Integrating population demography, genetics and self-incompatibility in a viability assessment of the Wee Jasper Grevillea (Grevillea iaspicula McGill., Proteaceae)
Bibliographic record
Abstract
Grevillea iaspicula is an endangered shrub known from only eight small populations (<250 individuals) in south-eastern Australia. The species is threatened by combined ecological and genetic factors, e.g. land conversion, weed invasion, low recruitment and low gene flow among populations. The populations also show large variance in male fitness and limited mate availability which are thought to arise as a consequence of gametophytic self-incompatibility (GSI). This study has used an individual-based, spatially explicit simulation model to explore the interaction between GSI and mate limitation in this species, as well as its effect on long-term population viability. The model was parameterised with demographic and genetic data obtained from 2 years of population monitoring. Simulation results identified extremely low establishment rates as the most critical factor currently influencing the persistence of G. iaspicula populations and indicated that the extant populations are at serious risk of extinction in the near future unless this is altered by, at very least, an order of magnitude higher. SI was shown to affect the magnitude of variation in establishment but this effect was masked when establishment was critically low. Disassortative mating, owing to low allelic richness at the S-locus, had the negative demographic effect of restricting mating to relatively few compatible plants. Restricted mate availability imposed additional limitations to the viability of populations but, given a 20-fold increase in establishment rate, population fluctuations stabilised. The long-term viability of G. iaspicula is bleak without artificial augmentation of the populations but management planning must also consider genetic processes, including SI, to ensure such strategies optimise the benefits gained. © 2007 Springer Science+Business Media B.V.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".