Invasive Prosopis juliflora harbours arbuscular mycorrhizal fungal communities distinct from its native congener P. cineraria
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) promote plant invasions through enhanced colonization of invasive species in introduced ranges compared to their native ranges or native species or congeners in the introduced range. Quantitative differences in AMF communities have been observed between roots of invasive and native plant species, but data on qualitative differences in AMF communities between roots of invasive and its native congeneric species is lacking. Here, we generate empirical evidence to propose a hypothesis that invasive species harbour host-specific AMF phylotypes that are distinct from native congeners. We compared AMF communities in roots of the global invader Prosopis juliflora and its native congener P. cineraria at two geographically separated sites in India. The aim was to determine whether invasive species host AMF communities distinct from native congeners in introduced ranges. Root AMF communities were analysed by amplifying a 550 bp portion of the AMF 18S small subunit rDNA. Soils from rhizospheres of P. juliflora and P. cineraria at the two sites were analyzed for pH, organic matter, NH4+ and PO4 3−. No site-specific divergence in root AMF communities of the congeners was observed, but a significant host-specific divergence in root AMF communities of both Prosopis species was detected.
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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".