Differences in seedling water-stress response of two co-occurring Banksia species
Bibliographic record
Abstract
In the South-west Australian Floristic Region, timing of rainfall is critical for successful seedling establishment, as is surviving the first year’s summer drought for population persistence. Predictions of a warmer, drier future, therefore, threaten the persistence of obligate seeding species. Here, we investigate the drought tolerance of two co-occurring Banksia (Proteaceae) species by withholding water in pots to different extents of soil drying. Seed was collected from high- and low-rainfall populations, to test for niche differentiation in water-use strategies at the species level, as well as population differentiation. On the basis of a more negative leaf water potential at minimal levels of stomatal conductance and quantum yield, B. coccinea was considered to be more drought tolerant than B. baxteri. This was supported at the anatomical level according to xylem-vessel attributes, with a higher estimated collapse pressure suggesting that B. coccinea is less vulnerable to xylem cavitation. Population contrasts were observed mainly for B. baxteri, with a lower leaf-expansion increment rate in the low-rainfall population providing for drought avoidance, which was reflected in a higher rate of survival than with the high-rainfall population in which 87.5% of plants showed complete leaf senescence. The implications of species differences in water-use strategies are that community dynamics may start to shift as the climate changes. Importantly, this shift may be population dependent. A systematic understanding of adaptive capacity will help inform the choice of population for use in revegetation programs, which may lead to increased resilience and persistence in the face of environmental change. The results of the present study suggest that should declines in B. baxteri populations be noted, revegetating with seed collected from the low-rainfall population may help improve the chances of this species surviving into the future.
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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 | 0.000 |
| 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".