Dissolved organic carbon (DOC) is essential to balance the metabolic demands of North-Atlantic deep-sea sponges
Bibliographic record
Abstract
Abstract Sponges are ubiquitous components of various deep-sea habitats, including cold water coral reefs and deep-sea sponge grounds. Despite being surrounded by oligotrophic waters, these ecosystems are known to be hotspots of biodiversity and carbon cycling. To assess the role of sponges in the carbon cycling of deep-sea ecosystems, we studied the energy budgets of six dominant deep-sea sponges (the hexactinellid species Vazella pourtalesi , and demosponge species Geodia barretti, Geodia atlantica, Craniella zetlandica, Hymedesmia paupertas and Acantheurypon spinispinosum) in an ex situ aquarium setup. Additionally, we determined morphological metrics for all species (volume, dry weight (DW), wet weight (WW), carbon (C) content, and ash-free dry weight (AFDW)) and provide species-specific conversion factors. Oxygen (O 2 ) removal rates averaged 3.3 ± 2.8 µ mol O 2 DW sponge h −1 (all values mean ± SD), live particulate (bacterial and phytoplankton) organic carbon (LPOC) removal rates averaged 0.30 ± 0.39 µ mol C DW sponge h −1 and dissolved organic carbon (DOC) removal rates averaged 18.70 ± 25.02 µ mol C DW sponge h −1 . Carbon mass balances were calculated for four species ( V. pourtalesi, G. barretti, G. atlantica and H. paupertas ) and revealed that the sponges acquired 1.3–6.6 times the amount of carbon needed to sustain their minimal respiratory demands. These results indicate that irrespective of taxonomic class, growth form, and abundance of microbial symbionts, DOC is responsible for over 90 % of the total net organic carbon removal of deep-sea sponges and allows them to sustain in otherwise food-limited environments on the ocean floor.
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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 | 0.000 | 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".