Studies of forest declines are important, because they both reduce timber production and affect successional trajectories of landscapes and ecosystems. Of particular interest is the decline of red pines, which is characterized by expanding areas of dead and chlorotic trees in plantations throughout the Great Lakes region. Here we examine the impact of two bark beetle groups, red turpentine beetles and pine engraver bark beetles, on tree mortality and the subsequent gap formation over time in a plantation in Wisconsin. We construct spatial-temporal statistical models that quantify the relations among red turpentine beetle colonization, pine engraver bark beetle colonization, and mortality of red pine trees while accounting for correlation across space and over time. We extend traditional Markov random-field models to include temporal terms and multiple-response variables aimed at developing a suitable set of statistical models for addressing the scientific questions about the forest ecosystem under study. For statistical inference, we adopt a Bayesian hierarchical modeling approach and devise Markov chain Monte Carlo algorithms for obtaining the posterior distributions of model parameters as well as posterior predictive distributions. In particular, we implement path sampling combined with perfect simulation for autologistic models while formally addressing the posterior propriety under an improper uniform prior. Our data analysis results suggest that red turpentine beetle colonization is associated with a higher likelihood of pine engraver bark beetle colonization and that pine engraver bark beetle colonization is associated with higher likelihood of red pine tree mortality, whereas there is no direct association between red turpentine beetle colonization and red pine tree mortality. There is strong evidence that red turpentine beetle colonization does not kill a red pine tree directly, but rather predisposes the tree to subsequent colonization by pine engraver bark beetles. The evidence is also strong that pine engraver bark beetles are the ultimate mortality agents of red pine trees.
Bibliographical noteFunding Information:
Jun Zhu is Associate Professor, Department of Statistics, University of Wisconsin–Madison, Madison, WI 53706 (E-mail: email@example.com). Jakob G. Rasmussen is Post Doctor (E-mail: firstname.lastname@example.org) and Jesper Møller is Professor (E-mail: email@example.com), Department of Mathematical Sciences, Aalborg University, Aalborg 9220, Denmark. Brian H. Aukema is Research Scientist and Assistant Professor (Adjunct), Canadian Forest Service, Natural Resources Canada at University of Northern British Columbia, Prince George, British Columbia, V2N 4Z9, Canada (E-mail: firstname.lastname@example.org). Kenneth F. Raffa is Professor, Department of Entomology, University of Wisconsin–Madison, Madison, WI 53706 (E-mail: email@example.com. edu). Funding has been provided for this research from National Science Foundation grant DEB-0314215, U.S. Department of Agriculture Hatch grant WIS01096, the Wisconsin Alumni Research Foundation, and Danish Natural Science Research Council grant 272-06-0442, “Point Process Modeling and Statistical Inference.” The authors thank the Wisconsin Department of Natural Resources for providing the research site, and the editor, an associate editor, and two referees for constructive and helpful comments.
- Autologistic model
- Bayesian inference
- Forest entomology
- Markov chain Monte Carlo
- Perfect simulation
- Spatial-temporal processes