The effects of drought on <i>Sphagnum</i> moss species and the implications for hydrology in peatlands
Bibliographic record
Abstract
Summary Peatlands store more carbon (C) than any other terrestrial ecosystem and as a C sink they are vital to mitigating climate change. The keystone of many peatland ecosystems is Sphagnum , a bryophyte genus of c . 350 species found on every continent except Antarctica. With climate change, many peatlands face increasing frequency and severity of drought. How Sphagnum responds to and recovers from drought will be key to sustaining peatlands over the coming decades. Here, we synthesise the latest evidence for how interactions of drought with Sphagnum affect peatland functioning. We discuss how Sphagnum traits, from the cellular to the community, control its ecohydrology and what changes occur during drought. We detail the effects of drought on Sphagnum C cycling and biochemistry, including photosynthesis, growth, respiration and methane (CH 4 ) fluxes. We also highlight drought resilience and tipping points for Sphagnum physiology and at the ecosystem level. The implications of Sphagnum drought responses for peatland hydrology, restoration and wildfires are also outlined. Finally, we identify knowledge gaps and propose some urgent questions which should be addressed in future research.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".