Timing outweighs amount of rainfall in shaping population dynamics
Bibliographic record
Abstract
Abstract Climate variability has been widely documented to have bottom-up effects on the population dynamics of animals1,2, but the mechanisms underlying these effects have been rarely investigated through field manipulative experiments that control for confounding factors3. Here, we examined the effects of different rainfall patterns (i.e. timing and amount) on the population size of Brandt’s voles Lasiopodomys brandtii in semi-arid steppe grassland in Inner-Mongolia by conducting a 10-year (2010-2019) rainfall manipulation experiment in twelve 0.48 ha field enclosures. We found that moderate rainfall increase during the early rather than late growing season drove marked increases in population size through increasing the biomass of preferred plant species, whereas heavily increased rainfall produced no further increase in vole population growth. The increase in vole population size was more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide the first experimental evidence for the bottom-up effects of changing rainfall on the population growth of small mammals, and highlight the importance of rainfall timing on the population dynamics of wildlife in the steppe grassland environment.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".