Grassland management effects on earthworm communities under ambient and future climatic conditions
Bibliographic record
Abstract
Abstract The impacts of climate change on biodiversity can be modulated by other changing environmental conditions (e.g. induced by land‐use change). The potential interactive effects of climate change and land use have rarely been studied for soil organisms. To test the effects of changing climatic conditions and land use on soil invertebrates, we examined earthworm communities across different seasons in different grassland‐use types (intensively managed grassland, extensively managed meadow and extensively managed sheep pasture). We predicted that the strength of climate change effects would vary with season and land use. Overall, extracted earthworm populations showed the strongest variations in response to the season, indicating major differences in activity patterns and extraction efficiency, whereas climate change and different grassland‐use types had fewer and weaker effects. Future climate, characterized by slightly higher precipitation in spring and autumn but a strong reduction during the summer, had positive effects on the abundance of extracted adult earthworms in spring but then reduced the abundance of active earthworms across the remaining seasons. In contrast, the total biomass of juveniles tended to be consistently lower under future climate conditions. Earthworm species responded differently to the climate change and different grassland management types, and these species‐specific responses further varied strongly across seasons. Intensive grassland management had negative effects, due to plant community composition, whereas sheep grazing favoured earthworm populations, due to dung deposition. There were only limited interactive effects between climate and land use, which thus did not support our main hypothesis. Nevertheless, these results highlight the complex and context‐dependent responses of earthworm communities and activity patterns to climate change, with potential consequences for long‐term population dynamics and crucial ecosystem functions. Highlights We explored earthworm communities in response to climate change, different grassland‐use types and seasons Climate had species‐specific effects on active earthworms, but few interactions with land‐use type Intensive grassland management decreased, but sheep grazing favoured, active earthworm populations Strong seasonal variations in earthworm activity periods will be modulated by climate change
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".