The biogeomorphological life cycle of poplars during the fluvial biogeomorphological succession: a special focus on <i>Populus nigra</i> L.
Bibliographic record
Abstract
ABSTRACT Riverine ecosystems are recurrently rejuvenated during destructive flood events and vegetation succession starts again. Poplars (i.e. species from Populus genera) respond to hydrogeomorphological constraints, but, in turn, also influence these processes. Thus, poplar development on bare mineral substrates is not exclusively a one‐way vegetative process. Reciprocal interactions and adjustments between poplar species and sediment dynamics during their life cycle lead to the emergence of biogeomorphological entities within the fluvial corridor, such as vegetated islands, benches and floodplains. Based on a review of geomorphological, biological and ecological literature, we have identified and described the co‐constructing processes between riparian poplars and their fluvial environment. We have explored the possibility that the modification of the hydrogeomorphological environment exerted, in particular, by the European black poplar ( Populus nigra L.), increases its fitness and thus results in positive niche construction. We focus on the fundamental phases of dispersal, recruitment and establishment until sexual maturity of P . nigra by describing the hierarchy of interactions and the pattern of feedbacks between biotic and abiotic components. We explicitly relate the biological life cycle of P . nigra to the fluvial biogeomorphic succession model by referring to the ‘biogeomorphological life cycle’ of P . nigra . Finally, we propose new research perspectives based on this theoretical framework. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.001 | 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".