Combined effects of temperature change and natural habitat on the abundance of arthropod trait syndromes in agroecosystems
Bibliographic record
Abstract
Land‐use changes and climatic changes are two entwined stressors on ecosystems. Studies on such interactions often focus on species‐level or region‐specific responses, but fewer have examined differences in responses based on functional traits. Here we examine the influence of natural habitat cover and temperature change on the abundance of all arthropods and on the abundance of pollinator, pest and natural enemy trait syndromes (based on diet breadth, habitat breadth and dispersal mode) in arthropod communities within European agroecosystems. Using a previously compiled dataset along with historical climatic data, we found that all arthropods, diet generalist pollinators and habitat generalist pests were more abundant in sites with a high amount of natural habitat regardless of temperature changes experienced. For diet specialist pollinators, natural habitat and temperature change antagonistically influenced abundance; high amounts of natural habitat in landscapes appeared to mitigate the negative effects of increasing temperature extremes. Habitat specialist pest abundance was higher in sites that experienced greater increases in mean annual temperature, regardless of natural habitat cover. Natural enemies appeared to be more abundant in sites that experienced greater increases in temperature variation. For natural enemies that were flight‐dispersing and habitat generalists this was regardless of natural habitat cover, while for ground‐dispersing natural enemies, temperature change and high natural habitat cover appeared to benefit habitat generalists (ground beetles) and specialists (primarily spiders). Given the variability in responses we observed between different arthropods based on diet breadth, habitat specialism, dispersal ability and functional group, we conclude that functional approaches examining impacts of qualitatively different stressors can help inform future conservation actions or mitigation efforts.
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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 | 0.000 |
| 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".