Methods

    i.   Site Selection
    ii.  Additional Controls on Site Selection
    iii. GIS Analysis

Site Selection

I will use a stratified-random sampling approach to select a maximum of 36 sites. Stratification will take place by (1) northeast vs. southwest facing aspects (Figure 2), and (2) across the elevation gradient, categorizing sites by low-, mid- and high-elevation positions (Figure 3).

Distinguishing the coolest, most mesic northeast plots from the warmest and driest southwest facing plots will increase the likelihood of capturing variation within and between the strata resulting from differences in the bottom-up micro-climatic controls (Agee 1993; Heyerdahl et al. 2007). In the Darkwoods, the warmest aspects are within the azimuth range of 225 ± 60°, while the coolest aspects are within the range of 45 ± 60°.

Classifying by elevation will increase the likelihood of capturing variation within and between the strata resulting from differences in bottom-up topographic controls. Previous research in southeastern BC has shown mixed-severity regimes to dominate in mid-elevation ranges of the dry-cool Montane Spruce (MSdk) subzone (Gray et al. 2002; Wong et al. 2003; Cochrane 2007), which covers an elevation range of approximately 1100 to 1650 m (Meidinger and Pojar 1991). This elevation range covers the middle one-third (1/3) of the Darkwoods elevation range, clearly within the upper one-half (1/2) of the ICH zone. Furthermore, unpublished research has reported high-severity regimes to dominate the ESSF zone above the MSdk subzone, and low-severity regime dominance in elevation ranges below the MSdk subzone (Wong et al. 2003b). Dividing the elevation gradient of the Darkwoods property into three equal intervals yields low- (533 – 1100 m), mid- (1100 – 1800 m), and high-elevation (1800 – 2455 m) positions, roughly mirroring elevation ranges of these previous studies. Thus, I will have six categories of stratification, all 36 sites distributed evenly between them (Table 4).

Additional Controls on Site Selection

In consideration of the Interior Cedar-Hemlock (ICH) and Engelmann Spruce-Subalpine Fir (ESSF) BEC zones (Figure 4), I will focus on subzones with NDTs ranging from 2 – 4 (Figure 5); the more frequently occurring of the five (see Table 2 and Table 3). These NDTs are important for several reasons. First, they encompass the entire range of elevations found within the study area, allowing for sampling from stands situated in low-, mid- and high-slope positions. Thus, I will be more likely to capture evidence of all three fire regimes. Based on previous research (Table 1), focusing on stands in low- and mid-slope positions, in particular, will maximize the likelihood of locating trees with fire scars, allowing for a greater opportunity to reconstruct low- and mixed-severity fire regimes. Second, the geographic confines of the NDTs place further constraints on site selection. Finally, these NDTs allow me to address the issue pointed out by Gray et al. (2002) regarding discrepancies in the mapped distributions of biogeoclimatic units. In particular, I can determine the appropriateness of NDT3 designations in the area.

Therefore, I will choose multi-cohort stands (at least two separate cohorts), with at least one species being ponderosa pine (Pinus ponderosa), Rocky Mountain Douglas-Fir (Pseudotsuga menziesii var. glauca) or western larch (Larix occidentalis). To increase the chance of selecting a structurally complex, multi-cohort stand, the dominant species must not comprise more than 60% of the stand.

To control for anthropogenic influences of fire suppression or forest manipulation, I will distinguish between pre- and post-Euro-American settlement periods by selecting only forest stands that established prior to 1860. To reduce direct anthropogenic manipulation of forest structure, I will remove stands that were logged, either selectively or clear-cut, unless the logging took place within the last seven years. Stumps can provide easily accessible platforms to obtain cross-sections, provided they are not rotted and unusable (Taylor and Skinner 2003). Previous research has shown seven years to be an ideal time-frame to obtain reliable cross-sections from logged trees (Cochrane 2007). Finally, to avoid ecologically/biologically sensitive areas, I will remove stands designated by Darkwoods officials as environmental protection areas (EPAs).

GIS Analysis

GIS will be used to stratify and identify forest stand polygons meeting the above criteria. Aspect and elevation strata will be generated from a 10m resolution digital elevation model (DEM). Data for BEC zones, subzones and their associated NDTs (2-4 only) will be used to place geographic constraints on the aspect and elevation strata. Forest cover data will be used to select for structurally complex stands (> 3 ha to reduce edge effects), using species composition, age classes, logging history and EPA status as controls.

The following attributes are used as stand selection criteria:

1. NE or SW aspect dominated stands (Figure 2);

2. Within NDT 2-4 classification boundaries (Figure 5, Table 2);

3. Presence of at least two separate cohorts with the following characteristics:

3a. Primary species <= 60% of stand composition AND is either ponderosa pine (Pinus ponderosa), Rocky Mountain Douglas-fir (Pseudotsuga menziesii var. glauca), western larch (Larix occidentalis) or lodgepole pine (Pinus contorta),

3b. Secondary species >= 35% of stand composition AND is either ponderosa pine (Pinus ponderosa), Rocky Mountain Douglas-fir (Pseudotsuga menziesii var. glauca) or western larch (Larix occidentalis);

4a. Stand older than 150 years (established prior to 1860) AND Stand not clear-cut,

4b. Stand clear-cut within the last seven years;

5. Stand is not designated with EPA status.

Once these criteria are met, GIS will be used to randomly place a point within each stand, whereby each point will be buffered by a 1 ha (~56 m radius) circular plot. Plot sizes of 1 ha have been demonstrated to reduce bias toward shorter fire return intervals by limiting the number of trees sampled; the total number of trees sampled will influence fire intervals because not all fires will scar the same trees, where the more trees sampled will increase the likelihood of encountering new fires (Cochrane 2007).

Plots entirely within the stand boundary that are at most 1 km from road access will be accepted as possible site locations. Plots either not entirely within the stand boundary or farther than 1 km from road access will be shifted, if possible, to the closest acceptable position. Furthermore, to avoid sampling from stands likely affected by similar fire events, I will not sample from stands adjacent to one another. Plots not meeting these criteria, even after modification, will be excluded, whereby other randomly selected plots, meeting all of the above stratification and controlling criteria, will be selected for site locations. This process will continue until 36 plots, plus 10 extra, have been selected.

Continue...