Early warning indicators of population collapse in a seasonal environment
Bibliographic record
Abstract
Recent studies have demonstrated that generic statistical signals derived from time series of population abundance and fitness-related traits of individuals can provide reliable indicators of impending shifts in population dynamics. However, how the seasonal timing of environmental stressors influences these early warning indicators is not well understood. The goal of this study was to experimentally assess whether the timing of stressors influences the production, detection and sensitivity of abundance- and trait-based early warning indicators derived from declining populations. In a multi-generation, season-specific habitat loss experiment, we exposed replicate populations of Drosophila melanogaster to one of two rates of chronic habitat loss (10% or 20% per generation) in either the breeding or the non-breeding period. We counted population abundance at the beginning of each season, and measured body mass and activity levels in a sample of individuals at the end of each generation. When habitat was lost during the breeding period, declining populations produced signals consistent with those documented in previous studies. Inclusion of trait-based indicators generally improved the detection of impending population collapse. However, when habitat was lost during the non-breeding period, the predictive capacity of these indicators was comparatively diminished. Our results have important implications for interpreting signals in the wild because they suggest that the production and detection of early warning indicators depends on the season in which stressors occur, and that this is likely related to the capacity of populations to respond numerically the following season.
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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) | 0.001 | 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 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".