Changes in plant species and functional composition with time since fire in two mediterranean climate plant communities
Bibliographic record
Abstract
Abstract Question Do floristic composition and plant functional type ( PFT ) richness and dominance change with time since fire, in the directions predicted through consideration of their fire response traits? Location Two vegetation communities in the globally significant biodiversity hotspot of south‐western Australia: mallee, dominated by resprouters, and mallee‐heath, dominated by non‐resprouters. Methods Species richness and cover were sampled in replicated plots across a time since fire gradient ranging from 2 to >55 yr post‐fire, using a space‐for‐time approach. Species were allocated to PFT s according to traits relevant to the processes of vegetation change underpinning the initial floristic composition model of vegetation assembly: their capacity to resprout, the location and persistence of the seed bank, competitive stratum and longevity. Ordination and ANOVA were used to test for differences in floristic and PFT composition between young (<10 yr post‐fire), mature (18–35 yr) and old (>40 yr) vegetation in each community. Results Plant functional type and floristic analyses were similar, showing substantial changes in the composition of mallee‐heath vegetation with time since fire, but not in mallee. The direction of change in PFT composition in mallee‐heath was consistent with predictions, with increasing cover of non‐resprouting, serotinous PFT s, an intermediate peak in cover of PFT s with persistent soil‐stored seed banks, and decreasing cover of post‐fire ephemerals and non‐resprouting, non‐serotinous dwarf shrubs, herbs and graminoids with increasing time since fire. Success in predicting changes in PFT dominance in mallee was lower. Conclusions The similarity of floristic and PFT analyses suggest that these approaches are interchangeable for characterizing vegetation change with increasing time since fire. PFT s were more effective for predicting fire response trajectories in the vegetation community dominated by non‐resprouting, serotinous shrubs (mallee‐heath) than that dominated by resprouting, serotinous trees (mallee). The underlying vegetation assembly model and PFT s used appear suitable for broader application in fire‐prone communities with competitive dominance by non‐resprouting, serotinous shrubs, but less so in communities dominated by other PFT s.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".