Predicting insect outbreaks using machine learning: A mountain pine beetle case study.

ABSTRACT: Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate-term future, e.g., 5-year. Machine-learning algorithms are potential solutions to this challenging problem due to their many successes across a variety of prediction tasks. However, there are many subtle challenges in applying them: identifying the best learning models and the best subset of available covariates (including time lags) and properly evaluating the models to avoid misleading performance-measures. We systematically address these issues in predicting the chance of a mountain pine beetle outbreak in the Cypress Hills area and seek models with the best performance at predicting future 1-, 3-, 5- and 7-year infestations. We train nine machine-learning mode

SUBMITTER: Ramazi P 

PROVIDER: S-EPMC8495826 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature