The global distribution of Isoprenoidal Glycerol Dialkyl Diethers (isoGDDs) is consistent with a predominant degradation origin
Bibliographic record
Abstract
Glycerol dialkyl diethers (GDDs) are membrane lipids and a variation of the more commonly known glycerol dialkyl glycerol tetraethers (GDGTs). GDGTs include both archaeal and bacterial membrane lipids that are both frequently used for paleoclimate reconstruction in a range of terrestrial and aquatic environments. In contrast to GDGTs, GDDs lack one of the terminal glycerol moieties. Although both isoprenoidal (iso) and branched (br) GDDs have been found, this study focuses on isoGDDs. These lipids have been found in a few terrestrial and aquatic environments. However, the origin of isoGDDs is debated and the extent of their distribution across the surface of the Earth is poorly constrained. Based on a few single site studies, previous authors hypothesised that isoGDDs are degradation products of isoGDGTs, but more recent studies that isolated isoGDDs from cultured nitrososphaerota (formerly thaumarchaeota) proposed a biological source through direct archaeal biosynthesis. Here we compiled a global dataset of isoGDD and isoGDGT abundance in environmental samples to thoroughly investigate the distribution of isoGDDs and the correlation with isoGDGTs on a global scale and across a variety of environments (peat, mineral soils, lake sediments, and marine sediments). We find that isoGDDs are present in most samples that we analysed. Their abundance is strongly proportional to isoGDGT abundance (r2 = 0.85), dominated by the GDGT-crenarchaeol/GDD-crenarchaeol ratio (r2 = 0.94) and supported by individual compound isoGDGT/isoGDD ratios (r2 = 0.56–0.94). In addition, the degree of cyclisation of isoGDDs, reflected in the ring index, is positively correlated (r2 = 0.84) with that of isoGDGTs across all environments. We conclude that isoGDDs are abundant on the surface of the Earth and predominantly originate from the degradation of isoGDGTs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".