Top-down effects of intraspecific predator behavioral variation
Bibliographic record
Abstract
Abstract Among-individual variation in predator traits is ubiquitous in nature. However, the role of intraspecific trait variation in trophic dynamics has been seldom considered in community ecology. This has left unexplored a) to what degree does among-individual variation in predator traits regulate prey populations and b) to what degree do these effects vary spatially. We address these questions by examining how predator among-individual variation in functional traits shapes communities across habitats of varying structural complexity, in field conditions for the first time. We manipulated Chinese mantis (Tenodera sinensis) density and trait variability in experimental patches of old fields with varying habitat complexity and quantified the impacts on lower trophic levels, specifically prey and plant biomass. Our mantis groups thus contrasted in density (six or twelve individuals) and levels of variation in a key behavioral trait, activity level (movement on an open field). Our metric of habitat complexity was the density of plant material. In complex habitats and at high mantis densities, behaviorally variable groups decreased prey biomass by 35.1%, while at low densities, low levels of behavioral trait variability decreased arthropod biomass by 27.1%. Behavioral variability also changed prey community composition. Our results are among the first to demonstrate that among-individual trait variation can shape open species-rich prey communities. Moreover, these effects depend on both predator density and habitat complexity. Incorporating this important facet of ecological diversity revealed normally unnoticed effects of functional traits on the structure and function of food webs.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".