Decreases in beetle body size linked to climate change and warming temperatures
Bibliographic record
Abstract
Body size is a fundamental ecological trait and is correlated with population dynamics, community structure and function, and ecosystem fluxes. Laboratory data from broad taxonomic groups suggest that a widespread response to a warming world may be an overall decrease in organism body size. However, given the myriad of biotic and abiotic factors that can also influence organism body size in the wild, it is unclear whether results from these laboratory assays hold in nature. Here we use datasets spanning 30 to 100 years to examine whether the body size of wild-caught beetles has changed over time, whether body size changes are correlated with increased temperatures, and we frame these results using predictions derived from a quantitative review of laboratory responses of 22 beetle species to temperature. We found that 95% of laboratory-reared beetles decreased in size with increased rearing temperature, with larger-bodied species shrinking disproportionately more than smaller-bodied beetles. In addition, the museum datasets revealed that larger-bodied beetle species have decreased in size over time, that mean beetle body size explains much of the interspecific variation in beetle responses to temperature, and that long-term beetle size changes are explained by increases in autumn temperature and decreases in spring temperature in this region. Our data demonstrate that the relationship between body size and temperature of wild-caught beetles matches relatively well with results from laboratory studies, and that variation in this relationship is largely explained by interspecific variation in mean beetle body size. This long-term beetle dataset is one of the most comprehensive arthropod body size datasets compiled to date, it improves predictions regarding the shrinking of organisms with global climate change, and together with the meta-analysis data, call for new hypotheses to explain why larger-bodied organisms may be more sensitive to temperature.
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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) | 0.012 | 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".