Impact of dominant tree dynamics on site index curves



Pinus banksiana Lamb

Pinus banksiana Lamb

Site index curves were modeled for two species of different shade tolerance, black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.), from an extended network of permanent sample plots (PSP) that covers periods of time varying from 10 to 30 years, in the province of Quebec. A data set reserved for validation allowed us to compare the site index curves derived from PSPs with published site index curves fitted to temporary sample plots (TSP) and stem analyses (SA). For both species, the site index curves calibrated from PSPs and TSPs behave similarly as they have comparable average bias and accuracy.

The major difference is seen with the SA curves that strongly overpredict the dominant height growth of the PSPs. The similar pattern of change of site index curves calibrated from TSP and PSP data reinforces their validity as both types of curves were calibrated with independent data sets and methodologies. The differences observed between SA and PSP curves were likely produced by the dynamics of dominant height related to tree mortality and change in social status. For both species, approximately one tree out of five (22% for black spruce and 16% for jack pine) was replaced every 10 years in the tree group that was used to estimate dominant height. Consequently, the trajectory of dominant height through time for a particular plot is saw-toothed, the size of the ‘‘teeth’’ being, among other things, a function of stand regularity, as measured by an evenness index. Due to this tree replacement dynamic, stand dominant height curves are also more rapidly asymptotic than those of individual trees



Age–height relationships of trees are commonly used for assessing site potential productivity of forest stands. These relationships, known as site index curves, are usually modelled with data gathered during forest inventories. The trees from which age–height data is obtained have a dominant position in the canopy at the time of inventory. Site index curves can be derived from three distinct sources of age–height data: temporary sample plots (TSPs), stem analyses (SAs) and permanent sample plots (PSPs). TSP data are the most commonly available data since they are obtained in periodic inventories that usually cover most of the forested areas of a given territory. Age–height data from TSPs give single points that are used to fit a guide curve around which a series of anamorphic site index curves are adjusted Brickell (1968) argued that TSPs provide a reliable source of data for developing site index curves because age–height relationships are modelled from the same kind of data as those used for site index estimation.

TSP samples must be large and unbiased in order to model representative site index curves from this data source. However, a negative correlation is often observed between stand age and site index (Smith, 1984; Biging, 1985; Walters et al., 1989; Lappi and Malinen, 1994). This source of bias in data obtained from TSPs decreases their value for the development of site index curves, although the use of instrumental variables can partly overcome this problem (Walters et al., 1989). The potential source of bias in TSPs has led forest biometricians to consider stem analysis as an alternative data source for site index modelling.

According to Monserud (1984), stem analyses provide a continuous record of growth, yield a direct observation of tree height at index age, and allow the estimation of polymorphic site index curves. When dominant trees are selected for stem analyses, an assumption is made that these trees have always been dominant or codominant and will continue to be so (Smith, 1984; Alemdag, 1991). This hypothesis is doubtful because dominant trees observed at the time of sampling may have been suppressed before. Social status changes are also known to occur (Delvaux, 1964; Smith, 1984; Franklin et al., 1987; Harcombe, 1987; Schober, 1988). Therefore, height development of individual trees does not necessarily reflect the changes in stand dominant height over time, and site index curves fitted to stem analyses could be distorted accordingly.

The repeated height measurements made in PSPs are the third and best source of data for site index modelling. Remeasurement of PSPs provides the exact pattern of change of a stand’s dominant height by taking into account the dynamics of tree replacement within the dominant stratum of a stand. In addition, Biging (1985); Lappi and Bailey (1988) and Lappi and Malinen (1994) have developed a statistical method that can use the information of repeated height measurements to generate unbiased site index curves. However, most PSP programs across Canada were established a few decades ago, and thus provide only a short growth history of the plots. Therefore, it is not certain whether this information can be used to adequately model site index curves.

The objective of this study thus was to model site index curves from an extended network of PSPs that typically covers periods of time varying from 10 to 30 years. Comparisons were achieved between site index curves derived from PSP remeasurements and published site index curves fitted to TSPs and stem analyses, using a PSP validation data set. Moreover, two species of different shade tolerance, black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.), were used for calculation to understand the potential effect of social status changes on site index curves.

Crown Copyright # 2003 Published by Elsevier Science B.V. All rights reserved.

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