Clay larvae do not accurately measure biogeographic patterns in predation
Bibliographic record
Abstract
Abstract Aim Spatial variation in predation can shape geographic patterns in ecology and evolution, but testing how predation varies across ecosystems is challenging as differing species compositions and defensive adaptations can mask underlying patterns. Recently, biogeography has borrowed a tool from ecology: clay prey models. But clay models have not been adequately tested for geographic comparisons, and a well‐known problem –that clay prey only appeal to a subset of potential predators– could bias detected geographic patterns whenever the relative importance of predator guilds varies among sites. Here, we test whether clay larvae accurately capture geographic differences in predation on real larvae. Location 90° of latitude and >2000 m elevation across the Americas. Taxon Vertebrate and invertebrate predation on ‘superworms’ ( Zophobas larvae). Methods Across six sites that vary dramatically in latitude, elevation, and biome, we quantified predation on live, dead, and clay larvae. We physically excluded vertebrate predators from some larvae to distinguish total predation and invertebrate‐only predation. Results Predation on live superworms almost doubled from our high‐elevation high‐latitude site to our low‐elevation tropical site. Geographic patterns were consistent among live and dead larvae, but clay larvae missed extremely high predation at some sites and therefore mis‐measured true geographic patterns. Clay larvae did a particularly bad job at capturing geographic patterns in predation by invertebrates, although sample sizes for invertebrate predation were small. Main Conclusions Clay larvae are inappropriate for comparing predation rates across sites. They should be abandoned for biogeographic studies and reserved for comparisons within, rather than across, predator communities.
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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 | 0.001 |
| 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".