Search results for " data"

showing 10 items of 7516 documents

A new algorithm for the identification of dives reveals the foraging ecology of a shallow-diving seabird using accelerometer data

2017

International audience; The identification of feeding events is crucial to our understanding of the foraging ecology of seabirds. Technology has made small devices, such as time-depth recorders (TDRs) and accelerometers available. However, TDRs might not be sensitive enough to identify shallow dives, whereas accelerometers might reveal more subtle behaviours at a smaller temporal scale. Due to the limitations of TDRs, the foraging ecology of many shallow-diving seabirds has been poorly investigated to date. We thus developed an algorithm to identify dive events in a shallow-diving seabird species, the Scopoli’s shearwater, using only accelerometer data. The accuracy in the identification of…

0106 biological sciencesEcologybiologyEcology010604 marine biology & hydrobiologyEcology (disciplines)ForagingAquatic Sciencebiology.organism_classification010603 evolutionary biology01 natural sciencesShearwaterCalonectris diomedea foraging divingSettore AGR/11 - Entomologia Generale E Applicatabiology.animal[SDE]Environmental Sciences14. Life underwaterAccelerometer dataSeabirdAlgorithmEcology Evolution Behavior and Systematics
researchProduct

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
researchProduct

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
researchProduct

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
researchProduct

Multiple‐batch spawning as a bet‐hedging strategy in highly stochastic environments: An exploratory analysis of Atlantic cod

2021

Stochastic environments shape life‐history traits and can promote selection for risk‐spreading strategies, such as bet‐hedging. Although the strategy has often been hypothesised to exist for various species, empirical tests providing firm evidence have been rare, mainly due to the challenge in tracking fitness across generations. Here, we take a ‘proof of principle’ approach to explore whether the reproductive strategy of multiple‐batch spawning constitutes a bet‐hedging. We used Atlantic cod (Gadus morhua) as the study species and parameterised an eco‐evolutionary model, using empirical data on size‐related reproductive and survival traits. To evaluate the fitness benefits of multiple‐batc…

0106 biological sciencesEmpirical dataEvolutionReproductive strategyBiology010603 evolutionary biology01 natural sciencesrisk‐spreadingturskaEnvironmental riskGeneticsQH359-425Gadus14. Life underwaterEcology Evolution Behavior and SystematicsSelection (genetic algorithm)VDP::Landbruks- og Fiskerifag: 900::Fiskerifag: 920kuntosopeutuminenlisääntymiskäyttäytyminenEcology010604 marine biology & hydrobiologyOriginal ArticlesExploratory analysisbiology.organism_classificationlisääntyminenfitnesselinkiertomultiple‐batch spawningAtlantic codTraitOriginal Articlebet‐hedgingGeneral Agricultural and Biological SciencesAtlantic codenvironmental stochasticityympäristönmuutoksetEvolutionary Applications
researchProduct

Mechanisms of reciprocity and diversity in social networks: a modeling and comparative approach

2018

Individual-based computer models show that different mechanisms, proximity-based or emotional bookkeeping, can lead to reciprocation. By comparing social networks from different computer models with those of empirical data, we show that the models’ social networks bear limited resemblance with some features of the observed social networks. This indicates that additional social processes (third-party awareness) may be needed in these models to represent more accurately the social behavior and interaction patterns observed in group-living animals.

0106 biological sciencesEmpirical dataSocial networkbusiness.industryComparative method[SDV]Life Sciences [q-bio]05 social sciencesGroup livingBiology010603 evolutionary biology01 natural sciencesBookkeepingSocial processesReciprocity (social psychology)[SDE]Environmental Sciences[SDV.BA.ZV]Life Sciences [q-bio]/Animal biology/Vertebrate Zoology0501 psychology and cognitive sciencesAnimal Science and Zoology050102 behavioral science & comparative psychologybusinessEcology Evolution Behavior and SystematicsComputingMilieux_MISCELLANEOUSCognitive psychologyDiversity (business)
researchProduct

Notulae to the Italian native vascular flora: 8

2019

In this contribution, new data concerning the distribution of native vascular flora in Italy are presented. It includes new records, confirmations, exclusions, and status changes to the Italian administrative regions for taxa in the genera Ajuga, Chamaemelum, Clematis, Convolvulus, Cytisus, Deschampsia, Eleocharis, Epipactis, Euphorbia, Groenlandia, Hedera, Hieracium, Hydrocharis, Jacobaea, Juncus, Klasea, Lagurus, Leersia, Linum, Nerium, Onopordum, Persicaria, Phlomis, Polypogon, Potamogeton, Securigera, Sedum, Soleirolia, Stachys, Umbilicus, Valerianella, and Vinca. Nomenclatural and distribution updates, published elsewhere, and corrigenda are provided as Suppl. material 1.

0106 biological sciencesEndemic Floristic data Italy NomenclatureFloraNomenclatureZoologyFloristic dataPlant ScienceBiology010603 evolutionary biology01 natural scienceslcsh:QK1-989EndemicItalylcsh:BotanySettore BIO/03 - Botanica Ambientale E ApplicataNomenclatureEcology Evolution Behavior and SystematicsEndemic; Floristic data; Italy; Nomenclature010606 plant biology & botany
researchProduct

Parameter identification and state estimation of a microalgae dynamical model in sulphur deprived conditions: Global sensitivity analysis, optimizati…

2014

International audience; In this article, a dynamic model describing the growth of the green microalgae Chlamydomonas reinhardtii , under light attenuation and sulphur‐deprived conditions leading to hydrogen production in a photobioreactor is presented. The strong interactions between biological and physical phenomena require complex mathematical expressions with an important number of parameters. This article presents a global identification procedure in three steps using data from batch experiments. First, it includes the application of a sensitivity function analysis, which allows one to determine the parameters having the greatest influence on model outputs. Secondly, the most influentia…

0106 biological sciencesEngineeringObserver (quantum physics)business.industryGeneral Chemical Engineering05 social sciencesExperimental dataPhotobioreactorFunction (mathematics)01 natural sciences7. Clean energy[SPI]Engineering Sciences [physics]Extended Kalman filterSoftware010608 biotechnology0502 economics and business[INFO]Computer Science [cs]Stage (hydrology)Gas composition050207 economicsBiological systembusinessSimulationThe Canadian Journal of Chemical Engineering
researchProduct

Notulae to the Italian alien vascular flora: 11

2021

Publisher Copyright: © This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited In this contribution, new data concerning the distribution of vascular flora alien to Italy are presented. It includes new records, confirmations, exclusions, and status changes for Italy or for Italian administrative regions. Nomenclatural and distribution updates published elsewhere are provided as Suppl. material 1. Peer rev…

0106 biological sciencesFloraAlien speciesPlant ScienceAlien010603 evolutionary biology01 natural sciencesfloristic dataFloristic DataAlien speciesNomenclatureAlien specieEcology Evolution Behavior and SystematicsNomenclatureEcologyBotany11831 Plant biologyBiología y Biomedicina / BiologíaAlien SpeciesGeographyItalyQK1-989Alien species floristic data Italy nomenclaturenomenclatureAlien species; floristic data; Italy; nomenclature010606 plant biology & botanyItalian Botanist
researchProduct

Notulae to the Italian alien vascular flora: 9

2020

In this contribution, new data concerning the distribution of vascular flora alien to Italy are presented. It includes new records, confirmations, exclusions, and status changes for Italy or for Italian administrative regions. Furthermore, three new combinations are proposed. Nomenclatural and distribution updates published elsewhere are provided as Suppl. material 1.

0106 biological sciencesFloraAlien species; Floristic data; Italy; New combinations; NomenclatureAlien speciesnew combinationsPlant ScienceAlienBiology010603 evolutionary biology01 natural sciencesfloristic datalcsh:BotanyAlien speciesAlien species floristic data Italy new combinations nomenclatureNomenclatureAlien specieEcology Evolution Behavior and SystematicsBIO/03 - BOTANICA AMBIENTALE E APPLICATAEcologyAlien species Floristic data Italy New combinations Nomenclaturelcsh:QK1-989ItalyBIO/02 - BOTANICA SISTEMATICASettore BIO/03 - Botanica Ambientale E ApplicatanomenclatureNew combination010606 plant biology & botanyItalian Botanist
researchProduct