Environmental heterogeneity mediates scale-dependent declines in kelp diversity on intertidal rocky shores
Bibliographic record
Abstract
Biodiversity loss is driven by interacting factors operating at different spatial scales. Yet, there remains uncertainty as to how fine-scale environmental conditions mediate biological responses to broad-scale stressors. We surveyed intertidal rocky shore kelp beds situated across a local gradient of wave action and evaluated changes in kelp diversity and abundance after more than two decades of broad scale stressors, most notably the 2013-2016 heat wave. Across all sites, species were less abundant on average in 2017 and 2018 than during 1993-1995 but changes in kelp diversity were dependent on wave exposure, with wave exposed habitats remaining stable and wave sheltered habitats experiencing near complete losses of kelp diversity. In this way, wave exposed sites have acted as refugia, maintaining regional kelp diversity despite widespread local declines. Fucoids, seagrasses and two stress-tolerant kelp species (Saccharina sessilis, Egregia menziesii) did not decline as observed in other kelps, and the invasive species Sargassum muticum increased significantly at wave sheltered sites. Long-term monitoring data from a centrally-located moderate site suggest that kelp communities were negatively impacted by the recent heatwave which may have driven observed losses throughout the region. Wave-sheltered shores, which saw the largest declines, are a very common habitat type in the Northeast Pacific and may be especially sensitive to losses in kelp diversity and abundance, with potential consequences for coastal productivity. Our findings highlight the importance of fine-scale environmental heterogeneity in mediating biological responses and demonstrate how incorporating differences between habitat patches can be essential to capturing scale-dependent biodiversity loss across the landscape.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".