Plant-associated bacterial populations on native and invasive plant species: comparisons between 2 freshwater environments
Bibliographic record
Abstract
Plant-microbial interactions have been well studied because of the ecological importance of such relationships in aquatic systems. However, general knowledge regarding the composition of these biofilm communities is still evolving, partly as a result of several confounding factors that are attributable to plant host properties and to hydrodynamic conditions in aquatic environments. In this study, the occurrences of various bacterial phylogenetic taxa on 2 native plants, i.e., mayapple (Podophyllum peltatum L.) and cow parsnip (Heracleum maximum Bartram), and on an invasive species, i.e., garlic mustard (Alliaria petiolata (M. Bieb.) Cavara & Grande), were quantitatively examined using nucleic acid staining and fluorescence in situ hybridization. The plants were incubated in triplicates for about a week within the Kalamazoo River and Pierce Cedar Creek as well as in microcosms. The bacterial groups targeted for enumeration are known to globally occur in relatively high abundance and are also ubiquitously distributed in freshwater environments. Fluorescence in situ hybridization analyses of the bacterioplankton assemblages revealed that the majority of bacterial cells that hybridized with the different probes were similar between the 2 sites. In contrast, the plant-associated populations while similar on the 3 plants incubated in Kalamazoo River, their representations were highest on the 2 native plants relative to the invasive species in Pierce Cedar Creek. Overall, our results further suggested that epiphytic bacterial assemblages are probably under the influences of and probably subsequently respond to multiple variables and conditions in aquatic milieus.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".