Thirst or Malnutrition: The Impacts of Invasive Insect Agrilus mali on the Physiological Status of Wild Apple Trees
Bibliographic record
Abstract
Malus sieversii (Ledeb.) M. Roem is a tertiary relict tree species and a rare and valuable resource for germplasm conservation. Since 1995, its wild forest has been severely destroyed by a devastating wood-boring beetle Agrilus mali Matsumura (Coleoptera: Buprestidae) in Xinjiang Uygur Autonomous Region, China. Where it invaded, this beetle infested more than 95% of the forests, and 80% of wild apple trees were reported dead in the hotspots. The physiological damage by A. mali infestation and their causality to tree death remain unclear. In this study, we attempted to explain the wild apple dieback from plant physiological perspectives, based on the hypothesis that the more damage M. sieversii suffered from the infestation of A. mali, the less water and fewer nutrients it could utilize. The study was conducted on trees with different extents of damage in wild apple forests over a large scale during 2016 and 2017. The stable carbon isotope ratio in leaves was analyzed to indicate tree water stress status. Total N, total P, total K, Ca2+ and Mg2+ were analyzed to reflect plant mineral nutrient status. The extent of damage was significantly associated with the leaf stable carbon isotope ratio in the drier year of 2016, but not significantly in 2017 with heavy rainfall in spring. The mineral nutrient contents of leaves were not significantly different among the four damage rankings in either year. The water stress experienced by M. sieversii was aggravated by the damage caused by A. mali, especially in a drought year, and indicates that the long-term water deficit caused by A. mali infestation may be the key factor leading to the decline of wild apple forests. The finding suggests the necessity of aerial irrigation for sustainable integrated pest management in wild apple trees.
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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 | 0.001 |
| 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) | 0.001 | 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 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".