Exploring Zooplankton Community Structure and Environmental Relationships in a Glacial-Terminating Fjord in Southeast Greenland
Notice bibliographique
Résumé
High-latitude oceans are among the most vulnerable regions to a warming climate. Historically covered by sea ice for much of the year, these areas are now experiencing accelerated environmental changes, such as increasing atmospheric and ocean temperatures, resulting in rapid glacial melt and calving. Sermilik Fjord, located in southeastern Greenland, is an Arctic fjord system influenced by marine-terminating glaciers and characterized by complex bathymetry and distinct water masses, including warm, saline Atlantic Water (AW), cold, saline polar water, and cold, fresh subglacial meltwater. These characteristics create a diverse and productive ecosystem, with unique physical characteristics among the inner fjord, outer fjord, shelf, and slope/off-shelf regions.This study aims to explore and compare zooplankton community assemblages across Sermilik Fjord, specifically focusing on the presence or absence of AW in the surface waters (40-200 m depth). This research will determine relationships between zooplankton community composition and AW, define community structure for each region, and identify indicator species associated with specific regions or water masses. Field collections were conducted using 29 samples from a bongo sampler deployed to a depth of 100 m. Vertical profiles of temperature, salinity, and other parameters were collected using a CTD, providing a detailed understanding of the water column structure and the presence of different water masses.About half of all stations that zooplankton were collected at had AW present in the surface waters. A hierarchical cluster analysis determined five key zooplankton community clusters in the fjord, and distinct separation between communities that had a presence or absence of AW in the surface waters. Zooplankton statistical analyses will be accomplished through a NMDS on community clusters. SIMPER analysis identified euphausiids and chaetognaths as key contributors (over 50%) to community dissimilarity. Diversity analysis using Shannon and Simpson indices revealed considerable variability in zooplankton community composition across samples. Low Shannon values (e.g., Upper fjord with H' = 0.032 and Mid-fjord with H’ = 0.011) and high Simpson values (e.g., Fjord Mouth, D = 0.65) indicated dominance by a single species, suggesting low community diversity. In contrast, samples near the glacier-terminus (H' = 1.10, D = 0.66) and coast (H' = 0.87, D = 0.55) exhibited higher diversity and evenness. These findings highlight areas with both high species dominance and more evenly distributed communities, reflecting spatial differences in zooplankton community structure. Preliminary results indicate potential gradients in community composition, with warmer water species and higher zooplankton abundance associated with AW presence in surface waters. Distinct communities were also observed between regions influenced by glacial meltwater and those characterized by warmer AW influx.This work contributes to our understanding of the ecological dynamics of Greenland's fjords in response to climate change, highlighting the importance of zooplankton as key players in Arctic marine ecosystems. It further emphasizes the challenges and urgency of studying these vulnerable regions, as they undergo profound shifts in their physical and biological environments.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».