Modelling tree competition in a boreal mixedwood forest in Alberta

• Author / Creator

  Yijia, Yu

• In boreal forests, tree competition has been widely considered as a key process contributing to forest dynamics including driving species turnover, succession and shaping stand-level structure. Understanding how the competition process in boreal forests regulates tree growth and survival is critical to both the ecology and management of boreal forests. In this thesis, I focused on several questions, essential for understanding the role that competition plays in maintaining boreal forests: (i) How do intraspecific and interspecific competition affect tree survival and growth in boreal forests? (ii) Is there a competition measure with universally superior performance? (iii) What is the maximum distance over which a tree affects the growth of its neighbours? (iv) How does difference in the size of neighbouring trees affect the intensity of competition between them? To answer these questions, I investigated competition in a 1-hectare stem-mapped plot where all free-standing trees with a diameter at breast height ≥ 1cm were censused in 2010 and again in 2015 in a boreal mixed-wood forest in George Lake, Edmonton, Alberta which is dominated by deciduous species (birch and aspen) and coniferous species (white spruce). Spatial distribution patterns in the plot were analyzed using an inhomogeneous pair-correlation function to infer competition effect on tree survival. Neighbourhood analysis was used to determine the relationship between neighbourhood density and individual tree survival. I also used likelihood-based non-linear regression models to quantify effects of neighbourhood competition on tree growth.The analysis of the competition effect on both growth and survival of individual trees confirmed the importance of both inter- and intraspecific competition in regulating the study forest. Spatial analysis showed that the survival of coniferous trees was subjected to strong intraspecific crowding effect, while for deciduous trees, the effect of intraspecific competition was less detectable. However, spatial analysis indicated strong interspecific competition between coniferous and deciduous trees, suggesting that species replacement from deciduous to coniferous was occurring in the plot. Consistent with these results from the spatial analysis, coniferous trees showed lower survival rates in both the neighbourhood of denser conspecific and heterospecific stems. The coniferous trees had a slightly higher per capita effect on the survival of deciduous trees, suggesting the higher competitive ability of coniferous trees. The evidence of strong interspecific competition was also found from the neighbourhood analysis of individual tree growth, where crowding of both coniferous and deciduous trees has strong per capita effect on each other. However, the effect of intraspecific competition on growth of white spruce was weak.Results also showed that individual tree model performance varied with different competition measurements. The commonly used neighbourhood competition index (NCI) was the best index for birch, while for aspen and white spruce, an index that is based on horizontal angles performed best. The estimated effective neighbourhood radius varied from 3 to 17 m, depending on the species identity of the target trees. Inclusion of the effective neighbour size ratio (a parameter to filter small-size neighbouring trees) improved the model likelihood for birch and white spruce but not for aspen. The estimated effective neighbour size ratio was close to 1 for both species, suggesting that target tree growth of birch and white spruce was more likely to be affected by larger neighbours. This thesis highlights the importance of competition in driving dynamics and structure of boreal forests. Applying the effective neighbourhood radius and effective neighbour size to tree growth models allowed us to better investigate the effect of competition. Moreover, the analysis of competition effect on both tree growth and survival allowed us to quantify the competition and predict the dynamics of the forest.

• Subjects / Keywords

  • density dependent effect
  • neighbourhood analysis
  • autologistic regression
  • tree competition

• Graduation date

  Spring 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-e3cj-0479

• License

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