Forest Investment Account (FIA) - Forest Science Program
FIA Project Y071254

    Effect of site type on competitive interactions among trees in complex-structured mixed species sub-boreal forests
Project lead: Coates, David
Contributing Authors: Astrup, Rasmus; Coates, K. David
Imprint: [BC] :, 2007
Subject: Forest Investment Account (FIA), Trees, British Columbia
Series: Forest Investment Account (FIA) - Forest Science Program
In many parts of the world forest management is evolving rapidly, moving from an agricultural model that emphasized simple stand structures toward more complex stand structures based on natural disturbance or ecosystem models. Variable structure is desirable within stands after silvicultural manipulation in order to meet a host of forest management objectives. Traditional even-aged forest management has relied on the concept of site index to characterize productivity for single-species stands. Site index trees are dominant or codominant individuals that are considered free growing and hence represent site conditions. Site index is a critical component of growth and yield models used to project stand growth, however, it merely represents a retrospective estimate of site productivity for a single species grown in open conditions. Consequently, site index can fail to predict productivity in mixed-species and structurally complex stands. Site index provides little insight into how the competitive interactions among tree species may be affected across resource gradients (or site types) found in forested landscapes. Understanding the nature of competitive interactions among forest trees is central to our understanding of forest community organization and dynamics. This knowledge is also critical to the development of sustainable management of forest ecosystems, particularly in complex structured mixed-species stands. An open and unresolved question is how interspecific competitive interactions (and hence expected growth rates) of different tree species vary across site types in complex stands. The competitive effects and the interactions of different species are likely non-additive. It is important to understand how the relative strength of competitive interactions among tree species varies across resource gradients. For example, it is well known that trembling aspen (Populus tremuloides) can out-compete lodgepole pine (Pinus contorta var. latifolia) on moister ecosystems in the interior of British Columbia, however, on drier site types pine may be an equal or superior competitor (Haeussler et al. 1990). How do these competitive interactions affect growth rates in mixed-species stands? If we are going to manage complex stands, then we must understand how differing environmental conditions affect competitive interactions among tree species, and how this in turn affects growth rates of individual trees. There have been two substantial impediments to understanding competitive interactions in complex stands. First, competition among trees is a spatially-explicit neighbourhood dynamic and its quantification requires establishment of expensive stem-mapped plots. Existing plots are usually small (e.g., permanent sample plots) and/or on uniform site conditions (e.g., Canham et al. 2004 only mapped mesic sites). Additionally, in mixed-species complex stands, the number of possible combinations (species, tree sizes, and spatial distribution) of individual tree neighbourhoods is substantial requiring large sample sizes to tease apart competitive interactions (Coates et al. (in prep). Once you include site variability the number of combinations increases rapidly. Consequently, a study of individual tree growth and competition in heterogeneous environments requires a large sample size from large stem-mapped areas. Second, studies of forest ecosystem processes have traditionally used plot data that averages across variation in local neighbourhood composition and structure. With such an approach, it is very difficult to predict changes in ecosystem processes as stand composition changes. We need novel approaches that account for changing conditions and heterogeneous environments. We propose to resolve these two problems by: (1) applying new remote sensing technology that allows economic creation of large stem-map areas across natural resource gradients, and (2) applying statistical techniques that allow for spatially-explicit analysis of individual-tree based competitive interactions among tree species across resource gradients. These statistical techniques allow tight linkage between field data and the parameterization of stand-level forest dynamics models (e.g., SORTIE-ND). Models can then be used to predict natural stand development, residual tree responses after natural disturbances such as the Mountain Pine Beetle in central BC, or responses after silvicultural interventions.
Related projects:  FSP_Y082254
Contact: Coates, Dave, (250) 847-6386,


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Updated August 16, 2010 

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