Urbanization and environmental variation drive phenological changes in the spotted lanternfly, <i>Lycorma delicatula</i> (Hemiptera: Fulgoridae)
Bibliographic record
Abstract
Abstract The spotted lanternfly (Lycorma delicatula) invaded the USA in 2014. The population has grown into the millions and spread across multiple states, primarily in the north-east but extending into the midwest. We analysed nearly 20 000 records of spotted lanternflies from the citizen-science platform iNaturalist across all reported locations in the USA to explore spatiotemporal patterns of activity and abundance as the invasion progresses. Observations on iNaturalist are consistent with reports of rapid exponential growth in the early years of the invasion. However, in the oldest parts of the invasive range, abundance exhibits logarithmic growth suggestive of reaching carrying capacity in these regions. Since 2015, observed activity has shifted earlier each year and life-cycle stages have lengthened concurrent with a general northern expansion. Activity patterns were correlated with urbanization generally, and earlier activity was associated with higher temperatures in both urban and non-urban locations. Together, these findings suggest that urbanization, and the urban heat island in particular, could facilitate invasion into colder climates and beyond predictions based on current occupancy. Understanding how life-cycle timing is shifting as the invasion progresses, in addition to the environmental factors shaping these changes, underscores the importance of integrating evolutionary ecology into invasion forecasts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".