How maternal investment varies with environmental factors and the age and physiological state of wild tsetse <i>Glossina pallidipes</i> and <i>Glossina morsitans morsitans</i>
Bibliographic record
Abstract
Theory suggests females should optimize resource allocation across reproductive bouts to maximize lifetime reproduction, balancing current and future reproductive efforts according to physiological state and projected survival and reproduction. Tests of these ideas focus on long-lived vertebrates: few measure age-related reproductive output in iteroparous invertebrates, or partition reserves between those allocated to offspring versus mothers. We investigated how maternal age, and environmental and physiological factors influence reproductive investment in wild tsetse, Glossina pallidipes Austen and G. morsitans morsitans Westwood. Tsetse provide a tractable system to measure reproductive allocation. Females exhibit high maternal investment, producing single, large offspring that rely exclusively on maternal reserves. We find that mothers in better physiological condition and experiencing cooler temperatures produce larger offspring. Pupal size increases significantly but weakly with age. In both species, females with less fat invest proportionately more in offspring. Post-partum fat decreases in flies with badly frayed wings: poor flight capability may limit their feeding efficiency, or they may sacrifice more reserves as a terminal investment. Our results support evidence that offspring size increases with maternal size, investment depends on the environment, and females with lower chances of future reproduction invest more into current offspring. We discuss the implications of maternal effects for predicting vector population responses to environmental change.
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 | 0.000 | 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 | 0.001 | 0.008 |
| 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".