Impact of long-term experimental water level drawdown on vegetation and carbon gas dynamics of boreal mire ecosystems
Bibliographic record
Abstract
Recent paleoecological studies have demonstrated an ongoing drying trend in temperate and boreal peatlands in Europe and in Canada. This drying is likely to alter vegetation and carbon gas exchange with atmosphere. However, to revel the expected change in carbon gas dynamics associated with decrease in water level experimental studies and long-term monitoring are needed. In here we present results from long term experiment in Finland where the impact of water level drawdown (WLD) of ~10 cm on three different peatland sites, two fens and a bog, has been studied since year 2000. Response to WLD differed between the three ecosystem types. In the nutrient rich fen WLD initiated rapid directional succession from sedge dominated system to the dominance of woody species. In the poor fen changes were less drastic: Initially WLD benefitted dwarf scrubs already present at the site, later they were overtaken by pines. Sedges as a group hold their position but Carex species were replaced by Eriophorum. Similarly to sedges, in the moss layer proportions of different Sphagnum moss species changed. Bog vegetation was more stable than fen vegetation. In all the ecosystems methane emissions decreased directly after WLD. In contrast, the response of CO2 dynamics was more complex. While long term net ecosystem exchange decreased to lower level than in controls in all studied ecosystems, the response of photosynthesis and respiration differed between the three ecosystems and between short term and long term. Results show how the response of peatlands to climate change is diverse and emphasize the need to understand what factors regulate the stability and resilience of peatland functioning.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".