Rooting depth and below ground biomass in a freshwater coastal marsh invaded by European Reed (<i>Phragmites australis</i>) compared with remnant uninvaded sites at Long Point, Ontario
Bibliographic record
Abstract
Invasive European Reed (Phragmites australis subsp. australis) outcompetes native vegetation, reducing floristic diversity and habitat value for wildlife. Research in coastal salt marshes has indicated that P. australis invasion may be facilitated by its relatively deep rooting depth, but in freshwater marshes the growth pattern of below ground tissues in relation to water depth is uncertain. To determine if P. australis is rooting more deeply than resident wetland plant species in a freshwater coastal marsh on Lake Erie, Ontario, we measured the vertical distribution of below ground biomass in P. australis invaded marsh sites and compared it to the below ground biomass distribution in nearby sites not yet invaded by P. australis. These invaded and uninvaded sites were paired by water depth, which is known to influence resource allocation and rooting depth. Below ground biomass in invaded sites was greater than in uninvaded sites (t28 = 3.528, P = 0.001), but rooting depth (i.e., the depth at which 90% of total below ground biomass is accounted for) was comparable (t28 = 0.992, P = 0.330). Using water depth and site type, general linear models could predict below ground biomass (F2,55 = 9.115, P < 0.001) but not rooting depth (F2,55 = 1.175, P = 0.316). Rooting depth is likely affected by other factors such as substrate type and the depth of the organic soil horizon.
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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) | 0.001 | 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".