Ephemeral-habitat colonization and neotropical species richness of Caenorhabditis nematodes
Bibliographic record
Abstract
BACKGROUND: The drivers of species co-existence in local communities are especially enigmatic for assemblages of morphologically cryptic species. Here we characterize the colonization dynamics and abundance of nine species of Caenorhabditis nematodes in neotropical French Guiana, the most speciose known assemblage of this genus, with resource use overlap and notoriously similar external morphology despite deep genomic divergence. METHODS: To characterize the dynamics and specificity of colonization and exploitation of ephemeral resource patches, we conducted manipulative field experiments and the largest sampling effort to date for Caenorhabditis outside of Europe. This effort provides the first in-depth quantitative analysis of substrate specificity for Caenorhabditis in natural, unperturbed habitats. RESULTS: We amassed a total of 626 strain isolates from nine species of Caenorhabditis among 2865 substrate samples. With the two new species described here (C. astrocarya and C. dolens), we estimate that our sampling procedures will discover few additional species of these microbivorous animals in this tropical rainforest system. We demonstrate experimentally that the two most prevalent species (C. nouraguensis and C. tropicalis) rapidly colonize fresh resource patches, whereas at least one rarer species shows specialist micro-habitat fidelity. CONCLUSION: Despite the potential to colonize rapidly, these ephemeral patchy resources of rotting fruits and flowers are likely to often remain uncolonized by Caenorhabditis prior to their complete decay, implying dispersal-limited resource exploitation. We hypothesize that a combination of rapid colonization, high ephemerality of resource patches, and species heterogeneity in degree of specialization on micro-habitats and life histories enables a dynamic co-existence of so many morphologically cryptic species of Caenorhabditis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".