have been analysed for polycyclic aromatic hydrocarbons. Fluoranthene, pyrene, chrysene, benzo[b]fluoranthene and benzo[a]pyrene were the most found. An analysis of the relative abundance of selected PAHs revealed that petrogenic and mixed petrogenic/pyrogenic sources are predominant in the area. The total concentrations of the target compounds ranged from 14.7 to 615.3 ng/g dry weight. The effec…

0106 biological sciencesChrysenePollutionGeologic Sedimentsmedia_common.quotation_subject010501 environmental sciencesAquatic ScienceOceanography01 natural scienceschemistry.chemical_compoundMediterranean seaDry weightPolycyclic Aromatic HydrocarbonsRelative species abundance0105 earth and related environmental sciencesmedia_commonFluoranthene010604 marine biology & hydrobiologySampling (statistics)PollutionchemistrySpainEnvironmental chemistryPyreneEnvironmental scienceWater Pollutants ChemicalEnvironmental MonitoringMarine pollution bulletin
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gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models inr

2019

The work of J.N. was supported by the Wihuri Foundation. The work of S.T. was supported by the CRoNoS COST Action IC1408.F.K.C.H. was also supported by an ANU cross disciplinary grant.

0106 biological sciencesClustering high-dimensional dataMultivariate statisticsMultivariate analysisCross disciplinary010604 marine biology & hydrobiologyEcological ModelingMaximum likelihoodLatent variable010603 evolutionary biology01 natural sciencesAbundance (ecology)StatisticsCost actionEcology Evolution Behavior and SystematicsMathematicsMethods in Ecology and Evolution
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Analysis of spatial patterns informs community assembly and sampling requirements for Collembola in forest soils

2018

Abstract The relative importance of niche separation, non-equilibrial and neutral models of community assembly has been a theme in community ecology for many decades with none appearing to be applicable under all circumstances. In this study, Collembola species abundances were recorded over eleven consecutive years in a spatially explicit grid and used to examine (i) whether observed beta diversity differed from that expected under conditions of neutrality, (ii) whether sampling points differed in their relative contributions to overall beta diversity, and (iii) the number of samples required to provide comparable estimates of species richness across three forest sites. Neutrality could not…

0106 biological sciencesCommunityEcologyBeta diversityNiche differentiationSampling (statistics)04 agricultural and veterinary sciences010603 evolutionary biology01 natural sciencesSpatial heterogeneityGeography040103 agronomy & agricultureSpatial ecology0401 agriculture forestry and fisheriesRarefaction (ecology)Species richnessEcology Evolution Behavior and SystematicsNature and Landscape ConservationActa Oecologica
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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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Benchmark database for fine-grained image classification of benthic macroinvertebrates

2018

Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…

0106 biological sciencesComputer scienceta1172Sample (statistics)monitorointi02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural network0202 electrical engineering electronic engineering information engineeringkonenäköfine-grained classification14. Life underwaterFine-grained classificationInvertebrateta113ta112Contextual image classificationbusiness.industry010604 marine biology & hydrobiologyDeep learningConvolutional Neural NetworksBenchmark databasedeep learningPattern recognitionDeep learningselkärangattomatvedenlaatu6. Clean waterkoneoppiminenBenthic zoneBenthic macroinvertebratesbiomonitoringSignal ProcessingBiomonitoringta1181lajinmääritys020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceWater qualitybusinessbenthic macroinvertebrates
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