No description available.

No description available.

Phenol formaldehyde (PF) resol resins have long been used widely as wood adhesives due to their excellent bonding performance, water resistance and durability. With the growing concern for fossil fuel depletion and climate change, there is a strong interest in exploring renewable biomass materials as substitutes for petroleum-based feedstock. Bark, rich in phenolic compounds, has demonstrated potential to partially substitute phenol in synthesizing bio-based PF resins. In this study, acid-catalyzed phenol liquefaction and alkaline extraction were used to convert mountain pine beetle (MPB; Dendroctonus ponderosae) infested lodgepole pine (Pinus contorta) barks to phenol substitutes, liquefied bark and bark extractives. Two types of bio-based phenol formaldehyde (PF) resol resins, namely liquefied bark-PF resin and bark extractive-PF resins, were then synthesized and characterized. It was found that acid-catalyzed phenol liquefaction and alkaline extraction were effective conversion methods to obtain phenol substitute with the maximum yield of 85% and 68%, respectively. The bio-based PF resol resins had higher molecular weights, higher polydispersity indices, shorter gel times, and faster curing rates than the lab synthesized control PF resin without the bark components. Based on the lap-shear tests, the bio-based PF resol resins exhibited comparable wet and dry bonding strength to lab PF resin and commercial PF resin. The post-curing thermal stability of the bio-based PF resins was similar to the lab control PF resin. The liquid-state 13C nuclear magnetic resonance (NMR) study revealed significant influences on the resin structures by the inclusion of the bark components. Methylene ether bridges, which were absent in the lab PF resin, were found in the bio-based PF resins. The bark components favored the formation of para-ortho methylene linkages in the bio-based bark extractive-PF resins. The liquefied bark-PF resin showed a higher ratio of para-para/ortho-para methylene link (-CH2-), a higher unsubstituted/substituted hydrogen (-H/-CH2OH) ratio and a higher methylol/methylene (-CH2OH/-CH2-) ratio than the bark extractive-PF resin. Both tannin components of bark alkaline extractives and phenolated barks contributed to the acceleration of the curing rate of the bio-based resins. This research demonstrated the promise of the bio-based PF resins containing either bark alkaline extractives or liquefied barks as environmentally friendly alternatives to PF adhesives derived solely from fossil fuel based phenol and proposed a novel higher value-added application of the largely available barks from the mountain pine beetle-infested lodgepole pine trees.

Phenol formaldehyde (PF) resol resins have long been used widely as wood adhesives due to their excellent bonding performance, water resistance and durability. With the growing concern for fossil fuel depletion and climate change, there is a strong interest in exploring renewable biomass materials as substitutes for petroleum-based feedstock. Bark, rich in phenolic compounds, has demonstrated potential to partially substitute phenol in synthesizing bio-based PF resins. In this study, acid-catalyzed phenol liquefaction and alkaline extraction were used to convert mountain pine beetle (MPB; Dendroctonus ponderosae) infested lodgepole pine (Pinus contorta) barks to phenol substitutes, liquefied bark and bark extractives. Two types of bio-based phenol formaldehyde (PF) resol resins, namely liquefied bark-PF resin and bark extractive-PF resins, were then synthesized and characterized. It was found that acid-catalyzed phenol liquefaction and alkaline extraction were effective conversion methods to obtain phenol substitute with the maximum yield of 85% and 68%, respectively. The bio-based PF resol resins had higher molecular weights, higher polydispersity indices, shorter gel times, and faster curing rates than the lab synthesized control PF resin without the bark components. Based on the lap-shear tests, the bio-based PF resol resins exhibited comparable wet and dry bonding strength to lab PF resin and commercial PF resin. The post-curing thermal stability of the bio-based PF resins was similar to the lab control PF resin. The liquid-state 13C nuclear magnetic resonance (NMR) study revealed significant influences on the resin structures by the inclusion of the bark components. Methylene ether bridges, which were absent in the lab PF resin, were found in the bio-based PF resins. The bark components favored the formation of para-ortho methylene linkages in the bio-based bark extractive-PF resins. The liquefied bark-PF resin showed a higher ratio of para-para/ortho-para methylene link (-CH2-), a higher unsubstituted/substituted hydrogen (-H/-CH2OH) ratio and a higher methylol/methylene (-CH2OH/-CH2-) ratio than the bark extractive-PF resin. Both tannin components of bark alkaline extractives and phenolated barks contributed to the acceleration of the curing rate of the bio-based resins. This research demonstrated the promise of the bio-based PF resins containing either bark alkaline extractives or liquefied barks as environmentally friendly alternatives to PF adhesives derived solely from fossil fuel based phenol and proposed a novel higher value-added application of the largely available barks from the mountain pine beetle-infested lodgepole pine trees.

My thesis research investigated monoterpene responses in jack pine (Pinus banksiana Lamb.) to different agents to better understand how these responses may influence the spread of the mountain pine beetle (Dendroctonus ponderosae Hopkins; MPB) in the boreal forest. The results support that monoterpenes are inducible responses in jack pine. In the first study, methyl jasmonate application elicited the greatest response in juvenile and mature trees suggesting that jasmonic acid plays a role in jack pine defence responses. In the cross-induction study, I found evidence of an increase in resistance to Grosmannia clavigera with prior jack pine budworm defoliation (Choristoneura pinus pinus Freeman; JPBW). In contrast, needle monoterpenes greatly increased after G. clavigera inoculation and continued to increase during JPBW defoliation; however, JPBW increased its feeding rate to compensate for a change in host quality. Overall, monoterpene induction in jack pine depended on the agent(s) involved and their order. The systemic responses that were observed may have implications for MPB spread in the boreal forest. / Forest Biology and Managment

Thesis (M.S.)--University of Wyoming, 2008. / Title from PDF title page (viewed on June 26, 2009). Includes bibliographical references (p. 86-111).

Thesis (MS)--Montana State University--Bozeman, 2009. / Typescript. Chairperson, Graduate Committee: Rick L. Lawrence. Includes bibliographical references (leaves 93-106).

With an increasing number of large area data sets, many study areas exhibit spatial non-stationarity or spatial variation in mean and variance of observed phenomena. This poses issues for a number of spatial analysis methods which assume data are stationary. The Getis and Ord’s Gi* statistic is a popular measure that, like many others, is impacted by non stationarity. The Gi* is used for locating hot and cold spots in marked data through the detection of spatial autocorrelation in values that are extreme relative to the global mean value, or the mean entire study area. This thesis describes modifications of the Getis and Ord’s Gi* local measure of spatial association, in part to account for regional differences (spatial non-stationarity) in a dataset. Instead of using data from the entire study area to calculate the mean parameter, as is done for the standard Gi*, I capture points for calculation of the mean using a circular distance band centred on the pivot location, which I call the local region (similar to the Ord and Getis Oi statistic). This approach can be applied to a single instance of a local region or to multiple spatial scales of the local region. I explore both in this paper using simulated datasets and a case study on mountain pine beetle infestation data. I find that the local region, when of a similar size to a true region (homogeneous section of the study area where the mean is approximately the same across locations), obtains similar results to the standard Gi* calculated separately on distinct regions (simulated to be distinct), but has the advantage of not needing explicit delineation of regional boundaries or partitioning into separate subareas. The results of a probability score for a multi-scale approach include high and low scores that are more evenly distributed across the study area and that are thus able to pick out more subtle variations within different regions. Through the case study I demonstrate how the multi-scale approach may be applied to a real dataset.

Southern pine beetle (SPB), Dendroctonus frontalis (Zimmerman), is one of the most destructive insect pests of pine trees in southern United States, Mexico and Central America. There is relatively little information on the effect of habitat fragmentation on the connectivity and the spatial population genetics of SPB. This study therefore, adds to previously generated information by assessing how habitat fragmentation affects the spatial population genetic structure of SPB. It also introduces a new approach to the study of bark beetle population dynamics by assessing how landscape variables shape their effective dispersal. To address this issue, a suite of eight highly polymorphic DNA microsatellite markers were used to measure SPB movement over a representative range of SPB habitat and non-habitat (matrix). At the broadest scale, highly significant genetic differentiation suggests that the sampled populations are not panmictic. Loci with higher variability yielded higher resolution for both the infinite allele model based measure of differentiation (FST) and the stepwise mutation based measure (RST) estimates. It is apparent that allelic frequency differences, allelic size ranges and repeat motif played a role in the observed patterns of pair-wise differentiations between the sampled localities. It is supposed that gene flow, wide-range dispersal and recent divergent time could have contributed to the lower level of genetic structure observed in the pair wise estimates. The sampled populations did not show any differentiation attributable to the host species from which they were collected. Mantel test of genetic distance and Euclidean geographic distance revealed no correlation. Mantel tests of the correlation between genetic distance and cost weighted Euclidean distances also suggest that dispersal of SPB across geographic barriers is not significantly reduced. Thus, landscape features and host preference do not appear to have had an impact on population genetic structure of SPB. Since movements of these beetles were not significantly hindered by environmental factors like major rivers, roads, elevation and host type, it is advisable for regional pest management offices to put an effort and coordinate their prevention and management plans in a broader scale to alleviate the problem associated with this native insect pest. Disequilibrium in the observed homogenized pattern of the beetle in this study suggests human contribution in the dispersal of SPB. Therefore, stringent control is deemed necessary in transportation of logs. This could improve our pest management system hence its positive implication in timber industry is obvious.

With an increasing number of large area data sets, many study areas exhibit spatial non-stationarity or spatial variation in mean and variance of observed phenomena. This poses issues for a number of spatial analysis methods which assume data are stationary. The Getis and Ord’s Gi* statistic is a popular measure that, like many others, is impacted by non stationarity. The Gi* is used for locating hot and cold spots in marked data through the detection of spatial autocorrelation in values that are extreme relative to the global mean value, or the mean entire study area. This thesis describes modifications of the Getis and Ord’s Gi* local measure of spatial association, in part to account for regional differences (spatial non-stationarity) in a dataset. Instead of using data from the entire study area to calculate the mean parameter, as is done for the standard Gi*, I capture points for calculation of the mean using a circular distance band centred on the pivot location, which I call the local region (similar to the Ord and Getis Oi statistic). This approach can be applied to a single instance of a local region or to multiple spatial scales of the local region. I explore both in this paper using simulated datasets and a case study on mountain pine beetle infestation data. I find that the local region, when of a similar size to a true region (homogeneous section of the study area where the mean is approximately the same across locations), obtains similar results to the standard Gi* calculated separately on distinct regions (simulated to be distinct), but has the advantage of not needing explicit delineation of regional boundaries or partitioning into separate subareas. The results of a probability score for a multi-scale approach include high and low scores that are more evenly distributed across the study area and that are thus able to pick out more subtle variations within different regions. Through the case study I demonstrate how the multi-scale approach may be applied to a real dataset.