Do Larval Supply and Recruitment Vary among Chemosynthetic Environments of the Deep Sea?
Bibliographic record
Abstract
BACKGROUND: The biological communities that inhabit chemosynthetic environments exist in an ephemeral and patchily distributed habitat with unique physicochemical properties that lead to high endemicity. Consequently, the maintenance and recovery from perturbation of the populations in these habitats is, arguably, mainly regulated by larval supply and recruitment. METHODOLOGY/PRINCIPAL FINDINGS: WE USE DATA FROM THE PUBLISHED SCIENTIFIC LITERATURE TO: (1) compare the magnitudes of and variability in larval supply and settlement and recruitment at hydrothermal vents, seeps, and whale, wood and kelp falls; (2) explore factors that affect these life history processes, when information is available; and (3) explore taxonomic affinities in the recruit assemblages of the different chemosynthetic habitats, using multivariate statistical techniques. Larval supply at vents can vary across segments by several orders of magnitude for gastropods; for bivalves, supply is similar at vents on different segments, and at cold seeps. The limited information on larval development suggests that dispersal potential may be highest for molluscs from cold seeps, intermediate for siboglinids at vents and lowest for the whale-bone siboglinid Osedax. Settlement is poorly studied and only at vents and seeps, but tends to be highest near an active source of emanating fluid in both habitats. Rate of recruitment at vents is more variable among studies within a segment than among segments. Across different chemosynthetic habitats, recruitment rate of bivalves is much more variable than that of gastropods and polychaetes. Total recruitment rate ranges only between 0.1 and 1 ind dm(-2) d(-1) across all chemosynthetic habitats, falling above rates in the non-reducing deep sea. The recruit assemblages at vents, seeps and kelp falls have lower taxonomic breadth, and include more families and genera that have many species more closely related to each other than those at whale and wood falls. Vents also have the most uneven taxonomic structure, with fewer recruits represented by higher taxonomic levels (phyla, orders, classes) compared to seeps and wood and kelp falls, whereas the opposite is true at whale falls. CONCLUSIONS/SIGNIFICANCE: Based on our evaluation of the literature, the patterns and regulatory factors of the early history processes in chemosynthetic environments in the deep sea remain poorly understood. More research focused on these early life history stages will allow us to make inferences about the ecological and biogeographic linkages among the reducing habitats in the deep sea.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".