Fire variability, as well as frequency, can explain coexistence between seeder and resprouter life histories
Bibliographic record
Abstract
Summary Studies in fire‐prone Mediterranean ecosystems have repeatedly shown that the mean values of fire regimes (particularly frequency, but also size and intensity) are important for managing sensitive species and maintaining diversity. However, recent studies suggest that invariant fire regimes – that is, those with no variation about the mean value – may not be sufficient to maintain the coexistence mechanisms which could help explain the high levels of species diversity. However, there has been a little examination of the potential mechanisms by which variability in fire regimes might foster coexistence. In these species‐diverse ecosystems, fluctuations in fire regimes promote the coexistence of competitively unequal species, thus providing a potential mechanism of coexistence. We examine the role of variability in the length of the interfire interval and ask whether this variability can allow a fluctuation‐dependent mechanism, namely the storage effect, to promote the coexistence of species. We focus on dominant trade‐offs in fire regeneration strategies (i.e. obligate resprouting vs. obligate seeding) common among Mediterranean plant species and use simulations to explore the inter‐relationship between variability in the time between fires and the coexistence of species. Several empirical studies have found that variability in the length of the interfire interval improved diversity – our simulations suggested one mechanism that could explain this result. Variability can greatly increase the regions over which coexistence between two species – a fire obligate seeder and a resprouter – occurs. Synthesis and applications . Mediterranean ecosystems tend to have high plant diversity, and yet the mechanisms maintaining this diversity are often incompletely understood, and thus management actions that aim to promote coexistence may be relying on imprecise information. In general, fire events drive the evolution and maintenance of diversity and are an important management tool. It is high likely that fluctuations or variability in fire are also important, and this suggests that invariant regimes of prescribed burning or fire suppression could be detrimental to the mechanisms that play a role in the maintenance of diversity in these Mediterranean ecosystems. As a result, attention should be paid to historical fire regimes and the variation in fire return times they displayed when developing prescribed burning regimes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".