Search results for "Environmental Data"

showing 10 items of 21 documents

Individual-Based Tracking Systems in Ornithology: Welcome to the Era of Big Data

2016

Technological innovations have led to exciting fast-moving developments in science. Today, we are living in a technology-driven era of biological discovery. Consequently, tracking technologies have facilitated dramatic advances in the fundamental understanding of ecology and animal behaviour. Major technological improvements, such as the development of GPS dataloggers, geolocators and other bio-logging technologies, provide a volume of data that were hitherto unconceivable. Hence we can claim that ornithology has entered the era of big data. In this paper, which is particularly addressed to undergraduate students and starting researchers in the emerging field of movement ecology, I summaris…

0106 biological sciencesData processingComputer sciencebusiness.industryEcology (disciplines)Big dataTracking system010603 evolutionary biology01 natural sciencesData scienceField (computer science)010605 ornithologyEnvironmental dataData loggerOrnitologiaAnimal Science and ZoologyTracking (education)businessEcology Evolution Behavior and SystematicsArdeola
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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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Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks

2019

Abstract The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of an…

0106 biological sciencesMarine conservationMaximum sustainable yieldFish stockFish school010603 evolutionary biology01 natural sciencesAcoustic surveyEnvironmental dataAnchovymedia_common.cataloged_instanceEuropean unionEcology Evolution Behavior and Systematicsmedia_commonEcologybiologySettore INF/01 - Informaticabusiness.industry010604 marine biology & hydrobiologyApplied MathematicsEcological ModelingEnvironmental resource managementPelagic zonebiology.organism_classificationClassificationComputer Science ApplicationsGeographyComputational Theory and MathematicsFishing industryModeling and SimulationbusinessNeural networks
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Moving Toward a Strategy for Addressing Climate Displacement of Marine Resources: A Proof-of-Concept

2020

Realistic predictions of climate change effects on natural resources are central to adaptation policies that try to reduce these impacts. However, most current forecasting approaches do not incorporate species-specific, process-based biological information, which limits their ability to inform actionable strategies. Mechanistic approaches, incorporating quantitative information on functional traits, can potentially predict species- and population-specific responses that result from the cumulative impacts of small-scale processes acting at the organismal level, and can be used to infer population-level dynamics and inform natural resources management. Here we present a proof-of-concept study…

0106 biological sciencesMarine conservationSettore BIO/07 - Ecologia010504 meteorology & atmospheric scienceslcsh:QH1-199.5Engraulis encrasicolusProcess (engineering)Computer scienceClimate changeOcean EngineeringAquatic Sciencelcsh:General. Including nature conservation geographical distributionclimate-informed management; Dynamic Energy Budget model; Engraulis encrasicolus; life-history traits; scenarios; temperature increaseOceanography01 natural sciencesEnvironmental dataDynamic Energy Budget model14. Life underwaterNatural resource managementlcsh:Scienceclimate-informed management0105 earth and related environmental sciencesWater Science and TechnologyGlobal and Planetary Changebusiness.industry010604 marine biology & hydrobiologyEnvironmental resource managementscenariosNatural resourcelife-history traitsAdaptive management13. Climate actionSettore BIO/03 - Botanica Ambientale E Applicatatemperature increaselcsh:QFisheries managementbusiness
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Artificial Neural Networks to assess energy and environmental performance of buildings: An Italian case study

2019

Abstract Approximately 40% of the European energy consumption and a large proportion of environmental impacts are related to the building sector. However, the selection of adequate and correct designs can provide considerable energy savings and reduce environmental impacts. To achieve this objective, a simultaneous energy and environmental assessment of a building's life cycle is necessary. To date, the resolution of this complex problem is entrusted to numerous software and calculation algorithms that are often complex to use. They involve long diagnosis phases and are characterised by the lack of a common language. Despite the efforts by the scientific community in the building sector, th…

Artificial neural networkDecision support systemSettore ICAR/12 - Tecnologia dell'ArchitetturaDecision support toolComputer science020209 energyStrategy and ManagementSettore ICAR/11 - Produzione EdiliziaEnergy balance02 engineering and technologyBuilding energy demandNetwork topologyIndustrial and Manufacturing EngineeringEnvironmental dataEnvironmental impactLife cycle assessmentSoftware0202 electrical engineering electronic engineering information engineeringEnvironmental impact assessmentLife-cycle assessment0505 lawGeneral Environmental ScienceArtificial neural networkRenewable Energy Sustainability and the Environmentbusiness.industry05 social sciencesEnergy consumptionEnvironmental impactsIndustrial engineeringArtificial neural network; Building energy demand; Decision support tool; Energy balance; Environmental impacts; Life cycle assessment050501 criminologybusinessJournal of Cleaner Production
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A Conceptual Review on Using Consequential Life Cycle Assessment Methodology for the Energy Sector

2020

Energy is engaged in the supply chain of many economic sectors; therefore, the environmental impacts of the energy sector are indirectly linked to those of other sectors. Consequential life cycle assessment (CLCA) is an appropriate methodology to examine the direct and indirect environmental impacts of a product due to technological, economic or social changes. To date, different methodological approaches are proposed, combining economic and environmental models. This paper reviews the basic concept of CLCA and the coupling of economic and environmental models for performing CLCA in the energy sector during the period 2006–2020, with the aim to provide a description of the different tools, …

Control and Optimization020209 energySupply chainEnergy (esotericism)Energy Engineering and Power Technology02 engineering and technology010501 environmental sciences01 natural scienceslcsh:TechnologyEnvironmental data0202 electrical engineering electronic engineering information engineeringEconomicsProduct (category theory)economic and environmental modelElectrical and Electronic EngineeringEngineering (miscellaneous)Life-cycle assessment0105 earth and related environmental sciencesSettore ING-IND/11 - Fisica Tecnica AmbientaleRenewable Energy Sustainability and the Environmentlcsh:TEconomic sectorEnvironmental economicsEnergy sectorconsequential life cycle assessment (CLCA) conceptSustainabilityenergy sectorEnergy (miscellaneous)Energies
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Knowledge Extraction from Environmental Data Through a Cognitive Architecture

2008

Wireless Sensor Networks represent a novel technology which is expected to experience a dramatic diffusion thanks to the promise to be a pervasive sensory means; however, one of the issues limiting their potential growth relies in the difficulty of managing and interpreting huge amounts of collected data. This paper proposes a cognitive architecture for the extraction of high-level knowledge from raw data through the representation of processed data in opportune conceptual spaces. The presented framework interposes a conceptual layer between the subsymbolic one, devoted to sensory data processing, and the symbolic one, aimed at describing the environment by means of a high level language. T…

Data processingKnowledge extractionComputer scienceSensor nodeknowledge extraction cognitive architectureCognitive architectureCognitive networkRaw dataWireless sensor networkData scienceEnvironmental data
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An integrated information system for the acquisition, management and sharing of environmental data aimed to decision making

2012

This paper reports the first results of the Project SESAMO - SistEma informativo integrato per l’acquisizione, geStione e condivisione di dati AMbientali per il supportO alle decisioni (Integrated Information System for the acquisition, management and sharing of environmental data aimed to decision making). The main aim of the project is to design and develop an integrated environmental information platform able to provide monitoring services for decision support, integrating data from different environmental monitoring systems (including WSN). This ICT platform, based on a service-oriented architecture (SOA), will be developed to coordinate a wide variety of data acquisition systems, based…

Decision support systemEngineeringIrrigation planningProcess managementbusiness.industryService designSettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiacomputer.software_genreEnvironmental dataData acquisitionICTEnvironmental monitoringEarly warning systemICT; Irrigation planning; Rainfall induced landslidesData miningICT Irrigation planning Rainfall induced landslidesRainfall induced landslidesCommunications protocolbusinessWireless sensor networkcomputerSPIE Proceedings
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Testing the effects of temporal data resolution on predictions of the effects of climate change on bivalves

2014

a b s t r a c t The spatial-temporal scales on which environmental observations are made can significantly affect our perceptions of ecological patterns in nature. Understanding potential mismatches between environmen- tal data used as inputs to predictive models, and the forecasts of ecological responses that these models generate are particularly difficult when predicting responses to climate change since the assumption of model stationarity in time cannot be tested. In the last four decades, increases in computational capacity (by a factor of a million), and the evolution of new modeling tools, have permitted a corresponding increase in model complexity, in the length of the simulations,…

Environmental changeEcologyEcological ModelingDynamic energy budgetClimate changeMarine intertidal zoneMytilus galloprovincialiDarwinian fitneMediterraneanAtmospheric sciencesEnvironmental dataTemporal databaseDarwinian fitnessDynamic Energy Budget modelsDarwinian fitness;Mediterranean;Marine intertidal zone;Dynamic Energy Budget models;Mytilus galloprovincialis;Regional climate modelsMytilus galloprovincialis13. Climate actionDynamic Energy Budget modelTemporal resolutionEnvironmental scienceClimate model14. Life underwaterTemporal scalesRegional climate models
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