Longitudinal analysis in <i><scp>P</scp>lantago</i>: strength of selection and reverse age analysis reveal age‐indeterminate senescence
Bibliographic record
Abstract
Summary Senescence is usually viewed as increased age‐specific mortality or decreased age‐specific fecundity due to the declining ability of natural selection to remove deleterious age‐specific mutations with age. In herbaceous perennial plants, trends in age‐specific mortality are often confounded by size. Age‐indeterminate senescence, where accumulated physiological damage varies strongly with environment, may be a better model of senescence in these species. We analysed trends in size and fertility in Plantago lanceolata , using a long‐term demographic census involving > 10 years and > 8000 individuals in four cohorts. We used elasticity and pairwise invasion analysis of life‐history function parameterized age × stage matrices to assess whether the force of natural selection declined with age. Then, we used reverse age analysis of size and fertility to assess whether age‐indeterminate senescence occurred. Reverse age analysis uses longitudinal data for individuals that have died to look at trait patterns as a function of both age and remaining time to death. We hypothesized that (i) the strength of natural selection would decline strongly with age, and (ii) physiological condition would deteriorate for several years prior to death. Both elasticity and invasion analyses suggested that the strength of natural selection through mortality declined strongly with age once size was accounted for. Further, reverse age analyses showed that individuals shrank for 3 years prior to death, suggesting physiological decline. Inflorescence production declined with age, and also declined in the 3 years prior to death regardless of overall age. Synthesis . The hypothesis that plants escape senescence generally assumes that plants can continue to grow larger and increase reproduction as they get older. The results here show that size and reproduction decline with age and the rates of these declines towards death are life span‐ and age dependent. Further research is needed to delineate the importance of age‐determinate vs. age‐indeterminate factors in senescence patterns across species.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".