Data for: Plant and herbivorous insect communities respond in complex ways to rainfall manipulation in an oak savanna grassland
Bibliographic record
Abstract
Abstract Changes in precipitation due to climate change will have consequences for plant and herbivorous insect communities alike. Multiple hypotheses explain how changes in plant diversity and productivity can lead to changes in herbivore community composition. Yet as rainfall patterns change, the bottom-up effects on the relationships between plant and herbivore communities are less well understood. Using a long-term rainfall manipulation experiment in a remnant patch of Garry oak (Quercus garryana) savanna, we examined how plant diversity and productivity have responded to variation in soil moisture over six years. This highly endangered ecosystem is predicted to experience significantly wetter springs and drier summers by 2080. We also investigated plant-mediated, indirect effects of manipulated rainfall on herbivore diversity and abundance, drawing on multiple hypotheses describing the relationships between plant and herbivore communities. For example, the more individuals hypothesis predicts that increased plant productivity results in increased herbivore abundance which in turn results in increased herbivore diversity. We found that plant productivity was influenced by soil moisture, but the direction and magnitude of the response varied across years, and no support for plant diversity influencing productivity. We also found that the cover and productivity of grasses increased significantly with increasing precipitation. In addition to a significant direct effect on herbivore diversity, soil moisture had a significant indirect negative effect on herbivore abundance, via the negative effect of plant productivity on abundance, contradicting the more individuals hypothesis. Synthesis: Our results highlight that not only can drought result in significant reductions in plant productivity in this threatened ecosystem, but that these changes will also result in increases in herbivore abundance. In contrast, where soil moisture is higher, grasses will become more dominant resulting in decreased abundance. Ultimately, predicting how this system responds to changes in precipitation will depend on the ability to predict whether growing season soil moisture will be consistently drier or wetter in the future, a significant challenge. Going forward, investigating how variation in precipitation due to climate change affects the links between trophic levels, including how herbivores affect plant communities, remains critical for understanding ecosystem processes and stability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.018 | 0.004 |
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".