Kelp dynamics and environmental drivers in the southern Salish Sea, British Columbia, Canada
Bibliographic record
Abstract
The impacts of local-scale temperatures and winds on bull kelp ( Nereocystis luetkeana ) vary along a coastal gradient, while also being influenced by corresponding global-scale oceanic conditions. Around Vancouver Island and the Gulf Islands, BC, Canada, bull kelp floating canopies were mapped using high-resolution imagery from 2005 to 2022, whereas the largest kelp bed of the area was mapped with medium-resolution imagery spanning from 1972 to 2022. In order to understand spatial patterns of kelp resilience, the abiotic characteristics were used to organize the coastline into four clusters, ranging from the coldest and most exposed coast to a more sheltered and warmer location. Additionally, local-scale sea surface temperatures, winds, and marine heatwaves were categorized by global-scale temporal conditions defined by the positive/negative oceanic oscillations of the Oceanic Niño Index (ONI) and Pacific Decadal Oscillation (PDO). Comparing spatial and temporal categories, we observed that years with positive ONI and PDO, in particular the 2014–2019 period, concentrated most of the marine heatwaves and the spring temperature peaks. However, there are some indications of an underlying long-term trend. During the period 2020–2022, when ONI and PDO were negative, summer temperatures kept increasing and wind displayed a higher frequency of extreme events. Mapped kelp showed different trends to these stressors: the coldest and most exposed area showed a constant presence of kelp during the entire period, even dating back to 1972. Warmer and semi-sheltered coasts increased in kelp percentage cover after the positive ONI+PDO period of 2014–2019, and the coasts facing the Strait of Georgia displayed a lower kelp percentage cover than the other clusters. In summary, bull kelp was resilient in the study area, but for different reasons: colder and more exposed coasts had the most favorable conditions for kelp, but warmer and more sheltered coastal kelp beds may have benefited from wind-wave forcing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".