Current Patterns of Macroalgal Diversity and Biomass in Northern Hemisphere Rocky Shores
Bibliographic record
Abstract
Latitudinal gradients in species abundance and diversity have been postulated for nearshore taxa but few analyses have been done over sufficiently broad geographic scales incorporating various nearshore depth strata to empirically test these gradients. Typically, gradients are based on literature reviews and species lists and have focused on alpha diversity across the entire nearshore zone. No studies have used a standardized protocol in the field to examine species density among sites across a large spatial scale while also focusing on particular depth strata. The present research used field collected samples in the northern hemisphere to explore the relationships between macroalgal species density and biomass along intertidal heights and subtidal depths and latitude. Results indicated no overall correlations between either estimates of species density or biomass with latitude, although the highest numbers of both were found at mid-latitudes. However, when strata were examined separately, significant positive correlations were found for both species numbers and biomass at particular strata, namely the intertidal ones. While the data presented in this paper have some limitations, we show that latitudinal macroalgal trends in species density and biomass do exist for some strata in the northern hemisphere with more taxa and biomass at higher latitudes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".