I/UCRC FRP: Collaborative Research: Understanding and Modeling Competition Effects on Tree Growth and Stand Development Across Varying Forest Types and Management Intensities

University Of Washington, Seattle WA

Investigators

Abstract

Competition in plant communities is a fundamental ecological process that has been studied through experimentation and by modeling. Given the long time periods over which tree populations interact and the increasing availability of extensive data bases with long-term measurements of tree growth and mortality, this project aims to use advanced modeling methodology to develop enhanced quantitative expressions of competition. Improved models of competition in forest populations are required to further advance our predictive ability for management options in a range of forest types. Understanding competition dynamics is paramount for evaluating management activities such as deploying genetic material, prescribing site preparation treatments and planting density, predicting response to varying levels of inter-and intra-specific competition resulting from vegetation control and thinning, and ameliorating nutrient deficiencies through fertilizer applications. Increased understanding of competition processes and formulation of improved models for quantifying competition effects will enhance evaluation of a wide array of forest management options. These results will have far-reaching implications, not only for forest management decision-making but also for forest conservation and restoration, and for understanding and modeling environmental influences, including climate change, on forests. Additional broader impacts include an enriched educational experience for graduate students and postdoctoral fellows due to the involvement of industry scientists as well as university faculty in the conduct of this research. The overall goal of this research project is to use contemporary modeling and statistical techniques and computing technology to exploit information in forestry field studies in an effort to develop improved quantitative measures of tree- and stand-level competition. Modeling is a powerful tool for integrating and synthesizing existing theory and empirical evidence, identifying knowledge gaps, and suggesting relevant hypotheses regarding underlying plant competition that might be tested through experimentation. Relating resource availability and competition intensity to growth and survival is central to understanding and projecting forest stand dynamics. A key challenge is determining effects of species, genetic variation, microsite heterogeneity, and local neighborhood effects on tree-size variation through time. These effects are confounded, highly interactive, and especially difficult to separate for stands of trees, which interact over long time periods. Furthermore, tree-to-tree competition cannot be measured directly, but rather is inferred based on measurements of overall stand density, relative tree size, and/or point density measures that include sizes of and distances to neighbors. Advanced statistical analyses and modeling techniques will be applied to data bases to deal with the complexity of forest ecosystem dynamics over extended time periods. Gaps in knowledge will be identified and experimental approaches for testing relevant hypotheses regarding competition process will be advanced.