A spatiotemporal Ripley’s<i>K</i>-function to analyze interactions between spruce budworm and fire in British Columbia, Canada
Bibliographic record
Abstract
In this paper, we extend traditional methods of spatial statistics to study spatiotemporal correlations between two different point processes. After introducing the methodology, we apply this analysis to a particular case study of interest in ecology, the interaction between damage by a particular forest pest (western spruce budworm ( Choristoneura occidentalis )) and forest fires. Our analysis, which covers parts of British Columbia in the 26-year period from 1970 to 1995, indicates that areas affected by budworm infestation have a significantly decreased risk of forest fire for the 7 years following the infestation. Conversely, forest fires decrease the risk of infestation for at least 6 years after the fire. These temporal correlations extend over a spatial range of at least 25 km. Our study rejects the common assumption that insect infestation necessarily results in increased fire risk. This case study illustrates the utility of point process modeling and spatial statistics to understanding ecosystem dynamics extending over both space and time.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".