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Enregistrement W6943908434 · doi:10.17895/ices.pub.19267613

Workshop on Time-Series Data relevant to Eutrophication Ecological Quality Objectives (WKEUT)

2006· report· en· W6943908434 sur OpenAlexaboutno aff

Notice bibliographique

RevueInternational Council for the Exploration of the Sea (ICES) · 2006
Typereport
Langueen
DomaineEarth and Planetary Sciences
ThématiqueMarine and coastal ecosystems
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBayPhytoplanktonEutrophicationStructural basinMediterranean seaWater qualityMediterranean climateHarbour

Résumé

récupéré en direct d'OpenAlex

The Workshop on Time Series Data relevant to Eutrophication Ecological Quality Objectives [WKEUT] co-chaired by Ted Smayda, USA, and Gunni Ærtebjerg, Denmark, met on 11–14 September 2006 at Sankt Helene, Tisvildeleje, Denmark. Peter Henriksen, Denmark, served as Rapporteur. OSPAR originally co-sponsored the WKEUT Workshop, but then withdrew. WKEUT discussed 17 long-term phytoplankton data sets available from European and relevant North American coastal sites. The criteria used to select the time series for ecological comparison were (1) the data set was to be minimally 10 years in duration, and the sampling frequency of the physical, nutrient and phytoplankton parameters adequate for workshop objectives; (2) the time series habitats and associated phytoplankton processes were to be representative of the different European coastal water environments found; (3) western Atlantic sites of equivalent ecological value were to be included to allow evaluation of possible trans-Atlantic basin similarities in the trends observed at the selected European sites, particularly with regard to climate-driven commonalities. In total, 14 European and 3 North American sites were selected for ecological comparison. The 3 North American sites selected were the Bay of Fundy (Canada), Narragansett Bay (Rhode Island) and the Tampa Bay – Charlotte Bay complex (Florida). European sites included Irish coastal waters, Stonehaven (Scotland), Floedevigen and Gullmar Fjord (Skagerrak), the Kattegat – Oresund – Belt Sea complex, Sylt, Helgoland, the German and Dutch Wadden Sea ecosystem, Belgian coastal waters, Iberian coast and Thau Lagoon in French Mediterranean waters. This selection provided time series data that allowed a comparative analysis of phytoplankton dynamics in response to nutrification and weather-driven changes (proxied by the North Atlantic Oscillation Index) along a latitudinal habitat gradient in European coastal waters that extended from Ireland to the French Mediterranean. The time series sites group into four general habitats: (1) Large open coastal systems – the Skagerrak, Kattegat; Belgian, Dutch and German coastal waters in the southern North Sea (2) Fjord-like or well-mixed shelf waters – Bay of Fundy, Irish coastal waters, Stonehaven, Spanish rias; (3) Shallow systems – the Dutch and German Wadden Sea, Thau Lagoon; (4) Aquacultural sites – Irish coastal waters, Spanish rias, Thau Lagoon, Bay of Fundy.Narragansett Bay is a coastal estuary which does not have a close counterpart in the European sites selected, but has habitat features and phytoplankton responses that overlap with groups 1,2 and 3 listed above. Within the habitat groupings, the Wadden Sea ecosystem is under heavy riverine influence, while the Skagerrak and Kattegat systems are open to North Sea and Baltic watermass intrusions, i.e. to farfield effects of Wadden Sea, Southern Bight of the North Sea and Baltic nutrient loading. The workshop first focused on presentations of the long-term patterns and trends in physical features, nutrients and phytoplankton behavior at the time series locations selected for ecological comparison. This was followed by three invited talks: 1) on the need to evaluate the role of irradiance as a factor regulating the response of phytoplankton to elevated nutrient levels; 2). the influence of time series duration on the detection of the effects of long-term changes in nutrients and climate change on phytoplankton behavior; and 3). the role of modelling in time series analysis, with emphasis on the fact that statistical analyses may reveal parallel trends, but do not explain the underlying mechanisms which are more tractable by mechanistic modelling approaches. The Abstracts and the descriptions of the time series data sets considered are given as Annexes 6 and 7.The time series descriptions and invited lectures led to various conclusions that influenced the working group responses to the Workshop Terms of Reference (Annex 1) and Workshop Questions: (1) trend analyses should be supported by statistical analyses; (2) the techniques used in time series analyses are not standarized, but should vary with the intended use of the analyses, e.g. correlation, prediction, etc.; (3) time series analyses are vulnerable to interpretive error if the sampling frequency, or length of the time series, does not reflect the system components and dynamics; (4) an interaction between statistical analyses and modellers is required, and time series analysis can help to calibrate models.The papers presented at the Workshop will be published in a special issue of the Journal of Sea Research kindly being made available by Dr.Katja Philippart, Chief Editor.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,078
score de la tête « metaresearch » (Gemma)0,078
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,078
Score d'incertitude au seuil0,413

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0780,078
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,003
Bibliométrie0,0030,004
Études des sciences et des technologies0,0010,001
Communication savante0,0080,005
Science ouverte0,0030,007
Intégrité de la recherche0,0030,007
Charge utile insuffisante (le modèle a refusé de juger)0,0100,003

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 Opus0,260
Tête enseignante GPT0,327
Écart entre enseignants0,067 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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

En bref

Citations0
Publié2006
Routes d'admission1
Résumé présentoui

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