The persistence niche: what makes it and what breaks it for two fire-prone plant species
Bibliographic record
Abstract
Persistence niches are expected to favour qualitatively different plant life histories compared with regeneration niches. In fire-prone habitats, for example, resprouting plants may be expected to exploit persistence niches, whereas obligate-seeders by definition exploit regeneration niches. Resprouter life histories should be typified by high rates of survival, which may be offset by relatively low rates of growth and reproduction. This combination of characters is expected to result from trade-offs in resource allocation and because the longevity of individual plants should buffer their populations against the effects of recruitment failure. We asked whether two resprouting perennial shrubs, Epacris barbata Melville and Xanthorrhoea resinifera (Sol. Ex Kite) E.C.Nelson & D.J.Bedford, exhibited the life-history character combinations that are expected for species exploiting a persistence niche. We also investigated how a change in habitat suitability caused by the invasion of a root pathogen may limit the ability of these species to occupy persistence niches. Demographic censuses of several years’ duration in two populations of each species yielded estimates of vital rates that were consistent with the life-history profile expected for a persistence niche. Rates of background survival were high and rates of fire-related mortality were low in both species. As expected, these were associated with low rates of growth and seedling establishment, although rates of seed production and viability were relatively high in both species. The importance of survival was confirmed by stochastic population models, which showed that population viability was more sensitive to decreases in survival of mature plants and increases in fire mortality of established plants than to changes in other vital rates. Seedling growth rates were also relatively important in E. barbata. Populations of both species that had been infected by root rot disease, Phytophthora cinnamomi, had substantially reduced survival rates and, consequently, reduced population viability. These effects were more extreme in E. barbata than in X. resinifera. We conclude that processes that reduce survival, such as disease infection and habitat loss, rather than processes that impede seed production and recruitment mediate the persistence niche. However, we discuss the possibility that this dependency might be mitigated by high fecundity if infrequent conditions that permit large recruitment events have so far eluded detection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".