Soil nutrients mediate the indirect effects of shrub canopy removal: How distance from shrubs affects the herbs and grasses community in a shrub‐encroached grassland
Bibliographic record
Abstract
Abstract Understanding community processes is essential to predict community dynamics and succession processes. To explore how shrub canopy removal frequency (hereafter ‘removal frequency’) and distance from shrubs affect herbs and grasses community assembly in a shrub‐encroached grassland, we carried out a 4‐year shrub canopy removal experiment with three removal frequencies (no removal, removal once, and removal twice per year) in aCaragana microphyllashrub‐encroached grassland, and assessed community assembly mechanisms directly beneath shrubs (0 m from shrubs, i.e., in the centre of the shrub) and in shrub interspaces (at least 2 m from shrubs) under each removal frequency treatment using both functional trait‐based and phylogenetic‐based approaches. Removal frequency positively affected standard effect sizes (SESs) of the mean pairwise distance (MPD) for multi‐trait, specific leaf area (SLA) and leaf dry matter content (LDMC), denoted by SES.MPDMulti‐trait, SES.MPDSLA, and SES.MPDLDMC, indirectly via regulating soil nitrogen (N) and soil carbon (C) content, while it negatively affected SES.MPDHeightindirectly via regulating soil available phosphorus (P) content. Distance from shrubs negatively affected SES.MPDHeightindirectly via regulating soil available P content, and negatively affected SES.MPDLDMCindirectly via regulating soil C content. The trait‐based approach was more powerful than the phylogenetic‐based one in explaining the responses of community assembly processes to environmental changes. These findings highlight the importance of shrub canopy removal and distance from shrubs in affecting soil nutrient status and consequently community assembly processes, which provides a new insight into how canopy removal or fertile island effects affect community assembly in the shrub‐encroached grassland regions.
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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 | 0.001 |
| 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".