Defining Distinct Nearshore Marine Biotopes Coastwide in British Columbia
Notice bibliographique
Résumé
Nine nearshore epibenthic biotopes along with three physiotopes based on environmental conditions were defined and mapped for the coast of BC. The definition of the biotopes includes correlated species with seven environmental conditions (substrate, slope, depth, exposure, temperature, salinity, and tidal current) occurring within each biotope. Three physiotopes were defined as unique environmental areas and were not defined using species data. 72 Species Distribution Models (single-SDMs) were included in the analysis to define the biotopes. Many species included in the survey are widely distributed across the BC coast and may not be useful in differentiating biotopes (e.g., red sea urchin, Mesocentrotus franciscanus, was correlated with five biotopes) therefore indicator species were not able to be identified. After 10 years of conducting the benthic habitat mapping (BHM) survey, gaps in our understanding of nearshore species still remain. We lack knowledge of many nearshore species distributions, what drives their distribution, and what species they are associated with. Continued data collection could refine the species list and improve biotope classification. Additional species, including rarer species, should be considered in future surveys and data collection should focus on lower-level taxonomy (i.e., genus, species). There are limited environmental predictors available for the nearshore. Many predictors used in marine SDMs are derived from oceanographic models with kilometre scale resolution which only provide broad-scale species-environmental relationships. The scale disparity between the survey data and environmental covariates may limit the utility of oceanographic variables in modeling (i.e., no relationships are found) or restricts their applicability to finer scales. Out of the seven environmental covariates, only three (substrate, depth, and exposure), have a range of values that are not overlapping across all biotopes. Except for slope, the remaining predictors (salinity, temperature and current) are derived from oceanographic models for which the nearshore is not well resolved. This indicates that higher predictor resolution might result in better resolved relationships with species distribution, as well as better definitions of the biotopes, and\or an increase in the number of biotopes. While the maps provide valuable insights into biotope distribution, they should be interpreted with an understanding of their resolution limitations and the potential for finer-scale variability in nearshore environments. Over the course of the 10 years of this project, the team consisted of numerous biologists who were very experienced in species identification, with extensive experience working in intertidal and subtidal habitats throughout the BC coast. Their experience and knowledge were invaluable for validating the resulting biotopes in terms of species inclusion and environmental associations. The analysis is reliable and repeatable and, as such, the biotope outputs can be used to support management decisions, including environmental incidents and marine spatial planning initiatives, in the Pacific Region.
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 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».