How much additive mortality is needed to suppress an outbreak?—A neglected question in forest insect pest management
Bibliographic record
Abstract
Abstract The concepts of compensation and additive mortality form the ecological basis for understanding animal population responses to exploitation by humans. In the context of pest management, compensation is a density‐dependent response that allows populations to offset control‐related mortality, often via increased survival or reinvasion. Additive mortality, in contrast, accrues when a population's compensatory capacity is insufficient to offset losses, resulting in a net reduction in population size or growth rate. These concepts are rarely considered in forest insect pest management, which tends to emphasise short‐term plant protection over long‐term population control. We used published life table data for a major native forest insect defoliator, the spruce budworm ( Choristoneura fumiferana [Lepidoptera: Tortricidae]) to simulate the amount of additive mortality required to suppress an outbreak. Simulations also assessed how the failure to account for different compensatory responses could hinder successful control. Our results suggest that only relatively modest amounts of additive mortality (perhaps as low as approximately 8%–18%) may be needed to stop spruce budworm from outbreaking, with immigration being the strongest potential compensatory hindrance to outbreak suppression. Many of the compensatory responses that thwarted outbreak suppression in the past (e.g., low detection efficiency, immigration, indiscriminate killing of predators and parasitoids) have contemporary solutions that could increase additive mortality and thereby enhance the feasibility of population control strategies for native forest insect pests. Our results suggest that some native forest insect pests may require relatively little additive mortality to suppress outbreaks if compensation‐limiting strategies are used. Incorporating theoretical and strategic frameworks used in vertebrate population management could advance the development of native insect population control programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".