Landscape level analysis of mountain pine beetle in British Columbia, Canada: spatiotemporal development and spatial synchrony within the present outbreak
Bibliographic record
Abstract
Eruptive herbivores can exert profound landscape level influences. For example, the ongoing mountain pine beetle outbreak in British Columbia, Canada, has resulted in mortality of mature lodgepole pine over >7 million ha. Analysis of the spatio‐temporal pattern of spread can lend insights into the processes initiating and/or sustaining such phenomena. We present a landscape level analysis of the development of the current outbreak. Aerial survey assessments of tree mortality, projected onto discrete 12×12 km cells, were used as a proxy for insect population density. We examined whether the outbreak potentially originated from an epicenter and spread, or whether multiple localized populations erupted simultaneously at spatially disjunct locations. An aspatial cluster analysis of time series from 1990 to 2003 revealed four distinct time series patterns. Each time series demonstrated a general progression of increasing mountain pine beetle populations. Plotting the geographical locations of each temporal pattern revealed that the outbreak occurred first in an area of west‐central British Columbia, and then in an area to the east. The plot further revealed many localized infestations erupted in geographically disjunct areas, especially in the southern portion of the province. Autologistic regression analyses indicated a significant, positive association between areas where the outbreak first occurred and conservation lands. For example, the delineated area of west‐central British Columbia is comprised of three conservation parks and adjacent working forest. We further examined how population synchrony declines with distance at different population levels. Examination of the spatial dependence of temporal synchrony in population fluctuations during early, incipient years (i.e. 1990–1996) suggested that outbreaking mountain pine beetle populations are largely independent at scales >200 km during non‐epidemic periods. However, during epidemic years (i.e. 1999–2003), populations were clearly synchronous across the entire province, even at distances of up to 900 km. The epicentral pattern of population development can be used to identify and prioritize adjacent landscape units for both reactive and proactive management strategies intended to minimize mountain pine beetle impacts.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".