Trait‐matching and mass effect determine the functional response of herbivore communities to land‐use intensification
Bibliographic record
Abstract
Summary Trait‐based approaches represent a promising way to understand how trophic interactions shape animal communities. The approach relies on the identification of the traits that mediate the linkages between adjacent trophic levels, i.e. ‘trait‐matching’. Yet, how trait‐matching explains the abundance and diversity of animal communities has been barely explored. This question may be particularly critical in the context of land‐use intensification, currently threatening biodiversity and associated ecosystem services. We collected a large dataset on plant and grasshopper traits from communities living in 204 grasslands, in an intensively managed agricultural landscape. We used a multi‐trait approach to quantify the relative contributions of trait‐matching and land‐use intensification acting at both local and landscape scales on grasshopper functional diversity. We considered two key independent functional traits: incisor strength and body size of grasshopper species. Incisor strength, a resource‐acquisition trait, strongly matches grasshopper feeding niche. Body size correlates with mobility traits, and may determine grasshopper dispersal abilities. Plant functional diversity positively impacted the diversity of grasshopper resource‐acquisition traits, according to the degree of trait‐matching observed between plants and herbivores. However, this positive effect was significantly higher in old grasslands. In addition, the presence of specific habitats in the landscape (i.e. wood and alfalfa) strongly enhanced grasshopper resource‐acquisition trait diversity in the focal grassland. Finally, grasshopper body size increased with landscape simplification, although the response was modulated by local factors such as soil depth. Trait‐matching between plants and herbivores was an important driver explaining the abundance and diversity of resource‐acquisition traits within grasshopper communities. However, the presence of specific habitats in the surrounding landscape had also a strong influence on herbivore functional diversity in grasslands. Our study suggests that also mass effects are a central mechanism promoting higher functional diversity within animal communities in highly disturbed anthropogenic systems. A lay summary is available for this article.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".