Aggregate patterns of macrofaunal diversity: An interocean comparison
Bibliographic record
Abstract
Abstract Aim While geographical patterns of species richness are reasonably well explored for single well‐studied taxa, less is known about aggregate patterns of total richness for major biomes and their environmental correlates. Here we analyse continental‐scale aggregate patterns of macrofaunal diversity for sandy beaches, a dominant habitat along the Atlantic and Pacific coasts of South America. Location South American coastlines. Time period Present day (data amassed from studies performed since 1971). Major taxa studied Benthic macrofauna, including crustaceans, polychaetes and molluscs. Methods We compiled richness information for all macrofaunal groups on 263 sandy beaches in South America using standard criteria. We further matched these data with environmental variables including sea surface temperature (SST), chlorophyll a , grain size, beach slope, tide range and various morphometrics. We used generalized linear mixed models to relate environmental factors to observed variation in total macrofaunal richness across all beaches, testing competing hypotheses about environmental correlates and possible drivers of latitudinal diversity. Results Macrofaunal richness decreased from tropical to temperate beaches in the Pacific and followed a parabolic trend in the Atlantic, with the highest biodiversity found at tropical and mid‐latitudinal bands. Beach slope, tidal range and chlorophyll a mostly explained latitudinal trends in macrofaunal richness, followed by grain size, SST and ocean basin. Main conclusions This study indicates that richness of macrofaunal species at a given beach is most closely related to characteristics of the physical habitat, such as beach slope, area and grain size. At this scale, planktonic food supply also appeared to be more important than temperature, which is a dominant explanatory variable of global‐scale variation in species richness.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".