The impact of climate change on tri-trophic interactions and crop production
Bibliographic record
Abstract
A major goal in agroecology is to sustainably maximize crop yield while minimizing pest damage. One way to accomplish this is utilizing the highly coevolved tritrophic interactions between crops, pests, and the natural enemies of those pests. With anthropogenic changes to global climate; however, there is an increased potential to alter these interactions. We investigated the effect of increasing carbon dioxide and temperature on crop yield of a common agricultural ecosystem: the cabbage species Brassica oleracea, specialized cabbage aphid Brevicoryne brassicae, and parasitic natural enemy Diaeretiella rapae. To evaluate crop yield under varying carbon dioxide and temperature conditions, an agent-based model was created using Netlogo. Percent crop loss, maximum pest population, and rate of parasitism were analyzed under three different temperature and carbon dioxide conditions: preindustrial, current, and 2050 projected. Crop loss was most significant at projected 2050 temperature and CO2 conditions, with an 18.71 ± 6.86% increase in crop loss compared to preindustrial times, and a 10.63 ± 7.73% increase compared to current conditions. Brevicoryne brassicae population sizes steadily increased from preindustrial times, while the rate of parasitism (proportion of Brevicoryne brassicae parasitized per day) remained constant under all three climate conditions. Our model predicts anthropogenic climate change will exacerbate crop loss over time, likely due to projected pest population increases, unless mitigative measures are implemented. Keywords: climate change, carbon dioxide, temperature, tri-trophic, agroecosystem, crop yield, biological control, pest management
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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".