The biogeography of insects' length–dry mass relationships
Bibliographic record
Abstract
Abstract Biomass measures are central to estimating secondary productivity and studying how resources are distributed within an ecosystem. Because directly measuring insect biomass is a lengthy process, many authors have resorted to empirical length–dry mass relationships. The objective of this study was to evaluate the relative importance of latitude, climate and physical habitat (aquatic vs. terrestrial) in explaining the variability in length–dry mass relationships among insect populations. A global meta‐analysis of the body length–dry mass power coefficients of 457 insect samples was conducted using mixed‐effects models. The length–dry mass power coefficients of insects were positively related to the absolute latitude of the study site and to habitat type; with insects captured in aquatic habitats being characterised by higher allometric coefficients than terrestrial ones. Neither the annualised climatic variables (temperature and precipitation) nor the metamorphosis type of insect taxa had a significant effect on the allometric coefficients. The findings may lead to a generalised body length–dry mass relationship for insects, accounting for both the phylogenetic relatedness and the environmental (biotic and abiotic) context of populations.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".