Abstract
In many cases, the traditional ground-based estimates of competition between trees are not directly applicable with modern aerial inventories, due to incompatible measurements. Moreover, many former studies of competition consider extreme stand densities, hence the effect of competition under the density range in managed stands remains less explored. Here we explored the utility of a simple tree height- and distance-based competition index that provides compatibility with data produced by modern inventory methods. The index was used for the prediction of structural tree attributes in three boreal tree species growing in low to moderate densities within mixed stands. In silver birch, allometric models predicting tree diameter, crown height, and branch length all showed improvement when the effect of between-tree competition was included. A similar but non-significant trend was also present in a proxy for branch biomass. In Siberian larch, only the prediction of branch length was affected. In Scots pine, there was no improvement. The results suggest that quantification of competitive interactions based on individual tree heights and locations alone has potential to improve the prediction of tree attributes, although the outcomes can be species-specific.
Highlights
Measurable forest or tree structural attributes are frequently used as statistical proxies to estimate structural attributes that are more difficult or time consuming to gauge
Inclusion of the competition index H in the allometric equations improved the estimates of several attributes for silver birch and Siberian larch (Table 2, Figure 1)
The parameter c associated with H was significantly different from zero and provided consistent improvement of model fit in dbh, hc, and lb (Table 2)
Summary
Measurable forest or tree structural attributes are frequently used as statistical proxies to estimate structural attributes that are more difficult or time consuming to gauge. Competitive interactions within individual tree groups are one candidate for model improvement, because they influence the size relationships among the basic structural attributes that are covered by many large-scale forest inventories, such as tree height, stem diameter, and crown size [2,3,4]. As the trees and forests are nowadays acknowledged to serve multiple ecosystem functions, there are needs to improve the estimation of multiple aspects of tree structure and function to guide forest management decisions [8] One step in this process can be improving the precision of predicting structural attributes using forest inventory data. Output from remote measurements including ALS can be used to estimate important attributes including stem volume, crown size or tree biomass [9,10], examples of utilising tree-level competition data with ALS remain scarce [11,12,13]. We quantify local tree-level competition with a simple index based on tree heights and distances, which could be readily applicable in forest inventories
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