Not a melting pot: plant species aggregate in their non-native range
Bibliographic record
Abstract
Aim: Plant species continue to be moved outside of their native range by human activities. Here, we aim at determining whether, once introduced, plants assimilate into native communities, or whether they aggregate, thus forming mosaics of native- and alien-rich communities. Alien species may aggregate in their non-native range due to shared habitat preferences, such as their tendency to establish in high-biomass, species-poor areas. Location: 22 herbaceous grasslands in 14 countries, mainly in the temperate zone. Time period: 2012 - 2016. Major taxa studied: Plants. Methods: We used a globally coordinated survey. Within this survey, we found 46 plant species, predominantly from Eurasia, for which we had co-occurrence data in their native and non-native range. We test for differences in co-occurrence patterns of 46 species, between their native (home) and non-native (away) range. We also tested whether species had similar habitat preferences, by testing for differences in total biomass and species richness of the patches species occupy in their native and non-native range. Results: We found the same species to show different patterns of association, depending on whether they were in their native or non-native range. Alien species were negatively associated with native species, and aggregated instead with other alien species in species-poor, high-biomass communities in their non-native, compared to their native range. Main conclusions: The strong differences between the native (home) and non-native (away) range in species co-occurrence patterns are evidence that how species associate with resident communities in their non-native range is not species-dependent, but rather a property of being away from their native range. These results thus highlight that species may undergo important ecological changes when introduced away from their native range. Overall, we show origin-dependent associations that result in novel communities in which alien-rich patches exist within a mosaic of native-dominated communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".