Niche shifts and range expansions after invasions of two major pests: the Asian longhorned beetle and the citrus longhorned beetle
Bibliographic record
Abstract
BACKGROUND: In recent years, the quarantine forestry pests the Asian longhorned beetle (ALB) Anoplophora glabripennis and the citrus longhorned beetle (CLB) Anoplophora chinensis have spread across the Northern Hemisphere, triggering concern about their potential distribution. However, little is known about the niche shifts of the pests during the invasion, making it difficult to assess their potential ranges. We thus employed two distinct approaches (i.e., ordination-based and reciprocal model-based) to compare the native and invaded niches of ALB and CLB after their spread to new continents based on global occurrence records. We further constructed models with pooled occurrences from both the native and invaded ranges to analyze the effects of occurrence partitioning on predicted ranges. RESULTS: We detected expansions in the invaded niches of both pests, indicating that the niches shifted to varying extents after the invasion. Large shares of the native niches of ALB and CLB remained unfilled, revealing the potential for further invasion in new regions. The models calibrated with pooled occurrences clearly underestimated the potential ranges in invaded regions compared with the projections based on partitioned models considering native and invaded areas separately. CONCLUSIONS: These results emphasize the importance of elucidating the niche dynamics of invasive species for obtaining accurately predicted ranges, which may help identify risk areas masked by the assumption of niche conservatism. Furthermore, prevention and quarantine measures for ALB and CLB are clearly needed to avoid future serious damage to forest ecosystems. © 2023 Society of Chemical Industry.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".