Effects of ENSO-linked climate and vegetation on population dynamics of sympatric rodent species in semiarid grasslands of Inner Mongolia, China
Bibliographic record
Abstract
El Niño Southern Oscillation (ENSO) linked climate has been known to be associated with several rodent species, but its effects on rodent community at both spatial and temporal scales are not well studied. In this study, we investigated the possible causal chain relating ENSO, precipitation, temperature, and vegetation index (normalized difference vegetation index, NDVI) to rodent abundance for 14 sympatric rodent species in 21 counties of semiarid grasslands in Inner Mongolia, China, from 1982 to 2006. We found that both precipitation and temperature showed a generally direct positive effect on rodent abundance in many species in the current year, but indirect effects that operate through NDVI in the current or following year could have a reverse effect on abundance. We described one ENSO-linked precipitation bottom-up chain and three ENSO-linked temperature bottom-up chains. These observed bottom-up links reveal that in El Niño years, or 1 year after La Niña years, or 2 years after El Niño years, ENSO-driven climate or vegetation factors tend to increase population abundances of many sympatric rodent species in this region. We also found time-lag effects and the life-history strategy (i.e., functional groups of hibernating behavior, activity rhythm, or food habits) also contribute to the observed complicated effects of SOI on precipitation, temperature, NDVI, and ultimately rodent abundance.
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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 | 0.000 | 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 | 0.000 | 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".