Biomass and nutrient responses of a clonal tundra sedge to climate warming
Bibliographic record
Abstract
We explored how climate change affects biomass, nutrient status, and late-season resource-allocation patterns in a rhizomatous tundra sedge, and how differentiation and development of ramets may constrain plant responses. We simulated climate warming for 5 years at a subarctic–alpine tundra site by using open-top chambers before destructively sampling clonal fragments of the dominant and widespread sedge, Carex bigelowii Torr. ex Schwein. We found differential growth response among ramets to experimental warming, but reduced aboveground tissue nutrient concentrations across entire clonal systems. Warming did not affect biomass allocation within ramets, but it did change biomass allocation among developmental stages and ramet types (i.e., long- and short-rhizome ramets, termed guerrilla and phalanx). A positive warming effect on biomass was mostly confined to mature vegetative ramets and the response of individual plant parts was significantly greater for guerrilla ramets than for phalanx ramets. Despite the differential biomass response, warming significantly reduced nitrogen and phosphorus concentrations in aboveground tissues across all developmental stages within the integrated clonal system (10% decrease in green leaf nitrogen concentration, 18%–25% decrease in phosphorus concentration). However, late-season nutrient concentrations in storage organs (rhizomes) were not affected. Nutrient pools significantly increased in mature vegetative ramets, especially those of the guerrilla type, apparently as a result of both redistribution of nutrients among ramets and increased nutrient uptake. At the community level, estimated aboveground biomass per unit area was similar in warmed and control plots. Rhizome and dead-leaf mass and all nutrient pools per unit area were 10%–20% less in warmed plots than in controls. The ecosystem implications of the responses of C. bigelowii, a forage species favoured by a range of herbivores, to warming are a reduction in forage quality without compensation in terms of quantity and, eventually, a reduction in litter quality.
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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".