Seasonal and landscape effects on the biotic resistance of forest communities to experimental insect introductions
Bibliographic record
Abstract
Natural enemies play an important role in the regulation of many forest insect populations. The hypothesis that these organisms also reduce invasion potential is one element of a concept known as biotic resistance. While many studies have shown that the abundances of natural enemies are affected by landscape structure and diversity, seasonality, and host tree species, this study tests the hypothesis that these factors affect the biotic resistance of forest communities to invasion by a non‐native tussock moth. At 20 sites on Vancouver Island, Canada, spanning a range of natural to urban forests, small populations of the rusty tussock moth, Orgyia antiqua , an exotic polyphagous tussock moth, were introduced. Introductions were repeated at three different periods in the year, on coniferous and deciduous host trees, and included both late‐instar larvae and pupae. The survival of these small populations was monitored in relation to four landscape variables measured around each site. Spring introductions had significantly lower mortality rates than either early or mid‐summer introductions. There was little difference in predation rates between coniferous and deciduous host trees. The amount and type of forest cover in the landscape had important, but seasonally dependent, effects on survival that likely reflect changes in the habitat requirements of a shifting community of generalist predators. Based on the results, this study concludes that landscapes with intermediate forest cover are the least resistant to invasion by early feeding species such as the rusty tussock moth.
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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) | 0.004 | 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".