| Summary: | Relationships between measures of ecological site quality and height
growth of Sitka spruce [Picea sitchensis (Bong.) Carr), measured as site index
(metres at 50 years at breast height), were investigated for the eastern Queen
Charlotte Islands using multiple linear regression techniques. Temperature
and light were assumed to be similar in a region of similar climate, expressed
as biogeoclimatic subzone, and the investigation focused on measures of
moisture and nutrients. This study tested the hypothesis that the
classification units of biogeoclimatic ecosystem classification system are good
indirect estimates of ecological site quality so are able to predict forest growth.
Fifty-five plots were chosen for study to represent a wide range i n
ecological site quality and geographic variation. Individual measures of
moisture and nutrients were represented as categorical variables; soil moisture
and nutrient regime; and continuous variables; soil nutrients and predicted
moisture deficit in combination with soil physical measures. Soil moisture and
nutrient regimes were represented as spectra of indicator species groups. The
synoptic effect of individual measures of moisture and nutrients were
expressed as site associations and assumed to be represented by plant
associations. The relationship between the categorical and continuous
variables for soil nutrients was also examined.
The most successful models used the BEC classification units; soil
moisture regime, soil nutrient regime and site association. Multiple linear
regression models using either soil moisture plus soil nutrient regimes or site
associations were equally successful in explaining variation in (ln) site index
(adjusted R2 = 0.80; I2 = 0.79). However, the former should be considered the
superior model for predictive purposes since the variance of the latter model
was not homogeneous. The soil nutrient regime model was as successful in
explaining variation in site index as the best continuous model (mineral soil
mineralizable N plus forest floor mineralizable N, extractable calcium and
potassium) (adjusted = 0.40 versus 0.42). The soil moisture regime model
was more successful than those using continuous variables (adjusted =
0.45 versus no relationship). The lack of relationship was attributed to
inaccuracy of the water balance models due to their lack of calibration for this
location and forest type. There was a moderate relationship with site index and
plant associations (adjusted R2 = 0.49); however vegetation is subject to
change with succession over time so would be difficult to apply for predictive
purposes. Indicator species groups showed no relationship with site index,
likely due to the paucity of understorey species from canopy closure and
intense browsing by introduced deer.
The soil nutrient regime classification was well supported by a
discriminant analysis using soil chemical nutrients which correctly classified
the plots in 83% of the cases, on average. The soil moisture regime
classification could not be tested since the models used to estimate moisture
deficit in this study were considered too inaccurate. Continuous synoptic
versus categorical models could also not be compared for the same reason.
It was concluded that the units of the biogeoclimatic ecosystem
classification were good indirect measures of ecological site quality and good
predictors of forest growth. The equations generated in this study need to be
tested with independent data and further investigation is necessary to
determine moisture relationships for Sitka spruce.
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