Developing Species Distribution Models to Predict Pea Aphid Habitat Suitability and Migration under Climate Change, an Insect Vector of Pea Seed-Borne Mosaic Virus
Bibliographic record
Abstract
Pea aphids (Acyrthosiphom pisum) (Hemiptera: Aphididae) are a global pest that cause significant yield loss in several pulse crops, including field pea (Lathyrus oleraceus L.), lentil (Lens culinaris Medik), and faba bean (Vicia faba L.). A global Species Distribution Model (SDM) was created to determine the areas of the world where the habitat suitability for pea aphids is the highest, with three shared socioeconomic pathway (SSP) climate change scenarios being incorporated into the model. Areas that were found to have high habitat suitability for pea aphids included the USA, Canadian prairies, across several countries within the Europe, China, and areas of Australia. SSP 126 was shown to be the most favourable climate scenario for pea aphids, as they were able to significantly expand their current land range and have the least amount of land range contraction. Given the threats that climate change poses, it is unknown how pea aphid life history traits, such as the number of offspring produced and days to reproductive maturity will respond to increasing temperatures. To address this knowledge gap, growth chamber experiments with six temperature conditions were conducted. A temperature of 21°C was the most favorable temperature for pea aphids, as they produced the highest number of offspring within 10 days and possessed the most consistent days to reproductive maturity. Severe consequences on pea aphid life history traits were encountered at 35°C, which resulted in a near 100% mortality rate. Next, a new “mechanistic” and “correlative” SDM was created focusing solely on North America, with the mechanistic SDM incorporating the temperature limitations informed by the pea aphid life history experiments. In these models, we implemented two SSP climate scenarios: SSP 126 and SSP 370. The results of the mechanistic SDM captured the effects of rising temperatures on pea aphid habitat suitability, highlighting the value of incorporating physiological parameters into SDMs to improve statistical predictions or using tools like CLIMEX that can account for temperature thresholds when evaluating species distributions. This project also investigated if a virus transmitted by pea aphids would be influenced by the changes in temperature conditions as a result of climate change. Specifically, Pea Seed-borne Mosaic Virus (PSbMV) was mechanically inoculated into pea plants grown in 28°C and 35°C. Samples were taken at three growth stages during the plant’s lifecycle: V1 (first node), R2 (flowering), and R4 (podding). The results demonstrated that PSbMV develops more efficiently at 35°C, as indicated by all three plant stages having higher viral titers. Further, the life history traits for pea aphids infected with PSbMV were compared with non-infected PSbMV pea aphids in 28°C, and there were no statistically significant differences between PSbMV-infected and non-infected pea aphids. Additionally, the increase in PSbMV viral titer at higher temperatures suggests that climate change could increase the severity of plant-virus interactions.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".