Thursday, August 6, 2009

PS 65-91: A neighborhood analysis: Effects of crowding on tree growth in a single-tree selectively logged forest

Meng-Hsueh Yu, The Graduate Center and Lehman College, City University of New York, Charles D. Canham, Cary Institute of Ecosystem Studies, and Charles M. Peters, New York Botanical Garden.


Understanding the nature of competitive interactions among co-occurring species is central to our understanding of plant communities. It is also critical to the development of sustainable management of forest ecosystems, which are routinely managed for complex residual structure following harvests. In the past decades, forest management in the United States and Canada has shifted to partial cutting, which seeks a balance between protecting natural systems and using them to meet societal demands. The single-tree selection system has been used for over one hundred years to regulate yield, maintain continuous cover and structural heterogeneity, and to protect biological legacies. However, research has lagged concerning interspecific competitive effects on tree growth following single-tree selection logging. One objective of this current study is to gain insight into the nature of tree competition, and further quantify the relative magnitude of all possible pairwise competitive interactions of five coexisting tree species in a deciduous forest in New York’s Catskill Mountains. We used a likelihood-based regression approach to analyze the effects of neighborhood competition on tree growth after harvest. Our questions included: (1) whether different species are functionally equivalent competitors; and (2) whether larger trees are less sensitive than smaller trees to the effects of crowding by neighbors.


Cores from a total of 443 trees of five species were used in this analysis. We used model selection techniques to compare models that make different assumptions about the nature of the competitive effects of neighbors on adult tree growth. For all five target species, simple models that excluded competitive interactions and predicted growth based on tree size alone were rejected in favor of models incorporating neighborhood competition. We found good support for a model that assumed functional equivalence of competitors on tree radial growth for the four species with the smallest sample sizes, but clear interspecific differences in per-capita competitive effects for the species with the largest sample size. In general, smaller trees were more sensitive to crowding than larger trees, across all five species. Our results suggest that managing for specific sizes and spatial configurations of species in the residual stand can significantly increase productivity following harvest.