Species richness and diversity in different functional groups across environmental stress gradients: a model for marine rocky shores
Bibliographic record
Abstract
We present a model predicting how the species richness and diversity within benthic functional groups should vary across the full environmental stress gradient across which a regional biota from marine rocky shores can occur. Built upon previous models, our model makes predictions for sessile species (macroalgae and filter feeders), herbivores, and carnivores. We tested some of its predictions by surveying vertical (intertidal elevation) and horizontal (wave exposure and ice scour) stress gradients in northern Nova Scotia, Canada. Because of harsh winter conditions, these coasts only depict approximately intermediate‐to‐high yearly levels of stress that the cold‐temperate, rocky intertidal biota from the northwestern Atlantic can experience. The observed trends matched predictions for sessile species in 75% of the studied gradients, and showed a moderate agreement for herbivores and carnivores only when they were combined as mobile consumers. Agreement meant that both richness and diversity increased from the most stressful to the most benign habitats that can be found in northern Nova Scotia. Also as predicted, sessile species generally showed a faster rate of increase in richness than mobile consumers. Our model also predicted a higher overall richness for sessile species than for mobile consumers, which was true by a factor of 3. Therefore, our model may constitute a useful tool to understanding community composition as a function of abiotic stress, which may in turn facilitate studies on community functioning. Model predictions for lower stress ranges could be tested on more southern shores where the same regional biota occurs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".