Forest Landscape Baseline No. 7 Brief Progress and Summary Reports 1995

RELATIONSHIPS BETWEEN WHITE PINE ABUNDANCE AND LANDSCAPE HABITATS IN THE RUSHBROOK LAKE AREA OF CENTRAL ONTARIO

by P. A. Quinby, F. McGuiness, T. Lee and A. Suski
(in association with the Canadian Nature Federation)

Introduction

In order to develop ecosystem-based, adaptive forest management for the white and red pine forest portion of the Lower Spanish Forest, the ecosystems of the area must first be located, surveyed and described. This project report focusses on white pine (Pinus strobus L.) in the ancient upland forests of the Rushbrook Lake area (approximately 2,500 ha). The study area is located in the southwest portion of Ouellette Township which is centrally located within the Lower Spanish Forest, approximately 50 km north of Webbwood, Ontario (Figure 1). Many studies have focussed on white pine ecology with a landscape perspective (Heinselman 1973, Gilbert 1978, Hibbs 1982, Baird 1983, Whitney 1984, Whitney 1986, Pinto 1989, Quinby 1989, Day and Carter 1990a, Day and Carter 1990b, Iles 1990, Arbex Forest Development 1991, Quinby 1991a, Quinby 1991b, Carleton and Gordon 1992, Spectranalysis 1992, Jensen 1993, Quinby 1993, Giroux 1994, Quinby 1994). None of these studies, however, has rigorously tested for differences in white pine abundance relative to gradients in habitat conditions at the landscape level.

In northern temperate forested landscapes with significant topographic diversity, it has been shown that habitat often varies primarily with respect to soil moisture (Loucks 1962, Gauch and Stone 1979, Spurr and Barnes 1980, Whitney 1982, Fralish 1988), microclimate (Loucks 1962, Spurr and Barnes 1980, Fralish 1988), and fire (Quirk and Sykes 1971, Loope and Gruell 1973, Romme and Knight 1981, Hemstrom and Franklin 1982). The purpose of this study was to test the hypothesis that white pine is most abundant on hilltops, least abundant in valleys and intermediate in abundance between these slope positions due to differences in habitat conditions along this topographic gradient.

Methods

Three criteria were used for determining the general location of plots: (1) a plot must be representative of one of four slope positions (hilltop, upper slope, lower slope and valley), (2) each plot must be located along a hill-system transect that ran in a north-south direction from one valley to the adjacent hilltop and down to the next valley, and (3) upper and lower slope plots were distributed as evenly as possible between the north- and south-facing aspects. Once the general location for a plot was established, the first side of the plot was positioned in the direction of a randomly selected azimuth. Plots that included large canopy gaps, escarpments or saturated soil were relocated to avoid sampling

the less common vegetation conditions within the upland forest. Within the 20 x 20 m overstory plots,

white pine trees (10+ cm dbh) were located and measured for dbh. White pine saplings (<10 cm dbh, .5+ m tall) were assessed for %cover in each of the five 2.5 x 2.5 m sub-plots located at the four corners and the centre of the 20 x 20 m plot. White pine seedlings (<.5 m tall) were assessed

Figure 1 - General Location of the Lower Spanish Forest

for %cover in three sets of 5 1 x 1 m quadrats placed at 5 m intervals along a straight line (15 quadrats total). A set of five quadrats ran along each side of the overstory plot parallel to each other and one set ran parallel to the other two sets through the middle of the overstory plot.

Raw data for white pine overstory were converted to basal area (m²/ha) for each plot, and for saplings and seedlings %cover was averaged for each plot. Because none of the data sets were normally distributed, the summarized data were analyzed using the nonparametric Rank Sum Test with the Mann-Whitney U statistic (Analytical Software 1994) to test the null hypotheses that there are no differences in white pine tree, sapling or seedling abundance among the four slope positions including valleys, lower slopes, upper slopes and hilltops.

Results

Mean values for white pine seedling, sapling and tree abundances are presented in Table 1 and the results of the Rank Sum Tests for white pine trees only are presented in Table 2.

Table 1 - White Pine Abundance Estimates for Four Slope
Position Categories in the Rushbrook Lake Study Area

Table 2 - Probability Results from the Rank Sum Test for
the Relationship Between the White Pine Tree Abundance Estimates and the Four Slope Position Categories (H=hilltop, U=upper slope, L=lower slope, V=valley)

^* significantly different (probability less than .05)

^** although this probability value is greater than .05, it is close enough to consider important

The results of the Rank Sum Test applied to the white pine seedling and sapling abundance data showed that there are no significant differences in abundance among slope position categories. However, for all slope position comparisons except for upper slope versus lower slope, the null hypothesis that there is no difference in white pine tree abundance was rejected. In other words, (1) white pine tree abundance on the hilltops was significantly greater than its abundance on the upper slopes, on the lower slopes and in the valleys and (2) white pine tree abundance on the upper and lower slopes was significantly greater than its abundance in the valleys.

Discussion

Compared to the valleys, white pine tree abundance on hilltops in the Rushbrook Lake area was 16 times greater, and compared to the slopes, about twice as abundant. This difference in white pine abundance by slope position supports observations made throughout the northern temperate forest region that forest habitat conditions often vary with topography in areas with significant relief. Generally speaking, white pine tree abundance increases as soil moisture decreases, light intensity at the forest floor increases and fire frequency increases along the slope position gradient from valleys to hilltops in the forested landscapes of central Ontario (Quinby 1991b).

Also, the finding that, of the three broad white pine population age groups, only the white pine trees vary significantly according to slope position indicates that mortality influences (e.g. competition, predation, disease) in the study area manifest in the white pine life cycle sometime after the age of 60 years (approximate maximum age of saplings). A size-class analysis of the tree data as an indicator of age-class distribution should be used in an attempt to identify this point in the white pine life cycle. Both this and the proposed study assume that former seedling and sapling abundance of the present overstory white pine cohort also did not differ by slope position - the use of a pristine, ancient forested landscape to study this phenomenon maximizes this possibility. A better understanding of white pine ecology will facilitate development of more sustainable white pine logging practices and restoration of white pine in areas where it has severely declined or disappeared.

References

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Produced by Ancient Forest Exploration & Research, 93 Westmoreland Ave., Toronto, Ontario M6H 2Z8 phone (416) 535-0205, fax 535-8336; A progress report of the "Lake Temagami Natural Region Conservation Strategy Project"; funding provided by Earthwatch, the Richard Ivey Foundation, the Ontario Heritage Foundation, the Ontario Ministry of Natural Resources, the Helen McCrea Peacock Foundation, and the George Lunan Foundation.

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