Spatial heterogeneity of the seed bank at a peat lake in Australia
Bibliographic record
Abstract
Context In the face of global biodiversity decline, understanding the effects of potential climate change on the persistence of soil seed banks is critical, especially in wetland ecosystems. Although studies have explored the response of soil seed banks to changes in periodically inundated wetlands, little is understood about seed banks in peatlands. Aims We examined the spatial variability of soil seed banks during a recent drying event, the last of which occurred over 60 years ago. Methods We sampled the soil seed bank in three zones away from the centre of the dry lakebed at five depth intervals down to 50 cm. Key results Our study showed that the seed bank distribution in a peatland reflected the wetland plants examined at the time of the drying event. The distribution of seeds was along a flood gradient, suggesting an interaction between historical inundation intensity (Zone) and vertical (Depth) distribution of seeds, and correlated with the extant vegetation, as determined during a significant water drawdown period. Conclusions and implications This study shows that the ability of seeds to survive burial, either submerged or desiccated, even after long periods, may prove to have advantages for plant survival and establishment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".