Variation in plant functional traits across and within four species of Western Australian <i>Banksia</i> (Proteaceae) along a natural climate gradient
Bibliographic record
Abstract
Abstract Plant traits are fundamental components of the ecological strategies of plants, relating to how plants acquire and use resources. Their study provides insight into the dynamics of species geographical ranges in changing environments. Here, we assessed the variation in trait values at contrasting points along an environmental gradient to provide insight into the flexibility of species response to environmental heterogeneity. Firstly, we identified how commonly measured functional traits of four congeneric species (Banksia baxteri, B. coccinea, B. media and B. quercifolia) varied along a longitudinal gradient in the South Western Australian Floristic Region. This regional gradient provides significant variation in moisture, temperature and soil nutrients: soil nitrogen content decreases with declining rainfall and increasing temperature. We hypothesized that (i) the regional pattern in trait–environment associations across the species would match those observed on a global scale and (ii) that the direction and slopes of the within‐species relationships would be similar to those across species for each of the measured traits. Along the regional gradient we observed strong shifts in trait values, and cross‐species relationships followed the expected trend: specific leaf area was significantly lower, and leaf Narea and seed dry mass significantly higher, at the drier end of the rainfall gradient. However, traits within species were generally not well correlated with habitat factors: we found weak patterns among populations, either due to the small ecological gradient or perhaps because fine‐scale structuring among populations (at a micro‐evolutionary scale) was low due to high gene flow within species. Understanding how species traits shift as a result of climatic influences, both at the regional (across species) and local (within species) scale, provides insight into plant adaptation to the environment. Such studies have important applications for conservation biology and population management in the face of global change.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".