Evidence map›Paper›PMID 40535940›Full record

ArticleRoyal Society open science2025

A multiscale stochastic cellular automata model for dispersion of mountain pine beetles.

Yanjun Liu, Donald Estep

Abstract read
In one paragraph

Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yanjun LiuStatistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Donald EstepStatistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.ORCID https://orcid.org/0000-0003-0687-2080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We construct a multiscale model of dispersion of mountain pine beetles in western North American forests. Dispersion is modelled at a macroscale (regional scale) by a novel nonlinear stochastic process for population density. This is coupled to a microscale (tree scale) model of population dynamics using a sequential approach, which assumes that dispersion occurs on a slower time scale than local dynamics. We conduct a numerical investigation of the multiscale model properties. While the model depends on a relatively small number of parameters, it can produce a wide range of behaviours, including dispersion patterns qualitatively similar to those of mountain pine beetle infestations. We also conduct a Bayesian calibration for key parameters in the model using synthetic and real data.

Indexed as

calibrationdispersion processmountain pine beetlemultiscale modellingstochastic cellular automata

Identifiers

PMID40535940
PMCPMC12174937

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.