Impacts of climate change and host plant availability on the global distribution of <i>Brontispa longissima</i> (Coleoptera: Chrysomelidae)
Bibliographic record
Abstract
BACKGROUND: The coconut hispine beetle Brontispa longissima Gestro (Coleoptera: Chrysomelidae) is one of the most serious pests of the coconut palm, Cocos nucifera L. (Arecales: Arecaceae) and other palms. The invasion of B. longissima causes major economic and ecological losses worldwide. In this study, the impacts of climate change on the risk of spread were evaluated. CLIMEX was used to project its global potential distribution based on historical climate data (1987-2016) and simulated future climate data (2071-2100). RESULTS: The distribution of B. longissima included each continent under historical and future climate conditions. However, climate suitability was predicted to decrease in most tropical and subtropical regions under a climate change scenario. Temperature was a more important determinant of the climatic suitability of the pest than relative humidity or precipitation. The availability of host plants (Arecaceae) only had a slight impact on climate suitability in some regions. CONCLUSION: The projected potential distribution of B. longissima will help to determine the impacts of climate change and will provide supportive information for the development of management strategies to reduce future economic and ecological losses. © 2019 Society of Chemical Industry.
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 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 | 0.001 | 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) | 0.002 | 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".