Complementarity and redundancy of interactions enhance attack rates and spatial stability in host–parasitoid food webs
Bibliographic record
Abstract
Complementary resource use and redundancy of species that fulfill the same ecological role are two mechanisms that can respectively increase and stabilize process rates in ecosystems. For example, predator complementarity and redundancy can determine prey consumption rates and their stability, yet few studies take into account the multiple predator species attacking multiple prey at different rates in natural communities. Thus, it remains unclear whether these biodiversity mechanisms are important determinants of consumption in entire predator-prey assemblages, such that food-web interaction structure determines community-wide consumption and stability. Here, we use empirical quantitative food webs to study the community-wide effects of functional complementarity and redundancy of consumers (parasitoids) on herbivore control in temperate forests. We find that complementarity in host resource use by parasitoids was a strong predictor of absolute parasitism rates at the community level and that redundancy in host-use patterns stabilized community-wide parasitism rates in space, but not through time. These effects can potentially explain previous contradictory results from predator diversity research. Phylogenetic diversity (measured using taxonomic distance) did not explain functional complementarity or parasitism rates, so could not serve as a surrogate measure for functional complementarity. Our study shows that known mechanisms underpinning predator diversity effects on both functioning and stability can easily be extended to link food webs to ecosystem functioning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".