Ecological partitioning and diversity in tropical planktonic foraminifera
Bibliographic record
Abstract
BACKGROUND: Ecological processes are increasingly being viewed as an important mode of diversification in the marine environment, where the high dispersal potential of pelagic organisms, and a lack of absolute barriers to gene flow may limit the occurrence of allopatric speciation through vicariance. Here we focus on the potential role of ecological partitioning in the diversification of a widely distributed group of marine protists, the planktonic foraminifera. Sampling was conducted in the tropical Arabian Sea, during the southwest (summer) monsoon, when pronounced environmental conditions result in a strong disparity in temperature, salinity and productivity between distinct northern and southern water masses. RESULTS: We uncovered extensive genetic diversity within the Arabian Sea planktonic foraminifera, identifying 13 morphospecies, represented by 20 distinct SSU rRNA genetic types. Several morphospecies/genetic types displayed non-random biogeographical distributions, partitioning between the northern and southern water masses, giving a strong indication of independent ecological adaptations. CONCLUSIONS: We propose sea-surface primary productivity as the main factor driving the geographical segregation of Arabian Sea planktonic foraminifera, during the SW monsoon, with variations in symbiotic associations possibly playing a role in the specific ecological adaptations observed. Our findings suggest that ecological partitioning could be contributing to the high levels of 'cryptic' genetic diversity observed within the planktonic foraminifera, and support the view that ecological processes may play a key role in the diversification of marine pelagic organisms.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".