High-resolution species distribution modelling of two coastal biogenic habitat-forming species in an Ecologically and Biologically Significant Area of the Bay of Fundy, Canada
Bibliographic record
Abstract
High-resolution species distribution models (SDMs) were developed for two benthic invertebrate species of marine conservation significance across a 113 km2 Ecologically and Biologically Significant Area (EBSA) of the Bay of Fundy, Canada. The stalked tunicate, Boltenia ovifera, and horse mussel, Modiolus modiolus, can form coastal biogenic habitat and are vulnerable to disturbance. A near-seabed imaging survey (depths ranging from 8 to 79 m) provided presence, absence, and abundance data for both species. Boosted Regression Tree SDMs combined these data with 11 environmental variables. Presence-probability distributions were generated; however, abundance patterns could not be adequately modelled. Oblique geographic coordinates, which incorporate location of samples as information, proved useful for predicting species presence, along with seabed rugosity, maximum current speed and bathymetry for B. ovifera, and maximum and minimum current speed along with seabed rugosity for M. modiolus. High-resolution SDMs (in this case, 5-m grid) provide enhanced spatial context for ocean managers towards marine spatial planning in high-use coastal marine environments where bottom contact fisheries access and other coastal development must be balanced against marine conservation objectives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".