Belowground impacts of alpine woody encroachment are determined by plant traits, local climate, and soil conditions
Bibliographic record
Abstract
Global climate and land use change are causing woody plant encroachment in arctic, alpine, and arid/semi-arid ecosystems around the world, yet our understanding of the belowground impacts of this phenomenon is limited. We conducted a globally distributed field study of 13 alpine sites across four continents undergoing woody plant encroachment and sampled soils from both woody encroached and nearby herbaceous plant community types. We found that woody plant encroachment influenced soil microbial richness and community composition across sites based on multiple factors including woody plant traits, site level climate, and abiotic soil conditions. In particular, root symbiont type was a key determinant of belowground effects, as Nitrogen-fixing woody plants had higher soil fungal richness, while Ecto/Ericoid mycorrhizal species had higher soil bacterial richness and symbiont types had distinct soil microbial community composition. Woody plant leaf traits indirectly influenced soil microbes through their impact on soil abiotic conditions, primarily soil pH and C:N ratios. Finally, site-level climate affected the overall magnitude and direction of woody plant influence, as soil fungal and bacterial richness were either higher or lower in woody encroached versus herbaceous soils depending on mean annual temperature and precipitation. All together, these results document global impacts of woody plant encroachment on soil microbial communities, but highlight that multiple biotic and abiotic pathways must be considered to scale up globally from site- and species-level patterns. Considering both the aboveground and belowground effects of woody encroachment will be critical to predict future changes in alpine ecosystem structure and function and subsequent feedbacks to the global climate system.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".