Global beta diversity patterns of microbial communities in the surface and deep ocean
Bibliographic record
Abstract
Abstract Aim Dispersal and environmental gradients shape marine microbial communities, yet the relative importance of these factors across taxa with distinct sizes and dispersal capacity in different ocean layers is unknown. Here, we report a comparative analysis of surface and deep ocean microbial beta diversity and examine how these patterns are tied to oceanic distance and environmental gradients. Location Tropical and subtropical oceans (30°N–40°S). Time period 2010–2011. Major taxa studied Prokaryotes and picoeukaryotes (eukaryotes between 0.2 and 3 μm). Methods Beta diversity was calculated from metabarcoding data on prokaryotic and picoeukaryotic microbes collected during the Malaspina expedition across the tropical and subtropical oceans. Mantel correlations were used to determine the relative contribution of environment and oceanic distance driving community beta diversity. Results Mean community similarity across all sites for prokaryotes was 38.9% in the surface and 51.4% in the deep ocean, compared to mean similarity of 25.8 and 12.1% in the surface and deep ocean, respectively, for picoeukaryotes. Higher dispersal rates and smaller body sizes of prokaryotes relative to picoeukaryotes likely contributed to the significantly higher community similarity for prokaryotes compared with picoeukaryotes. The ecological mechanisms determining the biogeography of microbes varied across depth. In the surface ocean, the environmental differences in space were a more important factor driving microbial distribution compared with the oceanic distance, defined as the shortest path between two sites avoiding land. In the deep ocean, picoeukaryote communities were slightly more structured by the oceanic distance, while prokaryotes were shaped by the combined action of oceanic distance and environmental filtering. Main conclusions Horizontal gradients in microbial community assembly differed across ocean depths, as did mechanisms shaping them. In the deep ocean, the oceanic distance and environment played significant roles driving microbial spatial distribution, while in the surface the influence of the environment was stronger than oceanic distance.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".