Results and Discussion
How does my data look like?
Dataset of pine trees
It is very obviously that Tsb 3 (red attack)(Fig 18), Tsb 4 (gray attack 4-5 yrs)(Fig 19) and Tsb 5 (gray attack 6-7 yrs)(Fig 20) have relative small sample size, compared to Tsb 1 (healthy pine trees), Tsb 2 (green attack) and Tsb 6 (oldest gray attack >8 yrs). So I decided to only look at Tsb 1 (healthy pine), Tsb 2 (green attack) and Tsb 6 categories (oldest gray attack over 8 yrs) (Fig 16, 17 & 21).
Dataset of soil nutrients
Answers of my hypothesis?
Is there any relation between pine trees and soil nutrients?
Only one relation appears after analysis. A negative linear relation shows between total percentage of nitrogen and percentage of green attack. Although coefficient correlation (R^2) is only 0.38, P value is 0.03037 which is less than 0.05 (pre-determined value). In the other words, when percentage of green attack increases, total percentage of nitrogen will decrease (Fig 23).
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Is there any differences of total percentage of soil nutrients between different TSB categories?
Different statistical tests have been applied to those three Tsb categories and three soil nutrients, unfortunately, no difference had been found between them. However, given to the quite distinguished percentage density of each stands, a deeper analysis of basic dataset need to be done before further statistics.
A principle components analysis was done to help understand my dataset deeply (Fig 24). Numbers showing in PCA figure represent different site IDs. The red circles are surrounding the sites right near the tip of arrows. Those sites could highly drive the arrows' direction and length. After tracking those sites back to original dataset, a new dataset was developed based on both Tsb categories and percentage attacking density of lodgepole pines. |
A developed dataset
A new developed dataset is composed of:
ID of sites in healthy category(PerMpb1D / Tsb 1): 2, 7, 15, 19, 20, 24, 25, 32, 33 (over 50% healthy pine trees in each site)
ID of sites in green attack category (PerMpb2D / Tsb 2): 4, 5, 6, 10, 17, 21 (over 30% green attack pine trees in each site)
ID of sites in oldest gray attack (over 8yrs attacking history) category (PerMpb6D / Tsb 6): 12, 14, 22, 23, 26, 27, 28 (over 40% oldest gray attack pine trees in each site)
ID of sites in healthy category(PerMpb1D / Tsb 1): 2, 7, 15, 19, 20, 24, 25, 32, 33 (over 50% healthy pine trees in each site)
ID of sites in green attack category (PerMpb2D / Tsb 2): 4, 5, 6, 10, 17, 21 (over 30% green attack pine trees in each site)
ID of sites in oldest gray attack (over 8yrs attacking history) category (PerMpb6D / Tsb 6): 12, 14, 22, 23, 26, 27, 28 (over 40% oldest gray attack pine trees in each site)
Now time to ask the same question: Is there any differences of total percentage of soil nutrients between different TSB categories?
After checking normality of each variables (3 Tsb category), and testing the equality of variance, ANOVA test is ready to apply on further analysis. All of ANOVA tests below were tested as a pre-determined value (α) of 0.05.
Even it looks like a gap between two standard error bars of green attack and healthy category, the P value, which is over 0.05 (over pre-determined value α), shows that there is no significant difference between green attack category (Tsb 2) and healthy category (Tsb 1) on total percentage of nitrogen. However, a significant difference of total percentage of nitrogen is showing between oldest gray attack (Tsb 6) and green attack (Tsb 2) category (p value < 0.05, less than pre-determined value α).
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The ANOVA test of total percentage of carbon has a similar result as the ANOVA of total percentage of nitrogen. Only oldest gray attack category (Tsb 6) and green attack category (Tsb 2) shows differences with a p value of 0.049552, which is right below the pre-determined value (α = 0.05). In this case, a type I error could be made. Therefore, there is no enough reason to reject the null hypothesis (there is no differences on total percentage of carbon between oldest gray attack and green attack).
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Even the error bars between each category look like quite different from each other, the p value which are over 0.05 show that there is no differences between none of them (α = 0.05). |
Discussion
Nitrogen is a subject which can be released out of soil when surrounding environment changed. When lodgepole pines are in green attack stage, it is the exact stage that lodgepole pines are successfully invaded by mountain pine beetles. Pines start to allocate more energy on defense, however if mountain pine beetles have a big population or trees were stressed before the attack, hosts will die very quickly (less than one year). With a large proportion of green attack in stands, the quick dying pine trees actually changed the ecology to a big degree. With increasing amounts of green attack pine trees and declining amounts of living plants, the total percentage of nitrogen released very quickly after mountain pine beetle attack.
On the other hand, people have found that after mountain pine beetle attack, needles of lodgepole pines usually have higher level of nitrogen (Cigan et al., 2015). It may explain why total percentage of nitrogen is relative low in green attack stands. However, once the attack starts, foliage will start to fall down. But the dead pine trees can keep standing up to 10 years without abiotic disturbances and the foliage could keep falling down for several years after trees are dead. These progress could slow the nitrogen compensation speed from lodgepole pine tissues to soil. However, after 8 years, dead lodgepole pines are dropped all of their foliage, even barks, some of them fell down already, which could give most of the nitrogen back to soil or atmosphere. In the meantime, new generations are growing up and other residual trees into the disturbed stands which could help to steady nitrogen in soil. But during my fieldwork, there is no preferences of a particular tree species could effect soil nutrients after mountain pine beetle attack (p value > 0.05).
There is always an argument about whether or not mountain pine beetles are "regulators" of ecosystem. Based on this research results, the no differences of total percentage of nitrogen, carbon and phosphorus between healthy stands and attacked stands (both green attack stands and oldest attack stands) could partially prove that mountain pine beetles are not the regulators as people hope. It has been found that mountain pine beetles tend to attack larger lodgepole pines which usually have thicker bark (Amman et al., 1977). And those larger lodgepole pines usually are over 80 years old which have passed their peak growth rate. In those kind of forestry, the primary productivity usually has started to decline (Shore et al., 2006; Romme et al., 1986). But when mountain pine beetles are coming in to the ecosystem, there is a good chance for them to wipe out the large and old trees so that young generations will have a better living situations (more open canopy, more available nutrients) and the primary productivity of stands will start to increase after a short duration (Mattson and Addy, 1975). However, the not significant results express that the nutrients level of attacked stands were not different from the original level (healthy stands). Given that the history of recent mountain pine beetle outbreak in Alberta is relative shorter than British Columbia, which could be dated back to 8 or 9 years ago only, and the "recover" duration is possible to be longer than 8 or 9 years. But there was not a significant change in the short duration after mountain pine beetle attack (green attack stands) either. Int this case, mountain pine beetles do not seem to be able to "regulate" ecosystem during 8 to 9 years at least.
Because of the short attacking history in Alberta, more researches need to be followed up to track down the change of nutrients. In the meantime, a research monitoring residual tree species health status and new generation should be set up so that a more detail picture of post-MPB stands can be revealed for future forest managements.
There is always an argument about whether or not mountain pine beetles are "regulators" of ecosystem. Based on this research results, the no differences of total percentage of nitrogen, carbon and phosphorus between healthy stands and attacked stands (both green attack stands and oldest attack stands) could partially prove that mountain pine beetles are not the regulators as people hope. It has been found that mountain pine beetles tend to attack larger lodgepole pines which usually have thicker bark (Amman et al., 1977). And those larger lodgepole pines usually are over 80 years old which have passed their peak growth rate. In those kind of forestry, the primary productivity usually has started to decline (Shore et al., 2006; Romme et al., 1986). But when mountain pine beetles are coming in to the ecosystem, there is a good chance for them to wipe out the large and old trees so that young generations will have a better living situations (more open canopy, more available nutrients) and the primary productivity of stands will start to increase after a short duration (Mattson and Addy, 1975). However, the not significant results express that the nutrients level of attacked stands were not different from the original level (healthy stands). Given that the history of recent mountain pine beetle outbreak in Alberta is relative shorter than British Columbia, which could be dated back to 8 or 9 years ago only, and the "recover" duration is possible to be longer than 8 or 9 years. But there was not a significant change in the short duration after mountain pine beetle attack (green attack stands) either. Int this case, mountain pine beetles do not seem to be able to "regulate" ecosystem during 8 to 9 years at least.
Because of the short attacking history in Alberta, more researches need to be followed up to track down the change of nutrients. In the meantime, a research monitoring residual tree species health status and new generation should be set up so that a more detail picture of post-MPB stands can be revealed for future forest managements.