Accuracy of Defoliation Estimates from Aerial and Ground Surveys in a Boreal Forest during an Outbreak of the Hemlock Looper, Lambdina fiscellaria (Guenée)
Bibliographic record
Abstract
Annual estimates of defoliation are important tools for managing forest insect defoliators such as the hemlock looper, which feeds on conifer needles of all age classes. We tested the accuracy of defoliation classes obtained from aerial surveys by comparing them with ground-based estimates during a recent outbreak of this insect. We used an approach derived from the Fettes method to estimate defoliation on the current-year shoots as well as on the shoots of the four previous years. Defoliation on the current-year shoots provided accurate estimates of the overall defoliation and the strength of the relationship gradually decreasing for one-year-old to four-year-old foliage. The aerial survey provided accurate estimates of light and moderate defoliation during the first year of the outbreak, but accuracy was lower for both ends of the defoliation gradient and was much less reliable after the second year of the outbreak. All levels of defoliation were then observed in stands where defoliation had not been detected by an aerial survey. Cumulative defoliation on all age classes of foliage brings a new challenge to crews assigned to aerial survey programs. Ground-level defoliation estimates on the current-year shoots can help appraise the risk of tree mortality in the following year.
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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 | 0.001 | 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".