Geographic distance, sedimentation, and substrate shape cryptic crustose coralline algal assemblages in the world’s largest subtropical intertidal algal reef
Bibliographic record
Abstract
Algal reefs, concreted by crustose coralline algae (CCA), are the main biotic reefs in temperate waters but rare in the subtropics and tropics. The world's largest known intertidal algal reef in the subtropics is the Taoyuan Algal Reef (TAR) located in the northwestern coast of Taiwan. The biodiversity and ecology of the TAR are scarcely explored, and now the reef is imperiled by industrialization. Here, we document cryptic species of CCA in Taiwan, particularly the TAR, by sequencing the psbA genes of over 1800 specimens collected across Taiwan. We also examine the ecological background of the TAR by surveying its benthic composition and measuring its environmental parameters. Our data reveal that the TAR harbours a high diversity of cryptic CCA species (27 molecular operational taxonomic units, or mOTUs), many of which are potentially new to science (18 mOTUs) and/or endemic to the TAR (9 mOTUs). Comparing the CCA species inventory of the TAR with the rest of Taiwan shows that the TAR represents a unique hotspot of CCA taxa in the waters of Taiwan. Our analyses show that variation in the CCA assemblages in the TAR is associated with geographic distance, sedimentation, and substrate type (for example, reef vs. hermit crab shell), suggesting that dispersal limitation and contemporary environmental selection shape the CCA assemblages in the TAR. The data from this study can inform the monitoring of human impacts on the health of the TAR and contribute to our understanding of the ecological processes underlying algal reef development.
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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 | 0.000 | 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 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".