Population and Seascape Genomics of the Deep-sea Octocoral Acanella arbuscula
Notice bibliographique
Résumé
Deep-sea corals are under threat from anthropogenic factors such as destruction from bottom contact fishing gear, gas and oil exploration, deep-sea mining, pollution, and climate change. One unique coral, Acanella arbuscula (Isididae), is the only known species of branching coral that is found in large gardens stretching tens of kilometers where its shallow root-like hold fasts anchor it in soft sediment. They are incredibly fragile with fine branches only a few millimeters in diameter. These coral gardens provide habitat for commercially important fish species as well as several invertebrates that live obligately on A. arbuscula. Soft sediment coral gardens are heavily fished in the North Atlantic Ocean, and A. arbuscula are very commonly caught as by-catch. People working in the fisheries have reported gill nets on shore in Newfoundland, Canada containing upwards of one hundred dead Acanella colonies. Due to their importance to the deep-sea ecosystem, their unique nature, and the current threat to their survival, these octocorals are a sensible target for conservation. In order to conserve populations of deep-sea corals, it is imperative that researchers and stakeholders understand the connectivity of populations across the North Atlantic Ocean, because the recovery of areas decimated by bottom contact fishing gear will rely on larval recruitment from local populations. Recruited larvae are unlikely to survive if their source environment is largely different from where they settle, because corals are sensitive to changes in environmental conditions such as temperature, salinity, oxygenation, nutrient availability, and calcium carbonate concentration. Therefore, along with genetic connectivity, it is essential to understand the environmental seascape and what factors are contributing to local adaptation in populations. This research was carried out in three stages. First, the most beneficial methods of extracting DNA from deep-sea corals were investigated. Five different extraction methods were compared in the search for a method that produced high quality genomic DNA. The salting-out method and plant mini kit extractions were found to be the best methods for Acanella arbuscula. Second, Single Nucleotide polymorphisms (SNPs) generated from ultra-conserved elements (UCE) sequencing were used to investigate the connectivity of 362 colonies from 33 sites spanning depths of 60-2,300 m across nearly the entire geographical range of A. arbuscula from Greenland, Canada, Scotland, Ireland, and Spain. Four genetic clusters emerged, and trans-Atlantic connectivity of these octocorals was discovered with high levels of geneflow between Canadian samples and European samples at similar depths. A barrier to geneflow was discovered in the Eastern Atlantic where samples collected shallower than 1,200m showed almost no genetic connectivity to samples collected deeper than 1,200 m depth. Additionally, distinct genetic cluster formed exclusively for samples collected in the Bay of Biscay (Spain) around 860 m was identified. It is suspected that warm highly saline Mediterranean outflow water traveling northward creates a barrier to geneflow in this region. Finally, we used the SNPs generated from this study to investigate local adaptation to environmental factors across the 33 study sites in the North Atlantic. We compared 12 environmental variables such as seafloor temperature, oxygenation, nutrient availability, salinity, and pH across all of the sites with the genotypic diversity of the corals found at those sites for each UCE SNP marker. Twelve significant environment marker associations were found, and all of them were associated with seafloor temperature. Temperature on the seafloor appears to be the main driver of local adaptation in A. arbuscula. Using the associations between genotype and the environmental variables measured, it was possible to model the potential genotype for the entire study area and predict potential stepping-stones to connectivity. The combination of connectivity and migration data with local adaptation data was used to point out areas that are potentially vulnerable to climate change and destruction from direct anthropogenic threats. Some broad suggestions were made for potential MPA locations to help maintain populations in the North Atlantic such as Eastern Greenland, Southern Iceland, the Celtic Sea, and Cantabrian Sea.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».