MétaCan
Menu
Retour à la cohorte
Enregistrement W3155127060 · doi:10.1109/ieeeconf38699.2020.9389268

Cabled Community Observatories for Coastal Monitoring - Developing Priorities and Comparing Results

2020· article· en· W3155127060 sur OpenAlexaffabout
Ryan Flagg, Tanner J. Owca, Lucianne M. Marshall, A. M. Snauffer, Jeannette Bedard, Maia Hoeberechts

Notice bibliographique

RevueGlobal Oceans 2020: Singapore – U.S. Gulf Coast · 2020
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueMarine Biology and Ecology Research
Établissements canadiensOcean Networks Canada Society
Organismes subventionnairesnon disponible
Mots-clésCitizen scienceEnvironmental resource managementShoreStewardship (theology)Environmental scienceOceanographyRemote sensingMarine spatial planningMarine ecosystemGovernment (linguistics)GeographyEcosystemGeologyEcology

Résumé

récupéré en direct d'OpenAlex

Coastal marine environments are some of the most bio-rich ecosystems on earth, providing food and livelihoods for many coastal community members. Yet, many of these coastal environments are threatened by anthropogenic and climate stressors resulting in the need for robust monitoring to inform current and future environmental stewardship decisions. While traditional oceanographic sampling is typically done from a research vessel, this is often costly and logistically difficult for scientists and coastal communities alike. Ocean Networks Canada (ONC) in partnership with communities along Canada's western, eastern, and Arctic coasts have continued to advance a number of solutions for long-term marine monitoring. Here, we discuss the development and implementation of seafloor cabled observatories, which collect continuous real-time data intended to help inform government, industry, and communities, and advance the scientific understanding of coastal environments. The strategic placement of these observatories, with collaboration from community partners, allows for high resolution datasets in both significant and remote regions of Canada. Each underwater platform has the potential to house a variety of instruments, which are connected to an underwater cable for real-time data transmission to the surface and which often allows the instruments to be powered from shore. Shore stations provide connectivity to the instruments and also provide an opportunity to host other shore-based instruments that can complement the underwater suite. Since large amounts of data are more easily and efficiently stored and transferred continuously rather than with battery-dependent autonomous systems, these observatory systems are well suited for collecting year-round, high temporal-resolution data. Thisallows for traditional physical oceanographic parameters to reveal environmental changes not only over annual and decadal time scales but also over diurnal (and shorter) time scales. These systems are more efficient at supporting year-round deployments of hydrophones, active acoustic instruments, surface and subsea video cameras, radars, and other high data-density instruments than their autonomous counterparts. Data from ONC's network of observatories are relayed from shore stations over the internet via fibre, cellular, or satellite connection to the Oceans 2.0 data management system. Oceans 2.0 supports open data access, detailed metadata support, sensor health monitoring, QA/QC of the data, data products, and a wide range of web services. All of these factors together serve to fill several major data and knowledge gaps to better understand our dynamic coastal waters. These community-based platforms have proven to be excellent tools for advancing and supporting ocean literacy and education resources by providing valuable and engaging resources to educators around the world, for all grade levels from primary education to postgraduate studies. They have also been used successfully as technology incubators where manufacturers and research groups can trial new sensor technologies in a real-world setting that is relatively easy to access and where they can leverage the continuous, real-time data stream and sensor-health monitoring that allows for instantaneous feedback on sensor performance. Finally, ONC's broad vision includes providing knowledge and leadership that deliver solutions to society in general; community-based cabled observatories are one of the means to support this vision. ONC's Community-Based Monitoring team usesthese cabled “community observatories” as one of many possible complementary tools when working directly with leadership in coastal communities, including Indigenous communities, environmental stewardship organizations, non-governmental organizations, and Municipal, Provincial, Federal government departments, and researchers, to implement local environmental monitoring programs. This paper will present a summary of multiple community observatory installations and will compare them to one another. It will discuss the various inputs and priorities that have influenced the development of each of the systems and how the data has been used in each scenario.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,083
Tête enseignante GPT0,282
Écart entre enseignants0,199 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueGlobal Oceans 2020: Singapore – U.S. Gulf CoastMême sujetMarine Biology and Ecology ResearchTravaux en français237 207