Warming and shrub encroachment decrease decomposition in arid alpine and subalpine ecosystems
Bibliographic record
Abstract
Climate change is shifting species distributions and altering plant community composition worldwide. For instance, with rising temperatures shrubs are encroaching into alpine ecosystems, resulting in important implications for ecosystem functioning. In particular, woody-plant encroachment could slow decomposition in systems traditionally dominated by herbaceous species. To evaluate how litter decomposition responded jointly to warming and shrub presence, we conducted a passive warming chamber experiment in subalpine and alpine plant communities in the White Mountains of California. Passive warming chambers were placed over plots with and without the range-expanding sagebrush Artemisia rothrockii at two elevations. Litter from A. rothrockii and the common perennial herb Trifolium andersonii decomposed for two years under the experimental treatments. Nitrate availability was measured with ion-exchange resins during the same time period. Warming decreased decomposition rates overall, associated with decreased soil moisture, but did not influence soil nitrate availability. Sagebrush presence decreased both decomposition rates and nitrate availability. Hence, future warming in this system will likely reduce decomposition rates, both directly and indirectly, via shrub encroachment. However, impacts on nutrient mineralization are less clear. These findings highlight how shifting species composition, through processes such as range expansions, can influence ecosystem responses to climate change.
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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) | 0.001 | 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".