Effects of soil biota from different ranges on<i>Robinia</i>invasion: acquiring mutualists and escaping pathogens
Bibliographic record
Abstract
The net effects of soil biota on exotic invaders can be variable, in part, because net effects are produced by many interacting mutualists and antagonists. Here we compared mutualistic and antagonistic biota in soils collected in the native, expanded, and invasive range of the black locust tree, Robinia pseudoacacia. Robinia formed nodules in all soils with a broad phylogenetic range of N-fixing bacteria, and leaf N did not differ among the different sources of soil. This suggests that the global expansion of Robinia was not limited by the lack of appropriate mutualistic N-fixers. Arbuscular mycorrhizal fungi (AMF) from the native range stimulated stronger positive feedbacks than AMF from the expanded or invasive ranges, a biogeographic difference not described previously for invasive plants. Pythium taxa collected from soil in the native range were not more pathogenic than those from other ranges; however, feedbacks produced by the total soil biota were more negative from soils from the native range than from the other ranges, overriding the effects of AMF. This suggests that escape from other pathogens in the soil or the net negative effects of the whole soil community may contribute to superior performance in invaded regions. Our results suggest that important regional evolutionary relationships may occur among plants and soil biota, and that net effects of soil biota may affect invasion, but in ways that are not easily explained by studying isolated components of the soil biota.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".