Experimental and mensurative data on the abundance of primary producers and consumers from intertidal habitats in Canada
Bibliographic record
Abstract
Our data set describes the abundance of seaweeds and invertebrates found in rocky intertidal habitats on the Atlantic coast of Nova Scotia, Canada. One subset of data resulted from a manipulative experiment that tested the effects of macroalgal ecosystem engineers (Ascophyllum nodosum and Fucus spp.) on the richness, diversity, and composition of understory communities along the environmental stress gradient that occurs across elevations because of tides. Abundance data for all understory taxa are provided for 120 quadrats that characterized two macroalgal canopy treatments (canopy vs. no canopy) and three elevation zones (high, middle, and low). Another subset of data resulted from a mensurative study done regionally based on four locations spanning 350 km of coastline. Data from that study describe the abundance of seaweeds (including the canopy-forming species mentioned above) and invertebrates found at three elevation zones (high, middle, and low) for a total of 1170 quadrats. Both the manipulative experiment and the mensurative study revealed that intertidal macroalgal canopies affect the structure of benthic communities at high and middle elevations (where the canopies ameliorate the otherwise harsh conditions during low tides) but have no effects at low elevations (where conditions remain mild during low tides due to short aerial exposures). Because of its taxonomic amplitude and coverage of a wide environmental stress gradient, our data set is potentially useful to address in novel or infrequent ways other broad ecological issues, such as abundance–occupancy relationships, species co-occurrence, species abundance distributions, dominance and rarity, spatial scales of population and community variability, and distribution of phylogenetic diversity.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".