Hydrological controls on productivity of regenerating <i>Sphagnum</i> in a cutover peatland
Bibliographic record
Abstract
Abstract Recent research into the production of Sphagnum biomass in extracted peatlands, an alternative to ecological restoration as a post‐industrial use of peatlands, has highlighted the need for an improved understanding of the ecohydrology of Sphagnum regenerating in these environments. Previous work suggested that limited connectivity between surficial layers and the underlying partially decomposed plant matter and peat would result in water stress and inhibited growth. This study links the soil water dynamics of regenerated layers ranging in age from 3 to 43 years and from 3 to 40 cm in thickness to the productivity of Sphagnum in order to determine the hydrological controls on productivity and the optimal range of water content for producing Sphagnum biomass. Productivity was never observed to be limited by insufficient supply of water, including during periods where water table was >40 cm below the surface and periods of 16 days without measured precipitation. While layers of different ages and thicknesses were able to sustain adequate water supply to remain productive under a range of conditions, the ability of layers to transmit water upwards differed greatly. Water content in the near‐surface inhibited productivity during wetter periods, especially at newly regenerating sites where the layer was <5 cm thick. This has important implications for biomass production using the Sphagnum species studied here. Using a mixed linear modelling approach to isolate the effects of water content on variance in productivity from those of other measured variables, a volumetric water content of 0.10 is identified as optimal. Copyright © 2015 John Wiley & Sons, Ltd.
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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) | 0.000 | 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".