Secondary invasion? Emerald ash borer (<i>Agrilus planipennis</i>) induced ash (<i>Fraxinus</i> spp.) mortality interacts with ecological integrity to facilitate European buckthorn (<i>Rhamnus cathartica</i>)
Bibliographic record
Abstract
Invasive insects facilitate secondary invasive species by altering forest structure and function. Specifically, invasive insect herbivores may promote the establishment and growth of invasive plants by creating canopy gaps. Such secondary invasions may be influenced by ecological integrity — the degree to which ecosystem composition, structure, and function deviate from their natural or historical range of variation. Here we investigate (i) whether emerald ash borer (Agrilus planipennis; EAB) induced ash (Fraxinus spp.) mortality facilitates European buckthorn (Rhamnus cathartica) — an invasive, shade-tolerant shrub, and (ii) the role of ecological integrity in this relationship. We use a principal component analysis (PCA) to calculate an index of ecological integrity and a zero-altered negative binomial generalized linear mixed model (GLMM) to describe European buckthorn occurrence and abundance. European buckthorn occurrence is influenced by canopy gaps, independent of EAB-induced gap formation. Ecological integrity and EAB-induced ash mortality interact to control European buckthorn abundance, with high ecological integrity limiting EAB-facilitated buckthorn invasion. This is the first evidence for EAB-facilitated buckthorn invasion and for an interaction between a secondary invasion and ecological integrity. Thus, ecological integrity plays an important role in the EAB–buckthorn system and may be used to manage the impacts of secondary invasions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".