"Forestry, Faculty of"@en . "DSpace"@en . "UBCV"@en . "Law, Siew"@en . "2010-08-06T20:38:53Z"@en . "2010-08-06"@en . "The purpose of this study was to determine whether branch gall size of lodgepole pine can indicate the level of resistance towards Western Gall Rust. The diameters of galls were measured from different infection years on the same individuals. The ratio of Gall diameter to Branch diameter was calculated and then correlated with gall incidence. An additional statistical test of Completely Random Design was conducted in hopes of answering the objective. The results suggest that branch gall size cannot indicate level of resistance towards Western Gall Rust."@en . "https://circle.library.ubc.ca/rest/handle/2429/27152?expand=metadata"@en . " Does gall size indicate the level of resistance towards Western Gall Rust? Siew Law An Essay Submitted in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Forestry In The Faculty of Forestry April 24, 2009 2 Abstract The purpose of this study was to determine whether branch gall size of lodgepole pine can indicate the level of resistance towards Western Gall Rust. The diameters of galls were measured from different infection years on the same individuals. The ratio of Gall diameter to Branch diameter was calculated and then correlated with gall incidence. An additional statistical test of Completely Random Design was conducted in hopes of answering the objective. The results suggest that branch gall size cannot indicate level of resistance towards Western Gall Rust. 3 Table of Contents Index of Figures 4 Index of Tables 5 Introduction 6 Methods 9 Results 14 Discussion 18 Summary 22 Literature Cited 22 Appendix 1 \u00E2\u0080\u0093 SAS output 24 Appendix 2 \u00E2\u0080\u0093 SAS input for Completely Random Design 37 Appendix 3 \u00E2\u0080\u0093 Data collected on lodgepole pine with 39 high/low resistance towards Western Gall Rust 4 Index of Figures Figure 1.A gall on lodgepole pine caused by Western Gall Rust. 9 http://www.fs.fed.us/r1-r4/spf/fhp/field_guide/largeimages/fig28b-x.jpg Figure 2. The average number of galls counted for each clone. 12 Figure 3. The methodology in obtaining gall measurements from each 12 level of resistance. Figure 4. How to determine the year of infection. 13 Figure 5. The section of a gall and branch measured on lodgepole pine. 13 Figure 6. Graph showing the correlation between the number of galls 15 and the ratio of gall to branch using the data from Appendix 3 Figure 7. The residual plot for ln (ratio of gall to branch diameter). 16 5 Index of Tables Table 1. Summary of data collection on gall abundance and size 15 relative to resistance level Table 2. Bartlett\u00E2\u0080\u0099s test, verifying whether the variances are equal 16 or not. Table 3. Shapiro-Wilk\u00E2\u0080\u0099s Test for Normality 17 Table 4. Testing for differences between mean gall size of high 17 resistance and low resistance. Table 5. Scheffe\u00E2\u0080\u0099s test, checking for differences between levels 18 of resistance, where LSD = Least Squared Differences. Table 6. Data collected on lodgepole pine with \u00E2\u0080\u0098high resistance\u00E2\u0080\u0099 40 towards Western Gall Rust. June 2007. [Appendix 3] Table 6. Data collected on lodgepole pine with \u00E2\u0080\u0098low resistance\u00E2\u0080\u0099 41 towards Western Gall Rust. June 2007. [Appendix 3] 6 Introduction One major concern in managing forests is the diseases that reduce tree growth and vigour, enabling secondary infections to thrive, resulting in a decrease in timber volume. Rusts are one of the main causes of most diseases resulting in widespread losses of trees due to diseases such as Comandra blister rust, Western Gall Rust (WGR), Cronartium rust and many others. Rusts are unique fungi compared to other fungal types because they are able to infect their host without the requirement of any inflicted wounds on the host (Blenis et al. 1993a). They can enter the host through the host\u00E2\u0080\u0099s natural openings such as the stoma (Blenis et al. 1993a). Western Gall Rust is a tree disease caused by the rust fungus Peridermium harknessii J.P. Moore (=Endocronartium harknessii JP Moore (Y. Hiratsuka)(Blenis and Li 2005). It typically infects hard pines such as lodgepole pine, ponderosa pine, and Jack pine in the western part of North America (Blenis and Li 2005). One of the characteristic symptoms caused by this disease is the formation of galls, which are swollen, globose lesions on the branches or stems of pines (Blenis and Li 2005). Western Gall Rust has a significant impact on the commercial use of pines, which results in considerable losses and damage in timber. To better manage this disease, a number of studies have looked at measuring tools to help indicate the pine\u00E2\u0080\u0099s susceptibility towards this disease. In a few studies, the authors found that Western Gall rust infection decreases with tree age (Blenis and Duncan 1997; Blenis and Li 2005). Blenis and Duncan (1997) tested the following hypothesis: incidence of new infections decreases with tree age and height. They looked at twenty four lodgepole pine stands at ages 26-32 years old that were previously thinned in West Central Alberta. From their study, Blenis and Duncan (1997) found that incidence of gall formation decreases with tree age and tree height. In a 7 similar study, Blenis and Li (2005) tested to see if infection decreases with age and height. They inoculated 327 trees of different ages in two separate height classes and measured temperature, percentage of spore germination, shoot growth, main stem leader length, tree height, and age. With this data, they modeled the percentage of infected trees and number of galls per 10 cm of shoot and found that as tree age increased between 2 and 10 years, the numbers of galls per 10 cm of shoot length decreases (Blenis and Li 2005). In another study, White (2000) studied WGR resistance by comparing a 21-year infection trial with inoculated 2-year old seedlings. White (2000) labeled families as \u00E2\u0080\u009Cleast resistant\u00E2\u0080\u009D when there were 9 or more galls present, while the families labeled as \u00E2\u0080\u009Cmost resistant\u00E2\u0080\u009D contained 2 or fewer galls per individual. From the susceptible families, 99% of inoculated seedlings produced galls, while 50% of seedlings from resistant families did not form galls 13 months after inoculation. White (2000) concluded from his study that inoculating seedlings with E. harknessii helps determine which families are susceptible to Western Gall rust infection; furthermore, it enables for early culling. Resistance can be defined and evaluated in different ways. Snow (1991) looked at gall morphology to measure resistance on loblolly pine (Pinus taeda L.) towards Cronartium quercuum (Berk) Miyabe ex Shirai f.sp. fusiforme (Blenis et al. 1993b). Another technique to evaluate resistance is to calculate the rate of symptom appearance by determining the ratio of the number of galls present four months after inoculation to the number of galls present twenty-eight months after inoculation (Blenis et al. 1993b). A direct measure of resistance is to count the number of seedlings that show initial infection symptoms but fail to develop galls (Blenis et al. 1993b). Hoff (1991) followed this 8 definition of resistance to determine the variation in susceptibility of ponderosa pine. Another way to determine susceptibility is to co-relate presence of live galls with the amount of time the galls were present (Hoff 1991). Hoff (1991) inspected symptoms after inoculating WGR into ponderosa pine trees. He inspected signs and symptoms of the disease after certain time periods: after 27 months, all trees had full and live gall formations; after 39 months, Hoff (1991) concluded that trees that had dead galls were resistant, while trees that still contained live galls were susceptible to WGR. However, it is important to note that ponderosa pine and lodgepole pine exhibit different types of resistance towards western gall rust which was demonstrated in provenance tests by Blenis et al. (1993b). Thus, a similar study like the one done by Hoff (1991) can be conducted for lodgepole pine by looking at the time range of gall formation to determine the level of resistance against WGR. Previous studies conducted by Hiratsuka and Maruyama (1983) suggest that P. densiflora exhibits resistance to WGR (Hopkin et al. 1989).Thus, Hopkin et al. (1989) focused on looking at the biological responses indicating resistance in seedlings of Japanese red pine, Pinus densiflora, when inoculated with E. harknessii. After inoculation, Hopkin et al. (1989) noticed two unique responses exhibited by the pines. In one response, host cell necrosis (the abnormal production of cells), lagged behind the infection region and only occurred after the haustorium (the infective fungal structure) was produced. After 28 days from inoculation, the infected cortex and uninfected vascular tissue were separated by a ring of suberized and lignified endodermal cells which prevented the fungus from further infection. In another response, the host cells would produce chemicals that would encapsulate around the haustorium, which was shortly followed by host cell death and thus destroying the haustorium in the 9 process. From their study, Hopkin et al. (1989) concluded that although the Japanese pine developed necrosis after infection it was able to prevent further infection; therefore, there was no gall formation. To help tree breeders select for resistance, a measure of susceptibility is needed from the past. Past studies have focused on tree height, tree age, gall incidence, early inoculation, life expectancy of galls, and the microbiology of infection, but very few studies look at the size of galls (Allen et al. 1990; Blenis and Duncan 1997; Blenis and Li 2005; Hopkin 1989; White 2000). Can gall size be a measuring tool for susceptibility? The objective of this study is to determine whether gall size can indicate the level of susceptibility towards Western Gall Rust infection for lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.). For the purpose of this study, high susceptibility was determined by a high frequency of galls per individual. Figure 1. A gall on lodgepole pine caused by Western Gall Rust. http://www.fs.fed.us/r1-r4/spf/fhp/field_guide/largeimages/fig28b-x.jpg Method Data was collected at the Tree Improvement Station, which is a seed orchard located in Prince George, British Columbia. The orchard contained forty clones, each consisting of 10 fourty ramets (replicates of a clone), with a total of 1600 trees randomly dispersed in equidistant rows spaced approximately 3 meters apart. Before gall measurements were conducted, the number of galls was counted on each tree to characterize the level of susceptibility for each clone. By looking at the average gall count per clone, four of the most resistant and three of the least resistant clones were selected for gall measurements (Figure 2). The data from Figure 2 was sorted from low gall counts to high gall counts to determine the clones with the absolute minimum and maximum number of galls compared to other clones in the orchard. The clones labeled as most resistant were the ones that contained no more than 10 galls per individual, while the clones labeled as least resistant trees contained over 80 galls per individual on average. Table ## summarizes the clones of high and low resistance and the number of galls found for the randomly selected ramets. After determining the most susceptible and least susceptible clones, three of the most susceptible (or least resistant) ramets were chosen from each clone, with a total of twenty four ramets sampled. From each ramet, a gall from each infection year was measured: 1997, 2000, and 2002, with a total of three galls per ramet (Figure 3). For the high resistant clones, it was difficult to find galls from the 2002 infection year; thus, additional measurements from the 2000 infection year were obtained. A total of 58 observations were made: 27 galls were measured from clones of high resistance and 31 galls were measured from clones of low resistance. Infection years were determined by counting each node, starting at the tips of the branches, which represented the growth of the current year (Figure 4).Galls usually grow from one portion of the branch and eventually girdle the entire branch. Not all galls fully encircle a branch, nor do they grow uniformly (not a perfect sphere). Thus, the thickest 11 part of the gall was measured using a caliper. The branch diameter was measured on both sides of the gall, parallel to the portion of the gall measured, and the average was obtained (Figure 5). Since branch diameter and gall diameter are related, the ratio of gall diameter to branch diameter (ratioGB) was calculated to reduce bias. The objective of this experiment is to determine whether gall size can indicate level of resistance towards WGR was met utilizing a Completely Randomized Design with one factor by inputting data into SAS version 9.1. The resistance level (treatment), tree position (experimental unit), and ratioGB(y-variable) were analyzed using SAS version 9.1. The SAS output and input can be found in Appendix 1 and 2, respectively. In order to determine whether this design is reliable, certain assumptions need to be met: equal variance of residuals as indicated by the residual plot, the Bartlett\u00E2\u0080\u0099s test, normality of residuals, and independence of the observations. Since the assumptions were not met for the original data, transformations were made to meet the assumptions. 12 0 20 40 60 80 100 120 140 160 180 200 1 5 3 6 1 5 8 5 1 5 3 8 1 5 7 1 1 5 9 5 9 8 1 9 8 4 1 4 6 5 1 5 9 6 1 5 8 4 1 5 8 1 1 5 8 6 1 4 6 4 1 5 4 0 1 5 9 0 1 4 6 1 1 4 6 0 9 8 9 1 5 3 2 1 4 6 6 9 1 0 1 5 3 3 1 5 6 3 1 5 9 4 1 5 8 3 1 5 8 8 9 8 7 9 8 2 1 5 3 9 9 8 3 9 5 1 9 8 6 1 5 6 0 1 4 6 7 1 5 9 3 1 4 6 2 2 0 0 0 1 5 8 9 1 4 6 3 1 5 9 9 M e a n G a ll C o u n t Clone ID Comparison of Surveyor Bias Bulkley # 228 S&J Gall D&A Gall Figure 2. The average number of galls counted for each clone. The y-axis is the mean number of galls of 40 ramets, and the x-axis is the different clones. Gall measurements were obtained from clones with high gall numbers (far right) and clones with very low gall numbers (left). Data was collected twice: once in 2006 and once in 2007, labeled blue and green, respectively. Graph provided by Richard Reich (2007) Figure 3. The methodology in obtaining gall measurements from each level of resistance. 13 Figure 4. How to determine the year of infection. The circles represent the beginning of the growth (the node), and the black circle represents a gall. In this figure, the gall has formed between the 2002 and 2003 node; this indicates that the tree was infected in 2002. . Figure 5. The section of a gall and branch measured on lodgepole pine. Since the circumference of a branch varies along the length of it, the diameter of the branch was measured (as close as possible to the gall) on either side of the gall; and the average was calculated. 14 Results The average number of galls found on susceptible clones was greater than 80 galls per tree, while the average number of galls found on resistant clones was less than 2 galls per tree. Table 1 summarizes the data collected. Using Excel 2002, a correlation test was conducted to determine whether there was a positive correlation between the number of galls per tree and the number of galls per tree. The gall abundance and ratio of gall size to branch size values were obtained from Table 1 and incorporated into the correlation test. Figure 6 shows the correlation test, with an r-squared value of 0.009, which suggests there is no correlation between increasing gall number with increasing gall size. Tables and figures in this section were obtained from the SAS output in Appendix 1. To determine whether there is a significant difference between the gall size of high resistance and low resistance, analysis of variance is required from a Completely Randomized Design with one factor. Firstly, the assumptions need to be met before further analysis can be conducted to determine whether this is a reliable model or not. Looking at the residual plot in Figure 7, the residuals appear to have equal variance. To confirm this observation, Bartlett\u00E2\u0080\u0099s test was conducted, and indicated that variances are equal (Table 2). 15 Table 1. Summary of data collection on gall abundance and size relative to resistance level. Detailed data collection can be found in Appendix 3. Clone ID Average Number of galls Average Gall size to Branch size Ratio (G:B) Level of Resistance 1571 0.389 2.2 High 1584 1.725 2.4 High 1595 0.439 2.1 High 1596 1.452 2.6 High 1463 105.712 2.6 Low 1599 198.405 2.4 Low 2000 80.051 2.2 Low y = -11.051x + 100.24 R 2 = 0.0088 0 50 100 150 200 250 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Ratio gall:branch n u m b e r o f g a ll s Figure 6. Graph showing the correlation between the number of galls and the ratio of gall to branch using the data from Appendix 3. The r-squared value was calculated to be 0.0088. 16 Plot of RESID*PREDICT. Symbol used is '*'. RESID \u00E2\u0080\u009A 0.6 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A * 0.4 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * 0.2 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * 0.0 \u00CB\u0086 * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * -0.2 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * -0.4 \u00CB\u0086 * \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A * -0.6 \u00CB\u0086 \u00E2\u0080\u009A \u00C5\u00A0\u00C6\u0092\u00C6\u0092\u00CB\u0086\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00CB\u0086\u00C6\u0092\u00C6\u0092 0.8381 0.8532 PREDICT NOTE: 21 obs hidden. Figure 7. The residual plot for ln (ratio of gall to branch diameter). Table 2. Bartlett\u00E2\u0080\u0099s test, verifying whether the variances are equal or not. Test Outcome \u00CE\u00B1 0.05 H0 Variances are equal H1 At least one of the variances is not equal If p < \u00CE\u00B1 , Reject H0. p-value 0.2837 p-value>\u00CE\u00B1 Fail to reject H0 Conclusion: The variances are equal. 17 Due to the nature of the sampling, I must assume the observations are independent of each other. The results for the test for normality are summarized in Table 3. Table 3. Shapiro-Wilk\u00E2\u0080\u0099s Test for Normality Test Outcome \u00CE\u00B1 0.05 H0 Data are normal H1 Data are not normal If p<\u00CE\u00B1 Reject H0 p-value 0.8081 p-value>\u00CE\u00B1 Fail to reject H0. Conclusion The data are normal. . The assumptions appear to have been met according to the residual plot and normality test; thus this model is fairly reliable. Table 4 shows the test for differences between high resistance and low resistance, where the p-value was obtained from page 4 of Appendix 1. Table 4. Testing for differences between mean gall size of high resistance and low resistance. Test Outcome \u00CE\u00B1 0.05 H0: 21 \u00C2\u00B5\u00C2\u00B5 = (not significant; no difference) H1: 21 \u00C2\u00B5\u00C2\u00B5 \u00E2\u0089\u00A0 (significant; there is a difference) F-value 0.05 If p-value < \u00CE\u00B1 Reject H0. p-value 0.8177 p-value > \u00CE\u00B1 Fail to reject H0. Conclusion: There is no significant difference between mean gall size of low resistance and high resistance. Scheffe\u00E2\u0080\u0099s test was conducted to double check for differences between the levels of resistance (Table 5); the test values were obtained from Scheffe\u00E2\u0080\u0099s Test for ln in Appendix 1. 18 Table 5. Scheffe\u00E2\u0080\u0099s test, checking for differences between levels of resistance, where LSD = Least Squared Differences. Test Outcome If LSD < (meanhigh \u00E2\u0080\u0093 meanlow) Then this pair is different (meanhigh \u00E2\u0080\u0093 meanlow) = 0.85319 \u00E2\u0080\u0093 0.83809 = 0.0151 LSD = 0.1306 F-value 4.01297 Since LSD > (meanhigh \u00E2\u0080\u0093 meanlow) Then, this pair is not different Discussion The results suggest that there is no significant difference in mean gall size between lodgepole pine trees of low resistance versus lodgepole pine trees of high resistance according to the correlation test as well as the Completely Random Design. Since the assumptions have been met, the Completely Random Design is a reliable model and it can be concluded from this analysis that gall size cannot help indicate the level of resistance of lodgepole pine infected with Western Gall Rust. One study conducted by Gross (1983) suggests that branch galls are a result of lateral shoots being infected, which have very little effect on growth, while stem galls, which are a result of stem leaders getting infected, can have fatal effects. Additional studies should be conducted to support the hypothesis that branch galls have very little impact on tree growth and vigour. There are other studies that look at other factors that indicate resistance to Western Gall Rust. Allen et al. (1990) studied resistance to Western Gall Rust in lodgepole pine by looking at the different types of tissues: epidermal, cortical, and cambial. He found that the epidermal tissue is resistant. First the fungus successfully invades into the epidermal tissue, but growth was halted by a hypersensitive response. In resistant cambium, infection spread to the vascular cambium and deactivated cambial initials. As a consequence, there was abnormal growth in the secondary xylem (Allen et al. 1990). In most seedlings, areas of infection were overgrown and cambial function was re- 19 established (Allen et al. 1990). This study suggests that some trees need to be infected in order to activate their resistant genes. One of the assumptions made in this study was that all ramets were all the same individuals and were representative of a clone. The study conducted by Zagory and Libby (1985) strengthens the methods in this study because the trees in which the data was collected from were all clones. Their objective was to determine the relationship between maturation and resistance to western gall rust (Zaggory and Libby 1985). They compared mature Pinus radiata donor plants to vegetatively-propogated juveniles of the same species. The results showed that the mature individuals had fewer galls caused by western gall rust than did the juvenile clones two years after inoculation. Moreover, the heritability of the clones was high, and they found that there was no interaction between the mature individuals and their clones. These results suggest that cloning resistant individuals at a certain maturity stage may mitigate the impact caused by western gall rust (Zagory and Libby, 1985). It is evident that a majority of Pinus contorta individuals are susceptible to Western Gall Rust (WGR). Currently, no native hard pines have been found to be resistant to Western Gall Rust via provenance tests (Hopkin et al. 1989). Hiratsuka and Maruyama (1983) found two Asian pines, Pinus densiflora and Pinus thunbergii, to be resistant to WGR (Hopkin et al. 1989). If breeders can successfully cross breed the Asian pines with the hard pines that are native to British Columbia, then the resulting hybrids may inherit the trait that enables the trees to be resistant to WGR infection. 20 In this study, level of resistance was based on gall incidence. From this definition of resistance, gall size was measured and compared to gall incidence, but no correlation was found. However, in a study conducted by White (2000), the author also based the level of resistance on gall incidence and found a positive correlation between incidence and time of gall formation. Thus, gall incidence may be used as a basis to define level of resistance. There has been controversy on whether foliage or lesion colour can indicate gall formation and level of susceptibility (Walla et al. 1997; Kojwang and van der Kamp 1992). Walla et al. (1997) conducted a study to determine a relationship between pre-gall symptoms and gall formation in Ponderosa pine. Pre-gall symptoms included a light red tinge at the base of the needles. The authors noted the change in needle colour after inoculation, and then measured gall width 230 days after inoculation. Walla et al. (1997) suggested a functional relationship between increased light red pigment and gall characteristic (ie width); the increased amount of light red pigment correlated to wider galls. Seedlings with little or no red pigment developed narrower galls. Kojwang and vander Kamp (1992) conducted a study with a similar objective of finding a relationship between pre-gall symptoms and gall formation for lodgepole pine. Pre-gall symptoms included red stain, red flecks, and red streaks on the bark. Instead of measuring gall width, the authors counted the number of galls one year after inoculation. Early symptoms were poorly correlated with gall formation. Thus, the results suggest that early symptoms cannot accurately identify resistant families or individuals (Kojwang and van der Kamp 1991). If Kojwang and van der Kamp (1991) had mimicked the study 21 conducted by Walla (1997), would the results have been similar or different for lodgepole pine? Aside from testing for resistance within the individual, there is also research on beneficial organisms that help the trees establish resistance against WGR (Moltzan and Blenis 1999). Moltzan and Blenis (1999) surveyed 18 lodgepole pine stands for the endoparasite, Scytalidium uredinicola (Kuhlman et al.) in west central Alberta. The purpose of their study was to determine how gall age, size, and occurrence of WGR affected hyperparasite incidence, since it may be a possible biocontrol agent. Their results suggest a positive correlation between the increase of gall size and age with incidence of the parasite. However, the parasite was still present in very low numbers, thus it would not be practical to use it as a biocontrol agent. Moltzan and Blenis (1999) measured stem gall size and ignored branch galls, while the focus in this study was mainly branch galls and stem gall was ignored. Thus, a possible study may focus on stem galls instead of branch galls and determine whether stem gall size can indicate level of resistance towards WGR. Another study can focus on cross breeding. Hopkin et al. (1989) studied the phenology of Japanese pines after inoculating them with E. harknessii to comprehend how the trees become resistant to WGR disease. A possible study can focus on trying to cross breed Japanese pines with lodgepole pines of British Columbia, which may successfully produce a sterile hybrid with resistant genes against WGR infection. 22 Summary The objective was to determine whether gall size could help indicate the level of resistance towards Western Gall Rust for lodgepole pine trees by comparing the mean gall size of resistant versus susceptible (low resistant) trees. According to the analysis, there is no significant difference in mean gall size between the two levels of resistant trees. Other factors that could not be accounted for in the analysis but may have affected the ratioGB are branch type (whether it be primary, secondary, or tertiary), branch location (high up near the crown, or down at breast height), tree position (some trees were at the edge of the orchard while others were right in the middle of the orchard surrounded by other trees), susceptibility to other diseases or pests (mountain pine beetle, pitch moth, the midge, and foliage diseases). However, if too many variables are considered, the model will become too complex to analyze. Another possible study could look at the growth rate of galls and trying to correlate it with level of resistance. This study demonstrates the challenges in finding a correlation between gall size and level of susceptibility. Literature cited Allen, E.A., P.V. Blenis, and Y. Hiratsuka. 1990. Histological evidence of resistance to Endocronartium harknessii in Pinus contorta var. latifolia. Can. J. Bot. 68(8): 1728\u00E2\u0080\u00931737. Blenis, P.V., K.-F. Chang, and Y. Hiratsuka. 1993a. Spore dispersal gradients and disease gradients of western gall rust. Can. J. For. Res. 23: 2481-2486. Blenis, P.V., H.D. Pinnell, and S.E.T. John. 1993b. Stand, family, and rust-source effects on four attributes of lodgepole pine resistance to western gall rust. Can. J. For. Res. 23(2): 144-150. 23 Blenis, P.V., and I. Duncan. 1997. Management implications of western gall rust in precommercially thinned lodgepole pine stands. Can. J. For. Res. 27: 603-608. Blenis, P.V., and W. Li.2005. Incidence of main stem infections of lodgepole pine by western gall rust decreases with tree age. Can. J. For. Res. 32: 1314-1318 Gross, H.L. 1983. Negligible Cull and Growth Loss of Jack Pine Associated with Globose Gall Rust. For. Chron 59 (6): 309-311. Hiratsuka, Y., and P.J. Maruyama. 1983. Resistant reactions of two Asian pines to western gall rust. Phytopathology 73: 835. (Abstr.) Hoff, R. J. 1991. Resistance to western gall rust in artificially inoculated ponderosa pine. Can. J. For. Res. 21: 1316-1320. Hopkin, A.A., P.V. Blenis, and Y. Hiratsuka. 1989. Resistant responses in juvenile seedlings of Pinus densiflora (Japanese red pine) inoculated with Endocronartium harknessii. Can. J. Bot. 67: 3545-3552. Kojwang, H.O., and B.J. van der Kamp. 1992. Early symptoms and resistance of lodgepole pine seedlings inoculated with western gall rust. Can. J. Bot. 70: 1274- 1278. Moltzan, B.D., and P.V. Blenis. 1999. Effects of gall age, gall size, and rust severity on the incidence of the mycoparasite Scytalidium uredinicola. Can. J. For. Res. 29: 319-343. Snow, G.A. 1991. Gall shape as an indicator of resistance to fusiform rust on loblolly pine. In Rusts of Pine. Proceedings of the IUFRO Rusts of Pine Working Party Conference, 18-22 Sept. 1989, Banff, Alta. Edited by Y. Hiratsuka, J.K. Samoil, P.V. Blenis, P.E. Crane, and B.L. Laishley. Can For. Serv. North. For. Res. Cent. Inf. Rep. NOR-X-236. pp. 265-267. Walla, J.A., G.A. Tuskan, J.E. Lundquist, and C. Wang. 1997. Expression of inoculum and family specific responses in the ponderosa pine\u00E2\u0080\u0094western gall rust pathosystem. Plant Dis. 81: 57-62 White, E.E., E.A. Allen, C.C. Ying, and B.M. Foord. 2000. Seedling inoculation distinguishes lodgepole pine families most and least susceptible to gall rust. Can. J. For. Res. 30: 841-843. Zagory, D., and W.J. Libby. 1985. Maturation-related resistance of Pinus radiata to western gall rust. Phytopathology 75(12): 1443-1447. 24 APPENDIX 1 25 The CONTENTS Procedure Data Set Name WORK.HTDATA Observations 58 Member Type DATA Variables 4 Engine V9 Indexes 0 Created Tuesday, November 27, Observation Length 24 2008 11:44:12 AM Last Modified Tuesday, November 27, Deleted Observations 0 2008 11:44:12 AM Protection Compressed NO Data Set Type Sorted YES Label Data Representation WINDOWS_32 Encoding wlatin1 Western (Windows) Engine/Host Dependent Information Data Set Page Size 4096 Number of Data Set Pages 1 First Data Page 1 Max Obs per Page 168 Obs in First Data Page 58 Number of Data Set Repairs 0 File Name C:\Program files\SAS\Temp\SAS Temporary Files\_TD3740\htdata.sas7bdat Release Created 9.0101M3 Host Created XP_PRO Alphabetic List of Variables and Attributes # Variable Type Len Format Informat Label 2 Exp_unit Char 4 $4. $4. Exp_unit 4 ln Num 8 ln 3 ratioGwB Num 8 ratioGwB 1 resistance Char 4 $4. $4. resistance Sort Information Sortedby resistance Validated YES Character Set ANSI 26 The SAS System 2 11:42 Tuesday, November 27, 2008 -------------------------- resistance=high --------------------------- The MEANS Procedure Analysis Variable : ln ln N Mean Std Dev Minimum Maximum \u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092 27 0.8531924 0.2194225 0.5071491 1.4234734 \u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092 --------------------------- resistance=low --------------------------- Analysis Variable : ln ln N Mean Std Dev Minimum Maximum \u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092 31 0.8380910 0.2697913 0.2583419 1.4417242 \u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092 27 The SAS System 3 11:42 Tuesday, November 27, 2008 The GLM Procedure Class Level Information Class Levels Values resistance 2 high low Number of Observations Read 58 Number of Observations Used 58 28 The SAS System 4 11:42 Tuesday, November 27, 2008 The GLM Procedure Dependent Variable: ln ln Sum of Source DF Squares Mean Square F Value Model 1 0.00329105 0.00329105 0.05 Error 56 3.43542184 0.06134682 Corrected Total 57 3.43871289 Source Pr > F Model 0.8177 Error Corrected Total R-Square Coeff Var Root MSE ln Mean 0.000957 29.30739 0.247683 0.845121 Source DF Type I SS Mean Square F Value resistance 1 0.00329105 0.00329105 0.05 Source Pr > F resistance 0.8177 Source DF Type III SS Mean Square F Value resistance 1 0.00329105 0.00329105 0.05 Source Pr > F resistance 0.8177 29 The SAS System 5 11:42 Tuesday, November 27, 2008 The GLM Procedure Bartlett's Test for Homogeneity of ln Variance Source DF Chi-Square Pr > ChiSq resistance 1 1.1492 0.2837 30 The SAS System 6 11:42 Tuesday, November 27, 2008 The GLM Procedure Scheffe's Test for ln NOTE: This test controls the Type I experimentwise error rate. Alpha 0.05 Error Degrees of Freedom 56 Error Mean Square 0.061347 Critical Value of F 4.01297 Minimum Significant Difference 0.1306 Harmonic Mean of Cell Sizes 28.86207 NOTE: Cell sizes are not equal. Means with the same letter are not significantly different. Scheffe Grouping Mean N resistance A 0.85319 27 high A A 0.83809 31 low 31 The SAS System 7 11:42 Tuesday, November 27, 2008 Plot of RESID*PREDICT. Symbol used is '*'. RESID \u00E2\u0080\u009A 0.6 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A * 0.4 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * 0.2 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * 0.0 \u00CB\u0086 * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * * -0.2 \u00CB\u0086 * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * \u00E2\u0080\u009A * * \u00E2\u0080\u009A * -0.4 \u00CB\u0086 * \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A \u00E2\u0080\u009A * -0.6 \u00CB\u0086 \u00E2\u0080\u009A \u00C5\u00A0\u00C6\u0092\u00C6\u0092\u00CB\u0086\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00C6\u0092\u00CB\u0086\u00C6\u0092\u00C6\u0092 0.8381 0.8532 PREDICT NOTE: 21 obs hidden. 32 The SAS System 8 11:42 Tuesday, November 27, 2008 The UNIVARIATE Procedure Variable: RESID Moments N 58 Sum Weights 58 Mean 0 Sum Observations 0 Std Deviation 0.24550063 Variance 0.06027056 Skewness 0.2989509 Kurtosis 0.01077645 Uncorrected SS 3.43542184 Corrected SS 3.43542184 Coeff Variation . Std Error Mean 0.03223581 Basic Statistical Measures Location Variability Mean 0.00000 Std Deviation 0.24550 Median -0.03556 Variance 0.06027 Mode . Range 1.18338 Interquartile Range 0.33584 Tests for Location: Mu0=0 Test -Statistic- -----p Value------ Student's t t 0 Pr > |t| 1.0000 Sign M -3 Pr >= |M| 0.5118 Signed Rank S -28.5 Pr >= |S| 0.8276 Tests for Normality Test --Statistic--- -----p Value------ Shapiro-Wilk W 0.987392 Pr < W 0.8081 Kolmogorov-Smirnov D 0.077061 Pr > D >0.1500 Cramer-von Mises W-Sq 0.044311 Pr > W-Sq >0.2500 Anderson-Darling A-Sq 0.264532 Pr > A-Sq >0.2500 33 The SAS System 9 11:42 Tuesday, November 27, 2008 The UNIVARIATE Procedure Variable: RESID Quantiles (Definition 5) Quantile Estimate 100% Max 0.6036332 99% 0.6036332 95% 0.4284022 90% 0.3620283 75% Q3 0.1757991 50% Median -0.0355579 25% Q1 -0.1600452 10% -0.3288666 5% -0.3534677 1% -0.5797491 0% Min -0.5797491 Extreme Observations ------Lowest------ ------Highest----- Value Obs Value Obs -0.579749 28 0.385300 55 -0.394670 29 0.416526 56 -0.353468 30 0.428402 57 -0.346043 1 0.570281 27 -0.336154 31 0.603633 58 34 The SAS System 10 11:42 Tuesday, November 27, 2008 The UNIVARIATE Procedure Variable: RESID Stem Leaf # Boxplot 6 0 1 | 5 7 1 | 5 | 4 | 4 23 2 | 3 69 2 | 3 0 1 | 2 5 1 | 2 01234 5 | 1 5688 4 +-----+ 1 12 2 | | 0 677 3 | | 0 1144 4 | + | -0 4330 4 *-----* -0 9887666 7 | | -1 42200 5 | | -1 7765 4 +-----+ -2 320 3 | -2 86 2 | -3 431 3 | -3 955 3 | -4 | -4 | -5 | -5 8 1 | ----+----+----+----+ Multiply Stem.Leaf by 10**-1 35 The SAS System 11 11:42 Tuesday, November 27, 2008 The UNIVARIATE Procedure Variable: RESID Normal Probability Plot 0.625+ * + | * ++ | ++ | ++ | * *+ | **++ | *++ | *+ | *** | **+ | ** | ** 0.025+ ++** | ++** | **** | ** | ** | *** | +** | **** | * *++ | ++ | ++ | ++ -0.575+ +* +----+----+----+----+----+----+----+----+----+----+ -2 -1 0 +1 +2 36 hi gh l ow 0. 25 0. 50 0. 75 1. 00 1. 25 1. 50 l n resi st ance X=. 845 UCL LCL 3 Li mi t s: Subgroup Si zes: Mi n n=27 Max n=31 37 APPENDIX 2 38 SAS input PROC IMPORT OUT= WORK.htdata DATAFILE= \"\\forestry.ubc.ca\Drives\Undergrads\slaw\Desktop\Siewstats .xls\" DBMS=EXCEL REPLACE; SHEET=\"data$\"; GETNAMES=YES; MIXED=NO; SCANTEXT=YES; USEDATE=YES; SCANTIME=YES; RUN; options ls=70 ps=50 pageno=1; run; proc sort data=htdata; by resistance; run; proc contents data=htdata; run; Proc means data=htdata; var ln; by resistance; run; proc shewhart data=htdata; boxchart ln*resistance; run; PROC GLM data=htdata; CLASS resistance; MODEL ln=resistance; MEANS resistance/scheffe hovtest=bartlett; estimate '1 VS others' resistance 2 -1 -1/divisor=2; OUTPUT OUT=GLMOUT PREDICTED=PREDICT RESIDUAL=RESID; RUN; PROC PLOT DATA=GLMOUT; PLOT RESID*PREDICT='*'; RUN; PROC UNIVARIATE DATA=GLMOUT PLOT NORMAL; VAR RESID; RUN; 39 APPENDIX 3 4 0 T a b le 6 . D at a co ll ec te d o n l o d g ep o le p in e w it h \u00E2\u0080\u0098 h ig h r es is ta n ce \u00E2\u0080\u0099 to w ar d s W es te rn G al l R u st . Ju n e 2 0 0 7 . R a m e t C lo n e ID R e s is ta n c e L e v e l G a ll D ia m e te r, W id th h o ri z o n ta l (m m ) G a ll D ia m e te r, th ic k n e s s v e rt ic a l (m m ) G a ll th ic k n e s s (n o b ra n c h ) B ra n c h D ia m e te r, A v e ra g e (m m ) In fe c ti o n Y e a r B ra n c h O rd e r H e ig h t o f W h o rl (c m ) P e rc e n t o f C ir c u m fe re n c e g ir d le d A z im u th 2 1 5 7 1 h ig h 4 0 .1 3 8 .2 1 5 .0 2 3 .2 2 0 0 0 1 \u00C2\u00B0 2 2 9 5 0 % 2 5 8 \u00C2\u00B0 1 6 1 5 7 1 h ig h 3 2 .5 2 8 .3 1 7 1 1 .3 2 0 0 0 2 .5 \u00C2\u00B0 1 3 2 9 5 % 4 \u00C2\u00B0 2 2 1 5 7 1 h ig h 2 6 .3 2 0 .1 7 .8 1 2 .4 2 0 0 0 2 \u00C2\u00B0 2 1 1 5 5 % 8 \u00C2\u00B0 2 1 5 8 4 h ig h 2 2 .4 1 7 .3 9 .9 7 .4 2 0 0 0 2 \u00C2\u00B0 1 4 0 7 5 % 4 2 \u00C2\u00B0 2 1 5 8 4 h ig h 5 4 .3 4 7 .0 1 4 .3 3 2 .7 2 0 0 0 1 \u00C2\u00B0 2 0 8 5 5 % 2 4 8 \u00C2\u00B0 5 1 5 8 4 h ig h 5 4 .4 5 0 .0 1 9 .5 3 0 .6 2 0 0 0 1 \u00C2\u00B0 2 5 2 5 0 % 1 3 0 \u00C2\u00B0 5 1 5 8 4 h ig h 3 1 .8 2 5 .3 1 2 .7 1 2 .6 2 0 0 0 2 \u00C2\u00B0 1 9 3 7 0 % 2 2 8 \u00C2\u00B0 5 1 5 8 4 h ig h 3 1 .5 3 0 .0 1 7 .4 1 2 .6 2 0 0 0 2 \u00C2\u00B0 2 9 2 9 5 % 6 6 \u00C2\u00B0 5 1 5 8 4 h ig h 1 8 .0 1 8 .5 9 .0 9 .6 2 0 0 0 2 \u00C2\u00B0 1 8 2 5 5 % 2 1 7 \u00C2\u00B0 7 1 5 8 4 h ig h 5 3 .2 5 0 .7 3 3 .0 1 7 .8 2 0 0 0 2 \u00C2\u00BA 1 9 9 9 5 % 3 2 9 \u00C2\u00B0 7 1 5 8 4 h ig h 3 7 .8 3 3 .0 1 2 .2 2 0 .9 2 0 0 0 1 \u00C2\u00B0 2 3 0 4 5 % 2 6 2 \u00C2\u00B0 8 1 5 8 4 h ig h 4 0 .7 3 5 .9 2 1 .9 1 4 .0 2 0 0 0 2 \u00C2\u00B0 1 3 2 7 5 % 4 0 \u00C2\u00B0 8 1 5 8 4 h ig h 3 3 .0 3 2 .3 1 6 .1 1 6 .2 1 9 9 7 2 \u00C2\u00B0 1 6 5 9 5 % 3 1 2 \u00C2\u00B0 1 5 1 5 8 4 h ig h 3 7 .5 3 1 .1 1 7 .0 1 4 .2 2 0 0 0 2 \u00C2\u00B0 1 3 8 7 5 % 2 8 0 \u00C2\u00B0 2 0 1 5 8 4 h ig h 4 5 .3 3 8 .5 1 4 .3 2 4 .2 2 0 0 0 1 \u00C2\u00B0 1 7 6 5 0 % 1 6 6 \u00C2\u00B0 2 1 1 5 8 4 h ig h 5 5 .9 4 7 .8 2 4 .9 2 2 .9 1 9 9 7 1 \u00C2\u00B0 1 6 2 9 5 % 2 7 3 \u00C2\u00B0 2 1 1 5 8 4 h ig h 3 9 .7 3 6 .4 1 6 .5 2 0 .0 2 0 0 0 2 \u00C2\u00B0 2 6 9 1 0 0 % 2 3 1 \u00C2\u00B0 2 2 1 5 8 4 h ig h 2 7 .4 2 4 .9 1 8 .3 6 .6 2 0 0 0 2 \u00C2\u00B0 2 0 2 1 0 0 % 9 7 \u00C2\u00B0 2 3 1 5 8 4 h ig h 2 2 .2 1 7 .2 9 .1 8 .2 2 0 0 0 1 \u00C2\u00B0 1 6 3 6 5 % 2 9 0 \u00C2\u00B0 2 3 1 5 8 4 h ig h 3 4 .6 2 7 .8 1 4 .6 1 3 .3 2 0 0 0 2 \u00C2\u00B0 1 5 0 8 0 % 6 3 \u00C2\u00B0 1 1 5 9 5 h ig h 5 5 .8 4 1 .0 1 4 .2 2 6 .8 2 0 0 0 1 \u00C2\u00B0 2 7 4 7 0 % 2 4 7 \u00C2\u00B0 6 1 5 9 5 h ig h 2 6 .5 2 1 .0 8 .9 1 2 .1 2 0 0 0 2 \u00C2\u00B0 3 2 1 6 5 % 3 3 6 \u00C2\u00B0 1 8 1 5 9 5 h ig h 2 1 .2 2 0 .6 1 0 .0 1 0 .6 2 0 0 0 2 \u00C2\u00B0 1 8 3 5 0 % 1 2 8 \u00C2\u00B0 1 4 1 5 9 6 h ig h 4 1 .6 4 1 .3 2 2 .9 1 8 .5 1 9 9 7 2 \u00C2\u00B0 2 0 3 1 0 0 % 2 8 0 \u00C2\u00B0 1 4 1 5 9 6 h ig h 2 4 .0 2 2 .5 1 2 .4 1 0 .1 2 0 0 0 2 \u00C2\u00B0 3 2 9 7 0 % 2 6 3 \u00C2\u00B0 1 4 1 5 9 6 h ig h 4 0 .2 2 7 .6 1 5 .0 1 2 .7 2 0 0 0 1 \u00C2\u00B0 2 7 0 8 5 % 6 9 \u00C2\u00B0 1 4 1 5 9 6 h ig h 2 3 .2 1 9 .8 1 0 .6 9 .2 2 0 0 0 1 \u00C2\u00B0 3 1 1 9 0 % 9 4 \u00C2\u00B0 4 1 T a b le 2 . D at a co ll ec te d o n l o d g ep o le p in e w it h \u00E2\u0080\u0098 lo w r es is ta n ce \u00E2\u0080\u0099 to w ar d s W es te rn G al l R u st . Ju n e 2 0 0 7 . R a m e t C lo n e ID R e s is ta n c e L e v e l G a ll D ia m e te r, W id th h o ri z o n ta l (m m ) G a ll D ia m e te r, th ic k n e s s v e rt ic a l (m m ) G a ll th ic k n e s s (n o b ra n c h ) B ra n c h D ia m e te r, A v e ra g e (m m ) In fe c ti o n Y e a r B ra n c h O rd e r H e ig h t o f W h o rl (c m ) P e rc e n t o f C ir c u m fe re n c e g ir d le d A z im u th 1 1 1 4 6 3 lo w 3 9 .0 3 0 .7 1 4 .1 1 6 .7 2 0 0 0 1 \u00C2\u00B0 1 7 8 1 0 0 % 3 0 7 \u00C2\u00B0 1 1 1 4 6 3 lo w 2 2 .0 2 2 .3 1 0 .7 1 1 .7 2 0 0 2 1 \u00C2\u00B0 2 1 5 8 5 % 3 0 1 \u00C2\u00B0 1 1 1 4 6 3 lo w 6 7 .0 5 7 .3 2 6 .1 3 1 .3 1 9 9 7 1 \u00C2\u00B0 2 0 2 1 0 0 % 3 1 7 \u00C2\u00B0 1 9 1 4 6 3 lo w 4 3 .8 4 2 .4 2 7 .3 1 5 .2 2 0 0 0 1 .5 \u00C2\u00B0 1 7 7 1 0 0 % 2 7 8 \u00C2\u00B0 1 9 1 4 6 3 lo w 4 0 .8 3 5 .6 2 6 .0 9 .7 2 0 0 2 2 \u00C2\u00B0 1 1 9 1 0 0 % 3 1 2 \u00C2\u00B0 1 9 1 4 6 3 lo w 6 9 .4 5 4 .4 2 1 .8 3 2 .6 1 9 9 7 1 \u00C2\u00B0 1 9 1 8 5 % 1 8 3 \u00C2\u00B0 2 4 1 4 6 3 lo w 5 6 .0 4 1 .9 8 .0 3 3 .9 1 9 9 7 1 \u00C2\u00B0 1 5 3 8 5 % 1 6 2 \u00C2\u00B0 2 4 1 4 6 3 lo w 3 2 .8 2 8 .9 1 7 .0 1 1 .9 2 0 0 0 2 \u00C2\u00B0 1 4 6 1 0 0 % 3 \u00C2\u00B0 2 4 1 4 6 3 lo w 2 5 .9 2 3 .1 1 5 .3 7 .8 2 0 0 2 2 \u00C2\u00B0 1 9 5 1 0 0 % 1 6 8 \u00C2\u00B0 3 1 5 9 9 lo w 2 6 .0 2 4 .6 1 7 .0 7 .7 2 0 0 2 3 \u00C2\u00B0 1 8 7 1 0 0 % 2 0 1 \u00C2\u00B0 9 1 5 9 9 lo w 5 6 .5 5 0 .3 1 5 .5 3 4 .8 1 9 9 7 1 .5 \u00C2\u00B0 2 1 0 1 0 0 % 2 8 0 9 1 5 9 9 lo w 3 3 .4 2 7 .1 9 .9 1 7 .2 2 0 0 0 3 \u00C2\u00B0 2 2 3 1 0 0 % 3 3 4 \u00C2\u00B0 9 1 5 9 9 lo w 2 3 .9 2 1 .3 1 0 .3 1 1 .0 2 0 0 2 3 \u00C2\u00B0 2 3 3 7 5 % 3 2 1 \u00C2\u00B0 1 2 1 5 9 9 lo w 4 5 .9 4 8 .0 1 2 .6 3 5 .5 1 9 9 7 1 \u00C2\u00B0 2 2 5 4 5 % 2 7 7 \u00C2\u00B0 1 2 1 5 9 9 lo w 3 7 .3 3 5 .4 1 7 .3 1 8 .1 2 0 0 0 2 \u00C2\u00B0 1 9 3 1 0 0 % 3 3 \u00C2\u00B0 1 3 1 5 9 9 lo w 2 7 .5 2 4 .8 1 7 .1 7 .8 2 0 0 2 3 .5 \u00C2\u00B0 1 2 9 1 0 0 % 2 5 7 \u00C2\u00B0 1 3 1 5 9 9 lo w 3 6 .2 3 0 .6 1 3 .3 1 7 .3 2 0 0 0 2 \u00C2\u00B0 1 7 8 1 0 0 % 2 9 7 \u00C2\u00B0 1 3 1 5 9 9 lo w 2 7 .0 2 1 .9 1 4 .2 7 .7 2 0 0 0 2 \u00C2\u00B0 1 4 0 9 5 % 3 2 5 \u00C2\u00B0 1 3 1 5 9 9 lo w 2 6 .3 2 0 .0 1 0 .5 9 .5 2 0 0 2 2 .5 \u00C2\u00B0 1 9 3 7 0 % 3 2 6 \u00C2\u00B0 1 3 1 5 9 9 lo w 2 7 .1 2 4 .5 1 5 .2 9 .3 2 0 0 2 2 \u00C2\u00B0 1 3 2 1 0 0 % 3 5 6 \u00C2\u00B0 1 3 1 5 9 9 lo w 3 1 .2 2 6 .3 7 .6 1 8 .8 2 0 0 0 1 \u00C2\u00B0 2 4 7 5 5 % 3 3 1 \u00C2\u00B0 1 3 1 5 9 9 lo w 4 6 .9 4 5 .8 2 2 .3 2 3 .6 2 0 0 0 1 .5 \u00C2\u00B0 2 5 9 1 0 0 % 1 9 \u00C2\u00B0 1 2 0 0 0 lo w 6 8 .8 5 9 .3 2 8 .8 3 0 .6 1 9 9 7 1 .5 \u00C2\u00B0 2 3 3 9 5 % 2 1 6 \u00C2\u00B0 1 2 0 0 0 lo w 3 3 .8 3 2 .0 1 6 .6 1 5 .5 2 0 0 0 1 \u00C2\u00B0 2 0 2 6 0 % 1 9 \u00C2\u00B0 4 2 0 0 0 lo w 2 3 .6 1 8 .8 8 .0 1 0 .9 2 0 0 2 3 \u00C2\u00B0 2 2 2 5 0 % 3 5 6 \u00C2\u00B0 1 0 2 0 0 0 lo w 4 2 .1 3 4 .4 1 4 .4 2 0 .0 1 9 9 7 2 \u00C2\u00B0 2 0 3 7 0 % 3 1 0 \u00C2\u00B0 1 0 2 0 0 0 lo w 4 2 .7 3 9 .8 2 0 .8 1 9 .1 2 0 0 0 2 \u00C2\u00B0 2 0 2 1 0 0 % 2 6 7 \u00C2\u00B0 1 0 2 0 0 0 lo w 1 6 .0 1 4 .9 9 .0 5 .9 2 0 0 2 3 \u00C2\u00B0 1 0 5 1 0 0 % 1 7 3 \u00C2\u00B0 1 7 2 0 0 0 lo w 1 8 .7 1 4 .6 6 .9 7 .8 2 0 0 2 2 \u00C2\u00B0 1 7 1 5 5 % 2 0 \u00C2\u00B0 1 7 2 0 0 0 lo w 3 9 .6 3 7 .8 2 0 .7 1 7 .2 2 0 0 0 1 \u00C2\u00B0 1 7 5 1 0 0 % 1 3 4 \u00C2\u00B0 1 7 2 0 0 0 lo w 4 9 4 0 .7 9 .3 3 1 .5 1 9 9 7 1 \u00C2\u00B0 2 4 8 5 5 % 1 8 8 \u00C2\u00B0 "@en . "Graduating Project"@en . "10.14288/1.0075616"@en . "eng"@en . "Unreviewed"@en . "Vancouver : University of British Columbia Library"@en . "Attribution-NonCommercial-NoDerivatives 4.0 International"@en . "http://creativecommons.org/licenses/by-nc-nd/4.0/"@en . "Undergraduate"@en . "University of British Columbia. FRST 498"@en . "Western Gall Rust"@en . "Lodgepole pine"@en . "Does gall size indicate the level of resistance towards Western Gall Rust?"@en . "Text"@en . "http://hdl.handle.net/2429/27152"@en .