Trophic Selective Pressures Organize the Composition of Endolithic Microbial Communities From Global Deserts
Bibliographic record
Abstract
Studies of microbial biogeography are often convoluted by extremely high diversity and differences in microenvironmental factors such as pH and nutrient availability. Desert endolithic (inside rock) communities are relatively simple ecosystems that can serve as a tractable model for investigating long-range biogeographic effects on microbial communities. We conducted a comprehensive survey of endolithic sandstones using high-throughput marker gene sequencing to characterize global patterns of diversity in endolithic microbial communities. We also tested a range of abiotic variables in order to investigate the factors that drive community assembly at various trophic levels. Macroclimate was found to be the primary driver of endolithic community composition, with the most striking difference witnessed between hot and polar deserts. This difference was largely attributable to the specialization of prokaryotic and eukaryotic primary producers to different climate conditions. On a regional scale, microclimate and properties of the rock substrate were found to influence community assembly, although to a lesser degree than global hot versus polar conditions. We found new evidence that the factors driving endolithic community assembly differ between trophic levels. While phototrophic taxa, mostly oxygenic photosynthesizers, were rigorously selected for among different sites, heterotrophic taxa were more cosmopolitan, suggesting that stochasticity plays a larger role in heterotroph assembly. This study is the first to uncover the global drivers of desert endolithic diversity using high-throughput sequencing. We demonstrate that phototrophs and heterotrophs in the endolithic community assemble under different stochastic and deterministic influences, emphasizing the need for studies of microorganisms in context of their functional niche in the community.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".